Local Loss Research Articles

SHIP1 deficiency causes inflammation-dependent retardation in skeletal growth.

Inflammation and skeletal homeostasis are closely intertwined. Inflammatory diseases are associated with local and systemic bone loss, and post-menopausal osteoporosis is linked to low-level chronic inflammation. Phosphoinositide-3-kinase signalling is a pivotal pathway modulating immune responses and controlling skeletal health. Mice deficient in Src homology 2-containing inositol phosphatase 1 (SHIP1), a negative regulator of the phosphoinositide-3-kinase pathway, develop systemic inflammation associated with low body weight, reduced bone mass, and changes in bone microarchitecture. To elucidate the specific role of the immune system in skeletal development, a genetic approach was used to characterise the contribution of SHIP1-controlled systemic inflammation to SHIP1-dependent osteoclastogenesis. Lymphocyte deletion entirely rescued the skeletal phenotype in Rag2 -/- /Il2rg -/- /SHIP1 -/- mice. Rag2 -/- /Il2rg -/- /SHIP1 -/- osteoclasts, however, displayed an intermediate transcriptomic signature between control and Rag2 +/+ /Il2rg +/+ /SHIP1 -/- osteoclasts while exhibiting aberrant in vitro development and functions similar to Rag2 +/+ /Il2rg +/+ /SHIP1 -/- osteoclasts. These data establish a cell-intrinsic role for SHIP1 in osteoclasts, with inflammation as the key driver of the skeletal phenotype in SHIP1-deficient mice. Our findings demonstrate the central role of the immune system in steering physiological skeletal development.

On Local Stability Loss of Modified Composites with Whiskerized Fibers

This article examines the critical compressive stresses required for a modified fiber composite to remain straight while the fibers within it bend. It was assumed that the modified composite consists of three phases: fiber, whiskerized interfacial layer, and matrix. An example of a composite material made up of carbon fibers, a whiskerized layer of carbon nanotubes with an epoxy matrix, and an epoxy matrix was considered. Its physical parameters affecting the critical compressive stresses were assessed, and methods for determining them were proposed. The effective properties of the inclusion and binder composite material were identified using the Voigt and Reis methods. Similarly, the effective properties of the interfacial whiskerized layer were analyzed by the three-phase method. The influence of fiber wavelength and phase shift, which define the destruction of the composite material, on the critical compressive stress value was explored. The wavelengths at which the composite material is destroyed were found. The effect of the volume content of the modified inclusion on the minimum critical compressive stress value was shown. The results for the modified composites were compared with those for the classical composites with a similar volume content of inclusions.

Investigation on the pressure drop characteristics of ITER thermal shield cooling pipes

This paper presents the experimental results of the pressure drop through the cooling pipes of the ITER Thermal Shield (TS) panels. High pressure and room temperature nitrogen gas is selected for the experiment, which is equivalent operating condition with the 80 K helium gas from fluid mechanics point of view. Flow rate is set by a mass flow controller and pressure difference between the inlet and the outlet of the cooling pipe is measured by a differential pressure gauge. The experimental set-up is open loop type, which is connected to high pressure gas bottle. Flexible corrugated pipes are used to connect the TS cooling pipes with the measurement system line. The effect of the corrugated pipe is evaluated separately and excluded from the measurement results of the TS pipes. Test results of several TS panels are shown in this paper and are compared with the calculation using existing friction factor correlation and local loss coefficient of the pipe bends. The limitation of the calculation is discussed considering the hydrodynamic developing flow in the pipe routing.

Data augmentation for deep visual recognition using superpixel based pairwise image fusion

Data augmentation is an important paradigm for boosting the generalization capability of deep learning in image classification tasks. Image augmentation using cut-and-paste strategies has shown very good performance improvement for deep learning. However, these existing methods often overlook the image’s discriminative local context and rely on ad hoc regions consisting of square or rectangular local regions, leading to the loss of complete semantic object parts. In this work, we attempt to overcome these limitations and propose a superpixel-wise local-context-aware efficient image fusion approach for data augmentation. Our approach requires only one forward propagation using a superpixel attention-based label fusion with less computational complexity. The model is trained using a combination of a global classification of the fused (augmented) image loss, a superpixel-wise weighted local classification loss, and a superpixel-based weighted contrastive learning loss. The last two losses are based on the superpixel-aware attentive embeddings. Thus, the resulting deep encoder can learn both local and global features of the images while capturing object-part local context and information. Experiments on diverse benchmark image datasets indicate that the proposed method out-performs many region-based augmentation methods for visual recognition. We have demonstrated its effectiveness not only on CNN models but also on transformer models. The codes are accessible at https://github.com/DanielaPlusPlus/SAFuse.

Confirmation of Skywalker Hoolock Gibbon (Hoolock tianxing) in Myanmar Extends Known Geographic Range of an Endangered Primate

Characterizing genetically distinct populations of primates is important for protecting biodiversity and effectively allocating conservation resources. Skywalker gibbons (Hoolock tianxing) were first described in 2017, with the only confirmed population consisting of 150 individuals in Mt. Gaoligong, Yunnan Province, China. Based on river geography, the distribution of the skywalker gibbon has been hypothesized to extend into Myanmar between the N’Mai Kha and Ayeyarwaddy Rivers to the west, and the Salween River (named the Thanlwin River in Myanmar and Nujiang River in China) to the east. We conducted acoustic point-count sampling surveys, collected noninvasive samples for molecular mitochondrial cytochrome b gene identification, and took photographs for morphological identification at six sites in Kachin State and three sites in Shan State to determine the presence of skywalker gibbons in predicted suitable forest areas in Myanmar. We also conducted 50 semistructured interviews with members of communities surrounding gibbon range forests to understand potential threats. In Kachin State, we audio-recorded 23 gibbon groups with group densities ranging between 0.57 and 3.6 group/km2. In Shan State, we audio-recorded 21 gibbon groups with group densities ranging between 0.134 and 1.0 group/km2. Based on genetic data obtained from skin and saliva samples, the gibbons were identified as skywalker gibbons (99.54–100% identity). Although these findings increase the species’ known population size and confirmed distribution, skywalker gibbons in Myanmar are threatened by local habitat loss, degradation, and fragmentation. Most of the skywalker gibbon population in Myanmar exists outside protected areas. Therefore, the IUCN Red List status of the skywalker gibbon should remain as Endangered.

A Deep Learning Method for Building Extraction from Remote Sensing Images by Fuzing Local and Global Features

As important disaster-bearing bodies, buildings are the focus of attention in seismic disaster risk assessment and emergency rescue. It is of great practical significance to extract buildings quickly and accurately with complex textures and variable scales and shapes from high-resolution remote sensing images. We proposed an improved TransUnet model based on multiscale grouped convolution and attention named MATUnet to retain more local detail features and enhance the representation ability of global features, while reducing the network parameters. We designed the multiscale grouped convolutional feature extraction module with attention (GAM) to enhance the representation of detailed features. The convolutional positional encoding module (PEG) was added to redetermine the number of transformer, it solved the problem of local feature information loss and the difficulty of convergence of the network. The channel attention module (CAM) of the decoder enhanced the salient information of the features and solved the problem of information redundancy after feature fusion. We experimented through MATUnet on the WHU building dataset and Massachusetts dataset. MATUnet achieved the best IOU results of 92.14% and 83.22%, respectively, and achieved better than the other generalized and state-of-the-art networks under the same conditions. We also have achieved good segmentation results on the GF2 Xichang building dataset.

Face photo-line drawings synthesis based on local extraction preserving generative adversarial networks

ABSTRACT Facial photo-to-sketch synthesis is crucial for entertainment and criminal investigations, yet challenges persist, including local detail blurring and identity feature loss. To mitigate these problems in face sketch synthesis, We propose a technique for synthesizing photographic sketches of faces using generative adversarial networks that focus on image localization to extract and preserve image identity features – namely LEPGAN. Our method introduces an image local extraction module, an attention mechanism in the generator, and an extended U-Net structure to enhance critical image features and preserve identity information. Multi-scale perceptual and local loss functions further enhance synthetic image quality. LEPGAN outperforms existing methods, producing images with crisper facial details that closely align with human visual perception, effectively preserving unique identity characteristics. Our approach represents a significant advancement in face sketch synthesis for various applications.

Microstructural integrity of the locus coeruleus and its tracts reflect noradrenergic degeneration in Alzheimer’s disease and Parkinson’s disease

BackgroundDegeneration of the locus coeruleus (LC) noradrenergic system contributes to clinical symptoms in Alzheimer’s disease (AD) and Parkinson’s disease (PD). Diffusion magnetic resonance imaging (MRI) has the potential to evaluate the integrity of the LC noradrenergic system. The aim of the current study was to determine whether the diffusion MRI-measured integrity of the LC and its tracts are sensitive to noradrenergic degeneration in AD and PD.MethodsPost-mortem in situ T1-weighted and multi-shell diffusion MRI was performed for 9 AD, 14 PD, and 8 control brain donors. Fractional anisotropy (FA) and mean diffusivity were derived from the LC, and from tracts between the LC and the anterior cingulate cortex, the dorsolateral prefrontal cortex (DLPFC), the primary motor cortex (M1) or the hippocampus. Brain tissue sections of the LC and cortical regions were obtained and immunostained for dopamine-beta hydroxylase (DBH) to quantify noradrenergic cell density and fiber load. Group comparisons and correlations between outcome measures were performed using linear regression and partial correlations.ResultsThe AD and PD cases showed loss of LC noradrenergic cells and fibers. In the cortex, the AD cases showed increased DBH + immunoreactivity in the DLPFC compared to PD cases and controls, while PD cases showed reduced DBH + immunoreactivity in the M1 compared to controls. Higher FA within the LC was found for AD, which was correlated with loss of noradrenergic cells and fibers in the LC. Increased FA of the LC-DLPFC tract was correlated with LC noradrenergic fiber loss in the combined AD and control group, whereas the increased FA of the LC-M1 tract was correlated with LC noradrenergic neuronal loss in the combined PD and control group. The tract alterations were not correlated with cortical DBH + immunoreactivity.ConclusionsIn AD and PD, the diffusion MRI-detected alterations within the LC and its tracts to the DLPFC and the M1 were associated with local noradrenergic neuronal loss within the LC, rather than noradrenergic changes in the cortex.

Landslide disaster risk analysis at Karanganyar district, Central Java province

The condition of Karanganyar Regency is formed by fragile and volcanic rocks weathered soil thickness and supported by high rainfall is a condition that has the potential to cause landslides. increasing population and intensive land use led to high risk of landslides. Landslides have occurred many times in the district Karanganyar. A combination of anthropogenic and natural factors often becomes cause of landslides that killed local residents and property loss. Large landslides have occurred in Karanganyar on December 26, 2007 which claimed 62 people died world. Landslide risk analysis research was carried out by entering several main components, namely hazard, susceptibility, and capacity. A qualitative approach was applied to carry out the analysis in the districts Karanganyar. The output of this study is a landslide risk map. Avalanche risk analysis was carried out at 3 selected locations experience landslides and the potential for such disasters in the Regency Karanganyar. The results of research on this topic are expected to be able to socialized so that local governments are able to develop plans sustainable development.

A STUDY OF CLINICAL PROFILE AND OUTCOME OF PATIENTS SUFFERING FROM NECROTIZING SOFT TISSUE INFECTION

Necrotizing fasciitis (NF) is a rare but dangerous soft tissue necrosis that frequently affects fascia and subcutaneous tissues and has a high hospital mortality rate. The term necrotizing soft tissue infections refers to a wide variety of bacterial and fungal skin conditions. The location, depth, and extent of the infection are all considered when describing the condition examples are necrotizing fasciitis and Fourniers gangrene, which are both deep subcutaneous infections. Necrotizing soft tissue infections can result in substantial local tissue loss, tissue necrosis, systemic toxicity, and even mortality, depending on the degree of invasion. Despite improvements in surgery and the development of antibiotics, necrotizing soft tissue infections are known to have fatality rates that range from 6 percent to up to 76 percent. The goals of the current study are to: Understand the clinical characteristics of patients who present with NSTI early diagnosis by imaging study the microbial flora, antibiotic therapy and observe the clinical effects of the debridement.

Investigation of hydraulic losses in different clocking positions of pump-turbine in pump mode

With the increasing significance of pumped storage in the power system, there is a growing emphasis on improving the hydraulic performance of pump-turbine at pump mode. Consequently, this study aims to investigate the clocking effects of the stay vane and guide vane in order to enhance hydraulic performance. Moreover, the local hydraulic loss rate method is employed to visualize the loss distribution of each component. The results demonstrate that the clocking effect significantly impacts off-design conditions. Specifically, for different clocking positions of the stay vane, the maximum efficiency difference at 0.8Qd and 1.2Qd conditions is 0.14 % and 0.86 % respectively. Similarly, for the guide vane, the values are 0.54 % and 0.34 % respectively. Furthermore, different clocking schemes result in significant changes in hydraulic losses in the volute and stay vane. For the 0.8Qd condition, the hydraulic losses inside the impeller and guide vanes vary significantly with the change in the velocity gradient at the impeller outlet. The optimal clocking effect position for the guide vanes occurs when the trailing edge and the tongue are aligned, and similarly, the position for the stay vanes is when the tongue is located at the 2/3 point of the stay vane flow passage. The study can provide a theoretical guiding significance for structural optimization and installation position of pump-turbine.

Urban Heat Island and Reduced Habitat Complexity Explain Spider Community Composition by Excluding Large and Heat-Sensitive Species

Along with worldwide urbanization, upheavals in habitat and temperature are major threats for biodiversity. However, due to their interdependence, their relative roles as drivers of animal community composition remain entangled. Here, we investigated how taxonomic and functional compositions of arthropod communities were related to uncorrelated habitat and temperature gradients, and compared landscape (i.e., urbanization, Urban Heat Island (UHI)) to local variables (i.e., vegetation height and cover, near-ground temperature). We sampled 20,499 spiders (137 species) on 36 grasslands in Rennes (northwestern France). Unlike rural areas, urban sites were characterized by short vegetation and intense UHI, hosted species-poor communities, and were composed of small thermophilic species. UHI intensification and local loss of habitat complexity (short and dense vegetation) were associated with declining large and heat-sensitive species. These results highlight the prevalent role of urban warming, rather than land cover change, as an urban filter. Further, we show that landscape-scale UHI, not local temperature, filters species according to their functional attributes. UHI can therefore be considered as a thermal barrier, filtering species according to their physiological capacity to cope with urban thermal conditions. Finally, to counterbalance biotic homogenization, we argue for the importance of implementing complex habitat structures at the local scale within urban green infrastructure.

Optimization of characteristic parameters of rectangular solar chimney adapted to agricultural greenhouses

In order to build a composite application scenario for the synergistic development of clean energy generation and agricultural production, this research designs a solar chimney equipped with a rectangular collection system according to the structural characteristics of agricultural greenhouses. With collector efficiency as the primary objective and theoretical power as the secondary objective, the infusion angle is designed for the connecting section between the collection system and the chimney from the perspective of reducing the local resistance loss, and the transition factor ζ is introduced to define it accurately. Response surface methodology was then used to analyze the effect of the level of key system characteristics on collector efficiency and static pressure, and a regression model was developed to determine the best combination within the target optimization range. Results show that the infusion angle prevents too much solar energy from being lost in the vortex by reducing the local resistance loss, which increases the collector efficiency of the system. And when the transition factor is 0, the divergence angle is 2.86°, and the inlet height is 0.05 m, the collector efficiency and static pressure reach 48.75 % and −6.1 pa, respectively, which are 213 % and 563 % higher than the original model.

GLOCAL: A self-supervised learning framework for global and local motion estimation

Motions in videos are typically a mixture of local dynamic object motions and global camera motion, which are inconsistent in some cases, and even interfere with each other, causing difficulties in various downstream applications, such as video stabilization that requires the global motion, and action recognition that consumes local motions. Therefore, it is crucial to estimate them separately. Existing methods separate two motions from the mixed motion fields, such as optical flow. However, the quality of mixed motion determines the higher bounds of the performance. In this work, we propose a framework, GLOCAL, to directly estimate global and local motions simultaneously from adjacent frames in a self-supervised manner. Our GLOCAL consists of a Global Motion Estimation (GME) module and a Local Motion Estimation (LME) module. The GME module involves a mixed motion estimation backbone, an implicit bottleneck structure for feature dimension reduction, and an explicit bottleneck for global motion recovery based on the global motion bases with foreground mask under the training guidance of proposed global reconstruction loss. An attention U-Net is adopted for LME which produces local motions while excluding motion of irrelevant regions under the guidance of proposed local reconstruction loss. Our method can achieve better performance than the existing methods on the homography estimation dataset DHE and the action recognition dataset NCAA and UCF-101.

GaitMGL: Multi-Scale Temporal Dimension and Global–Local Feature Fusion for Gait Recognition

Gait recognition has received widespread attention due to its non-intrusive recognition mechanism. Currently, most gait recognition methods use appearance-based recognition methods, and such methods are easily affected by occlusions when facing complex environments, which in turn affects the recognition accuracy. With the maturity of pose estimation techniques, model-based gait recognition methods have received more and more attention due to their robustness in complex environments. However, the current model-based gait recognition methods mainly focus on modeling the global feature information in the spatial dimension, ignoring the importance of local features and their influence on recognition accuracy. Meanwhile, in the temporal dimension, these methods usually use single-scale temporal information extraction, which does not take into account the inconsistency of the motion cycles of the limbs when a human body is walking (e.g., arm swing and leg pace), leading to the loss of some limb temporal information. To solve these problems, we propose a gait recognition network based on a Global–Local Graph Convolutional Network, called GaitMGL. Specifically, we introduce a new spatio-temporal feature extraction module, MGL (Multi-scale Temporal and Global–Local Spatial Extraction Module), which consists of GLGCN (Global–Local Graph Convolutional Network) and MTCN (Multi-scale Temporal Convolutional Network). GLGCN models both global and local features, and extracts global–local motion information. MTCN, on the other hand, takes into account the inconsistency of local limb motion cycles, and facilitates multi-scale temporal convolution to capture the temporal information of limb motion. In short, our GaitMGL solves the problems of loss of local information and loss of temporal information at a single scale that exist in existing model-based gait recognition networks. We evaluated our method on three publicly available datasets, CASIA-B, Gait3D, and GREW, and the experimental results show that our method demonstrates surprising performance and achieves an accuracy of 63.12% in the dataset GREW, exceeding all existing model-based gait recognition networks.

Patronus charm: a comparison of benefactor plants and climate mediation effects on diversity

Deserts are subject to significant anthropogenic pressure. The capacity to buffer against changes in the local environment and biodiversity are critical for ecosystem functioning. Foundation species can be a solution to rapidly assess ecological function and provide a simple nature‐based solution to protect against continuing biodiversity losses. A foundation species is defined as a species that exerts and promotes a positive set of processes for the biotic network. Two different shrub species in the central drylands of California were used to assay a potential buffer for plant species richness and to examine the species‐specificity of foundation facilitation. A five‐year dataset in two distinct regions differing in aridity was used to test the hypothesis that the direct effects of foundation plants facilitate other plant species and buffer diversity losses to a changing climate. The predicted positive effects of both shrub species on species richness increased with increasing local temperatures sampled. Finally, projected temperature increases for the region in trained Bayesian models demonstrated that both shrub species can profoundly increase in their capacity to facilitate plant species richness. Colloquially, this positive ecological effect can be described as the patronus charm hypothesis because regardless of the form of the protector, shrub species provided a talisman against local loss of richness driven by temperature increases.

Power-loss methodology for a compressor cascade at various Reynolds numbers and its validation

Finding ways to identify and quantify the losses from various sources in turbomachinery is significant for understanding the physical loss mechanisms and improving aerodynamic performance. However, traditional loss-assessment methods fail to reveal the local losses and decouple the flow field. In this paper, a new power-loss methodology is proposed. This methodology defines local and accumulated power losses, and a new method of averaging the total outlet pressure is presented. This establishes a direct relationship between the well-known total pressure loss and the accumulated power loss. The method was verified based on experimental results, the Reynolds-averaged Navier–Stokes equations, and large-eddy simulations of a compressor cascade at various Reynolds numbers. By applying this method, the boundary-layer loss, separation loss, and trailing-edge mixing loss of the compressor cascade were successfully distinguished and quantitatively accounted for. The method has been shown to be a valuable tool for understanding and quantifying the losses experienced in different flow regimes. In conclusion, the power-loss methodology demonstrates the potential for accurate quantitative analysis of local and global loss generation, the investigation of physical mechanisms, and the development of physical models for diverse complex flows beyond just the compressor cascade flow.

Умови та вплив глобалізаційних перетворень на діяльність бізнес-структур

The study is devoted to the analysis of how globalization processes affect various aspects of doing business. The novelty of the study lies in several key aspects: for the first time, the concept of preconditions for globalization transformations, factors and phenomena is defined and differentiated, their detailed description is made using the latest statistical data of world-wide development. Globalization phenomena and factors are systematized by both the positive and negative consequences of impact on socioeconomic development. The consequences of the impact of globalization transformations on business structures, in particular on innovative development, automation of processes, improvement of logistics, improvement of communications, management, expansion of sales markets, are studied. As a result of the study, approaches to understanding globalization as a multifaceted process that covers the socioeconomic, political, technological, and cultural aspects of society are systematized. The key preconditions for globalization, including the development of informatization, the introduction of new technologies, political changes and economic integration, are analyzed. It is found that these factors enable interdependence and interactivity at the global level, fostering the convergence of different national systems. Conclusions are drawn about the twofold impact of globalization: on the one hand, it stimulates economic integration, free movement of goods and services, development of technology, increase in productivity of economies, exchange of cultures and development of intellectual capital; on the other hand, it leads to economic inequalities, negative impact on local producers, environmental problems, political conflicts and loss of cultural uniqueness. The study also characterizes the impact of globalization on business, including innovation, digitalization, process automation, market expansion, the introduction of omnichannel retail, logistics optimization, reduction of delivery costs, as well as the development of new forms of financing and modern approaches to management.

HFcγRIIa: a double-edged sword in osteoclastogenesis and bone balance in transgenic mice.

Rheumatoid arthritis (RA) is a chronic autoimmune disease accompanied by local and systemic bone loss. FcγRs, especially FcγRIIa (hFcγRIIa), have been implicated in the pathogenesis of RA. However, the contribution of hFcγRIIa to bone loss has not been fully elucidated. In the present study, we demonstrated the double-edged sword role of hFcγRIIa on osteoclast differentiation through investigations involving hFcγRIIa-transgenic (hFcγRIIa-Tg) mice. Our findings reveal that hFcγRIIa-Tg mice, previously shown to exhibit heightened susceptibility to collagen-induced arthritis (CIA), displayed increased osteoporosis during CIA or at advanced ages (40 weeks), accompanied by heightened in vivo osteoclast differentiation. Notably, bone marrow cells from hFcγRIIa-Tg mice exhibited enhanced efficiency in differentiating into osteoclasts and bone resorption in vitro compared to wild-type mice when stimulated with receptor activators of NF-κB ligand (RANKL). Additionally, hFcγRIIa-Tg mice exhibited augmented sensitivity to RANKL-induced bone loss in vivo, highlighting the osteoclast-promoting role of hFcγRIIa. Mechanistically, bone marrow cells from hFcγRIIa-Tg mice displayed heightened Syk self-activation, leading to mTOR-pS6 pathway activation, thereby promoting RANKL-driven osteoclast differentiation. Intriguingly, while hFcγRIIa crosslinking hindered RANKL-induced osteoclast differentiation, it activated the kinase cAbl, subsequently triggering STAT5 activation and inhibiting the expression of osteoclast-associated genes. This study provides novel insights into hFcγRIIa-mediated osteoclast biology, suggesting promising therapeutic targets for managing bone remodeling disorders.

NUMERICAL METHODS OF HYDRO-DYNAMIC COUPLING IN SATURATED SOIL AND ITS APPLICATION TO RAILWAY ENGINEERING

Recent field case study shows that the roadbed of ballastless high-speed railway experienced water-induced defect such as excessive fines pumping and even local subgrade-track contact loss affecting the normal operation of highspeed train due to water immersion through gaps of waterproof materials in expansion joints between the concrete base, particularly in rainy seasons. However, the study about the dynamic behavior of high-speed railway subgrade involving water is currently rare. Based on the theory of fluid dynamics in porous medium and the vehicle-track coupling vibration theory, a numerical method of hydraulic-dynamic coupling was established to evaluate the dynamic responses of saturated roadbed surface layer under the high-speed train loading with the validation by comparing the calculated values and field data. The temporal and spatial characteristics of dynamic behaviors (stress, pore water pressure, seepage velocity, displacement) of saturated roadbed surface layer are fully discussed. Also, the effects of train velocity, permeability, on aforementioned dynamic responses of the saturated roadbed surface layer are evaluated. The study shows that improving the drainage of ballastless track roadbed has a significant effect on minimizing the mud pumping of ballastless track, and the influence zone of hydraulic-mechanical coupling is mainly within 0.1 m of the roadbed.