Rapid printing of 3D porous scaffolds for breast reconstruction

Prosthesis implantation and fat transplantation are common breast reconstructionmethods.In general,prosthesis implantation alone does not achieve a realistic enough appearance,and fat transplantation alone is difficult to achieve in the correct capacity.To date,no reports have focused on methods of combining fat with implanted prostheses for breast reconstruction.Using a newly designed bionic ink(i.e.,polyether F127 diacrylate(F127DA)&poly(ethylene glycol)diacrylate(PEGDA))and projection-based three-dimensional bioprinting(PBP),we report the development of a new method for printing porous prostheses.PEGDA was used to improve the printing precision of the prosthesis by increasing the gel point of F127DA and reducing the impact of external temperature.The compression modulus of the printed prosthesis was very close to that of prostheses currently used in clinical practice and to that of natural breasts.Finally,stromal vascular fraction gel(SVF-gel),a human fat extract,was injected into the pores of the synthesized prostheses to prepare a prosthesis mixed with adipose tissue.These were implanted subcutaneously in nude mice to observe their biological performance.After 14 and 28 days of observation,the prosthesis showed good biocompatibility,and adipose tissues grew well in and around the prosthesis.This result shows that a porous prosthesis containing pre-placed adipose tissues is a promising breast reconstruction material.

A quantum blind signature scheme based on dense coding for non-entangled states

In some schemes, quantum blind signatures require the use of difficult-to-prepare multiparticle entangled states. By considering the communication overhead, quantum operation complexity, verification efficiency and other relevant factors in practical situations, this article proposes a non-entangled quantum blind signature scheme based on dense encoding. The information owner utilizes dense encoding and hash functions to blind the information while reducing the use of quantum resources. After receiving particles, the signer encrypts the message using a one-way function and performs a Hadamard gate operation on the selected single photon to generate the signature. Then the verifier performs a Hadamard gate inverse operation on the signature and combines it with the encoding rules to restore the message and complete the verification.Compared with some typical quantum blind signature protocols, this protocol has strong blindness in privacy protection,and higher flexibility in scalability and application. The signer can adjust the signature operation according to the actual situation, which greatly simplifies the complexity of the signature. By simultaneously utilizing the secondary distribution and rearrangement of non-entangled quantum states, a non-entangled quantum state representation of three bits of classical information is achieved, reducing the use of a large amount of quantum resources and lowering implementation costs. This improves both signature verification efficiency and communication efficiency while, at the same time, this scheme meets the requirements of unforgeability, non-repudiation, and prevention of information leakage.

A Formal Model for Analyzing Fair Exchange Protocols Based on Event Logic

Fair exchange protocols play a critical role in enabling two distrustful entities to conduct electronic data exchanges in a fair and secure manner.These protocols are widely used in electronic payment systems and electronic contract signing,ensuring the reliability and security of network transactions.In order to address the limitations of current research methods and enhance the analytical capabilities for fair exchange protocols,this paper proposes a formal model for analyzing such protocols.The proposed model begins with a thorough analysis of fair exchange protocols,followed by the formal definition of fairness.This definition accurately captures the inherent requirements of fair exchange protocols.Building upon event logic,the model incorporates the time factor into predicates and introduces knowledge set axioms.This enhancement empowers the improved logic to effectively describe the state and knowledge of protocol participants at different time points,facilitating reasoning about their acquired knowledge.To maximize the intruder’s capabilities,channel errors are translated into the behaviors of the intruder.The participants are further categorized into honest participants and malicious participants,enabling a comprehensive evaluation of the intruder’s potential impact.By employing a typical fair exchange protocol as an illustrative example,this paper demonstrates the detailed steps of utilizing the proposed model for protocol analysis.The entire process of protocol execution under attack scenarios is presented,shedding light on the underlying reasons for the attacks and proposing corresponding countermeasures.The developedmodel enhances the ability to reason about and evaluate the security properties of fair exchange protocols,thereby contributing to the advancement of secure network transactions.

Multi-objective optimization and evaluation of supercritical CO_(2) Brayton cycle for nuclear power generation

The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayton cycle layouts are developed in this study for different reactors to reduce the cost and increase the thermohydraulic performance of nuclear power generation to promote the commercialization of nuclear energy.Parametric analysis,multi-objective optimizations,and four decision-making methods are applied to obtain each Brayton scheme’s optimal thermohydraulic and economic indexes.Results show that for the same design thermal power scale of reactors,the higher the core’s exit temperature,the better the Brayton cycle’s thermo-economic performance.Among the four-cycle layouts,the recompression cycle(RC)has the best overall performance,followed by the simple recuperation cycle(SR)and the intercooling cycle(IC),and the worst is the reheating cycle(RH).However,RH has the lowest total cost of investment(C_(tot))of$1619.85 million,and IC has the lowest levelized cost of energy(LCOE)of 0.012$/(kWh).The nuclear Brayton cycle system’s overall performance has been improved due to optimization.The performance of the molten salt reactor combined with the intercooling cycle(MSR-IC)scheme has the greatest improvement,with the net output power(W_(net)),thermal efficiencyη_(t),and exergy efficiency(η_(e))improved by 8.58%,8.58%,and 11.21%,respectively.The performance of the lead-cooled fast reactor combined with the simple recuperation cycle scheme was optimized to increase C_(tot) by 27.78%.In comparison,the internal rate of return(IRR)increased by only 7.8%,which is not friendly to investors with limited funds.For the nuclear Brayton cycle,the molten salt reactor combined with the recompression cycle scheme should receive priority,and the gas-cooled fast reactor combined with the reheating cycle scheme should be considered carefully.

Improved PSO-Extreme Learning Machine Algorithm for Indoor Localization

Wi Fi and fingerprinting localization method have been a hot topic in indoor positioning because of their universality and location-related features.The basic assumption of fingerprinting localization is that the received signal strength indication(RSSI)distance is accord with the location distance.Therefore,how to efficiently match the current RSSI of the user with the RSSI in the fingerprint database is the key to achieve high-accuracy localization.In this paper,a particle swarm optimization-extreme learning machine(PSO-ELM)algorithm is proposed on the basis of the original fingerprinting localization.Firstly,we collect the RSSI of the experimental area to construct the fingerprint database,and the ELM algorithm is applied to the online stages to determine the corresponding relation between the location of the terminal and the RSSI it receives.Secondly,PSO algorithm is used to improve the bias and weight of ELM neural network,and the global optimal results are obtained.Finally,extensive simulation results are presented.It is shown that the proposed algorithm can effectively reduce mean error of localization and improve positioning accuracy when compared with K-Nearest Neighbor(KNN),Kmeans and Back-propagation(BP)algorithms.

Research on the Generation Mechanism and Suppression Method of Aerodynamic Noise in Expansion Cavity Based on Hybrid Method

The expansion chamber serves as the primary silencing structure within the exhaust pipeline.However,it can also act as a sound-emitting structure when subjected to airflow.This article presents a hybrid method for numerically simulating and analyzing the unsteady flow and aerodynamic noise in an expansion chamber under the influence of airflow.A fluid simulation model is established,utilizing the Large Eddy Simulation(LES)method to calculate the unsteady flow within the expansion chamber.The simulation results effectively capture the development and changes of the unsteady flow and vorticity inside the cavity,exhibiting a high level of consistency with experimental observations.To calculate the aerodynamic noise sources within the cavity,the flow field results are integrated using the method of integral interpolation and inserted into the acoustic grid.The acoustic analogy method is then employed to determine the aerodynamic noise sources.An acoustic simulation model is established,and the flow noise source is imported into the sound field grid to calculate the sound pressure at the far-field response point.The calculated sound pressure levels and resonance frequencies show good agreement with the experimental results.To address the issue of airflow regeneration noise within the cavity,perforated tubes are selected as a means of noise suppression.An experimental platformfor airflow regeneration noise is constructed,and experimental samples are processed to analyze and verify the noise suppression effect of perforated tube expansion cavities under different airflow velocities.The research findings indicate that the perforated tube expansion cavity can effectively suppress low-frequency aerodynamic noise within the cavity by impeding the formation of strong shear layers.Moreover,the semi-perforated tube expansion cavity demonstrates the most effective suppression of aerodynamic noise.

Deployment of Edge Computing Nodes in IoT:Effective Implementation of Simulated Annealing Method Based on User Location

Edge computing paradigm for 5G architecture has been considered as one of the most effective ways to realize low latency and highly reliable communication,which brings computing tasks and network resources to the edge of network.The deployment of edge computing nodes is a key factor affecting the service performance of edge computing systems.In this paper,we propose a method for deploying edge computing nodes based on user location.Through the combination of Simulation of Urban Mobility(SUMO)and Network Simulator-3(NS-3),a simulation platform is built to generate data of hotspot areas in Io T scenario.By effectively using the data generated by the communication between users in Io T scenario,the location area of the user terminal can be obtained.On this basis,the deployment problem is expressed as a mixed integer linear problem,which can be solved by Simulated Annealing(SA)method.The analysis of the results shows that,compared with the traditional method,the proposed method has faster convergence speed and better performance.

Heterogeneous information phase space reconstruction and stability prediction of filling body–surrounding rock combination

Traditional research believes that the filling body can effectively control stress concentration while ignoring the problems of unknown stability and the complex and changeable stress distribution of the filling body–surrounding rock combination under high-stress conditions.Current monitoring data processing methods cannot fully consider the complexity of monitoring objects,the diversity of monitoring methods,and the dynamics of monitoring data.To solve this problem,this paper proposes a phase space reconstruction and stability prediction method to process heterogeneous information of backfill–surrounding rock combinations.The three-dimensional monitoring system of a large-area filling body–surrounding rock combination in Longshou Mine was constructed by using drilling stress,multipoint displacement meter,and inclinometer.Varied information,such as the stress and displacement of the filling body–surrounding rock combination,was continuously obtained.Combined with the average mutual information method and the false nearest neighbor point method,the phase space of the heterogeneous information of the filling body–surrounding rock combination was then constructed.In this paper,the distance between the phase point and its nearest point was used as the index evaluation distance to evaluate the stability of the filling body–surrounding rock combination.The evaluated distances(ED)revealed a high sensitivity to the stability of the filling body–surrounding rock combination.The new method was then applied to calculate the time series of historically ED for 12 measuring points located at Longshou Mine.The moments of mutation in these time series were at least 3 months ahead of the roadway return dates.In the ED prediction experiments,the autoregressive integrated moving average model showed a higher prediction accuracy than the deep learning models(long short-term memory and Transformer).Furthermore,the root-mean-square error distribution of the prediction results peaked at 0.26,thus outperforming the no-prediction method in 70%of the cases.

Multi-Branch High-Dimensional Guided Transformer-Based 3D Human Posture Estimation

The human pose paradigm is estimated using a transformer-based multi-branch multidimensional directed the three-dimensional(3D)method that takes into account self-occlusion,badly posedness,and a lack of depth data in the per-frame 3D posture estimation from two-dimensional(2D)mapping to 3D mapping.Firstly,by examining the relationship between the movements of different bones in the human body,four virtual skeletons are proposed to enhance the cyclic constraints of limb joints.Then,multiple parameters describing the skeleton are fused and projected into a high-dimensional space.Utilizing a multi-branch network,motion features between bones and overall motion features are extracted to mitigate the drift error in the estimation results.Furthermore,the estimated relative depth is projected into 3D space,and the error is calculated against real 3D data,forming a loss function along with the relative depth error.This article adopts the average joint pixel error as the primary performance metric.Compared to the benchmark approach,the estimation findings indicate an increase in average precision of 1.8 mm within the Human3.6M sample.

Multifunctional MOF@COF Nanoparticles Mediated Perovskite Films Management Toward Sustainable Perovskite Solar Cells

Although covalent organic frameworks(COFs)with highπ-conjugation have recently exhibited great prospects in perovskite solar cells(PSCs),their further application in PSCs is still hindered by face-to-face stacking and aggregation issues.Herein,metal-organic framework(MOF-808)is selected as an ideal platform for the in situ homogeneous growth of a COF to construct a core-shell MOF@COF nanoparticle,which could effectively inhibit COF stacking and aggregation.The synergistic intrinsic mechanisms induced by the MOF@COF nanoparticles for reinforcing intrinsic stability and mitigating lead leakage in PSCs have been explored.The complementary utilization ofπ-conjugated skeletons and nanopores could optimize the crystallization of large-grained perovskite films and eliminate defects.The resulting PSCs achieve an impressive power conversion efficiency of 23.61%with superior open circuit voltage(1.20 V)and maintained approximately 90%of the original power conversion efficiency after 2000 h(30-50%RH and 25-30℃).Benefiting from the synergistic effects of the in situ chemical fixation and adsorption abilities of the MOF@COF nanoparticles,the amount of lead leakage from unpackaged PSCs soaked in water(<5 ppm)satisfies the laboratory assessment required for the Resource Conservation and Recovery Act Regulation.

Exercise-induced adaptation of neurons in the vertebrate locomotor system

Vertebrate neurons are highly dynamic cells that undergo several alterations in their functioning and physiologies in adaptation to various external stimuli.In particular,how these neurons respond to physical exercise has long been an area of active research.Studies of the vertebrate locomotor system’s adaptability suggest multiple mechanisms are involved in the regulation of neuronal activity and properties during exercise.In this brief review,we highlight recent results and insights from the field with a focus on the following mechanisms:(a)alterations in neuronal excitability during acute exercise;(b)alterations in neuronal excitability after chronic exercise;(c)exercise-induced changes in neuronal membrane properties via modulation of ion channel activity;(d)exercise-enhanced dendritic plasticity;and(e)exercise-induced alterations in neuronal gene expression and protein synthesis.Our hope is to update the community with a cellular and molecular understanding of the recent mechanisms underlying the adaptability of the vertebrate locomotor system in response to both acute and chronic physical exercise.

Microstructural and thermal properties of coal measure sandstone subjected to high temperatures

To study the microscopic structure,thermal and mechanical properties of sandstones under the influence of temperature,coal measure sandstones from Southwest China are adopted as the research object to carry out high-temperature tests at 25℃-1000℃.The microscopic images of sandstone after thermal treatment are obtained by means of polarizing microscopy and scanning electron microscopy(SEM).Based on thermogravimetric(TG)analysis and differential scanning calorimetric(DSC)analysis,the model function of coal measure sandstone is explored through thermal analysis kinetics(TAK)theory,and the kinetic parameters of thermal decomposition and the thermal decomposition reaction rate of rock are studied.Through the uniaxial compression experiments,the stress‒strain curves and strength characteristics of sandstone under the influence of temperature are obtained.The results show that the temperature has a significant effect on the microstructure,mineral composition and mechanical properties of sandstone.In particular,when the temperature exceeds 400℃,the thermal fracture phenomenon of rock is obvious,the activity of activated molecules is significantly enhanced,and the kinetic phenomenon of the thermal decomposition reaction of rock appears rapidly.The mechanical properties of rock are weakened under the influence of rock thermal fracture and mineral thermal decomposition.These research results can provide a reference for the analysis of surrounding rock stability and the control of disasters caused by thermal damage in areas such as underground coal gasification(UCG)channels and rock masses subjected to mine fires.

Bird’s-eye view of recycled solid wastes in road engineering

Recent trends in road engineering have explored the potential of incorporating recycled solid wastes into infrastructures that including pavements,bridges,tunnels,and accessory structures.The utilization of solid wastes is expected to offer sustainable solutions to waste recycling while enhancing the performance of roads.This review provides an extensive analysis of the recycling of three main types of solid wastes for road engineering purposes:industrial solid waste,infrastructure solid waste,and municipal life solid waste.Industrial solid wastes suitable for road engineering generally include coal gangue,fly ash,blast furnace slag,silica fume,and steel slag,etc.Infrastructure solid wastes recycled in road engineering primarily consist of construction&demolition waste,reclaimed asphalt pavements,and recycled cement concrete.Furthermore,recent exploration has extended to the utilization of municipal life solid wastes,such as incinerated bottom ash,glass waste,electronics waste,plastic waste,and rubber waste in road engineering applications.These recycled solid wastes are categorized into solid waste aggregates,solid waste cements,and solid waste fillers,each playing distinct roles in road infrastructure.Roles of solid waste acting aggregates,cements,and fillers in road infrastructures were fully investigated,including their pozzolanic properties,integration effects to virgin materials,modification or enhancement solutions,engineering performances.Utilization of these materials not only addresses the challenge of waste management but also offers environmental benefits aiming carbon neutral and contributes to sustainable infrastructure development.However,challenges such as variability in material properties,environmental impact mitigation,secondary pollution to environment by leaching,and concerns regarding long-term performance need to be further addressed.Despite these challenges,the recycled solid wastes hold immense potential in revolutionizing road construction practices and fostering environmental stewardship.This review delves into a bird’seye view of the utilization of recycled solid wastes in road engineering,highlighting advances,benefits,challenges,and future prospects.

A Novel <i>in Vitro</i>Three-Dimensional Macroporous Scaffolds from Bacterial Cellulose for Culture of Breast Cancer Cells

In this work, patterned macropores with a diameter larger than 100 μm were introduced to pristine three-dimensional (3D) nanofibrous bacterial cellulose (BC) scaffolds by using the infrared laser micromachining technique in an attempt to create an in vitro model for the culture of breast cancer cells. The morphology, pore structure, and mechanical performance of the obtained patterned macroporous BC (PM-BC) scaffolds were characterized by scanning electron microscopy (SEM), mercury intrusion porosimeter, and mechanical testing. A human breast cancer cell (MDA-MB-231) line was cultured onto the PM-BC scaffolds to investigate the role of macropores in the control of cancer cell behavior. MTT assay, SEM, and hematoxylin and eosin (H&E) staining were employed to determine cell adhesion, growth, proliferation, and infiltration. The PM-BC scaffolds were found to be able to promote cellular adhesion and proliferation on the scaffolds, and further to allow for cell infiltration into the PM-BC scaffolds. The results demonstrated that BC scaffolds with laser-patterned macropores were promising for the in vitro 3D culture of breast cancer cells.

Countermeasures and Prevention of Railway Traffic Accidents in the Early Days of the Founding of the People’s Republic of China

In the early days of the founding of the People’s Republic of China,in order to restore the national economy as soon as possible,the Communist Party of China carried out maintenance and repairs on the railways that caused serious damage to transportation tasks through war-torn smoke,and carried out large-scale railway construction.However,in the course of operation,railway safety accidents occur frequently due to outdated equipment,low quality of staff,lack of rules and regulations,vandalism,and various natural disasters.In the face of severe conditions,the railway authorities summed up the accidents and learned the safety of the railways,so that the railway transportation industry,which started after the founding of the country,was gradually on the right track,and laid a solid foundation for the safe development of the railway industry.

Quantum homomorphic broadcast multi-signature based on homomorphic aggregation

Quantum multi-signature has attracted extensive attention since it was put forward.Beside its own improvement,related research is often combined with other quantum signature.However,this type of quantum signature has one thing in common,that is,the generation and verification of signature depend heavily on the shared classical secret key.In order to increase the reliability of signature,the homomorphic aggregation technique is applied to quantum multi-signature,and then we propose a quantum homomorphic multi-signature protocol.Unlike previous quantum multi-signature protocols,this protocol utilizes homomorphic properties to complete signature generation and verification.In the signature generation phase,entanglement swapping is introduced,so that the individual signatures of multiple users are aggregated into a new multi-signature.The original quantum state is signed by the shared secret key to realize the verification of the signature in the verification phase.The signature process satisfies the homomorphic property,which can improve the reliability of the signature.

A Novel Adaptive Kalman Filter Based on Credibility Measure

It is quite often that the theoretic model used in the Kalman filtering may not be sufficiently accurate for practical applications,due to the fact that the covariances of noises are not exactly known.Our previous work reveals that in such scenario the filter calculated mean square errors(FMSE)and the true mean square errors(TMSE)become inconsistent,while FMSE and TMSE are consistent in the Kalman filter with accurate models.This can lead to low credibility of state estimation regardless of using Kalman filters or adaptive Kalman filters.Obviously,it is important to study the inconsistency issue since it is vital to understand the quantitative influence induced by the inaccurate models.Aiming at this,the concept of credibility is adopted to discuss the inconsistency problem in this paper.In order to formulate the degree of the credibility,a trust factor is constructed based on the FMSE and the TMSE.However,the trust factor can not be directly computed since the TMSE cannot be found for practical applications.Based on the definition of trust factor,the estimation of the trust factor is successfully modified to online estimation of the TMSE.More importantly,a necessary and sufficient condition is found,which turns out to be the basis for better design of Kalman filters with high performance.Accordingly,beyond trust factor estimation with Sage-Husa technique(TFE-SHT),three novel trust factor estimation methods,which are directly numerical solving method(TFE-DNS),the particle swarm optimization method(PSO)and expectation maximization-particle swarm optimization method(EM-PSO)are proposed.The analysis and simulation results both show that the proposed TFE-DNS is better than the TFE-SHT for the case of single unknown noise covariance.Meanwhile,the proposed EMPSO performs completely better than the EM and PSO on the estimation of the credibility degree and state when both noise covariances should be estimated online.

Mobile Edge Computing Servers Deployment with Improved Genetic Algorithm in Cellular Internet of Things

Mobile edge computing(MEC)provides services to devices and reduces latency in cellular internet of things(IoT)networks.However,the challenging problem is how to deploy MEC servers economically and efficiently.This paper investigates the deployment problem of MEC servers of the real-world road network by employing an improved genetic algorithm(GA)scheme.We first use the threshold-based K-means algorithm to form vehicle clusters according to their locations.We then select base stations(BSs)based on clustering center coordinates as the deployment locations set for potential MEC servers.We further select BSs using a combined simulated annealing(SA)algorithm and GA to minimize the deployment cost.The simulation results show that the improved GA deploys MEC servers effectively.In addition,the proposed algorithm outperforms GA and SA algorithms in terms of convergence speed and solution quality.

Effect of Oils on SBS Modified Asphalt:Rheological Characteristics and Oxidation Aging

This study focuses on the effect of oils on rheology and oxidation aging of Styrene-Butadiene-Styrene modified asphalt(SBSMA)in the long term,after reducing one low-temperature Performance Grade(PG)of SBSMA by incorporating oils.Two oils,including corn-based bio-oil and re-refined engine oil bottom(REOB),were selected to enhance the low-temperature performance of SBSMA.All samples were subjected to Rolling Thin Film Oven(RTFO)aging and 20-h as well as 40-h Pressure Aging Vessel(PAV20 and PAV40)aging,prior to multiple stress creep recovery(MSCR),frequency sweep and Flourier transform infrared spectroscopy(FTIR)scanning.A good high-temperature performance of oil/SBS modified asphalt blends was reflected in MSCR and PG results,meanwhile non-recoverable creep compliance(Jnr)and recovery(R)were found to share a highly correlated relationship during aging progress.In addition,Glover–Rowe(G–R)parameter and phase angle master curves suggest that the improvement of cracking property mainly came from the softening effect of oils.Adding oils into SBSMA was observed to increase oxidation kinetics,but the blends with oils still exhibited better anti-oxidation aging than the base binder,mainly due to the SBS addition.Bio-oil exhibited an effect of relieving age hardening susceptibility of SBSMA.

Earth Pressure of the Trapdoor Problem Using Three-Dimensional Discrete Element Method

Load transformation from the yielding part of the soil to the adjacent part is known as the soil arching effect,which plays an important role in the design of various geotechnical infrastructures.Terzaghi’s trapdoor test was an importantmilestone in the development of theories on soil arching.The research on earth pressure of the trapdoor problem is presented in this paper using the three-dimensional(3D)discrete element method(DEM).Five 3D trapdoor models with different heights are established by 3DDEMsoftware PFC 3D.The variation of earth pressure on the trapdoor with the downward movement of the trapdoor,the distribution of vertical earth pressure along the horizontal direction,the distribution of vertical earth pressure along the vertical direction,the distribution of lateral earth pressure coefficient along the depth direction,the magnitude and direction of contact force chain are studied,respectively.Related research results show that the earth pressure on the trapdoor decreases rapidly after the downward movement of the trapdoor,and then reaches the minimum earth pressure.After that,the earth’s pressure will rise slightly,and whether this phenomenon occurs depends on the depth ratio.For the bottom soil,due to the stress transfer caused by the soil arching effect,the ratio of earth pressure in the loose area decreases,while the ratio of earth pressure in the stable area increases.With the trapdoor moving down,the vertical earth pressure along the depth in the stable zone is basically consistent with the initial state,which shows an approximate linear distribution.After the trapdoor moves down,the distribution of earth pressure along with the depth in the loose area changes,which is far less than the theoretical value of vertical earth pressure of its self-weight.Because of the compression of the soil on both sides,the lateral earth pressure coefficient of most areas on the central axis of the loose zone is close to the passive earth pressure coefficient Kp.The existence of a‘soil arch’can be observed intuitively from the distribution diagram of the contact force chain in the loose zone.