As massive underground projects have become popular in dense urban cities,a problem has arisen:which model predicts the best for Tunnel Boring Machine(TBM)performance in these tunneling projects?However,performance le...As massive underground projects have become popular in dense urban cities,a problem has arisen:which model predicts the best for Tunnel Boring Machine(TBM)performance in these tunneling projects?However,performance level of TBMs in complex geological conditions is still a great challenge for practitioners and researchers.On the other hand,a reliable and accurate prediction of TBM performance is essential to planning an applicable tunnel construction schedule.The performance of TBM is very difficult to estimate due to various geotechnical and geological factors and machine specifications.The previously-proposed intelligent techniques in this field are mostly based on a single or base model with a low level of accuracy.Hence,this study aims to introduce a hybrid randomforest(RF)technique optimized by global harmony search with generalized oppositionbased learning(GOGHS)for forecasting TBM advance rate(AR).Optimizing the RF hyper-parameters in terms of,e.g.,tree number and maximum tree depth is the main objective of using the GOGHS-RF model.In the modelling of this study,a comprehensive databasewith themost influential parameters onTBMtogetherwithTBM AR were used as input and output variables,respectively.To examine the capability and power of the GOGHSRF model,three more hybrid models of particle swarm optimization-RF,genetic algorithm-RF and artificial bee colony-RF were also constructed to forecast TBM AR.Evaluation of the developed models was performed by calculating several performance indices,including determination coefficient(R2),root-mean-square-error(RMSE),and mean-absolute-percentage-error(MAPE).The results showed that theGOGHS-RF is a more accurate technique for estimatingTBMAR compared to the other applied models.The newly-developedGOGHS-RFmodel enjoyed R2=0.9937 and 0.9844,respectively,for train and test stages,which are higher than a pre-developed RF.Also,the importance of the input parameters was interpreted through the SHapley Additive exPlanations(SHAP)method,and it was found that thrust force per cutter is the most important variable on TBMAR.The GOGHS-RF model can be used in mechanized tunnel projects for predicting and checking performance.展开更多
Rock bursts represent a formidable challenge in underground engineering,posing substantial risks to both infrastructure and human safety.These sudden and violent failures of rock masses are characterized by the rapid ...Rock bursts represent a formidable challenge in underground engineering,posing substantial risks to both infrastructure and human safety.These sudden and violent failures of rock masses are characterized by the rapid release of accumulated stress within the rock,leading to severe seismic events and structural damage.Therefore,the development of reliable prediction models for rock bursts is paramount to mitigating these hazards.This study aims to propose a tree-based model—a Light Gradient Boosting Machine(LightGBM)—to predict the intensity of rock bursts in underground engineering.322 actual rock burst cases are collected to constitute an exhaustive rock burst dataset,which serves to train the LightGBMmodel.Two population-basedmetaheuristic algorithms are used to optimize the hyperparameters of the LightGBM model.Finally,the sensitivity analysis is used to identify the predominant factors that may incur the occurrence of rock bursts.The results show that the population-based metaheuristic algorithms have a good ability to search out the optimal hyperparameters of the LightGBM model.The developed LightGBM model yields promising performance in predicting the intensity of rock bursts,with which accuracy on training and testing sets are 0.972 and 0.944,respectively.The sensitivity analysis discloses that the risk of occurring rock burst is significantly sensitive to three factors:uniaxial compressive strength(σc),stress concentration factor(SCF),and elastic strain energy index(Wet).Moreover,this study clarifies the particular impact of these three factors on the intensity of rock bursts through the partial dependence plot.展开更多
In this paper,the type,vertical evolution,and distribution pattern of sedimentary facies of the Paleogene Dainan Formation in the Gaoyou Depression of the North Jiangsu Basin are studied in detail.Results show that fa...In this paper,the type,vertical evolution,and distribution pattern of sedimentary facies of the Paleogene Dainan Formation in the Gaoyou Depression of the North Jiangsu Basin are studied in detail.Results show that fan delta,delta,nearshore subaqueous fan,and lacustrine facies developed during the Dainan Formation period and their distribution pattern was mainly controlled by tectonics and paleogeography.The fan delta and nearshore subaqueous fan facies predominantly occur in the southern steep slope region where fault-induced subsidence is thought to have created substantial accommodation,whereas the delta facies are distributed on the northern gentle slope which is thought to have experienced less subsidence.Finally,the lacustrine facies is shown to have developed in the center of the depression,as well as on the flanks of the fan delta,delta,and nearshore subaqueous fan facies.Vertically,the Dainan Formation represents an integrated transgressiveregressive cycle,with the E_2d_1 being the transgressive sequence and the E_2d_2 being the regressive sequence.This distribution model of sedimentary facies plays an important role in predicting favorable reservoir belts for the Dainan Formation in the Gaoyou Depression and similar areas.In the Gaoyou Depression,sandstones of the subaqueous distributary channels in the fan delta and the subaqueous branch channels in the delta are characterized by physical properties favorable for reservoir formation.展开更多
After the excavation of the roadway,the original stress balance is destroyed,resulting in the redistribution of stress and the formation of an excavation damaged zone(EDZ)around the roadway.The thickness of EDZ is the...After the excavation of the roadway,the original stress balance is destroyed,resulting in the redistribution of stress and the formation of an excavation damaged zone(EDZ)around the roadway.The thickness of EDZ is the key basis for roadway stability discrimination and support structure design,and it is of great engineering significance to accurately predict the thickness of EDZ.Considering the advantages of machine learning(ML)in dealing with high-dimensional,nonlinear problems,a hybrid prediction model based on the random forest(RF)algorithm is developed in this paper.The model used the dragonfly algorithm(DA)to optimize two hyperparameters in RF,namely mtry and ntree,and used mean absolute error(MAE),rootmean square error(RMSE),determination coefficient(R^(2)),and variance accounted for(VAF)to evaluatemodel prediction performance.A database containing 217 sets of data was collected,with embedding depth(ED),drift span(DS),surrounding rock mass strength(RMS),joint index(JI)as input variables,and the excavation damaged zone thickness(EDZT)as output variable.In addition,four classic models,back propagation neural network(BPNN),extreme learning machine(ELM),radial basis function network(RBF),and RF were compared with the DA-RF model.The results showed that the DARF mold had the best prediction performance(training set:MAE=0.1036,RMSE=0.1514,R^(2)=0.9577,VAF=94.2645;test set:MAE=0.1115,RMSE=0.1417,R^(2)=0.9423,VAF=94.0836).The results of the sensitivity analysis showed that the relative importance of each input variable was DS,ED,RMS,and JI from low to high.展开更多
Hard rock pillar is one of the important structures in engineering design and excavation in underground mines.Accurate and convenient prediction of pillar stability is of great significance for underground space safet...Hard rock pillar is one of the important structures in engineering design and excavation in underground mines.Accurate and convenient prediction of pillar stability is of great significance for underground space safety.This paper aims to develop hybrid support vector machine(SVM)models improved by three metaheuristic algorithms known as grey wolf optimizer(GWO),whale optimization algorithm(WOA)and sparrow search algorithm(SSA)for predicting the hard rock pillar stability.An integrated dataset containing 306 hard rock pillars was established to generate hybrid SVM models.Five parameters including pillar height,pillar width,ratio of pillar width to height,uniaxial compressive strength and pillar stress were set as input parameters.Two global indices,three local indices and the receiver operating characteristic(ROC)curve with the area under the ROC curve(AUC)were utilized to evaluate all hybrid models’performance.The results confirmed that the SSA-SVM model is the best prediction model with the highest values of all global indices and local indices.Nevertheless,the performance of the SSASVM model for predicting the unstable pillar(AUC:0.899)is not as good as those for stable(AUC:0.975)and failed pillars(AUC:0.990).To verify the effectiveness of the proposed models,5 field cases were investigated in a metal mine and other 5 cases were collected from several published works.The validation results indicated that the SSA-SVM model obtained a considerable accuracy,which means that the combination of SVM and metaheuristic algorithms is a feasible approach to predict the pillar stability.展开更多
Surface acoustic wave (SAW) technology has been extensively explored for wireless communication, sensors, microfluidics, photonics, and quantum information processing. However, due to fabrication issues, the frequenci...Surface acoustic wave (SAW) technology has been extensively explored for wireless communication, sensors, microfluidics, photonics, and quantum information processing. However, due to fabrication issues, the frequencies of SAW devices are typically limited to within a few gigahertz, which severely restricts their applications in 5G communication, precision sensing, photonics, and quantum control. To solve this critical problem, we propose a hybrid strategy that integrates a nanomanufacturing process (i.e., nanolithography) with a LiNbO_(3)/SiO_(2)/SiC heterostructure and successfully achieve a record-breaking frequency of about 44 GHz for SAW devices, in addition to large electromechanical coupling coefficients of up to 15.7%. We perform a theoretical analysis and identify the guided higher order wave modes generated on these slow-on-fast SAW platforms. To demonstrate the superior sensing performance of the proposed ultra-high-frequency SAW platforms, we perform micro-mass sensing and obtain an extremely high sensitivity of approximately 33151.9 MHz·mm2·μg−1, which is about 1011 times higher than that of a conventional quartz crystal microbalance (QCM) and about 4000 times higher than that of a conventional SAW device with a frequency of 978 MHz.展开更多
A M_(S)6.8 earthquake occurred on 5th September 2022 in Luding county,Sichuan,China,at 12:52 Beijing Time(4:52 UTC).We complied a dataset of PGA,PGV,and site vS30 of 73 accelerometers and 791 Micro-Electro-Mechanical ...A M_(S)6.8 earthquake occurred on 5th September 2022 in Luding county,Sichuan,China,at 12:52 Beijing Time(4:52 UTC).We complied a dataset of PGA,PGV,and site vS30 of 73 accelerometers and 791 Micro-Electro-Mechanical System(MEMS)sensors within 300 km of the epicenter.The inferred v_(S30)of 820 recording sites were validated.The study results show that:(1)The maximum horizontal PGA and PGV reaches 634.1 Gal and 71.1 cm/s respectively.(2)Over 80%of records are from soil sites.(3)The v_(S30)proxy model of Zhou J et al.(2022)is superior than that of Wald and Allen(2007)and performs well in the study area.The dataset was compiled in a flat file that consists the information of strong-motion instruments,the strong-motion records,and the v_(S30)of the recording sites.The dataset is available at https://www.seismisite.net.展开更多
Block-in-matrix-soils(bimsoils)are geological mixtures that have distinct structures consisting of relatively strong rock blocks and weak matrix soils.It is still a challenge to evaluate the mechanical behaviors of bi...Block-in-matrix-soils(bimsoils)are geological mixtures that have distinct structures consisting of relatively strong rock blocks and weak matrix soils.It is still a challenge to evaluate the mechanical behaviors of bimsoils because of the heterogeneity,chaotic structure,and lithological variability.As a result,only very limited laboratory studies have been reported on the evolution of their internal deformation.In this study,the deformation evolution of bimsoils under uniaxial loading is investigated using real-time X-ray computed tomography(CT)and image correlation algorithm(with a rock block percentage(RBP)of 40%).Three parameters,i.e.heterogeneity coefficient(K),correlation coefficient(CC),and standard deviation(STD)of displacement fields,are proposed to quantify the heterogeneity of the motion of the rock blocks and the progressive deformation of the bimsoils.Experimental results show that the rock blocks in bimsoils are prone to forming clusters with increasing loading,and the sliding surface goes around only one side of a cluster.Based on the movement of the rock blocks recorded by STD and CC,the progressive deformation of the bimsoils is quantitatively divided into three stages:initialization of the rotation of rock blocks,formation of rock block clusters,and formation of a shear band by rock blocks with significant rotation.Moreover,the experimental results demonstrate that the meso-motion of rock blocks controls the macroscopic mechanical properties of the samples.展开更多
Antibiotic contamination adversely affects human health and ecological balance.In this study,gasliquid underwater discharge plasma was employed to simultaneously degrade three antibiotics,sulfadiazine(SDZ),tetracyclin...Antibiotic contamination adversely affects human health and ecological balance.In this study,gasliquid underwater discharge plasma was employed to simultaneously degrade three antibiotics,sulfadiazine(SDZ),tetracycline(TC),and norfloxacin(NOR),to address the growing problem of antibiotic contaminants in water.The effects of various parameters on the antibiotic degradation efficiency were evaluated,including the discharge gas type and flow rate,the initial concentration and pH of the solution,and the discharge voltage.Under the optimum parameter configuration,the average removal rate of the three antibiotics was 54.0% and the energy yield was 8.9 g(kW·h)-1after 5 min treatment;the removal efficiency was 96.5% and the corresponding energy yield was4.0 g(kW·h)-1 after 20 min treatment.Reactive substance capture and determination experiments indicated that ·OH and O3 played a vital role in the decomposition of SDZ and NOR,but the role of reactive substances in TC degradation was relatively less significant.展开更多
Adding Na_(2)CO_(3) to the NaHCO_(3) cooling crystallizer, using the common ion effect to promote crystallization and improve product morphology, is a new process recently proposed in the literature. However, the mech...Adding Na_(2)CO_(3) to the NaHCO_(3) cooling crystallizer, using the common ion effect to promote crystallization and improve product morphology, is a new process recently proposed in the literature. However, the mechanism of the impact of Na_(2)CO_(3)on the crystal morphology is still indeterminate. In this work, the crystallization of NaHCO_(3)in water and Na_(2)CO_(3)–NaHCO_(3) aqueous solution was investigated by experiments and molecular dynamics simulations(MD). The crystallization results demonstrate that the morphology of NaHCO_(3) crystal changed gradually from needle-like to flake structure with the addition of Na_(2)CO_(3). The simulation results indicate that the layer docking model and the modified attachment energy formula without considering the roughness of crystal surface can obtain the crystal morphology in agreement with the experimental results, but the lower molecules of the crystal layer have to be fixed during MD. Thermodynamic calculation of the NaHCO_(3) crystallization process verifies that the common ion effect from Na^(+)and the ionization equilibrium transformation from CO_(3)^(2-) jointly promote the precipitation of NaHCO_(3) crystal. The radial distribution function analysis indicates that the oxygen atoms of Na_(2)CO_(3) formed strong hydrogen bonds with the hydrogen atoms of the(0 1 1) face, which weakened the hydration of water molecules at the crystal surface, resulting in a significant change in the attachment energy of this crystal surface. In addition, Na+and CO_(3)^(2-) are more likely to accumulate on the(011) face,resulting in the fastest growth rate on this crystal surface, which eventually leads to a change in crystal morphology from needle-like to flake-like.展开更多
Exposed to the natural light-dark cycle,24 h rhythms exist in behavioral and physiological processes of living beings.Interestingly,under constant darkness or constant light,living beings can maintain a robust endogen...Exposed to the natural light-dark cycle,24 h rhythms exist in behavioral and physiological processes of living beings.Interestingly,under constant darkness or constant light,living beings can maintain a robust endogenous rhythm with a free running period(FRP)close to 24 h.In mammals,the circadian rhythm is coordinated by a master clock located in the suprachiasmatic nucleus(SCN)of the brain,which is composed of about twenty thousand self-oscillating neurons.These SCN neurons form a heterogenous network to output a robust rhythm.Thus far,the exact network topology of the SCN neurons is unknown.In this article,we examine the effect of the SCN network structure on the FRP when exposed to constant light by a Poincare model.Four typical network structures are considered,including a nearest-neighbor coupled network,a Newman-Watts small world network,an Erd¨os-Renyi random network and a Barabasi-Albert(BA)scale free network.The results show that the FRP is longest in the BA network,because the BA network is characterized by the most heterogeneous structure among these four types of networks.These findings are not affected by the average node degree of the SCN network or the value of relaxation rate of the SCN neuronal oscillators.Our findings contribute to the understanding of how the network structure of the SCN neurons influences the FRP.展开更多
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 incorpo...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.展开更多
The Wnt/β-catenin signaling pathway is the main target of tooth regeneration regulation.Treatment of cells with AZD2858 stimulates the Wnt/β-catenin signaling pathway,yet the function of this pathway in tooth regene...The Wnt/β-catenin signaling pathway is the main target of tooth regeneration regulation.Treatment of cells with AZD2858 stimulates the Wnt/β-catenin signaling pathway,yet the function of this pathway in tooth regeneration remains unclear.Here,we found that AZD2858 promotes the accumulation ofβ-catenin in the nuclei of stem cells from the apical papilla(SCAPs)and enhances cell proliferation.Single-cell sequencing was performed on SCAPs treated with AZD2858.Eight clusters were identified,namely SCAPs-CNTNAP2,SCAPs-DTL,SCAPs-MYH11,SCAPs-MKI67,SCAPs-CXCL8,SCAPs-TPM2,SCAPs-IFIT2 and SCAPs-NEK10.The pseudo-time trajectory analysis showed that AZD2858 enhanced the evolution of SCAPs from SCAPs-TMP2 clusters to SCAPs-MYH11,SCAPs-CNTNAPs and SCAPs-NEK10 clusters via up-regulation of PRKCA,SMURF2,MAGI2,RBMS3,EXT1,CAMK2D,PLCB4,and PLCB1.These results demonstrate that AZD2858 enhances the proliferation of SCAPs-TPM2 cluster by activating the non-canonical Wnt/β-catenin signaling pathway.展开更多
Rock strength is a crucial factor to consider when designing and constructing underground projects.This study utilizes a gene expression programming(GEP)algorithm-based model to predict the true triaxial strength of r...Rock strength is a crucial factor to consider when designing and constructing underground projects.This study utilizes a gene expression programming(GEP)algorithm-based model to predict the true triaxial strength of rocks,taking into account the influence of rock genesis on their mechanical behavior during the model building process.A true triaxial strength criterion based on the GEP model for igneous,metamorphic and magmatic rocks was obtained by training the model using collected data.Compared to the modified Weibols-Cook criterion,the modified Mohr-Coulomb criterion,and the modified Lade criterion,the strength criterion based on the GEP model exhibits superior prediction accuracy performance.The strength criterion based on the GEP model has better performance in R2,RMSE and MAPE for the data set used in this study.Furthermore,the strength criterion based on the GEP model shows greater stability in predicting the true triaxial strength of rocks across different types.Compared to the existing strength criterion based on the genetic programming(GP)model,the proposed criterion based on GEP model achieves more accurate predictions of the variation of true triaxial strength(s1)with intermediate principal stress(s2).Finally,based on the Sobol sensitivity analysis technique,the effects of the parameters of the three obtained strength criteria on the true triaxial strength of the rock are analysed.In general,the proposed strength criterion exhibits superior performance in terms of both accuracy and stability of prediction results.展开更多
Atherosclerotic cardiovascular disease(ASCVD)includes a group of disorders of the heart and blood vessels and accounts for major morbidity and premature death worldwide.Periodontitis is a chronic inflammatory disease ...Atherosclerotic cardiovascular disease(ASCVD)includes a group of disorders of the heart and blood vessels and accounts for major morbidity and premature death worldwide.Periodontitis is a chronic inflammatory disease with the gradual destruction of supporting tissues around the teeth,including gingiva,periodontal ligament,alveolar bone,and cementum.Periodontitis has been found to potentially increase the risk of ASCVD.Generally,oral microorganisms and inflammation are the major factors for periodontitis to the incidence of ASCVD.Recently,evidence has shown that the loss of masticatory function is another important factor of periodontitis to the incidence of ASCVD.In this review,we illustrate the recent finding of the relationship between periodontitis and ASCVD,from a microscale perspective-oral microorganisms,inflammation,and tooth loss.With the high prevalence of periodontitis,it is important to add oral therapy as a regular ASCVD prevention strategy.Regular dental visits could be a helpful strategy for ASCVD patients or general medical practitioners.展开更多
Two-dimensional(2D)semiconductors have attracted considerable interest for their unique physical properties.Here,we report the intrinsic cryogenic electronic transport properties in few-layer MoSe_(2)field-effect tran...Two-dimensional(2D)semiconductors have attracted considerable interest for their unique physical properties.Here,we report the intrinsic cryogenic electronic transport properties in few-layer MoSe_(2)field-effect transistors(FETs)that are fully encapsulated in ultraclean hexagonal boron nitride dielectrics and are simultaneously van der Waals contacted with gold electrodes.The FETs exhibit electronically favorable channel/dielectric interfaces with low densities of interfacial traps(<1010cm^(-2)),which lead to outstanding device characteristics at room temperature,including near-Boltzmann-limit subthreshold swings(65 mV/dec),high carrier mobilities(53–68 cm^(2)·V-1·s^(-1)),and negligible scanning hystereses(<15 mV).The dependence of various contact-related parameters with temperature and carrier density is also systematically characterized to understand the van der Waals contacts between gold and MoSe_(2).The results provide insightful information about the device physics in van der Waals contacted and encapsulated 2D FETs.展开更多
背景与目的并发症是肺切除术后患者死亡的重要原因,目前我国肺癌胸腔镜手术普及率逐年增高,但肺癌胸腔镜手术术后并发症的预测模型尚缺乏基于大样本数据库的支持。本研究采用TM&M(Thoracic Mortality and Morbidity)分级系统全面描...背景与目的并发症是肺切除术后患者死亡的重要原因,目前我国肺癌胸腔镜手术普及率逐年增高,但肺癌胸腔镜手术术后并发症的预测模型尚缺乏基于大样本数据库的支持。本研究采用TM&M(Thoracic Mortality and Morbidity)分级系统全面描绘我中心胸腔镜肺癌手术术后并发症,并建立和验证并发症的预测模型。该模型可为此类患者术后并发症的预防和干预提供依据,从而加速患者康复。方法回顾性收集我中心2007年1月-2018年12月胸腔镜肺癌手术患者临床资料,仅纳入Ⅰ期-Ⅲ期肺癌行胸腔镜肺主要手术的肺癌患者,术后并发症登记严格采用TM&M分级系统。将患者按照手术时期分为两组:前期组(2007年-2012年)和后期组(2013年-2018年),以倾向评分匹配法对两组基线数据进行匹配;匹配后数据采用二元Logistic回归分析建立并发症的预测模型,Bootstrap法内抽样进行内部验证。结果研究共纳入2,881例肺癌患者,平均年龄(61.0±10.1)岁,其中发生主要并发症180例(6.2%)。匹配后的1,268例患者进行二元Logistic回归分析显示:年龄(OR=1.04,95%CI:1.02-1.06,P<0.001)、手术时期(OR=0.62,95%CI:0.49-0.79,P<0.001)、病理类型(OR=1.73,95%CI:1.24-2.41,P=0.001)、术中出血量(OR=1.001,95%CI:1.000-1.003,P=0.03)、清扫淋巴结数目(OR=1.022,95%CI:1.00-1.04,P=0.005)为术后并发症发生的独立危险因素;将其纳入列线图模型,受试者工作特征曲线(receiver operating characteristic curve,ROC)提示该模型区分度较好(C-指数为0.699),1,000次重复Bootstrap内部抽样验证C-指数为0.680。校准曲线显示预测模型的校准度良好。结论TM&M并发症分级系统可全面准确地报告胸腔镜肺癌外科的术后并发症。年龄、手术时期、病理类型、术中出血量、清扫淋巴结数目是胸腔镜肺癌手术后主要并发症的独立危险因素,以此建立的并发症预测模型具有较好的区分度和校准度。展开更多
基金the National Natural Science Foundation of China(Grant 42177164)the Distinguished Youth Science Foundation of Hunan Province of China(2022JJ10073).
文摘As massive underground projects have become popular in dense urban cities,a problem has arisen:which model predicts the best for Tunnel Boring Machine(TBM)performance in these tunneling projects?However,performance level of TBMs in complex geological conditions is still a great challenge for practitioners and researchers.On the other hand,a reliable and accurate prediction of TBM performance is essential to planning an applicable tunnel construction schedule.The performance of TBM is very difficult to estimate due to various geotechnical and geological factors and machine specifications.The previously-proposed intelligent techniques in this field are mostly based on a single or base model with a low level of accuracy.Hence,this study aims to introduce a hybrid randomforest(RF)technique optimized by global harmony search with generalized oppositionbased learning(GOGHS)for forecasting TBM advance rate(AR).Optimizing the RF hyper-parameters in terms of,e.g.,tree number and maximum tree depth is the main objective of using the GOGHS-RF model.In the modelling of this study,a comprehensive databasewith themost influential parameters onTBMtogetherwithTBM AR were used as input and output variables,respectively.To examine the capability and power of the GOGHSRF model,three more hybrid models of particle swarm optimization-RF,genetic algorithm-RF and artificial bee colony-RF were also constructed to forecast TBM AR.Evaluation of the developed models was performed by calculating several performance indices,including determination coefficient(R2),root-mean-square-error(RMSE),and mean-absolute-percentage-error(MAPE).The results showed that theGOGHS-RF is a more accurate technique for estimatingTBMAR compared to the other applied models.The newly-developedGOGHS-RFmodel enjoyed R2=0.9937 and 0.9844,respectively,for train and test stages,which are higher than a pre-developed RF.Also,the importance of the input parameters was interpreted through the SHapley Additive exPlanations(SHAP)method,and it was found that thrust force per cutter is the most important variable on TBMAR.The GOGHS-RF model can be used in mechanized tunnel projects for predicting and checking performance.
文摘Rock bursts represent a formidable challenge in underground engineering,posing substantial risks to both infrastructure and human safety.These sudden and violent failures of rock masses are characterized by the rapid release of accumulated stress within the rock,leading to severe seismic events and structural damage.Therefore,the development of reliable prediction models for rock bursts is paramount to mitigating these hazards.This study aims to propose a tree-based model—a Light Gradient Boosting Machine(LightGBM)—to predict the intensity of rock bursts in underground engineering.322 actual rock burst cases are collected to constitute an exhaustive rock burst dataset,which serves to train the LightGBMmodel.Two population-basedmetaheuristic algorithms are used to optimize the hyperparameters of the LightGBM model.Finally,the sensitivity analysis is used to identify the predominant factors that may incur the occurrence of rock bursts.The results show that the population-based metaheuristic algorithms have a good ability to search out the optimal hyperparameters of the LightGBM model.The developed LightGBM model yields promising performance in predicting the intensity of rock bursts,with which accuracy on training and testing sets are 0.972 and 0.944,respectively.The sensitivity analysis discloses that the risk of occurring rock burst is significantly sensitive to three factors:uniaxial compressive strength(σc),stress concentration factor(SCF),and elastic strain energy index(Wet).Moreover,this study clarifies the particular impact of these three factors on the intensity of rock bursts through the partial dependence plot.
基金financially supported by the National Natural Science Foundation of China (Grants Nos. 41272124 and 41402092)Natural Science Foundation (Youth Science Fund Project) of Jiangsu Province (BK20140604)+1 种基金the Fundamental Research Funds for the Central Universities (20620140386)the State Key Laboratory for Mineral Deposits Research of Nanjing University (Grant No. ZZKT-201321)
文摘In this paper,the type,vertical evolution,and distribution pattern of sedimentary facies of the Paleogene Dainan Formation in the Gaoyou Depression of the North Jiangsu Basin are studied in detail.Results show that fan delta,delta,nearshore subaqueous fan,and lacustrine facies developed during the Dainan Formation period and their distribution pattern was mainly controlled by tectonics and paleogeography.The fan delta and nearshore subaqueous fan facies predominantly occur in the southern steep slope region where fault-induced subsidence is thought to have created substantial accommodation,whereas the delta facies are distributed on the northern gentle slope which is thought to have experienced less subsidence.Finally,the lacustrine facies is shown to have developed in the center of the depression,as well as on the flanks of the fan delta,delta,and nearshore subaqueous fan facies.Vertically,the Dainan Formation represents an integrated transgressiveregressive cycle,with the E_2d_1 being the transgressive sequence and the E_2d_2 being the regressive sequence.This distribution model of sedimentary facies plays an important role in predicting favorable reservoir belts for the Dainan Formation in the Gaoyou Depression and similar areas.In the Gaoyou Depression,sandstones of the subaqueous distributary channels in the fan delta and the subaqueous branch channels in the delta are characterized by physical properties favorable for reservoir formation.
基金funded by the National Science Foundation of China(42177164)the Distinguished Youth Science Foundation of Hunan Province of China(2022JJ10073)the Innovation-Driven Project of Central South University(2020CX040).
文摘After the excavation of the roadway,the original stress balance is destroyed,resulting in the redistribution of stress and the formation of an excavation damaged zone(EDZ)around the roadway.The thickness of EDZ is the key basis for roadway stability discrimination and support structure design,and it is of great engineering significance to accurately predict the thickness of EDZ.Considering the advantages of machine learning(ML)in dealing with high-dimensional,nonlinear problems,a hybrid prediction model based on the random forest(RF)algorithm is developed in this paper.The model used the dragonfly algorithm(DA)to optimize two hyperparameters in RF,namely mtry and ntree,and used mean absolute error(MAE),rootmean square error(RMSE),determination coefficient(R^(2)),and variance accounted for(VAF)to evaluatemodel prediction performance.A database containing 217 sets of data was collected,with embedding depth(ED),drift span(DS),surrounding rock mass strength(RMS),joint index(JI)as input variables,and the excavation damaged zone thickness(EDZT)as output variable.In addition,four classic models,back propagation neural network(BPNN),extreme learning machine(ELM),radial basis function network(RBF),and RF were compared with the DA-RF model.The results showed that the DARF mold had the best prediction performance(training set:MAE=0.1036,RMSE=0.1514,R^(2)=0.9577,VAF=94.2645;test set:MAE=0.1115,RMSE=0.1417,R^(2)=0.9423,VAF=94.0836).The results of the sensitivity analysis showed that the relative importance of each input variable was DS,ED,RMS,and JI from low to high.
基金supported by the National Natural Science Foundation Project of China(Nos.72088101 and 42177164)the Distinguished Youth Science Foundation of Hunan Province of China(No.2022JJ10073)The first author was funded by China Scholarship Council(No.202106370038).
文摘Hard rock pillar is one of the important structures in engineering design and excavation in underground mines.Accurate and convenient prediction of pillar stability is of great significance for underground space safety.This paper aims to develop hybrid support vector machine(SVM)models improved by three metaheuristic algorithms known as grey wolf optimizer(GWO),whale optimization algorithm(WOA)and sparrow search algorithm(SSA)for predicting the hard rock pillar stability.An integrated dataset containing 306 hard rock pillars was established to generate hybrid SVM models.Five parameters including pillar height,pillar width,ratio of pillar width to height,uniaxial compressive strength and pillar stress were set as input parameters.Two global indices,three local indices and the receiver operating characteristic(ROC)curve with the area under the ROC curve(AUC)were utilized to evaluate all hybrid models’performance.The results confirmed that the SSA-SVM model is the best prediction model with the highest values of all global indices and local indices.Nevertheless,the performance of the SSASVM model for predicting the unstable pillar(AUC:0.899)is not as good as those for stable(AUC:0.975)and failed pillars(AUC:0.990).To verify the effectiveness of the proposed models,5 field cases were investigated in a metal mine and other 5 cases were collected from several published works.The validation results indicated that the SSA-SVM model obtained a considerable accuracy,which means that the combination of SVM and metaheuristic algorithms is a feasible approach to predict the pillar stability.
基金supported by the National Science Foundation of China(NSFC)(52075162)the Program of New and High-Tech Industry of Hunan Province(2020GK2015 and 2021GK4014)+5 种基金the Excellent Youth Fund of Hunan Province(2021JJ20018)the Key Program of Guangdong(2020B0101040002)the Joint Fund of the Ministry of Education(Young Talents)the Natural Science Foundation of Changsha(kq2007026)the Tianjin Enterprise Science and Technology Commissioner Project(19JCTPJC56200)the Engineering Physics and Science Research Council of the United Kingdom(EPSRC EP/P018998/1).
文摘Surface acoustic wave (SAW) technology has been extensively explored for wireless communication, sensors, microfluidics, photonics, and quantum information processing. However, due to fabrication issues, the frequencies of SAW devices are typically limited to within a few gigahertz, which severely restricts their applications in 5G communication, precision sensing, photonics, and quantum control. To solve this critical problem, we propose a hybrid strategy that integrates a nanomanufacturing process (i.e., nanolithography) with a LiNbO_(3)/SiO_(2)/SiC heterostructure and successfully achieve a record-breaking frequency of about 44 GHz for SAW devices, in addition to large electromechanical coupling coefficients of up to 15.7%. We perform a theoretical analysis and identify the guided higher order wave modes generated on these slow-on-fast SAW platforms. To demonstrate the superior sensing performance of the proposed ultra-high-frequency SAW platforms, we perform micro-mass sensing and obtain an extremely high sensitivity of approximately 33151.9 MHz·mm2·μg−1, which is about 1011 times higher than that of a conventional quartz crystal microbalance (QCM) and about 4000 times higher than that of a conventional SAW device with a frequency of 978 MHz.
基金supported by the National Natural Science Foundation of China(No.42120104002)the Program of China-Pakistan Joint Research Center on Earth Sciences.
文摘A M_(S)6.8 earthquake occurred on 5th September 2022 in Luding county,Sichuan,China,at 12:52 Beijing Time(4:52 UTC).We complied a dataset of PGA,PGV,and site vS30 of 73 accelerometers and 791 Micro-Electro-Mechanical System(MEMS)sensors within 300 km of the epicenter.The inferred v_(S30)of 820 recording sites were validated.The study results show that:(1)The maximum horizontal PGA and PGV reaches 634.1 Gal and 71.1 cm/s respectively.(2)Over 80%of records are from soil sites.(3)The v_(S30)proxy model of Zhou J et al.(2022)is superior than that of Wald and Allen(2007)and performs well in the study area.The dataset was compiled in a flat file that consists the information of strong-motion instruments,the strong-motion records,and the v_(S30)of the recording sites.The dataset is available at https://www.seismisite.net.
基金This work was supported by the National Natural Science Foundation of China(Grants Nos.41972287 and 42090023)the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(Grant No.2019QZKK0904).
文摘Block-in-matrix-soils(bimsoils)are geological mixtures that have distinct structures consisting of relatively strong rock blocks and weak matrix soils.It is still a challenge to evaluate the mechanical behaviors of bimsoils because of the heterogeneity,chaotic structure,and lithological variability.As a result,only very limited laboratory studies have been reported on the evolution of their internal deformation.In this study,the deformation evolution of bimsoils under uniaxial loading is investigated using real-time X-ray computed tomography(CT)and image correlation algorithm(with a rock block percentage(RBP)of 40%).Three parameters,i.e.heterogeneity coefficient(K),correlation coefficient(CC),and standard deviation(STD)of displacement fields,are proposed to quantify the heterogeneity of the motion of the rock blocks and the progressive deformation of the bimsoils.Experimental results show that the rock blocks in bimsoils are prone to forming clusters with increasing loading,and the sliding surface goes around only one side of a cluster.Based on the movement of the rock blocks recorded by STD and CC,the progressive deformation of the bimsoils is quantitatively divided into three stages:initialization of the rotation of rock blocks,formation of rock block clusters,and formation of a shear band by rock blocks with significant rotation.Moreover,the experimental results demonstrate that the meso-motion of rock blocks controls the macroscopic mechanical properties of the samples.
基金supported by the Key R&D Plan of Anhui Province(No.201904a07020013)Collaborative Innovation Program of Hefei Science Center,CAS(No.CX2140000018)the Funding for Joint Lab of Applied Plasma Technology(No.JL06120001H)。
文摘Antibiotic contamination adversely affects human health and ecological balance.In this study,gasliquid underwater discharge plasma was employed to simultaneously degrade three antibiotics,sulfadiazine(SDZ),tetracycline(TC),and norfloxacin(NOR),to address the growing problem of antibiotic contaminants in water.The effects of various parameters on the antibiotic degradation efficiency were evaluated,including the discharge gas type and flow rate,the initial concentration and pH of the solution,and the discharge voltage.Under the optimum parameter configuration,the average removal rate of the three antibiotics was 54.0% and the energy yield was 8.9 g(kW·h)-1after 5 min treatment;the removal efficiency was 96.5% and the corresponding energy yield was4.0 g(kW·h)-1 after 20 min treatment.Reactive substance capture and determination experiments indicated that ·OH and O3 played a vital role in the decomposition of SDZ and NOR,but the role of reactive substances in TC degradation was relatively less significant.
基金supported by the National Natural Science Foundation of China (21878143)the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)。
文摘Adding Na_(2)CO_(3) to the NaHCO_(3) cooling crystallizer, using the common ion effect to promote crystallization and improve product morphology, is a new process recently proposed in the literature. However, the mechanism of the impact of Na_(2)CO_(3)on the crystal morphology is still indeterminate. In this work, the crystallization of NaHCO_(3)in water and Na_(2)CO_(3)–NaHCO_(3) aqueous solution was investigated by experiments and molecular dynamics simulations(MD). The crystallization results demonstrate that the morphology of NaHCO_(3) crystal changed gradually from needle-like to flake structure with the addition of Na_(2)CO_(3). The simulation results indicate that the layer docking model and the modified attachment energy formula without considering the roughness of crystal surface can obtain the crystal morphology in agreement with the experimental results, but the lower molecules of the crystal layer have to be fixed during MD. Thermodynamic calculation of the NaHCO_(3) crystallization process verifies that the common ion effect from Na^(+)and the ionization equilibrium transformation from CO_(3)^(2-) jointly promote the precipitation of NaHCO_(3) crystal. The radial distribution function analysis indicates that the oxygen atoms of Na_(2)CO_(3) formed strong hydrogen bonds with the hydrogen atoms of the(0 1 1) face, which weakened the hydration of water molecules at the crystal surface, resulting in a significant change in the attachment energy of this crystal surface. In addition, Na+and CO_(3)^(2-) are more likely to accumulate on the(011) face,resulting in the fastest growth rate on this crystal surface, which eventually leads to a change in crystal morphology from needle-like to flake-like.
基金the National Natural Science Foundation of China(Grant Nos.12275179 and 11875042)the Natural Science Foundation of Shanghai(Grant No.21ZR1443900)。
文摘Exposed to the natural light-dark cycle,24 h rhythms exist in behavioral and physiological processes of living beings.Interestingly,under constant darkness or constant light,living beings can maintain a robust endogenous rhythm with a free running period(FRP)close to 24 h.In mammals,the circadian rhythm is coordinated by a master clock located in the suprachiasmatic nucleus(SCN)of the brain,which is composed of about twenty thousand self-oscillating neurons.These SCN neurons form a heterogenous network to output a robust rhythm.Thus far,the exact network topology of the SCN neurons is unknown.In this article,we examine the effect of the SCN network structure on the FRP when exposed to constant light by a Poincare model.Four typical network structures are considered,including a nearest-neighbor coupled network,a Newman-Watts small world network,an Erd¨os-Renyi random network and a Barabasi-Albert(BA)scale free network.The results show that the FRP is longest in the BA network,because the BA network is characterized by the most heterogeneous structure among these four types of networks.These findings are not affected by the average node degree of the SCN network or the value of relaxation rate of the SCN neuronal oscillators.Our findings contribute to the understanding of how the network structure of the SCN neurons influences the FRP.
基金found by Science and Technology Research Project of Jiangxi Provincial Department of Education(Grant Nos.GJJ210645,GJJ210623)Key R&D Projects of Xinjiang Uygur Autonomous Region(Grant No.2021B01005)and Science and Technology Project of Jiangxi Provincial Department of Transportation(Grant Nos.2020Z0002,2018Q0030)the financial support from China Scholarship Council and Chang’an University.The special thanks would go to Dr.Yuan Zhang and Dr.Hui Chen,both of who provide the professional training and help.
文摘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.
基金the fund of National Natural Science Foundation of China(82170951)Beijing Natural Science Foundation(7222079).
文摘The Wnt/β-catenin signaling pathway is the main target of tooth regeneration regulation.Treatment of cells with AZD2858 stimulates the Wnt/β-catenin signaling pathway,yet the function of this pathway in tooth regeneration remains unclear.Here,we found that AZD2858 promotes the accumulation ofβ-catenin in the nuclei of stem cells from the apical papilla(SCAPs)and enhances cell proliferation.Single-cell sequencing was performed on SCAPs treated with AZD2858.Eight clusters were identified,namely SCAPs-CNTNAP2,SCAPs-DTL,SCAPs-MYH11,SCAPs-MKI67,SCAPs-CXCL8,SCAPs-TPM2,SCAPs-IFIT2 and SCAPs-NEK10.The pseudo-time trajectory analysis showed that AZD2858 enhanced the evolution of SCAPs from SCAPs-TMP2 clusters to SCAPs-MYH11,SCAPs-CNTNAPs and SCAPs-NEK10 clusters via up-regulation of PRKCA,SMURF2,MAGI2,RBMS3,EXT1,CAMK2D,PLCB4,and PLCB1.These results demonstrate that AZD2858 enhances the proliferation of SCAPs-TPM2 cluster by activating the non-canonical Wnt/β-catenin signaling pathway.
基金supported by the National Natural Science Foundation of China(Grant No.42177164)the Distinguished Youth Science Foundation of Hunan Province of China(Grant No.2022JJ10073)the Innovation-Driven Project of Central South University(Grant No.2020CX040).
文摘Rock strength is a crucial factor to consider when designing and constructing underground projects.This study utilizes a gene expression programming(GEP)algorithm-based model to predict the true triaxial strength of rocks,taking into account the influence of rock genesis on their mechanical behavior during the model building process.A true triaxial strength criterion based on the GEP model for igneous,metamorphic and magmatic rocks was obtained by training the model using collected data.Compared to the modified Weibols-Cook criterion,the modified Mohr-Coulomb criterion,and the modified Lade criterion,the strength criterion based on the GEP model exhibits superior prediction accuracy performance.The strength criterion based on the GEP model has better performance in R2,RMSE and MAPE for the data set used in this study.Furthermore,the strength criterion based on the GEP model shows greater stability in predicting the true triaxial strength of rocks across different types.Compared to the existing strength criterion based on the genetic programming(GP)model,the proposed criterion based on GEP model achieves more accurate predictions of the variation of true triaxial strength(s1)with intermediate principal stress(s2).Finally,based on the Sobol sensitivity analysis technique,the effects of the parameters of the three obtained strength criteria on the true triaxial strength of the rock are analysed.In general,the proposed strength criterion exhibits superior performance in terms of both accuracy and stability of prediction results.
基金supported by the National Natural Science Foundation of China(82001067)the Innovation Research Team Project of Beijing Stomatological Hospital,Capital Medical University(CXTD202201)+2 种基金Beijing Municipal Administration of Hospitals’Youth Program(QML20191504)Scientific Research Common Program of Beijing Municipal Commission of Education(KM202110025009)Beijing Talents Fund(2018000021469G285).
文摘Atherosclerotic cardiovascular disease(ASCVD)includes a group of disorders of the heart and blood vessels and accounts for major morbidity and premature death worldwide.Periodontitis is a chronic inflammatory disease with the gradual destruction of supporting tissues around the teeth,including gingiva,periodontal ligament,alveolar bone,and cementum.Periodontitis has been found to potentially increase the risk of ASCVD.Generally,oral microorganisms and inflammation are the major factors for periodontitis to the incidence of ASCVD.Recently,evidence has shown that the loss of masticatory function is another important factor of periodontitis to the incidence of ASCVD.In this review,we illustrate the recent finding of the relationship between periodontitis and ASCVD,from a microscale perspective-oral microorganisms,inflammation,and tooth loss.With the high prevalence of periodontitis,it is important to add oral therapy as a regular ASCVD prevention strategy.Regular dental visits could be a helpful strategy for ASCVD patients or general medical practitioners.
基金the National Key R&D Program of China(Grant Nos.2022YFA1203802 and 2021YFA1202903)the National Natural Science Foundation of China(Grant Nos.92264202,61974060,and 61674080)the Innovation and Entrepreneurship Program of Jiangsu Province。
文摘Two-dimensional(2D)semiconductors have attracted considerable interest for their unique physical properties.Here,we report the intrinsic cryogenic electronic transport properties in few-layer MoSe_(2)field-effect transistors(FETs)that are fully encapsulated in ultraclean hexagonal boron nitride dielectrics and are simultaneously van der Waals contacted with gold electrodes.The FETs exhibit electronically favorable channel/dielectric interfaces with low densities of interfacial traps(<1010cm^(-2)),which lead to outstanding device characteristics at room temperature,including near-Boltzmann-limit subthreshold swings(65 mV/dec),high carrier mobilities(53–68 cm^(2)·V-1·s^(-1)),and negligible scanning hystereses(<15 mV).The dependence of various contact-related parameters with temperature and carrier density is also systematically characterized to understand the van der Waals contacts between gold and MoSe_(2).The results provide insightful information about the device physics in van der Waals contacted and encapsulated 2D FETs.
