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As a unique geological hazard in a high-geo-stress environment, rockburst happens with strong suddenness, randomness, and destructiveness, but the mechanism of its occurrence in a deep-buried tunnel in a high-geo-stress environment needs further study. Based on the analyses of the stress field of the rockburst section of Ping’an Tunnel, which is over-long and deep-buried, the occurrence mechanism of rockburst is figured out. Furtherly, the intensity and location of rockburst are predicted by using the rockburst criterion. Results show that there exists large compressive stress at the side wall of the tunnel, which is the main cause of rockburst. Under a high-geo-stress condition, due to the existence of unfavorable factors like structural planes, high intensity rockburst is likely to happen in the middle of the tunnel face after the sudden release of original rock stress. Arranging stress-releasing holes in the rockburst section can effectively reduce the possibility of rockburst by releasing the original rock stress in advance. The research results can deepen the understanding of the mechanism of rockburst in a high-geo-stress environment and provide scientific basis for the prevention and control of rockburst in similar engineering projects.

To study the potential disasters caused by tunnels crossing water-abundant fault areas, this study takes the Jinyunshan Tunnel as an example, and studies the groundwater flow law between different rock layers, the interaction between surrounding rock hydrostatic pressure and soil pressure, and the mechanical features and safety of the lining during construction by combining field tests and finite element simulation analysis. The results show that the displacement change rate of the tunnel vault reaches 2.8 mm/d, and the maximum earth pressure and hydrostatic pressure are 2.3 MPa and 1.15 MPa, respectively, both at the bottom of the tunnel in section II. When the tunnel enters the fault fracture zone from the V surrounding rock, the bending moment of the lining increases by 222.78% at the left haunch and 60.87% at the bottom of the right wall. The axial force of the right spandrel increases by 2579.2%, and the left spandrel increases by 221.18%. The safety factor of the two sections is greater than 2.4, indicating that the overall structure is in a safe state, but the safety factor of the second right shoulder is 2.54, which is close to the safety threshold of 2.4. The research results provide a basis for the safety design and construction safety of tunnels through water-rich sections in similar fault fracture zones, and provide a reference for reducing groundwater loss and protecting ecological vegetation.

Constructing a tunnel with a large longitudinal slope and a small-radius sharp curve is challenging. During the construction process, it necessitates a series of intricate operations, including adjusting the horizontal and vertical posture of the shield machine, controlling the tunnelling thrust, and consistently ensuring the appropriate over-excavation amount inside and outside of the turn. Improper operations can easily induce undue stress on the segments. This study establishes a finite element numerical model of lining segments subjected to jacking force under various construction conditions. The concrete damage plasticity (CDP) constitutive model was used to characterize the mechanical behavior of concrete under load. The mechanical characteristics and damage behavior of segments under construction conditions, such as significant thrust escape, vertical attitude adjustment of the shield machine, excavation in soft and hard interbedded strata, line turning, sudden failure of the propulsion system, and eccentricity of brace boots, were analyzed. The results revealed that, when advancing according to the maximum thrust design value (50 MPa), cracks in the tensile plastic damage zone near the brace boot plate and the edges of the segment can develop. This can lead to localized corner failure of the concrete at the lining’s edge. Therefore, it is recommended that the jack’s thrust value should not surpass 30 MPa. Maintaining the usual uneven jack thrust state of shield tunnelling along the design axis is unlikely to result in segment concrete cracking. Damage to the segment caused by the eccentricity of the brace boot plate is the most severe; hence, avoiding the eccentricity of the brace boot plate during construction is crucial. The findings of this research can guide the control of jack thrust during shield tunnelling construction and offer insights into the design of segment parameters.

This research paper systematically investigates the combined influence of fly ash, cementitious capillary crystalline waterproofing (CCCW) materials, and polypropylene fibers on the mechanical properties and impermeability of concrete through comprehensive orthogonal tests. Microscopic morphological changes in the concrete induced by different composite materials are examined via scanning electron microscopy (SEM) and X-ray diffraction (XRD) testing. The objective is to facilitate a beneficial synergetic interaction among these materials to develop highly permeable, crack-resistant concrete. Key findings of this study are: (1) The study unveils the impact of the concentration of three additive materials on the concrete’s compressive strength, tensile strength, and penetration height, thereby outlining their significant influence on the mechanical properties and impermeability of the concrete; (2) An integrated scoring method determined the optimal composite dosage of three materials: 15% fly ash, 2% CCCW, and polypropylene fibers at 1.5 kg/m3. This combination increased the concrete’s compressive strength by 12.5%, tensile strength by 48.4%, and decreased the average permeability height by 63.6%; (3) The collective introduction of these three materials notably augments the hydration reaction of the cement, resulting in denser concrete microstructure, enhanced bonding between fibers and matrix, and improved concrete strength and durability.

As a new type of pre-reinforcement material for tunnel faces, glass fiber-reinforced polymer (GFRP) bolts can effectively and safely improve the stability of tunnel faces in soft surrounding rocks and speed up excavation. Therefore, in this paper, systematic research is carried out on the bond strength of GFRP bolts in tunnel faces and their relative pre-reinforcement parameters. Firstly, the effects of rebar diameter, anchorage length, and mortar strength on the bonding properties of GFRP bars were studied by indoor pull-out tests. The bond strength–slip curves under different working conditions were obtained, and the curves showed that the ultimate bond strength between GFRP bars and mortar was negatively correlated with the diameter of GFRP bars but positively correlated with the strength of the mortar. In addition, the increase in anchorage length led to a reduction in bonding strength. Secondly, inverse analysis was used to analyse the mechanical parameters of the bond performance of the anchor bars by the finite difference software FLAC3D, and the results indicated that 1/5 of the compressive strength of the GFRP bar grouting body can be taken as the ultimate bond strength to calculate the cohesive strength of the grout. Additionally, the formula of GFRP bar grouting body stiffness was revised. Finally, based on the results of laboratory tests and the inverse analysis, the numerical simulation analysis results showed that the optimal reinforcement configuration for a shallow buried tunnel face surrounded by weak rock is to use GFRP bars with a length of 17 m arranged in the center circle of the tunnel face with a reasonable reinforcement density of 1.0 bolt/m2. The calculation formula of the stiffness and cohesion strength of the GFRP bar grouting body and the reinforcement scheme proposed in this paper can provide a reference for the construction of shallowly buried rock tunnels in soft surrounding rock.

Depression has become one of the most common mental illnesses, causing serious physical and mental harm. However, there remain unclear and uniform physiological indicators to support the diagnosis of clinical depression. This study aimed to use machine learning techniques to investigate the abnormal multidimensional EEG features in patients with depression. Resting-state EEG signals were recorded from 41 patients with depression and 34 healthy controls. Multiple dimensional characteristics were extracted, including power spectral density (PSD), fuzzy entropy (FE), and phase lag index (PLI). These three different dimensional characteristics with statistical differences between two groups were ranked by three machine learning algorithms. Then, the ranked characteristics were placed into the classifiers according to the importance of features to obtain the optimal feature subset with the highest classification accuracy. The results showed that the optimal feature subset contained 86 features with the highest classification accuracy of 98.54% ± 0.21%. According to the statistics of the optimal feature subset, PLI had the largest number of features among the three categories, and the number of beta features was bigger than other rhythms. Moreover, compared to the healthy controls, the PLI values in the depression group increased in theta and beta rhythms, but decreased in alpha1 and alpha2 rhythms. The PSD of theta and beta rhythms were significantly greater in depression group than that in healthy controls, and the FE of beta rhythm showed the same trend. These findings indicate that the distribution of abnormal multidimensional features is potentially useful for the diagnosis of depression and understanding of neural mechanisms.

Driving fatigue is the main cause of traffic accidents, which seriously affects people’s life and property safety. Many researchers have applied electroencephalogram (EEG) signals for driving fatigue detection to reduce negative effects. The main challenges are the practicality and accuracy of the EEG-based driving fatigue detection method when it is applied on the real road. In our previous study, we attempted to improve the practicality of fatigue detection based on the proposed non-hair-bearing (NHB) montage with fewer EEG channels, but the recognition accuracy was only 76.47% with the random forest (RF) model. In order to improve the accuracy with NHB montage, this study proposed an improved transformer architecture for one-dimensional feature vector classification based on introducing the Gated Linear Unit (GLU) in the Attention sub-block and Feed-Forward Networks (FFN) sub-block of a transformer, called GLU-Oneformer. Moreover, we constructed an NHB-EEG-based feature set, including the same EEG features (power ratio, approximate entropy, and mutual information (MI)) in our previous study, and the lateralization features of the power ratio and approximate entropy based on the strategy of brain lateralization. The results indicated that our GLU-Oneformer method significantly improved the recognition performance and achieved an accuracy of 86.97%. Our framework demonstrated that the combination of the NHB montage and the proposed GLU-Oneformer model could well support driving fatigue detection.

Mental fatigue is a widely studied topic on account of its serious negative effects. But how the neural mechanism of task switching before and after mental fatigue remains a question. To this end, this study aims to use brain functional network features to explore the answer to this question. Specifically, task-state EEG signals were recorded from 20 participants. The tasks include a 400-s 2-back-task (2-BT), followed by a 6480-s of mental arithmetic task (MAT), and then a 400-s 2-BT. Network features and functional connections were extracted and analyzed based on the selected task switching states, referred to from Pre_2-BT to Pre_MAT before mental fatigue and from Post_MAT to Post_2-BT after mental fatigue. The results showed that mental fatigue has been successfully induced by long-term MAT based on the significant changes in network characteristics and the high classification accuracy of 98% obtained with Support Vector Machines (SVM) between Pre_2-BT and Post_2-BT. when the task switched from Pre_2-BT to Pre_MAT, delta and beta rhythms exhibited significant changes among all network features and the selected functional connections showed an enhanced trend. As for the task switched from Post_MAT to Post_2-BT, the network features and selected functional connectivity of beta rhythm were opposite to the trend of task switching before mental fatigue. Our findings provide new insights to understand the neural mechanism of the brain in the process of task switching and indicate that the network features and functional connections of beta rhythm can be used as neural markers for task switching before and after mental fatigue.

Steel fibers are widely used because they can effectively improve the tensile, compressive and flexural properties of concrete structures. The selection of steel fiber dosage and aspect ratio at high temperature has an important impact on the flexural toughness of concrete components post-fire. In this paper, discussions are made on the simulated fire test in compliance with the ISO 834 standard to study the steel fiber-reinforced concrete (SFRC) components post-fire. The research reveals the influence of two commonly used steel fiber aspect ratios (50, 70) and steel fiber dosages (30 kg/m3, 40 kg/m3, 45 kg/m3) on the changes of the internal temperature field, the initial crack flexural strength and the flexural toughness of the SFRC components under a single-side fire. Moreover, combined with the four-point flexural test of the SFRC components post fire, the research also describes the damage of high temperatures to the flexural toughness of SFRC components, and suggests a calculation formula for SFRC thermal conductivity by way of the numerical inversion method. The results of this study have verified that the incorporation of steel fiber into concrete helps to reduce its internal thermal stress difference and improve the crack resistance and fire resistance of the concrete. Moreover, under high temperature conditions, the concrete component added with the steel fiber in an aspect ratio of 70 and a dosage of 45 kg/m3 increased their initial crack flexural strength by 56.8%, higher than that of plain concrete components, and the loss of equivalent flexural strength and flexural toughness of SFRC post fire was only 45.2% and 13.6%, respectively. The proposed calculation formula of thermal conductivity can provide a reference for a numerical simulation study of the temperature field of SFRC components in a high temperature environment.

Glutathione peroxidases (GPX) catalyze the reduction of H2O2 or organic hydroperoxides to water or corresponding alcohols using reduced glutathione, which plays an essential role in ROS (reactive oxygen species) homeostasis and stress signaling. Thellungiella salsuginea (Eutrema salsugineum), a relative of Arabidopsis thaliana, displays an extremely high level of tolerance to salt, drought, cold and oxidative stresses. The enzymatic antioxidant systems may contribute to the stress tolerance of T. salsuginea. In the present study, we aimed at understanding the roles of the antioxidant enzymes in T. salsuginea by focusing on the GPX family. We identified the eight GPX genes in T. salsuginea, and the structure of the N-terminal domains indicated their putative chloroplastic, mitochondrial and cytoplasmic location. The exon-intron organization of these genes exhibited a conserved pattern among plant GPX genes. Multiple environmental stresses and hormone response related cis-acting elements were predicted in the promoters of TsGPX genes. The gene and protein expression profiles of TsGPXs in response to high level of salinity and osmotic stresses, in leaves and roots of T. salsuginea were investigated using real-time RT-PCR and western blotting analysis. Our result showed that different members of the GPX gene family were coordinately regulated under specific environmental stress conditions, and supported the important roles of TsGPXs in salt and drought stress response in T. salsuginea.