Surrounding rock pressure in the tunnel portal section through moraine under freeze-thaw action

Moraines,characterized by the accumulation of rock and soil debris transported by glacial activity,present unique challenges for tunnel construction,particularly in portal sections,due to prevailing geographical and climatic conditions that facilitate freeze-thaw action.Despite these challenges,there is a dearth of studies investigating the influence of freeze-thaw action and water content on the mechanical properties of moraines,and no research on calculating surrounding rock pressure in moraine tunnels subjected to freeze-thaw conditions.In this study,direct shear tests under freeze-thaw cycles were conducted to examine the effects of freeze-thaw cycles and water content on the mechanical properties of frozen moraine.A comprehensive parameter K,integrating the number of freeze-thaws and water content,was introduced to model cohesion c.Drawing on Terzaghi Theory,we propose an improved algorithm for calculating surrounding rock pressure at the portal section of moraine tunnels.Using a tunnel as a case study,surrounding rock pressure was calculated under various conditions to validate the Improved Algorithm's efficacy.The results show that:(1)Strength loss exhibits a linear trend with the number of freeze-thaw cycles at water content levels of 4%and 8%,while at 12%water content,previous freeze-thaw cycles induce more significant damage to the soil.(2)Moraine saturation peaks between 8%and 12%water content.Following repeated freeze-thaw cycles,moraine shear strength initially increases before decreasing with varying water content.(3)The internal friction angle of moraine experiences slight reductions with prolonged freeze-thaw cycles,but both freeze-thaw cycles and water content significantly influence cohesion.(4)Vertical surrounding rock pressure increases after the initial freeze-thaw cycle,particularly with higher water content,although freeze-thaw cycles have minimal effect on it.(5)Freeze-thaw cycles lead to a substantial increase in lateral surrounding rock pressure,necessitating reinforced support structures at the arch wall,arch waist,and arch foot in engineering projects to mitigate freeze-thaw effects.This study provides a foundation for designing and selecting tunnel support structures in similar geological conditions.

Experimental investigation and prediction model for UCS loss of unsaturated sandstones under freeze-thaw action

Sandstone is widely distributed in cold regions and the freeze-thaw deterioration of them has caused many geological engineering disasters.As an important and direct index of frost resistance,the strength loss of sandstones under freeze-thaw actions should be investigated to provide a guidance for the stability assessment of geological engineering.In this research,the UCS(Uniaxial compressive strength)loss of six typical sandstones with different water contents after 0,20,40 and 60 freeze-thaw cycles was measured in the laboratory.The experimental results indicated that the freeze-thaw damage was more serious in sandstones containing high water contents,and the critical saturations for causing a significant loss of UCS under freeze-thaw were 60%-80%for these sandstones.Below this critical saturation,the UCS loss of the sandstones was mainly caused by water weakening rather than freeze-thaw damage.Besides,a developed strength prediction model was proposed by combining the exponential decay function and multiple linear regression method.The initial porosity,elastic modulus and tensile strength of fresh sandstones were a good parameter combination to accurately determine the decay constant in this developed model.The main novelty of this model is that it can accurately and easily estimate the UCS loss of sandstones after any freeze-thaw cycle only using the initial parameters of fresh sandstones,but it does not need to perform freeze-thaw and mechanical strength experiments.This study not only provides an accurate prediction model of UCS under freeze-thaw,but also makes a contribution to better understanding the frost resistance mechanism of sandstones.

Experimental study on the movement of oil spill under freeze-thaw action

Oil leakages cause environmental pollution,economic losses,and even engineering safety accidents.In cold regions,researchers urgently investigate the movement of oil spill in soils exposed to freeze-thaw cycles.In this study,a series of laboratory model experiments were carried out on the migration of oil leakage under freeze-thaw action,and the distributions of the soil temperature,unfrozen water content,and displacement were analyzed.The results showed that under freeze-thaw action,liquid water in soils migrated to the freezing front and accumulated.After the pipe cracked,oil pollutants first gathered at one side of the leak hole,and then moved around.The pipe wall temperature affected the soil temperature field,and the thermal influence range below and transverse the pipe wall(35–40 cm)was larger than that above the pipe wall(8 cm)owing to the soil surface temperature.The leaked oil's temperature would make the temperature of the surrounding soil rise.Oil would inhibit the cooling of the soils.Besides,oil migration was significantly affected by the gravity and water flow patterns.The freeze-thaw action would affect the migration of the oil,which was mainly manifested as inhibiting the diffusion and movement of oil when soils were frozen.Unfrozen water transport caused by freeze-thaw cycles would also inhibit oil migration.The research results would provide a scientific reference for understanding the relationship between the movement of oil pollutants,water,and soil temperature,and for establishing a waterheat-mass transport model in frozen soils.

Influence of relative compaction and degree of saturation on the deformation characteristics of bentonite under freeze-thaw cycles

Bentonite,consisting of clay minerals of the montmorillonite group,has been widely used as an adsorbent and backfill material in nuclear waste disposal and groundwater remediation.It is challenging to use bentonite as a filling material in cold regions since bentonite is highly sensitive to thermal environmental changes,during which its bulk volume and microstructure change significantly.In this study,a series of one-dimensional and three-dimensional freeze-thaw tests were carried out within a closed system to investigate the influencing factors of the deformation of bentonite under freeze-thaw cycles.Results show that the initial soil water content greatly impacts bentonite's deformation during freeze-thaw cycles.For an initial higher degree of saturation(Sr),the expansion caused by the formation of ice lenses has a greater impact than the shrinkage induced by dehydration,ice-cementation,and so on.Conversely,bentonite tends to shrink at a lower degree of saturation during freezing.And the critical degree of saturation that determines bentonite's behavior of frost heave or frost shrinkage seems to be roughly 0.8.As the number of freeze-thaw cycles rises,initially uncompacted bentonite clay becomes more compacted,and initially compacted bentonite clay remains unchanged.

基于LDA主题模型的GitHub Actions工作流项目推荐算法

在CI/CD实践中,自动化已成为软件开发实践中的一种规范。GitHub引入GitHub Actions为软件维护者提供自动化的持续集成工作流方案,尽管其为开发者提供了诸多便利,GitHub社区也提供了许多第三方的GitHub Actions服务,但仍然只有极少的项目在使用。为了满足开发人员对工作流自动化的需求,减少非开发任务工作量,提出一种基于隐含狄利克雷分布(LDA)主题模型和Jensen-Shannon距离的GitHub Actions工作流项目推荐算法。通过对GitHub Actions存储库的README文件进行主题建模,将GitHub的事件描述文本和用户输入作为模型输入,为正在开发的代码仓库推荐GitHub Actions服务。将该推荐模型与标准的基于余弦相似度的方法进行比较的实验结果表明,该方法能有效改善开源软件仓库的推荐精度。

Frost deformation and microstructure evolution of porous rock under uniform and unidirectional freeze-thaw conditions

The frost deterioration and deformation of porous rock are commonly investigated under uniform freeze-thaw(FT)conditions.However,the unidirectional FT condition,which is also prevalent in engineering practice,has received limited attention.Therefore,a comparative study on frost deformation and microstructure evolution of porous rock under both uniform and unidirectional FT conditions was performed.Firstly,frost deformation experiments of rock were conducted under cyclic uniform and unidirectional FT action,respectively.Results illustrate that frost deformation of saturated rock exhibits isotropic characteristics under uniform FT cycles,while it shows anisotropic characteristics under unidirectional FT condition with both the frost heaving strain and residual strain along FT direction much higher than those perpendicular to FT direction.Moreover,the peak value and residual value of cumulative frost strain vary as logarithmic functions with cycle number under both uniform and unidirectional FT conditions.Subsequently,the microstructure evolution of rock suffered cyclic uniform and unidirectional FT action were measured.Under uniform FT cycles,newly generated pores uniformly distribute in rock and pore structure of rock remains isotropic in micro scale,and thus the frost deformation shows isotropic characteristics in macro scale.Under unidirectional FT cycles,micro-cracks or pore belts generate with their orientation nearly perpendicular to the FT direction,and rock structure gradually becomes anisotropic in micro scale,resulting in the anisotropic characteristics of frost deformation in macro scale.

Fractal Study on the Evolution of Micro-Pores in Concrete Under Freeze-Thaw

After exposure to freeze-thaw cycles, scanning electron microscopy(SEM) and nuclear magnetic resonance(NMR) were used to test the four mixtures. The microstructure is qualitatively analyzed from the 2D SEM image and the 3D pore distribution curve before and after freezing and thawing. The fractal dimension is utilized to characterize the two-dimensional topography image and the three-dimensional pore distribution, quantitatively. The results reveal that the surface porosity and volume porosity increase as the freeze-thaw action increases. Self-similarity characteristics exist in micro-damage inside the concrete. In the fractal dimension, it is possible to characterize pore evolution quantitatively. The fractal dimension correlates with pore damage evolution. The fractal dimension effectively quantitatively characterizes micro-damage features at various scales from the local to the global level.

Workout Action Recognition in Video Streams Using an Attention Driven Residual DC-GRU Network

Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in videostreams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enableinstant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing actiondatasets often lack diversity and specificity for workout actions, hindering the development of accurate recognitionmodels. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significantcontribution. WAVd comprises a diverse collection of labeled workout action videos, meticulously curated toencompass various exercises performed by numerous individuals in different settings. This research proposes aninnovative framework based on the Attention driven Residual Deep Convolutional-Gated Recurrent Unit (ResDCGRU)network for workout action recognition in video streams. Unlike image-based action recognition, videoscontain spatio-temporal information, making the task more complex and challenging. While substantial progresshas been made in this area, challenges persist in detecting subtle and complex actions, handling occlusions,and managing the computational demands of deep learning approaches. The proposed ResDC-GRU Attentionmodel demonstrated exceptional classification performance with 95.81% accuracy in classifying workout actionvideos and also outperformed various state-of-the-art models. The method also yielded 81.6%, 97.2%, 95.6%, and93.2% accuracy on established benchmark datasets, namely HMDB51, Youtube Actions, UCF50, and UCF101,respectively, showcasing its superiority and robustness in action recognition. The findings suggest practicalimplications in real-world scenarios where precise video action recognition is paramount, addressing the persistingchallenges in the field. TheWAVd dataset serves as a catalyst for the development ofmore robust and effective fitnesstracking systems and ultimately promotes healthier lifestyles through improved exercise monitoring and analysis.

Freeze-thaw cycles and associated geomorphology in a post-glacial environment:current glacial,paraglacial,periglacial and proglacial scenarios at Pico de Orizaba volcano,Mexico

The glacial history of Pico de Orizaba indicates that during the Last Glacial Maximum,its icecap covered up to~3000 m asl;due to the air temperature increasing,its main glacier has retreated to 5050 m asl.The retraction of the glacier has left behind an intense climatic instability that causes a high frequency of freeze-thaw cycles of great intensity;the resulting geomorphological processes are represented by the fragmentation of the bedrock that occupies the upper parts of the mountain.There is a notable lack of studies regarding the fragmentation and erosion occurring in tropical high mountains,and the associated geomorphological risks;for this reason,as a first stage of future continuous research,this study analyzes the freezing and thawing cycles that occur above 4000 m asl,through continuous monitoring of surface ground temperature.The results allow us to identify and characterize four zones:glacial,paraglacial,periglacial and proglacial.It was found that the paraglacial zone presents an intense drop of temperature,of up to~9℃ in only sixty minutes.The rock fatigue and intense freeze-thaw cycles that occur in this area are responsible for the high rate of rock disintegration and represent the main factor of the constant slope dynamics that occur at the site.This activity decreases,both in frequency and intensity,according to the distance to the glacier,which is where the temperature presents a certain degree of stability,until reaching the proglacial zone,where cycles are almost non-existent,and therefore there is no gelifraction activity.The geomorphological processes have resulted in significant alterations to the mountain slopes,which can have severe consequences in terms of risk and water.

Abnormal Action Recognition with Lightweight Pose Estimation Network in Electric Power Training Scene

Electric power training is essential for ensuring the safety and reliability of the system.In this study,we introduce a novel Abnormal Action Recognition(AAR)system that utilizes a Lightweight Pose Estimation Network(LPEN)to efficiently and effectively detect abnormal fall-down and trespass incidents in electric power training scenarios.The LPEN network,comprising three stages—MobileNet,Initial Stage,and Refinement Stage—is employed to swiftly extract image features,detect human key points,and refine them for accurate analysis.Subsequently,a Pose-aware Action Analysis Module(PAAM)captures the positional coordinates of human skeletal points in each frame.Finally,an Abnormal Action Inference Module(AAIM)evaluates whether abnormal fall-down or unauthorized trespass behavior is occurring.For fall-down recognition,three criteria—falling speed,main angles of skeletal points,and the person’s bounding box—are considered.To identify unauthorized trespass,emphasis is placed on the position of the ankles.Extensive experiments validate the effectiveness and efficiency of the proposed system in ensuring the safety and reliability of electric power training.

Unveiling health rights:A call to action for sex workers'HIV care in the Philippines

We are writing in response to the article titled“Addressing the needs and rights of sex workers for HIV healthcare services in the Philippines”[1].The article calls for attention on the significant challenges faced by sex workers in the Philippines in accessing HIV healthcare.We appreciate the article’s effort to examine these issues in depth.We would like to present a constant flow of thoughts in this letter while highlighting the positive aspects,potential obstacles,and additional points that contribute to this ongoing discussion.

Effect of sodium starch octenyl succinate-based Pickering emulsion on the physicochemical properties of hairtail myofibrillar protein gel subjected to multiple freeze-thaw cycles

A Pickering emulsion based on sodium starch octenyl succinate(SSOS)was prepared and its effects on the physicochemical properties of hairtail myofibrillar protein gels(MPGs)subjected to multiple freeze-thaw(F-T)cycles were investigated.The whiteness,water-holding capacity,storage modulus(G')and texture properties of the MPGs were significantly improved by adding 1%-2%Pickering emulsion(P<0.05).Meanwhile,Raman spectral analysis demonstrated that Pickering emulsion promoted the transformation of secondary structure,enhanced hydrogen bonds and hydrophobic interactions,and promoted the transition of disulfide bond conformation from g-g-g to g-g-t and t-g-t.At an emulsion concentration of 2%,theα-helix content decreased by 10.37%,while theβ-sheet content increased by 7.94%,compared to the control.After F-T cycles,the structure of the MPGs was destroyed,with an increase in hardness and a decrease in whiteness and water-holding capacity,however,the quality degradation of MPGs was reduced with 1%-2%Pickering emulsion.These findings demonstrated that SSOS-Pickering emulsions,as potential fat substitutes,can enhance the gel properties and the F-T stability of MPGs.

Coupling Effect of Cryogenic Freeze-Thaw Cycles and Chloride Ion Erosion Effect in Pre-Cracked Reinforced Concrete

Chloride (Cl−) ion erosion effects can seriously impact the safety and service life of marine liquefied natural gas(LNG) storage tanks and other polar offshore structures. This study investigates the impact of different low-temperaturecycles (20°C, –80°C, and −160°C) and concrete specimen crack widths (0, 0.3, and 0.6 mm) on the Cl−ion diffusion performance through rapid erosion tests conducted on pre-cracked concrete. The results show thatthe minimum temperature and crack width of freeze-thaw cycles enhance the erosive effect of chloride ions. TheCl− ion concentration and growth rate increased with the increasing crack width. Based on the experimental modeland in accordance with Fick’s second law of diffusion, the Cl− ion diffusion equation was modified by introducingcorrection factors in consideration of the freeze-thaw temperature, crack width, and their coupling effect.The experimental and fitting results obtained from this model can provide excellent reference for practical engineeringapplications.

Repair of Second-Generation Recycled Fine Aggregate of Waste Concrete from Freeze-Thaw Environment by Carbonation Treatment

The reuse of waste recycled concrete from harsh environments has become a research hotspot in the field of construction.This study investigated the repair effect of carbonation treatment on second-generation recycled fine aggregate(SRFA)obtained from recycled fine aggregate concrete(RFAC)subjected to freeze-thaw(FT)cycles.Before and after carbonation,the properties of SRFA were evaluated.Carbonated second-generation recycled fine aggregate(CSRFA)at five substitution rates(0%,25%,50%,75%,100%)to replace SRFA was used to prepare carbonated second-generation recycled fine aggregate concrete(CSRFAC).The water absorption,porosity and mechanical properties of CSRFAC were tested,and its frost-resisting durability was evaluated.The results showed after carbonation treatment,the physical properties of SRFA was improved and met the requirements of II aggregate.The micro-hardness of the interfacial transition zone and attached mortar in CSRFA was 50.5%and 31.2%higher than that in SRFA,respectively.With the increase of CSRFA replacement rate,the water absorption and porosity of CSRFAC gradually decreased,and the mechanical properties and frost resistance of CSRFAC were gradually improved.Carbonation treatment effectively repairs the damage of SRFA caused by FT cycles and improves its application potential.

Impact of Action Observation Therapy along with Usual Physiotherapy Intervention of Individual with Alzheimer’s Disease

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by cognitive impairments in the initial stage, which lead to severe cognitive dysfunction in the later stage. Action observation therapy (AOT) is a multisensory cognitive rehabilitation technique where the patient initially observes the actions and then tries to perform. The study aimed to examine the impact of AOT along with usual physiotherapy interventions to reduce depression, improve cognition and balance of a patient with AD. A 67 years old patient with AD was selected for this study because the patient has been suffering from depression, dementia, and physical dysfunction along with some other health conditions like diabetes and hypertension. Before starting intervention, a baseline assessment was done through the Beck Depression Inventory (BDI) tool, the Mini-Cog Scale, and the Berg Balance Scale (BBS). The patient received 12 sessions of AOT along with usual physiotherapy interventions thrice a week for four weeks, which included 45 minutes of each session. After four weeks of intervention, the patient demonstrated significant improvement in depression, cognition, and balance, whereas the BDI score declined from moderate 21/63 to mild 15/63 level of depression. The Mini-Cog score improved from 2/5 to 4/5, and the BBS score increased from 18/56 to 37/56. It is concluded that AOT along with usual physiotherapy intervention helps to reduce depression, improve cognition and balance of people with AD.

Spatiotemporal variation and freeze-thaw asymmetry of Arctic sea ice in multiple dimensions during 1979 to 2020

Arctic sea ice is broadly regarded as an indicator and amplifier of global climate change.The rapid changes in Arctic sea ice have been widely concerned.However,the spatiotemporal changes in the horizontal and vertical dimensions of Arctic sea ice and its asymmetry during the melt and freeze seasons are rarely quantified simultaneously based on multiple sources of the same long time series.In this study,the spatiotemporal variation and freeze-thaw asymmetry of Arctic sea ice were investigated from both the horizontal and vertical dimensions during 1979–2020 based on remote sensing and assimilation data.The results indicated that Arctic sea ice was declining at a remarkably high rate of–5.4×10^(4) km^(2)/a in sea ice area(SIA)and–2.2 cm/a in sea ice thickness(SIT)during 1979 to 2020,and the reduction of SIA and SIT was the largest in summer and the smallest in winter.Spatially,compared with other sub-regions,SIA showed a sharper declining trend in the Barents Sea,Kara Sea,and East Siberian Sea,while SIT presented a larger downward trend in the northern Canadian Archipelago,northern Greenland,and the East Siberian Sea.Regarding to the seasonal trend of sea ice on sub-region scale,the reduction rate of SIA exhibited an apparent spatial heterogeneity among seasons,especially in summer and winter,i.e.,the sub-regions linked to the open ocean exhibited a higher decline rate in winter;however,the other sub-regions blocked by the coastlines presented a greater decline rate in summer.For SIT,the sub-regions such as the Beaufort Sea,East Siberian Sea,Chukchi Sea,Central Arctic,and Canadian Archipelago always showed a higher downward rate in all seasons.Furthermore,a striking freeze-thaw asymmetry of Arctic sea ice was also detected.Comparing sea ice changes in different dimensions,sea ice over most regions in the Arctic showed an early retreat and rapid advance in the horizontal dimension but late melting and gradual freezing in the vertical dimension.The amount of sea ice melting and freezing was disequilibrium in the Arctic during the considered period,and the rate of sea ice melting was 0.3×10^(4) km^(2)/a and 0.01 cm/a higher than that of freezing in the horizontal and vertical dimensions,respectively.Moreover,there were notable shifts in the melting and freezing of Arctic sea ice in 1997/2003 and 2000/2004,respectively,in the horizontal/vertical dimension.

BCCLR:A Skeleton-Based Action Recognition with Graph Convolutional Network Combining Behavior Dependence and Context Clues

In recent years,skeleton-based action recognition has made great achievements in Computer Vision.A graph convolutional network(GCN)is effective for action recognition,modelling the human skeleton as a spatio-temporal graph.Most GCNs define the graph topology by physical relations of the human joints.However,this predefined graph ignores the spatial relationship between non-adjacent joint pairs in special actions and the behavior dependence between joint pairs,resulting in a low recognition rate for specific actions with implicit correlation between joint pairs.In addition,existing methods ignore the trend correlation between adjacent frames within an action and context clues,leading to erroneous action recognition with similar poses.Therefore,this study proposes a learnable GCN based on behavior dependence,which considers implicit joint correlation by constructing a dynamic learnable graph with extraction of specific behavior dependence of joint pairs.By using the weight relationship between the joint pairs,an adaptive model is constructed.It also designs a self-attention module to obtain their inter-frame topological relationship for exploring the context of actions.Combining the shared topology and the multi-head self-attention map,the module obtains the context-based clue topology to update the dynamic graph convolution,achieving accurate recognition of different actions with similar poses.Detailed experiments on public datasets demonstrate that the proposed method achieves better results and realizes higher quality representation of actions under various evaluation protocols compared to state-of-the-art methods.

General Optimal Trajectory Planning:Enabling Autonomous Vehicles with the Principle of Least Action

This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and efficiently.Firstly,we employ the fifth-order Bezier curve to generate and smooth the reference path along the road centerline.Cartesian coordinates are then transformed to achieve the curvature continuity of the generated curve.Considering the road constraints and vehicle dynamics,limited polynomial candidate trajectories are generated and smoothed in a curvilinear coordinate system.Furthermore,in selecting the optimal trajectory,we develop a unified and auto-tune objective function based on the principle of least action by employing AVs to simulate drivers’behavior and summarizing their manipulation characteristics of“seeking benefits and avoiding losses.”Finally,by integrating the idea of receding-horizon optimization,the proposed framework is achieved by considering dynamic multi-performance objectives and selecting trajectories that satisfy feasibility,optimality,and adaptability.Extensive simulations and experiments are performed,and the results demonstrate the framework’s feasibility and effectiveness,which avoids both dynamic and static obstacles and applies to various scenarios with multi-source interactive traffic participants.Moreover,we prove that the proposed method can guarantee real-time planning and safety requirements compared to drivers’manipulation.

HgaNets:Fusion of Visual Data and Skeletal Heatmap for Human Gesture Action Recognition

Recognition of human gesture actions is a challenging issue due to the complex patterns in both visual andskeletal features. Existing gesture action recognition (GAR) methods typically analyze visual and skeletal data,failing to meet the demands of various scenarios. Furthermore, multi-modal approaches lack the versatility toefficiently process both uniformand disparate input patterns.Thus, in this paper, an attention-enhanced pseudo-3Dresidual model is proposed to address the GAR problem, called HgaNets. This model comprises two independentcomponents designed formodeling visual RGB (red, green and blue) images and 3Dskeletal heatmaps, respectively.More specifically, each component consists of two main parts: 1) a multi-dimensional attention module forcapturing important spatial, temporal and feature information in human gestures;2) a spatiotemporal convolutionmodule that utilizes pseudo-3D residual convolution to characterize spatiotemporal features of gestures. Then,the output weights of the two components are fused to generate the recognition results. Finally, we conductedexperiments on four datasets to assess the efficiency of the proposed model. The results show that the accuracy onfour datasets reaches 85.40%, 91.91%, 94.70%, and 95.30%, respectively, as well as the inference time is 0.54 s andthe parameters is 2.74M. These findings highlight that the proposed model outperforms other existing approachesin terms of recognition accuracy.

Research Progress on Purification Process, Content Determination and Pharmacological Action of Atractylodin

Atractylodis Rhizoma comes from the dry rhizome of Atractylis lancea or Atractylodes chinensis in the Compositae family,and it is suitable for preventing and treating diseases such as cold,edema,night blindness and rheumatic arthralgia.Atractylodin is the main active component extracted and isolated from Atractylodis Rhizoma.A large number of studies have found that atractylodin has excellent drug activity in improving gastrointestinal emptying,anti-inflammation,inhibiting malignant tumor and reducing blood lipid.In this paper,the purification process and pharmacological activity of Atractylodin were summarized to provide a theoretical basis for basic research,clinical application and further development and utilization of atractylodin.