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As shield tunnels increase, managing shield muck strains construction and the environment. To mitigate this problem, shield muck replaced bentonite in silty clay to improve synchronous grouting slurry. Initially, the physical attributes and microstructural composition of shield muck were obtained, alongside an analysis of the effects of the muck content, particle size, and general influencing factors on the slurry properties through standardized tests and regression models. Subsequently, leveraging three-dimensional response surface methodology, admixture interactions and multiple factor impacts on the slurry were explored. Finally, utilizing the SQP optimization technique, an optimal slurry blend ratio tailored for actual project needs was derived for improved muck slurry. The findings reveal with the decreasing bleeding rates as the muck content rises, the particle size diminishes. An inverse relationship exists between the muck content and slurry fluidity. At soil–binder ratios below 0.6, a decrease in the soil–binder ratio intensifies the influence of the water–binder ratio on the slurry density, bleeding rate, and setting time. The fly flash–cement ratio inversely correlates with the slurry bleeding rate, while the ratio greater than 0.6 is positively correlated. For muck particle sizes under 0.2 mm, the fly flash–cement ratio inversely impacts the density, while over 0.2 mm, it correlates positively. The optimal proportion for silty clay stratum synchronous grouting slurry, substituting muck for bentonite, includes a water–binder ratio of 0.559, binder–sand ratio of 0.684, fly flash–cement ratio of 2.080, soil–binder ratio of 0.253, particle size under 0.075 mm, and water-reducing admixture of 0.06. [ABSTRACT FROM AUTHOR]

Shear strength of sandy gravel with cobbles is difficult to determine for usually an in situ test needs to be performed. Six group of in situ tests were conducted to investigate the shear strength of sandy gravel with cobbles. However, the inner friction angle was highly underestimated compared with those from the other methods. This failure result could be explained comprehensively. The strength parameters were also investigated using a DCP test, an experimental method and a theoretical method. Moreover, a numerical simulation method was also used to determine the failure mode of the in situ test. Through comprehensive comparison of these results, the soil failure mechanism in the tests did not follow the direct shear failure but did follow the bearing-capacity failure model. The bottom boundary could not provide enough capacity during the test; hence, the shear strength was underestimated. Moreover, the in situ test results could be explained through the Meyerhof bearing-capacity theory on shallow foundations subjected to inclined loads. With increasing normal load, the horizontal force decreased, resulting in a small inner-friction angle. The theoretical result of the inner-friction angle of sandy gravel with cobbles was 42 ~ 47.5° in these test, which coincided with the numerical simulation and empirical methods. [ABSTRACT FROM AUTHOR]

Background: Spinal cord injury (SCI) can result in structural and functional damage to the spinal cord, which may lead to loss of limb movement and sensation, loss of bowel and bladder control, and other complications. Previous studies have revealed the critical influence of trans-acting transcription factor 1 (SP1) in neurological pathologies, however, its role and mechanism in SCI have not been fully studied. Methods: The study was performed using mouse microglia BV2 stimulated using lipopolysaccharide (LPS) and male adult mice subjected to spinal hitting. Western blotting was performed to detect protein expression of SP1, 5-hydroxytryptamine (serotonin) receptor 2B (HTR2B), BCL2-associated x protein (Bax), B-cell lymphoma-2 (Bcl-2), inducible nitric oxide synthase (iNOS), clusters of differentiation 86 (CD86), Arginase 1 (Arg-1) and clusters of differentiation 206 (CD206). Cell viability and apoptosis were analyzed by MTT assay and TUNEL assay. mRNA levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), interleukin-4 (IL-4) and tumor necrosis factor-β (TNF-β) were quantified by quantitative real-time polymerase chain reaction. The association of SP1 and HTR2B was identified by chromatin immunoprecipitation assay and dual-luciferase reporter assay. HE staining assay was performed to analyze the pathological conditions of spinal cord tissues. Results: LPS treatment induced cell apoptosis and inhibited microglia polarization from M1 to M2 phenotype, accompanied by an increase of Bax protein expression and a decrease of Bcl-2 protein expression, however, these effects were relieved after SP1 silencing. Mechanism assays revealed that SP1 transcriptionally activated HTR2B in BV2 cells, and HTR2B knockdown rescued LPS-induced effects on BV2 cell apoptosis and microglial M1/M2 polarization. Moreover, SP1 absence inhibited BV2 cell apoptosis and promoted microglia polarization from M1 to M2 phenotype by decreasing HTR2B expression. SCI mouse model assay further showed that SP1 downregulation could attenuate spinal hitting-induced promoting effects on cell apoptosis of spinal cord tissues and microglial M1 polarization. Conclusion: SP1 transcriptionally activated HTR2B to aggravate traumatic SCI by shifting microglial M1/M2 polarization. [ABSTRACT FROM AUTHOR]

Representation-based methods have found widespread applications in various classification tasks. However, these methods cannot deal effectively with imbalanced data scenarios. They tend to neglect the importance of minority samples, resulting in bias toward the majority class. To address this limitation, we propose a density-based discriminative nonnegative representation approach for imbalanced classification tasks. First, a new class-specific regularization term is incorporated into the framework of a nonnegative representation based classifier (NRC) to reduce the correlation between classes and improve the discrimination ability of the NRC. Second, a weight matrix is generated based on the hybrid density information of each sample’s neighbors and the decision boundary, which can assign larger weights to minority samples and thus reduce the preference for the majority class. Furthermore, the resulting model can be efficiently optimized through the alternating direction method of multipliers. Extensive experimental results demonstrate that our proposed method is superior to numerous state-of-the-art imbalanced learning methods. [ABSTRACT FROM AUTHOR]

Collaborative representation-based classification (CRC) has been extensively applied to various recognition fields due to its effectiveness and efficiency. Nevertheless, it is generally suboptimal for imbalanced learning. Previous studies have revealed that a class-imbalance distribution can lead CRC, and even most conventional classification methods, to ignore the minority class and prioritize the majority class. To address this deficiency, this paper proposes a hybrid density-based adaptive weighted collaborative representation model that incorporates a regularization technique and an adaptive weight generation mechanism into the CRC framework. A new regularization term, based on class-specific representation, is introduced to decrease the correlation between classes and enhance CRC's discriminative ability. The sample distribution and density information within and between classes are employed to assign greater weights to minority samples, thereby strengthening the representation capabilities of minority samples and reducing the bias towards the majority class. Furthermore, it is theoretically demonstrated that this model has a closed-form solution. Its complexity is comparable to that of CRC, ensuring its efficiency. Extensive experiments on diverse data sets from the KEEL repository show the superiority of the proposed method compared to other state-of-the-art imbalanced classification methods. [ABSTRACT FROM AUTHOR]

This work aims to address two issues that often exist in least square regression (LSR) models for classification tasks, which are (1) learning a compact projection matrix for feature selection and (2) adopting relaxed regression targets. To this end, we first propose a sparse regularized LSR framework for feature selection by introducing the ℓ 2 , 1 regularizer. Second, we utilize two different strategies to relax the strict regression targets based on the sparse framework. One way is to exploit the -dragging technique. Another strategy is to directly learn the labels from the inputs and constrain the distance between true and false classes simultaneously. Hence, more feasible regression schemes are constructed, and the models will be more flexible. Further, efficient iterative methods are derived to optimize the proposed models. Various experiments on image databases intend to manifest our proposed models have outstanding recognition capability compared with many state-of-the-art classifiers. [ABSTRACT FROM AUTHOR]

Railway track settlements are extremely important for the safe operation of trains. This study utilizes an in situ test and a three-dimensional finite element method (3D FEM) to investigate the settlement of underpasses and railway tracks caused by shield tunneling. First, the 3D FEM results are compared with field monitoring data. Second, the settlement variation of tracks during shield construction is analyzed. Finally, the effect of the tunnel–underpass distance is observed. A comparative study establishes the reliability of the achieved 3D FEM results, which showed the consistency of railway track settlement with that of the underpass top plate. Based on the cutter head location, the underpass and railway track settlements were divided into three stages. With an increase in the tunnel–underpass distance, the underpass and railway track settlements increased, and the speed of increase was significantly higher when the tunnel was beyond the scope of the underpass. When the tunnel axis was within the scope of the underpass, the settlement of the bottom plate > top plate > railway track, and the differences between them were relatively small. Contrarily, the top plate settlement was larger than the bottom plate, while the railway track settlement increased. In both cases, the difference between the top and bottom plate settlements gradually decreased as the tunnel–underpass distance increased. This study shows that the underpass may have a settlement control effect on the deformation of railway tracks of high stiffness. [ABSTRACT FROM AUTHOR]

Underwater target detection plays a crucial role in marine environmental monitoring and early warning systems. It involves utilizing optical images acquired from underwater imaging devices to locate and identify aquatic organisms in challenging environments. However, the color deviation and low illumination in these images, caused by harsh working conditions, pose significant challenges to an effective target detection. Moreover, the detection of numerous small or tiny aquatic targets becomes even more demanding, considering the limited storage and computing power of detection devices. To address these problems, we propose the YOLOv7-CHS model for underwater target detection, which introduces several innovative approaches. Firstly, we replace efficient layer aggregation networks (ELAN) with the high-order spatial interaction (HOSI) module as the backbone of the model. This change reduces the model size while preserving accuracy. Secondly, we integrate the contextual transformer (CT) module into the head of the model, which combines static and dynamic contextual representations to effectively improve the model's ability to detect small targets. Lastly, we incorporate the simple parameter-free attention (SPFA) module at the head of the detection network, implementing a combined channel-domain and spatial-domain attention mechanism. This integration significantly improves the representation capabilities of the network. To validate the implications of our model, we conduct a series of experiments. The results demonstrate that our proposed model achieves higher mean average precision (mAP) values on the Starfish and DUO datasets compared to the original YOLOv7, with improvements of 4.5% and 4.2%, respectively. Additionally, our model achieves a real-time detection speed of 32 frames per second (FPS). Furthermore, the floating point operations (FLOPs) of our model are 62.9 G smaller than those of YOLOv7, facilitating the deployment of the model. Its innovative design and experimental results highlight its effectiveness in addressing the challenges associated with underwater object detection. [ABSTRACT FROM AUTHOR]

The damage variation of a masonry structure during shield tunneling has been investigated. Furthermore, the damage degree of the masonry building has been investigated by combining the field measurement, finite element method results, and theoretical method. The results show that compared with the theoretical calculation method LSTM, the method provide by this paper can give the detail damage location of the masonry structure caused by shield construction. Due to the existence of door and window openings, the result of JMM is larger than LSTM result, the differences can be modified by concept of "characteristic tensile strain". The wall of the masonry building encounter the shield face first suffers more damage than the later ones. At the beginning of tunnlling, the damage were generated from a small area at the bottom for wall 1, but a larger area at the top of the building for wall 2. The damage area increase more at the top of the building as tunneling advanced, but the maximum damage occurred at the bottom of the building. [ABSTRACT FROM AUTHOR]

A soil pressure balance rectangular pipe jacking project is investigated to find out the interaction of jacking control and ground settlement in Zhengzhou, China. The dimension of the rectangular pipe jacking excavation face is 6.94 m (width) × 4.24 m (height). The tunnel is 35.6 m long and 10.6 m beneath the ground in silty clay strata. The trajectory of the pipe jacking tunneling machine was measured during the whole construction. Meanwhile the construction sets like cutter pressure, jacking force, and grouting pressure were measured with sensors on the pipe jacking machine. The ground settlement was obtained throughout the rectangular pipe jacking process. The results showed that ground settlement variation started from 7.46 m in front of the cutter and ended with 9.79 m away from cutter. The ground settlement can be divided into four phases according to the settlement increasing pattern which is consistent with the distance from the cutter. The ratio of these four phases settlement is approximately 3:3:2:2. The trajectory of the jacking pipe tail has a nonnegligible effect on the settlement distribution characteristics of the ground. The vertical trajectory variation induces lager settlement increasing than horizontal trajectory. Ground settlement increases during the whole progress, but the increasing amplitude decreases with the increasing of cutter pressure, jacking force and grouting. [ABSTRACT FROM AUTHOR]

Most of the existing classification systems assume that the data used is high-quality labeled. However, the labeling process in real-world may inevitably introduce corruptions into labels which can confuse the performances of classifiers. In this paper, based on Broad Learning System (BLS), we propose a novel label noise tolerant method to classify the pattern with corrupted labels. The standard BLS has shown promising efficiency and accuracy in general classification, but its learning process is prone to be affected by the noisy labels. Here, by detailed probabilistic analysis, we first give the reason for lacks of robustness in standard BLS. Then a maximum likelihood estimation-based objective function is derived for robust classification. In addition, a manifold regularization term is integrated to preserve the local geometry of data, which makes the model to be more robust and flexible to learn the output weights. Given some basic assumptions on the approximation errors, the obtained model can be transformed to a graph regularized reweighted BLS problem. The negative effects of noisy labels in data can be inhibited adaptively by assigning reasonable weights. Theoretical analysis and extensive experiments are provided to demonstrate the robustness and effectiveness of the proposed robust BLS model, especially for the case of large amounts of noisy labels. [ABSTRACT FROM AUTHOR]

Load-bearing pile foundations induce soil stress changes and ground deformation, which affect the safety of nearby tunnels. Centrifuge model tests and numerical simulations were conducted to investigate the effects of bored piles on existing tunnels in clay. The effects of pile length, pile–tunnel distance, and pile–tunnel depth on the tunnel moment and settlement were analyzed by comparing the results of both centrifuge model tests and numerical simulations. The results revealed that the tunnel longitudinal moment increased with the pile load but decreased with the net distance between the pile and tunnel. The circumferential moments near the pile bottom were larger than those near the other parts. The maximum tunnel moments were observed for the case with the pile and tunnel at the same depth. The tunnel moments for the case with the pile tip above the tunnel were greater than those in the case with the pile tip below the tunnel. The results obtained in this study provide valuable insight into the effect of loaded piles on nearby existing tunnels and the design of buildings near subways. [ABSTRACT FROM AUTHOR]

This paper studies the communication smooth switching problem of time-varying formation control. When the formation system performs topology switching, sudden changes in communication will cause communication failure and affect formation control. To avoid this adverse impact, we introduce a smooth transition function of communication topology. At the same time, for the formation system with unknown nonlinear dynamics, an adaptive backstepping controller combining the backstepping control method and the fuzzy logic system is designed. Then, based on Lyapunov stability theory, we prove the stability of the designed controller. The results of the simulation experiments can verify the effectiveness of the designed controller. [ABSTRACT FROM AUTHOR]

Due to the low computational complexity, the two-phase test sample representation method shows outstanding advantages in the field of real-time face recognition. However, its first phase does not fully consider the imbalance of the determined K-nearest training samples. This defect is not well reflected and will seriously affect the recognition accuracy of the second phase. In this paper, we explore the above issues and propose to incorporate the unselected training samples into the modeling process. The proposed method not only allows the unselected samples to perform the final representation but also makes the selected nearest training samples play a more significant role than the unselected ones in classification. It is efficiently solved with an analytical solution. The rationales and probability interpretation of the proposed method are presented to further guarantee its rationality and effectiveness. Extensive experiments on diverse face databases are conducted to demonstrate the superior recognition performance in comparison with other competing classifiers. [ABSTRACT FROM AUTHOR]

Model tests were performed to investigate the lateral earth pressure acting on the retaining structure adjacent to both natural ground (NG) and composite foundation (CFRLP), which were supported with rigid-flexible and long-short piles. Two testing procedures, namely, applying a load to the foundation and rotating the retaining structure along its toe, were considered. The results indicate that the additional lateral earth pressure acting on the retaining structure adjacent to the CFRLP is less than that of the NG in the depth of the reinforcement area strengthened by flexible piles. Compared with NG, the CFRLP yielded a smaller normalized height of application of the lateral earth pressure, suggesting that the CFRLP blocked the horizontal diffusion of the load and had a strong ability to transfer the surcharge load to the deep soil. When rotating the retaining structure, the lateral earth pressure acting on the upper part of the retaining structure experienced limited reduction once the displacement at the top of the retaining structure was greater than 8 mm, whereas the pressure acting on the lower part of the retaining structure continued to decrease with increasing displacement. In addition, a three-dimensional finite element model (FEM) was used to investigate the influence of the pile parameter and the wall-soil friction angle on the additional lateral earth pressure. [ABSTRACT FROM AUTHOR]

With the development of machine learning and computer vision, classification technology is becoming increasingly important. Due to the advantage in efficiency and effectiveness, collaborative representation-based classifiers (CRC) have been applied to many practical cognitive fields. In this paper, we propose a new neighborhood prior constrained collaborative representation model for pattern classification. Compared with the naive CRC models which approximate the test sample with all the training data globally, our proposed methods emphasize the guidance of the neighborhood priors in the coding process. Two different kinds of neighbor priors and the models' weighted extensions are explored from the view of sample representation ability and relationships between the samples. Consequently, the contributions of different samples can be distinguished adaptively and the obtained representations can be more discriminative for the recognition. Experimental results on several popular databases can verify the effectiveness of our proposed methods in comparison with other state-of-the-art classifiers. [ABSTRACT FROM AUTHOR]

Lateral swelling pressure (LSP) develops when expansive soil volume increment associated with water infiltration is restrained in a confined domain, for example, due to construction of civil infrastructure. In this paper, initially a flowchart is developed to highlight various key factors that influence the LSP mobilization according to lab and field studies collected from previous literature studies. Then extending unsaturated soil mechanics, a theoretical framework is proposed for illustrating the LSP mobilization in the field against retaining structures and pile foundations under different boundary conditions, respectively. An example problem for a basement wall and a pile foundation constructed in a typical expansive soil from Regina, Canada, is presented to illustrate the proposed theoretical framework. The framework and corresponding analysis presented in this paper can facilitate to provide rational designs of geotechnical infrastructures in expansive soils. [ABSTRACT FROM AUTHOR]

Bioretention facilities have commonly been used to reduce the runoff volume, peak discharge, and pollution in runoff to the downstream drainage system during sponge city construction. The curb inlet interception efficiency determines how much of the runoff from the road surface enters the bioretention cell directly. Most previous studies have focused on the method of designing the curb inlet itself, whereas few have paid attention to evaluating the curb inlet efficiency in unsteady rainfall situations. In this study, a full-scale rainfall simulation system and a road surface with a curb inlet were built to examine the curb inlet efficiency under such conditions. It was found that methods from the literature for predicting the curb inlet efficiency produced large errors in small rainfall (low runoff depth of upstream inflow) situations. Therefore, a modified method was proposed based on experimental results to evaluate the curb inlet efficiency more accurately under unsteady rainfall situations. [ABSTRACT FROM AUTHOR]

Background: Colloid-facilitated phosphorus (P) transport is recognized as an important pathway for the loss of soil P in agricultural systems; however, information regarding soil aggregate-associated colloidal P (Pcoll) is lacking. To elucidate the effects of aggregate size on the potential loss of Pcoll in agricultural systems, soils (0–20 cm depth) from six land-use types were sampled in the Zhejiang Province in the Yangtze River Delta region, China. The aggregate size fractions (2–8 mm, 0.26–2 mm, 0.053–0.26 mm and < 0.053 mm) were separated using the wet sieving method. Colloidal P and other soil parameters in aggregates were analyzed. Results: Our study demonstrated that 0.26–2 mm small macroaggregates had the highest total P (TP) content. In acidic soils, the highest Pcoll content was observed in the 0.26- to 2-mm-sized aggregates, while the lowest was reported in the < 0.053 mm (silt + clay)-sized particles, the opposite of that revealed in alkaline and neutral soils. Paddy soils contained less Pcoll than other land-use types. The proportion of Pcoll in total dissolved P (TDP) was dominated by < 0.053 mm (silt + clay)-sized particles. Aggregate size strongly influenced the loss potential of Pcoll in paddy soils, where Pcoll contributed up to 83% TDP in the silt + clay-sized particles. The Pcoll content was positively correlated with TP, Al, Fe, and the mean weight diameter. Aggregate-associated total carbon (TC), total nitrogen (TN), C/P, and C/N had significant negative effects on the contribution of Pcoll to potential soil P loss. The Pcoll content of the aggregates was controlled by the aggregate-associated TP and Al content, as well as the soil pH value. The potential loss of Pcoll from aggregates was controlled by its organic matter content. Conclusion: We concluded that management practices that increase soil aggregate stability or its organic carbon content will limit Pcoll loss in agricultural systems. [ABSTRACT FROM AUTHOR]

Most existing traffic sign detection models suffer from high computational complexity and superior performance but cannot be deployed on edge devices with limited computational capacity, which cannot meet the direct needs of autonomous vehicles for detection model performance and efficiency. To address the above concerns, this paper proposes an improved SEDG-Yolov5 traffic sign detection method based on knowledge distillation. Firstly, the Slicing Aided Hyper Inference method is used as a local offline data augmentation method for the model training. Secondly, to solve the problems of high-dimensional feature information loss and high model complexity, the inverted residual structure ESGBlock with a fused attention mechanism is proposed, and a lightweight feature extraction backbone network is constructed based on it, while we introduce the GSConv in the feature fusion layer to reduce the computational complexity of the model further. Eventually, an improved response-based objectness scaled knowledge distillation method is proposed to retrain the traffic sign detection model to compensate for the degradation of detection accuracy due to light-weighting. Extensive experiments on two challenging traffic sign datasets show that our proposed method has a good balance on detection precision and detection speed with 2.77M parametric quantities. Furthermore, the inference speed of our method achieves 370 FPS with TensorRT and 35.6 FPS with ONNX at FP16-precision, which satisfies the requirements for real-time sign detection and edge deployment. [ABSTRACT FROM AUTHOR]

In this paper, the main factors impacting the plug flow pattern of a clearwell were investigated by integrating pilot-scale, full-scale clearwell tracer testing and computational fluid dynamics (CFD) simulation. It was found that pilot tracer testing, full-scale tracer testing and CFD simulation all demonstrated that the correlation between the ratio of t 10/ T and L/W can be approximately expressed by: t 10/ T = 0.189 4ln( L/W)-0.049 4. This study confirmed that the installation of baffles within clearwells is an efficient way to optimize their configuration. In addition, the inlet velocity has a minimal contribution to the ratio of t 10/ T. However, the ratio of turning channel width to channel width ( d/W) significantly contributes to the ratio of t 10/ T. The optimal ratio of d/W is 0.8–1.2 for maintaining better plug flow pattern. The number of turning channels is one of the main factors that impact the ratio of t 10/ T. When increasing the number of turning channels, a lower ratio of t 10/ T is obtained. [ABSTRACT FROM AUTHOR]