Search Results (674)

In tunnel blasting, an analytical solution for dynamic stress in the surrounding rock of adjacent tunnels is critical for dynamic response analysis, mechanical evaluations, and crack propagation control. Previous studies on stress field analytical solutions primarily modeled rock as a linear elastic material, focusing mainly on the P-wave effects from instantaneous detonation. Based on Heelan’s short cylindrical cavity model, this paper derives an analytical solution for blast-induced dynamic stresses in adjacent tunnel rock, incorporating both induced SV-waves and a rock mass damage factor through rigorous theoretical analysis. Numerical case studies and field measurements were used to analyze stress propagation during tunnel blasting, and theoretical results were compared with measured data. The key findings were as follows: Radial stress > axial stress > hoop stress. All three stresses decay with increasing distance and damage factor, following an inversely proportional relationship with distance. Radial stress decays faster than axial and hoop stresses. Stress also decays exponentially over time, with the peak occurring after the transverse wave arrival. The theoretical results show approximately 10% deviation from the existing empirical formulas, while field measurements closely match the theoretical model, showing consistent stress trends and an average error of 7.02% (radial), 7.56% (axial) and 7.05% (hoop), confirming the reliability of the proposed analytical solution. Full article

This study investigates the thermal dynamics and material behavior involved in the baking process for Lebanese flatbread, focusing on the heat transfer mechanisms, water loss, and dough expansion under high-temperature conditions. Despite previous studies on flatbread baking using impingement or conventional ovens, this work presents the first experimental investigation of the traditional Lebanese flatbread baking process under realistic industrial conditions, specifically using a high-temperature tunnel oven with direct flame heating, extremely short baking times (~10–12 s), and peak temperatures reaching ~650 °C, which are essential to achieving the characteristic pocket formation and texture of Lebanese bread. This experimental study characterizes the baking kinetics of traditional Lebanese flatbread, recording mass loss pre- and post-baking, thermal profiles, and dough expansion through real-time temperature measurements and video recordings, providing insights into the dough’s thermal response and expansion behavior under high-temperature conditions. A custom-designed instrumented oven with a steel conveyor and a direct flame burner was employed. The dough, prepared following a traditional recipe, was analyzed during the baking process using K-type thermocouples and visual monitoring. Results revealed that Lebanese bread undergoes significant water loss due to high baking temperatures (~650 °C), leading to rapid crust formation and pocket development. Empirical equations modeling the relationship between baking time, temperature, and expansion were developed with high predictive accuracy. Additionally, an energy analysis revealed that the total energy required to bake Lebanese bread is approximately 667 kJ/kg, with an overall thermal efficiency of only 21%, dropping to 16% when preheating is included. According to previous CFD (Computational Fluid Dynamics) simulations, most heat loss in similar tunnel ovens occurs via the chimney (50%) and oven walls (29%). These findings contribute to understanding the broader thermophysical principles that can be applied to the development of more efficient baking processes for various types of bread. The empirical models developed in this study can be applied to automating and refining the industrial production of Lebanese flatbread, ensuring consistent product quality across different baking environments. Future studies will extend this work to alternative oven designs and dough formulations. Full article

This paper introduces a knowledge–data dual-driven method for predicting groundwater conditions during tunnel construction. Unlike existing methods, our approach effectively integrates trend characteristics of apparent resistivity from detection results with geological distribution characteristics and expert insights. This dual-driven strategy significantly enhances the accuracy of the prediction model. The intelligent prediction process for tunnel groundwater conditions proceeds in the following steps: First, the apparent resistivity data matrix is obtained from transient electromagnetic detection results and standardized. Second, to improve data quality, trend characteristics are extracted from the apparent resistivity data, and outliers are eliminated. Third, expert insights are systematically integrated to fully utilize prior information on groundwater conditions at the construction face, leading to the establishment of robust predictive models tailored to data from various construction surfaces. Finally, the relevant prediction segment is extracted to complete the groundwater condition forecast. Full article

Background: Gingival recession is a common condition involving apical displacement of the gingival margin, leading to root surface exposure and associated complications such as dentin hypersensitivity and root caries. Among the most effective treatment options are the tunneling technique (TUN) and the coronally advanced flap (CAF), both combined with connective tissue grafts (CTGs). This study aimed to evaluate and compare the clinical outcomes of TUN + CTG and CAF + CTG in terms of root coverage and keratinized tissue width (KTW) over a 6–12-month follow-up. Methods: A randomized, double-blind clinical trial was conducted following CONSORT guidelines (ClinicalTrials.gov ID: NCT06228534). Participants were randomly assigned to receive either TUN + CTG or CAF + CTG. Clinical parameters, including gingival recession depth (REC) and KTW, were assessed at baseline as well as 6 months and 12 months postoperatively using a calibrated periodontal probe. Statistical analysis was performed using descriptive statistics and linear mixed models to compare outcomes over time, with a significance level set at 5%. Results: Both techniques demonstrated significant clinical improvements. At 6 months, mean root coverage was 100% in CAF + CTG cases and 97% in TUN + CTG cases, while complete root coverage (REC = 0) was observed in 100% and 89% of cases, respectively. At 12 months, root coverage remained stable, at 99% in the CAF + CTG group and 97% in the TUN + CTG group. KTW increased in both groups, with higher values observed in the CAF + CTG group (3.53 mm vs. 3.11 mm in TUN + CTG at 12 months). No significant postoperative complications were reported. Conclusions: Both TUN + CTG and CAF + CTG are safe and effective techniques for treating RT1 and RT2 gingival recession, offering high percentages of root coverage and increased KTW. While CAF + CTG achieved slightly superior coverage and tissue gain, the TUN was associated with better aesthetic outcomes and faster recovery, making it a valuable alternative in clinical practice. Full article

Circular deep excavations, characterized by their symmetrical geometry, are commonly employed in constructing foundations for large-span suspension bridges and as launching shafts for shield tunneling. However, the mechanical behavior of such excavations under asymmetric surface surcharge remains inadequately understood due to a paucity of relevant investigations. This study addresses this knowledge gap by establishing a three-dimensional finite element model (3D-FEA) based on the anchor deep excavation project of a specific bridge. The model is utilized to investigate the influence of asymmetric surcharge on the forces and deformations within the supporting structure. The results show that both the internal force and displacement cloud diagrams of the support structure exhibit asymmetric characteristics. The distribution of displacement and internal forces has spatial effects, and the maximum values all occur in the areas where asymmetric loads are applied. The maximum values of the displacement, axial force, and shear force of underground continuous walls increase with the increase in the excavation depth. The total displacement curves all show the feature of a “bulging belly”. The maximum displacement is 13.3 mm. The axial force is mainly compression, with a maximum value of −9514 kN/m. The maximum positive and negative values of the shear force are 333 kN/m and −705 kN/m, respectively. The bending moment diagram of different monitoring points shows the characteristics of “bow knot”. The maximum values of the positive bending moment and negative bending moment are 1509.4 kN·m/m and −2394.3 kN·m/m, respectively. The axial force of the ring beam is mainly compression, with a maximum value of −5360 kN, which occurs in ring beams 3, 4, and 5. The displacement cloud diagram of the support structure under symmetrical loads shows symmetrical characteristics. Under different load conditions, the displacement curve of the diaphragm wall shows the characteristics of “bulge belly”. The forms of loads with displacements from largest to smallest at the same position are as follows: asymmetric loads, symmetrical loads, and no loads. These findings provide valuable insights for optimizing the structural design of similar deep excavation projects and contribute to promoting sustainable urban underground development. Full article

The deformation characteristics of the surrounding rock in tunnel groups are considered critical for the design of support structures and the assurance of the long-term safety of deep-buried diversion tunnels. The deformation behavior of surrounding rock in tunnel groups was investigated to guide structural support design. Field tests and numerical simulations were performed to analyze the distribution of ground stress and the ground reaction curve under varying conditions, including rock type, tunnel spacing, and burial depth. A solid unit–structural unit coupled simulation approach was adopted to derive the two-liner support characteristic curve and to examine the propagation behavior of concrete cracks. The influences of surrounding rock strength, reinforcement ratio, and secondary lining thickness on the bearing capacity of the secondary lining were systematically evaluated. The following findings were obtained: (1) The tunnel group effect was found to be negligible when the spacing (D) was ≥65 m and the burial depth was 1600 m. (2) Both P_0.3 and P_max of the secondary lining increased linearly with reinforcement ratio and thickness. (3) For surrounding rock of grade III (IV), 95% u_lim and 90% u_lim were found to be optimal support timings, with secondary lining forces remaining well below the cracking stress during construction. (4) For surrounding rock of grade V in tunnels with a burial depth of 200 m, 90% u_lim is recommended as the initial support timing. Support timings for tunnels with burial depths between 400 m and 800 m are 40 cm, 50 cm, and 60 cm, respectively. Design parameters should be adjusted based on grouting effects and monitoring data. Additional reinforcement is recommended for tunnels with burial depths between 1000 m and 2000 m to improve bearing capacity, with measures to enhance impermeability and reduce external water pressure. These findings contribute to the safe and reliable design of support structures for deep-buried diversion tunnels, providing technical support for design optimization and long-term operation. Full article

The recent identification of early-onset mutational signatures with geographic variations by Diaz-Gay et al. is a significant finding, since early-onset colorectal cancer has emerged as an alarming public health challenge in the past two decades, and the pathomechanism remains unclear. Environmental risk factors, including lifestyle and diet, are highly suspected. The identification of colibactin from Escherichia coli as a potential pathogenic source is a major step forward in addressing this public health challenge. Therefore, the following opinion manuscript aims to outline the likely onset of the pathomechanism and the critical role of acquired Piezo2 channelopathy in early-onset colorectal cancer, which skews proton availability and proton motive force regulation toward E. coli within the microbiota–host symbiotic relationship. In addition, the colibactin produced by the pks island of E. coli induces host DNA damage, which likely interacts at the level of Wnt signaling with Piezo2 channelopathy-induced pathological remodeling. This transcriptional dysregulation eventually leads to tumorigenesis of colorectal cancer. Mechanotransduction converts external physical cues to inner chemical and biological ones. Correspondingly, the proposed quantum mechanical free-energy-stimulated ultrafast proton-coupled tunneling, initiated by Piezo2, seems to be the principal and essential underlying novel oscillatory signaling that could be lost in colorectal cancer onset. Hence, Piezo2 channelopathy not only contributes to cancer initiation and impaired circadian regulation, including the proposed hippocampal ultradian clock, but also to proliferation and metastasis. Full article

To address the limitations of traditional hardened concrete road surfaces in coal mine tunnels, which are prone to damage and entail high maintenance costs, this study proposes using modular concrete blocks composed of fly ash and coal gangue as an alternative to conventional materials. These blocks offer advantages including ease of construction and rapid, straightforward maintenance, while also facilitating the reuse of substantial quantities of solid waste, thereby mitigating resource wastage and environmental pollution. Initially, the mineral composition of the raw materials was analyzed, confirming that although the physical and chemical properties of Liangshui Well coal gangue are slightly inferior to those of natural crushed stone, they still meet the criteria for use as concrete aggregate. For concrete blocks incorporating 20% fly ash, the steam curing process was optimized with a recommended static curing period of 16–24 h, a temperature ramp-up rate of 20 °C/h, and a constant temperature of 50 °C maintained for 24 h to ensure optimal performance. Orthogonal experimental analysis revealed that fly ash content exerted the greatest influence on the compressive strength of concrete, followed by the additional water content, whereas the aggregate particle size had a comparatively minor effect. The optimal mix proportion was identified as 20% fly ash content, a maximum aggregate size of 20 mm, and an additional water content of 70%. Performance testing indicated that the fabricated blocks exhibited a compressive strength of 32.1 MPa and a tensile strength of 2.93 MPa, with strong resistance to hydrolysis and sulfate attack, rendering them suitable for deployment in weakly alkaline underground environments. Considering the site-specific conditions of the Liangshuijing coal mine, ANSYS 2020 was employed to simulate and analyze the mechanical behavior of the blocks under varying loads, thicknesses, and dynamic conditions. The findings suggest that hexagonal coal gangue blocks with a side length of 20 cm and a thickness of 16 cm meet the structural requirements of most underground mine tunnels, offering a reference model for cost-effective paving and efficient roadway maintenance in coal mines. Full article

Aim: This study aimed to assess the effect of educational programs on symptom severity for women at high risk of carpal tunnel syndrome (CTS). Methods: A quasi-experimental design was applied. A purposive sample of 250 women at high risk of CTS was selected from the Faculty of Nursing, Assiut University, Egypt. Data collection instruments included a structured interview questionnaire and the Boston Carpal Tunnel Syndrome Questionnaire (BCTQ). Results: Most participants were middle-aged (41–50 years), married, and had higher education. At baseline, 61.2% of participants reported mild symptoms, 24.8% moderate, and 11.6% were asymptomatic. Following the educational program, symptom severity was significantly improved (p = 0.007). The proportion of asymptomatic participants increased from 11.6% to 20.4%, while those with moderate symptoms decreased from 24.8% to 6.4%. Functional status also improved significantly, with the percentage of participants reporting no difficulty increasing from 17.6% to 30% (p = 0.008). We found a significant reduction in symptom severity scores (p = 0.05) and functional impairment (p = 0.008). Conclusions: The educational program effectively reduced CTS symptoms and improved hand function, demonstrating its potential as a preventive and therapeutic intervention for women at high risk of CTS. However, this study’s quasi-experimental design without a control group and a short follow-up period limits conclusions regarding long-term effectiveness and causal inference. Full article

To address the limitations of traditional tunnel structural plane modeling—such as low automation, insufficient smoothness, and poor adaptability to real construction environments—this study proposes a novel three-dimensional (3D) modeling framework based on B-spline interpolation combined with deep learning. The method first employs YOLOv5 for rapid detection of structural regions and DeepLabV3+ for precise boundary segmentation, followed by skeleton extraction and coordinate transformation to obtain spatial structural traces. Finally, B-spline interpolation is applied across multiple tunnel sections to construct continuous 3D surfaces. In model training and testing, the segmentation network achieved an F1 score of 94.01%, and the final modeling accuracy demonstrated a mean relative error (MRE) below 2.5%, confirming the reliability of the geometric reconstruction. Additionally, the proposed method was applied to excavation face images from the Paiyashan Tunnel, where multiple structural surfaces were successfully reconstructed in 3D, validating the approach’s applicability and robustness in real geological conditions. Compared to traditional triangulated or linear surface methods, the proposed approach achieves higher smoothness, better geological continuity, and improved automation, making it suitable for real-world geotechnical applications. Full article

Pea-gravel grouting, which fills the gap between the lining of tunnels and the surrounding rock, is crucial for the structural stability and waterproofing of water delivery TBM tunnels. However, it is prone to defects due to complex construction conditions and geological factors. To provide practical insights for engineers to evaluate grouting quality and take appropriate remedial action during TBM tunnel construction, this paper assesses four types of pea-gravel grouting defects, including local cavities, less density, rich rock powder and rich cement slurry. Detailed numerical simulation models comprising segment lining, pea-gravel grouting and surrounding rock were built using the 3D finite element method to analyze the displacement and stress of the segments at the transition zone between different classes of surrounding rocks, labeled V–IV, V–III and IV–III. The results indicate that a local cavity defect has the greatest impact on the loading response of segment lining, followed by less density, rich rock powder and rich cement slurry defects. Their impact will weaken with better self-support of the surrounding rocks in the order of V–IV, V–III and IV–III. The tensile stress of segment lining is within the limit of concrete cracking for combinations of all four defects when the surrounding rock is of the class IV–III, and it is within this limit for two-defect combinations when the surrounding rock is of classes V–III and V–IV. When three defects or all four defects are present in the pea-gravel grouting, the possibility of segment concrete cracking increases from the transition zone of class V–III surrounding rock to the transition zone of class V–IV surrounding rock. Full article

To prevent the occurrence of excavation face instability incidents during shield tunneling, this study takes the Bailuyuan tunnel of the ‘Hanjiang-to-Weihe River Water Diversion Project’ as the engineering background. A three-dimensional discrete element method simulation was employed to analyze the tunneling process, revealing the displacement response of the excavation face to various tunneling parameters. This led to the development of a risk assessment method that considers both tunneling parameters and geological conditions for deep-buried shield tunnels. The above method effectively overcomes the limitations of finite element method (FEM) studies on shield tunneling parameters and, combined with the Analytic Hierarchy Process (AHP), enables rapid tunnel analysis and assessment. The results demonstrate that the displacement of the excavation face in shield tunnel engineering is significantly influenced by factors such as the chamber earth pressure ratio, cutterhead opening rate, cutterhead rotation speed, and tunneling speed. Specifically, variations in the chamber earth pressure ratio have the greatest impact on horizontal displacement, occurring predominantly near the upper center of the tunnel. As the chamber earth pressure ratio decreases, horizontal displacement increases sharply from 12.9 mm to 267.3 mm. Conversely, an increase in the cutterhead opening rate leads to displacement that first rises gradually and then rapidly, from 32.1 mm to 121.1 mm. A weighted index assessment model based on AHP yields a risk level of Grade II, whereas methods from other scholars result in Grade III. By implementing measures such as adjusting the grouting range, cutterhead rotation speed, and tunneling speed, field applications confirm that the risk level remains within acceptable limits, thereby verifying the feasibility of the constructed assessment method. Construction site strategies are proposed, including maintaining a chamber earth pressure ratio greater than 1, tunneling speed not exceeding 30 mm/min, cutterhead rotation speed not exceeding 1.5 rpm, and a synchronous grouting range of 0.15 m. Following implementation, the tunnel construction successfully passed the high-risk section without any incidents. This research offers a decision-making framework for shield TBM operation safety in complex geological environments. Full article

Detecting leakage using a point cloud acquired by mobile laser scanning (MLS) presents significant challenges, particularly from within three-dimensional space. These challenges primarily arise from the prevalence of noise in tunnel point clouds and the difficulty in accurately capturing the three-dimensional morphological characteristics of leakage patterns. To address these limitations, this study proposes a classification method based on XGBoost classifier, integrating both intensity and geometric features. The proposed methodology comprises the following steps: First, a RANSAC algorithm is employed to filter out noise from tunnel objects, such as facilities, tracks, and bolt holes, which exhibit intensity values similar to leakage. Next, intensity features are extracted to facilitate the initial separation of leakage regions from the tunnel lining. Subsequently, geometric features derived from the k neighborhood are incorporated to complement the intensity features, enabling more effective segmentation of leakage from the lining structures. The optimal neighborhood scale is determined by selecting the scale that yields the highest F_1-score for leakage across various multiple evaluated scales. Finally, the XGBoost classifier is applied to the binary classification to distinguish leakage from tunnel lining. Experimental results demonstrate that the integration of geometric features significantly enhances leakage detection accuracy, achieving an F_1-score of 91.18% and 97.84% on two evaluated datasets, respectively. The consistent performance across four heterogeneous datasets indicates the robust generalization capability of the proposed methodology. Comparative analysis further shows that XGBoost outperforms other classifiers, such as Random Forest, AdaBoost, LightGBM, and CatBoost, in terms of balance of accuracy and computational efficiency. Moreover, compared to deep learning models, including PointNet, PointNet++, and DGCNN, the proposed method demonstrates superior performance in both detection accuracy and computational efficiency. Full article

Background: Arachnoid cysts are typically benign and asymptomatic, but large cysts can exert a mass effect on adjacent neural structures. Based on the available literature, no cases of cortical visual impairment (CVI) in an adolescent caused by posterior fossa arachnoid cysts have been reported. Case presentation: We report the case of a previously healthy 16-year-old girl who presented with sudden and rapidly progressive bilateral visual loss due to a large retrocerebellar arachnoid cyst. She reported blurred vision, tunnel vision-like, and decreased visual acuity. Although neuro-ophthalmologic and imaging workup revealed no damage to the anterior visual pathways, she exhibited progressive visual decline. Functional tests confirmed bilateral cortical visual impairment: pattern-reversal visual evoked potentials (VEPs) showed preserved and symmetric P100 latencies and amplitudes, while automated perimetry revealed bilateral concentric visual field constriction with preserved central islands. Following cystoperitoneal drainage, her vision rapidly and completely recovered. Conclusions: To the best of our knowledge, this is the first reported case of reversible CVI in an adolescent caused by a posterior fossa arachnoid cyst without intracranial pressure (ICP) elevation or optic nerve involvement, and with tunnel vision-like. Our findings emphasize the role of posterior fossa lesions in visual dysfunction and highlight the potential reversibility of cortical visual loss when timely decompression is achieved. This case underscores the importance of including posterior fossa lesions in the differential diagnosis of unexplained bilateral visual loss, even in the absence of elevated intracranial pressure or anterior visual pathway involvement. Full article

A real-time structural health monitoring (SHM) system of an airplane composite wing with adjustable damage is reported, where testing under realistic flight conditions is carried out in the controllable and repeatable environment of an industrial wind tunnel. An FBG-based sensing array monitors a debonded region, whose compromised structural strength is regained by a set of lockable fasteners. Damage tunability is achieved by loosening some of or all these fasteners. Real-time analysis of the data collected involves Principal Component Analysis, followed by Hotelling’s T-squared and Q measures. With previously set criteria, real-time data collection and processing software can declare the structural health status as normal or abnormal. During testing, the system using the Q measure successfully identified the initiation of the damage and its extent, while the T-squared one returned limited outcomes. Full article