Insight Into the Separation-of-Variable Methods for the Closed-Form Solutions of Free Vibration of Rectangular Thin Plates

The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytical solutions for free vibration and eigenbuckling of rectangular plates and circular cylindrical shells.By taking the free vibration of rectangular thin plates as an example,this work presents the theoretical framework of the SOV methods in an instructive way,and the bisection–based solution procedures for a group of nonlinear eigenvalue equations.Besides,the explicit equations of nodal lines of the SOV methods are presented,and the relations of nodal line patterns and frequency orders are investigated.It is concluded that the highly accurate SOV methods have the same accuracy for all frequencies,the mode shapes about repeated frequencies can also be precisely captured,and the SOV methods do not have the problem of missing roots as well.

Structural Modal Parameter Recognition and Related Damage Identification Methods under Environmental Excitations: A Review

Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.

数字普惠金融赋能县域产业结构转型升级的动力机制——基于PLS-SEM模型分析

基于偏最小二乘法结构方程模型(PLS-SEM),运用河南省县域2014—2020年平衡面板数据研究数字普惠金融驱动河南省县域产业转型升级的机制与实证效果,结果表明:数字普惠金融能够推动河南省县域产业结构的转型升级;数字普惠金融主要通过经济发展、生态环境、社会共享三个方面共同推动河南省县域产业结构转型升级;从发展潜力方面看,数字普惠金融对产业结构升级有一定负相关性,可能的原因是河南省县域数字平台不够完善、数字信息技术落后,且大多以轻工业、农业为主,导致数字普惠金融的正向融入性存在延迟。必须持续推动数字普惠金融的产业融入性、夯实数字普惠金融服务实体经济的功能性,提高河南省县域产业经济韧性。

基于PLS-SEM模型的旅游目的地品牌资产形成路径研究——来自大理洱海生态廊道的实证研究

旅游目的地品牌资产建设是旅游目的地品牌化的核心内容。从游客的视角建立包括品牌知名度、品牌感知质量、品牌体验、品牌感知价值和品牌忠诚五个构成要素的旅游目的地品牌资产模型,并对大理洱海生态廊道的游客进行调查,收集了482份有效问卷,建立了基于PLS-SEM的大理洱海生态廊道品牌资产路径模型,发现品牌资产各构成要素对品牌忠诚的总效应从大到小依次排序为:品牌感知质量、品牌知名度、品牌体验、品牌感知价值,提出了构建旅游目的地品牌资产的建议。

学习参与、学生认可与高校线上教学满意度——基于PLS-SEM模型

基于学生视角,引入教学资源、学习参与、学生认可、教学满意度四个研究变量,利用结构方程模型,从资源因素→行为因素→认知因素三个角度深入探讨学生在教学满意度评价过程中各因素的影响机理和作用路径。研究结果显示:教学资源、学习参与和学生认可均对教学满意度评价有显著的正向影响;除直接影响外,教学资源还通过学习参与和学生认可间接对教学满意度评价有正向影响,学习参与也通过学生认可间接正向影响教学满意度评价。进一步探讨了不同性别、专业学生满意度评价的差异性,研究发现:男生的学习参与对教学满意度并不产生显著影响;理工医组课程的设计性和实验性使其学习参与对学生认可并不产生显著影响。因此,全力建设线上教学资源、提高线上学习参与、提升线上学习体验是提升线上教学满意度的有效途径。

基于BN和PLS-SEM的大学生网约车忠诚度研究

为分析大学生网约车乘客忠诚度及其影响因素的作用机制,将贝叶斯网络(Bayesian networks,BN)和偏最小二乘法结构方程模型(partial least squares structural equation modelling,PLS-SEM)结合,以2019年大连市大学生网约车乘客为例,分析大学生网约车乘客的负面体验、运营服务、环境满意、乘客满意度和忠诚度的关系。在BN中采用基于约束的自动学习方法学习因子间的作用关系,获得不同影响因素间相关关系的网络结构。通过PLS-SEM测试和分析BN结构,建立乘客忠诚度模型。结果表明:乘客满意度是影响忠诚度的最大因素,总效应为0.508;负面体验是影响忠诚度的最小因素,总效应为-0.146。乘客满意度是提高大学生网约车忠诚度的关键指标,网约车平台应通过优化车内环境、缩短出行时间、规范司机行为、升级应用软件等措施提升大学生的乘车体验,提高大学生网约车乘客的忠诚度。基于BN和PLS-SEM的大学生网约车忠诚度研究可丰富网约车乘客的决策行为机制与研究方法,为相关部门和网约车平台提供管理决策依据。

基于PLS-SEM的高速公路施工企业竞争文化建设路径研究

为充分挖掘高速公路施工企业竞争文化要素间的作用关系,提升高速公路施工企业竞争意识,推动交通强国战略目标实现,本文对高速公路施工企业竞争文化建设路径进行探究。利用词频-逆向文件频率(TF-IDF)算法对291家施工企业的竞争文化文本表现特征进行提取,构建个人要求、晋升激励、质量成本管理、部门管理理念、合作与竞争观念、社会责任与使命6个影响因素的高速公路施工企业竞争文化作用关系概念模型。通过偏最小二乘法结构方程模型(PLS-SEM)分析各要素间的作用关系。最后,基于竞争文化要素间的路径系数,构建激励型路径、引导型路径和反馈型路径共3种高速公路施工企业竞争文化建设路径。

小样本下岭PLS-SEM与岭CB-SEM的比较

目前主要有两种结构方程模型(SEM):CB-SEM和PLS-SEM。当样本量较小时,CB-SEM常常会出现不收敛的情况,使用岭方法可以改善这个问题。文章主要研究将岭方法运用到PLS-SEM中,对比岭方法下PLS-SEM与CB-SEM的表现。研究表明,岭CB-SEM和岭PLS-SEM估计量总体上比常规的CB-SEM和PLS-SEM估计量更精确,但偏差没有明显改善;当样本量较小时,PLS-SEM、岭PLS-SEM估计的精确性都优于CB-SEM、岭CB-SEM;对于受到中介变量影响的内生潜变量来说,岭PLS-SEM在估计其他潜变量对它的影响(路径系数)时最精确。

A Review on Sources,Extractions and Analysis Methods of a Sustainable Biomaterial:Tannins

Condensed and hydrolysable tannins are non-toxic natural polyphenols that are a commercial commodity industrialized for tanning hides to obtain leather and for a growing number of other industrial applications mainly to substitute petroleum-based products.They are a definite class of sustainable materials of the forestry industry.They have been in operation for hundreds of years to manufacture leather and now for a growing number of applications in a variety of other industries,such as wood adhesives,metal coating,pharmaceutical/medical applications and several others.This review presents the main sources,either already or potentially commercial of this forestry by-materials,their industrial and laboratory extraction systems,their systems of analysis with their advantages and drawbacks,be these methods so simple to even appear primitive but nonetheless of proven effectiveness,or very modern and instrumental.It constitutes a basic but essential summary of what is necessary to know of these sustainable materials.In doing so,the review highlights some of the main challenges that remain to be addressed to deliver the quality and economics of tannin supply necessary to fulfill the industrial production requirements for some materials-based uses.

基于PLS-SEM和NCA的大学生网约车满意度研究

为探索大学生利用网约车出行行为的内在机理,在网约车领域提出结合基于充分性逻辑的偏最小二乘法结构方程模型(PLS-SEM)和基于必要性逻辑的必要条件分析(NCA)两种方法,引入外部环境、运营服务、感知安全、负面体验和安保措施,构建了大学生利用网约车的乘客满意度模型。应用PLS-SEM对1 102份有效数据进行检验分析,识别模型中的充分性因素;利用PLS-SEM得出的潜变量得分作为应用NCA的起点,得出乘客满意度的必要性因素。研究结果表明,从充分性角度,运营服务、感知安全、负面体验和安保措施的总效应分别为0.422、0.184、-0.160、0.066,对乘客满意度有不同的显著性影响。从必要性角度,运营服务和感知安全也是必要性因素。要想获得中等水平(50%)的乘客满意度,需要运营服务至少达到27.2%,而要想获得最高水平(90%~100%)的乘客满意度,则不仅需要运营服务达到57.3%,还需要感知安全达到39.7%。研究结果突破了以往单一利用结构方程模型研究网约车出行行为机理,可以确定优先提升网约车服务质量的方向,丰富和拓展对青年群体(尤其是大学生)使用网约车出行行为的理解,为交通管理部门和网约车平台制定合理的网约车政策与措施提供理论依据。

A comparison study on structure-function relationship of polysaccharides obtained from sea buckthorn berries using different methods:antioxidant and bile acid-binding capacity

In this study,the structural characters,antioxidant activities and bile acid-binding ability of sea buckthorn polysaccharides(HRPs)obtained by the commonly used hot water(HRP-W),pressurized hot water(HRP-H),ultrasonic(HRP-U),acid(HRP-C)and alkali(HRP-A)assisted extraction methods were investigated.The results demonstrated that extraction methods had significant effects on extraction yield,monosaccharide composition,molecular weight,particle size,triple-helical structure,and surface morphology of HRPs except for the major linkage bands.Thermogravimetric analysis showed that HRP-U with filamentous reticular microstructure exhibited better thermal stability.The HRP-A with the lowest molecular weight and highest arabinose content possessed the best antioxidant activities.Moreover,the rheological analysis indicated that HRPs with higher galacturonic acid content and molecular weight showed higher viscosity and stronger crosslinking network(HRP-C,HRP-W and HRP-U),which exhibited stronger bile acid binding capacity.The present findings provide scientific evidence in the preparation technology of sea buckthorn polysaccharides with good antioxidant and bile acid binding capacity which are related to the structure affected by the extraction methods.

Drilling-based measuring method for the c-φ parameter of rock and its field application

The technology of drilling tests makes it possible to obtain the strength parameter of rock accurately in situ. In this paper, a new rock cutting analysis model that considers the influence of the rock crushing zone(RCZ) is built. The formula for an ultimate cutting force is established based on the limit equilibrium principle. The relationship between digital drilling parameters(DDP) and the c-φ parameter(DDP-cφ formula, where c refers to the cohesion and φ refers to the internal friction angle) is derived, and the response of drilling parameters and cutting ratio to the strength parameters is analyzed. The drillingbased measuring method for the c-φ parameter of rock is constructed. The laboratory verification test is then completed, and the difference in results between the drilling test and the compression test is less than 6%. On this basis, in-situ rock drilling tests in a traffic tunnel and a coal mine roadway are carried out, and the strength parameters of the surrounding rock are effectively tested. The average difference ratio of the results is less than 11%, which verifies the effectiveness of the proposed method for obtaining the strength parameters based on digital drilling. This study provides methodological support for field testing of rock strength parameters.

Efficient slope reliability and sensitivity analysis using quantile-based first-order second-moment method

This paper introduces a novel approach for parameter sensitivity evaluation and efficient slope reliability analysis based on quantile-based first-order second-moment method(QFOSM).The core principles of the QFOSM are elucidated geometrically from the perspective of expanding ellipsoids.Based on this geometric interpretation,the QFOSM is further extended to estimate sensitivity indices and assess the significance of various uncertain parameters involved in the slope system.The proposed method has the advantage of computational simplicity,akin to the conventional first-order second-moment method(FOSM),while providing estimation accuracy close to that of the first-order reliability method(FORM).Its performance is demonstrated with a numerical example and three slope examples.The results show that the proposed method can efficiently estimate the slope reliability and simultaneously evaluate the sensitivity of the uncertain parameters.The proposed method does not involve complex optimization or iteration required by the FORM.It can provide a valuable complement to the existing approximate reliability analysis methods,offering rapid sensitivity evaluation and slope reliability analysis.

基于PLS-SEM的高中生对数字化实验态度与认识的实证研究

为探析高中生对数字化实验的态度与认识,本文依据第三代技术接受模型理论基础,利用SmartPLS 4统计分析软件进行偏最小二乘法结构方程建模。根据研究结果,提出了整合资源,做好数字化实验资源建设;加强培训,提高数字化实验使用频率;拓展创新,进行数字化实验趣味实践。

Material point method simulation of hydro-mechanical behaviour in twophase porous geomaterials: A state-of-the-art review

The material point method(MPM)has been gaining increasing popularity as an appropriate approach to the solution of coupled hydro-mechanical problems involving large deformation.In this paper,we survey the current state-of-the-art in the MPM simulation of hydro-mechanical behaviour in two-phase porous geomaterials.The review covers the recent advances and developments in the MPM and their extensions to capture the coupled hydro-mechanical problems involving large deformations.The focus of this review is aiming at providing a clear picture of what has or has not been developed or implemented for simulating two-phase coupled large deformation problems,which will provide some direct reference for both practitioners and researchers.

Deciphering gastric inflammation-induced tumorigenesis through multi-omics data and AI methods

Gastric cancer(GC), the fifth most common cancer globally, remains the leading cause of cancer deaths worldwide. Inflammation-induced tumorigenesis is the predominant process in GC development;therefore, systematic research in this area should improve understanding of the biological mechanisms that initiate GC development and promote cancer hallmarks. Here, we summarize biological knowledge regarding gastric inflammation-induced tumorigenesis, and characterize the multi-omics data and systems biology methods for investigating GC development. Of note, we highlight pioneering studies in multi-omics data and state-of-the-art network-based algorithms used for dissecting the features of gastric inflammation-induced tumorigenesis, and we propose translational applications in early GC warning biomarkers and precise treatment strategies. This review offers integrative insights for GC research, with the goal of paving the way to novel paradigms for GC precision oncology and prevention.

Volumetric lattice Boltzmann method for pore-scale mass diffusionadvection process in geopolymer porous structures

Porous materials present significant advantages for absorbing radioactive isotopes in nuclear waste streams.To improve absorption efficiency in nuclear waste treatment,a thorough understanding of the diffusion-advection process within porous structures is essential for material design.In this study,we present advancements in the volumetric lattice Boltzmann method(VLBM)for modeling and simulating pore-scale diffusion-advection of radioactive isotopes within geopolymer porous structures.These structures are created using the phase field method(PFM)to precisely control pore architectures.In our VLBM approach,we introduce a concentration field of an isotope seamlessly coupled with the velocity field and solve it by the time evolution of its particle population function.To address the computational intensity inherent in the coupled lattice Boltzmann equations for velocity and concentration fields,we implement graphics processing unit(GPU)parallelization.Validation of the developed model involves examining the flow and diffusion fields in porous structures.Remarkably,good agreement is observed for both the velocity field from VLBM and multiphysics object-oriented simulation environment(MOOSE),and the concentration field from VLBM and the finite difference method(FDM).Furthermore,we investigate the effects of background flow,species diffusivity,and porosity on the diffusion-advection behavior by varying the background flow velocity,diffusion coefficient,and pore volume fraction,respectively.Notably,all three parameters exert an influence on the diffusion-advection process.Increased background flow and diffusivity markedly accelerate the process due to increased advection intensity and enhanced diffusion capability,respectively.Conversely,increasing the porosity has a less significant effect,causing a slight slowdown of the diffusion-advection process due to the expanded pore volume.This comprehensive parametric study provides valuable insights into the kinetics of isotope uptake in porous structures,facilitating the development of porous materials for nuclear waste treatment applications.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.

Experimental study on secondary air mixing along the bed height in a circulating fluidized bed with a multitracer-gas method

A multitracer-gas method was proposed to study the secondary air(SA)mixing along the bed height in a circulating fluidized bed(CFB)using carbon monoxide(CO),oxygen(O_(2)),and carbon dioxide(CO_(2))as tracer gases.Experiments were carried out on a cold CFB test rig with a cross-section of 0.42 m×0.73 m and a height of 5.50 m.The effects of superficial velocity,SA ratio,bed inventory,and particle diameter on the SA mixing were investigated.The results indicate that there are some differences in the measurement results obtained using different tracer gases,wherein the deviation between CO and CO_(2) ranges from 42%to 66%and that between O_(2) and CO_(2) ranges from 45%to 71%in the lower part of the fluidized bed.However,these differences became less pronounced as the bed height increased.Besides,the high solid concentration and fine particle diameter in the CFB may weaken the difference.The measurement results of different tracer gases show the same trends under the variation of operating parameters.Increasing superficial velocity and SA ratio and decreasing particle diameter result in better mixing of the SA.The effect of bed inventory on SA mixing is not monotonic.

Sparse Modal Decomposition Method Addressing Underdetermined Vortex-Induced Vibration Reconstruction Problem for Marine Risers

When investigating the vortex-induced vibration(VIV)of marine risers,extrapolating the dynamic response on the entire length based on limited sensor measurements is a crucial step in both laboratory experiments and fatigue monitoring of real risers.The problem is conventionally solved using the modal decomposition method,based on the principle that the response can be approximated by a weighted sum of limited vibration modes.However,the method is not valid when the problem is underdetermined,i.e.,the number of unknown mode weights is more than the number of known measurements.This study proposed a sparse modal decomposition method based on the compressed sensing theory and the Compressive Sampling Matching Pursuit(Co Sa MP)algorithm,exploiting the sparsity of VIV in the modal space.In the validation study based on high-order VIV experiment data,the proposed method successfully reconstructed the response using only seven acceleration measurements when the conventional methods failed.A primary advantage of the proposed method is that it offers a completely data-driven approach for the underdetermined VIV reconstruction problem,which is more favorable than existing model-dependent solutions for many practical applications such as riser structural health monitoring.