Linking Structural Equation Modeling with Bayesian Network and Its Application to Coastal Phytoplankton Dynamics in the Bohai Bay

Bayesian networks （BN） have many advantages over other methods in ecological modeling, and have become an increasingly popular modeling tool. However, BN are flawed in regard to building models based on inadequate existing knowledge. To overcome this limitation, we propose a new method that links BN with structural equation modeling （SEM）. In this method, SEM is used to improve the model structure for BN. This method was used to simulate coastal phytoplankton dynamics in the Bohai Bay. We demonstrate that this hybrid approach minimizes the need for expert elicitation, generates more reasonable structures for BN models, and increases the BN model＇s accuracy and reliability. These results suggest that the inclusion of SEM for testing and verifying the theoretical structure during the initial construction stage improves the effectiveness of BN models, especially for complex eco-environment systems. The results also demonstrate that in the Bohai Bay, while phytoplankton biomass has the greatest influence on phytoplankton dynamics, the impact of nutrients on phytoplankton dynamics is larger than the influence of the physical environment in summer. Furthermore, although the Redfield ratio indicates that phosphorus should be the primary nutrient limiting factor, our results show that silicate plays the most important role in regulating phytoplankton dynamics in the Bohai Bay.

A Re-Parametrization-Based Bayesian Differential Analysis Algorithm for Gene Regulatory Networks Modeled with Structural Equation Models

Under different conditions,gene regulatory networks(GRNs)of the same gene set could be similar but different.The differential analysis of GRNs under different conditions is important for understanding condition-specific gene regulatory relationships.In a naive approach,existing GRN inference algorithms can be used to separately estimate two GRNs under different conditions and identify the differences between them.However,in this way,the similarities between the pairwise GRNs are not taken into account.Several joint differential analysis algorithms have been proposed recently,which were proved to outperform the naive approach apparently.In this paper,we model the GRNs under different conditions with structural equation models(SEMs)to integrate gene expression data and genetic perturbations,and re-parameterize the pairwise SEMs to form an integrated model that incorporates the differential structure.Then,a Bayesian inference method is used to make joint differential analysis by solving the integrated model.We evaluated the performance of the proposed re-parametrization-based Bayesian differential analysis(ReBDA)algorithm by running simulations on synthetic data with different settings.The performance of the ReBDA algorithm was demonstrated better than another state-of-the-art joint differential analysis algorithm for SEMs ReDNet obviously.In the end,the ReBDA algorithm was applied to make differential analysis on a real human lung gene data set to illustrate its applicability and practicability.

Nonaffine Network Structural Model for Molten Low-Density Polyethylene and High-Density Polyethylene in Oscillatory Shear

We propose molten polymer's entanglement network deformation to be nonaffine and use transient network structural theory with the revised Liu's kinetics rate equation and the revised upper convected Maxwell constitutive equation to establish a nonaffine network structural constitutive model for studying the rheological behavior of molten Low Density Polyethylene (LDPE) and High Density Polyethylene (HDPE) in oscillatory shear. As a result, when the strain amplitude or frequency increases, the shear stress amplitude increases. At the same time, the accuracy of the nonaffine network model is higher than that of affine network model. It is clear that there is a small amount of nonaffine network deformation for LDPE melts which have long chain branches, and there is a larger amount of nonaffine network deformation in oscillatory shear for HDPE melts which has no long chain branches. So we had better consider the network deformation nonaffine when we establish the constitutive equations of polymer melts in oscillatory shear.

常规公交风险的SEM与Bayesian Network组合评估方法研究

常规公交系统具有载客量大、班次多、线路固定等特点,存在多种安全风险隐患。为综合评估常规公交风险,对国内外554条事故数据分析整理,构建了常规公交风险指标体系。建立了常规公交风险评估的结构方程模型,得到常规公交风险因素对事故的单向拓扑结构。在结构学习的基础上,利用信息熵理论研究风险因素对预测结果可信度的影响权重,从而进行变量筛选。以失火事故为例利用贝叶斯网络模型进行了城市常规公交风险评估参数学习。研究结果表明,失火事故的主要风险因素为油气泄漏、车内外温度均较高等。在风险因素组合作用下失火事故发生概率范围为0.002 1至0.842 9。所建模型预测精度高,验证了方法的科学性和准确性,可用于进行定量化的常规公交风险评估。

Influential nodes identification in complex networks based on global and local information

Identifying influential nodes in complex networks is essential for network robust and stability,such as viral marketing and information control.Various methods have been proposed to define the influence of nodes.In this paper,we comprehensively consider the global position and local structure to identify influential nodes.The number of iterations in the process of k-shell decomposition is taken into consideration,and the improved k-shell decomposition is then put forward.The improved k-shell decomposition and degree of target node are taken as the benchmark centrality,in addition,as is well known,the effect between node pairs is inversely proportional to the shortest path length between two nodes,and then we also consider the effect of neighbors on target node.To evaluate the performance of the proposed method,susceptible-infected(SI)model is adopted to simulate the spreading process in four real networks,and the experimental results show that the proposed method has obvious advantages over classical centrality measures in identifying influential nodes.

Antecedents of Social Network Trust in SNS Usage: The Moderating Role of Offline Familiarity

With the rapid development of social networks, there is a focus on marketing strategies and business models that are based on social media. In the academic world, scholars believe that online trust is a key factor contributing to online purchasing behavior. This article explored several factors in social media trust and verified the moderating role of offline familiarity by using relevant research on online trust in conjunction with a structure equation model. The results show that independent variables such as reputation, SNS interaction, information quality, reciprocity, satisfaction and shared values have a positive influence on trust, whereas perceived similarity does not, and information quality is the most important factor. In addition, offline familiarity significantly moderates the relations between information quality, reciprocity, reputation, shared values and social media trust. This information is important to assist companies in developing an effective social network marketing strategy.

The Study of SINA micro-blog Opinion Leaders Effect on Network Public Opinion Transmission

Opinion leaders play a critical role in network public opinion transmission, their perspectives can shape public opinion and influence policy formulation and implementation. The paper is based on SINA micro-blog, by structural equation model, as Fudan Poisoning Event for example, On the basis of in-depth analysis of opinion leaders effect on network public opinion transmission characteristics, Explore the opinion leaders on the influence of network public opinion transmission mechanism, in order to better play a role of opinion leader＇s guidance of public opinion.

基于综合贡献率的舰船装备体系寿命评估

为了更科学地预测装备寿命,提升装备的作战效益,从装备对体系的“综合贡献率”视角出发,探究了舰船装备“体系寿命”的评估方法。首先,基于作战环理论和非线性结构方程模型,引入二次交互项,构建舰船装备体系作战能力的指标体系,建立了体系作战效能的评估模型;然后,运用阈值法建立了舰船装备体系的复杂网络模型,基于拓扑特征统计值,构建了舰船装备体系网络结构特征的指标体系,将层次分析法与熵权法相结合来计算指标权重;最后,提出了舰船装备体系综合贡献率、体系寿命的定义和数学模型,并以航母编队体系对抗为算例,通过实验仿真数据,验证了模型和方法的可行性和有效性。

基于KAP理论的大学生网络安全教育研究

为改善大学生网络安全教育现状,提高大学生网络安全教育水平,结合知识-态度-行为(KAP)理论,构建大学生安全教育KAP模型;通过问卷发放和筛选,获取659份有效问卷;采用结构方程模型(SEM)检验网络安全教育对网络安全认知、网络安全态度、网络安全行为的影响,以及可能存在的中介作用影响路径。结果表明:网络安全教育显著影响网络安全认知、网络安全态度、网络安全行为,其中,网络安全认知、网络安全态度起到独立中介及链式中介作用;法律道德教育、知识教育、实践活动、榜样引领均能直接影响网络安全行为,其中,法律道德教育对网络安全行为的影响最强,知识教育次之,实践活动和榜样引领最弱。在具体作用路径方面,法律道德教育主要通过直接效应来影响网络安全行为,知识教育、实践活动、榜样引领主要通过安全认知间接影响网络安全行为。

基于SEM和神经网络的移动社交电商用户隐私信息披露意愿研究

在移动社交电商情境中,用户的交互方式发生改变,个人隐私信息安全问题凸显,上述变化将会对用户的隐私信息披露意愿产生重要影响。为了探究移动社交电商用户隐私信息披露意愿的影响因素,本文基于S-O-R理论建立结构方程模型,旨在探究影响用户隐私信息披露意愿的影响因素及其作用机理。结果表明隐私政策有效性、隐私设置有效性、信息交互、情感交互等因素均正向显著影响用户隐私信息披露意愿。在此基础上,基于平台特征和用户感知收益构建了GA-BP神经网络预测模型,并针对不同预测结果提出具体应对措施。最终,文章从隐私信息安全保障和平台个性化服务等方面提出促进移动社交电商平台可持续发展的建议。

究竟是什么影响了乡村教师对城乡一体化网络研修的满意度?

在教育数字化转型背景下,城乡一体化网络研修成为促进乡村教师专业发展的重要途径,然而在此研修过程中出现了乡村教师消极抵触、情绪低落等满意度不高的现象,直接影响了研修效果。对此,文章基于顾客满意度指数模型和教学系统要素理论,构建了乡村教师对城乡一体化网络研修满意度的影响因素模型,并通过描述性分析、结构方程模型分析和中介效应检验,探讨了乡村教师满意度影响因素及其作用路径。文章发现:教龄、学历对乡村教师满意度有显著影响,而性别无显著影响;“目标-资源-活动-环境-支持保障”可作为乡村教师满意度的关键质量指标;感知质量对乡村教师满意度的影响最大,感知价值次之,教师期望再次之;感知质量、感知价值在教师期望和满意度之间存在中介效应,而“感知质量-感知价值”存在链式中介效应。基于此,文章提出提升乡村教师满意度的建议,以期为促进乡村教育高质量发展和推动教育公平提供理论与实践参考。

基于移动互联网络下学习效果及最优模式分析——以南京农业大学信息管理学院为例

近年来,随着线上教学的不断发展,高校课程呈现多元化趋势,计算机可以起到很好的分析效果。以南京农业大学信息管理学院管理与工程相关专业学生为例,建立能够反映学生的学习成效和教学情况的观测变量,使用结构方程模型(SEM)建立线上学习路径,并通过GA-BP神经网络算法、MATLAB软件对相关数据进行拟合分析,得出线上学习最优路径,提出移动互联网络下大学生最高效学习模式及方案。

基于SEM-MIP状态估计的配电网拓扑辨识方法

配电网拓扑辨识是配电系统操作的关键问题和重要前提。由于缺乏足够的量测设备和配电系统拓扑的频繁变化,导致实际的配电网拓扑辨识问题十分具有挑战性。为此提出了基于同步量测数据状态估计的实时拓扑辨识方法。该方法可以利用少量相量测量单元的测量数据准确估计配电网拓扑结构。首先,在配电网中引入结构方程模型(structural equation model,SEM),用于捕捉拓扑与支路电流的关系。然后,针对拓扑辨识问题提出了混合整数规划(mixed integer programming,MIP)方法,通过复数方程的虚实部解耦,利用泰勒展开与等效松弛等手段对复数方程和约束条件进行线性化。此外,将配电网运行方式约束以节点为单位进行了重新规划。最后,所提基于结构方程模型的混合整数规划方法(SEM-MIP)可以使用现有的商业求解器求解,并通过一个实际12节点配电系统和IEEE 33节点测试系统验证了所提方法的有效性。

政民在线互动对突发公共卫生事件中网民积极情绪的影响研究——基于共情的中介作用分析

情绪治理对政府部门风险沟通实践和政策制定具有一定的参考意义。基于风险沟通理论和共情传播理论,聚焦突发公共卫生事件背景下的网络积极情绪,以风险认知为调节变量构建政民在线互动对网络积极情绪的影响因素评估模型,通过发放问卷收集数据并运用结构方程模型对研究假设进行验证。结果表明政民在线互动正向影响网络积极情绪的形成;共情在政民在线互动和积极情绪之间起中介作用;风险认知在政民在线互动对网络积极情绪影响路径中起调节作用。

Analysis of Commuting Modal Shift in Consideration of Social Interaction of Consciousness for Environment

It is the matter for achievement of the low carbon transport system that the excessive use of private vehicles can be controlled appropriately.Not only improvement of service level of modes except private vehicle,but also consciousness for environmental problem of individual trip maker is important for eco-commuting promotion.On the other hand,consciousness for environment would be changed by influence of other person.Accordingly,it is aimed in the study that the structure of decision-making process for modal shift to the eco-commuting mode in the local city is described considering environmental consciousness and social interaction.For the purpose,the consciousness for the environment problem and the travel behavior of the commuter at the suburban area in the local city are investigated by the questionnaire survey.The covariance structure about the eco-consciousness is analyzed with the database of the questionnaire survey by structural equation modeling.As the result,it can be confirmed with the structural equation model that the individual environmental consciousness is strongly related with the intention of self-sacrifice and is influenced with the local interaction of the individual connections.On the other hand,the intention of modal shift for the commuting mode is analyzed with the database of the questionnaire survey.It can be found out that the environmental consciousness is not statistically significant for commuting mode choice with the present poor level of service of public transport.However,the intention of self-sacrifice for the prevention of the global warming is statistically confirmed as the factor of modal shift with the operation of eco-commuting bus service with the RP/SP integrated estimation method.As the result,the multi-agent simulation system with social interaction model for eco consciousness is developed to measure the effect of the eco-commuting promotion.For the purpose,the carbon dioxide emission is estimated based on traffic demand and road network condition in the traffic environment model.On the other hand,the relation between agents is defined based on the small world network.The proposed multi-agent simulation is applied to measure the effect of the eco-commuting promotion such as improvement of level of service on the public transport or education of eco-consciousness.The effect of the promotion plan can be observed with the proposed multi-agent system.Finally,it can be concluded that the proposed multi-agent simulation with social interaction for eco-consciousness is useful for planning of eco-commuting promotion.

社会网络对企业国际创业绩效的影响:基于元分析与结构方程模型的研究

社会网络是企业在国际创业进程中克服资源瓶颈、拓展资源边界、丰富资源属性的重要支撑。基于社会网络、资源基础和动态能力理论,从国际创业相关领域的国内外主流学术期刊中选取与社会网络、企业国际创业绩效、动态能力、知识获取等有关的75个独立样本作为研究对象,采用元分析与结构方程模型相结合的方法,探索社会网络对企业国际创业绩效的影响。研究发现:社会网络对提高企业国际创业绩效具有正向影响作用;动态能力在社会网络和企业国际创业绩效两者关系中具有部分中介作用;知识获取在社会网络和企业国际创业绩效两者关系中具有部分中介作用;从国家经济发展水平来看,经济发展水平相对低的情境下社会网络对企业国际创业绩效的促进作用更加显著。

协同创新网络视角下装备制造企业创新绩效影响研究

随着技术复杂性的日益提升,装备制造业产业链不断优化升级,仅依靠企业单打独斗难以实现创新,必须将企业置于协同创新网络中,与协作企业、大学和科研院所、政府、金融机构等多主体一起协同发展。因此,以协同创新网络为视角,探究装备制造企业创新绩效的影响因素。将知识管理作为中介,探究协同创新、知识管理以及创新绩效之间的关系,参考相关文献,构建三者之间的假设关系。运用SPSS26.0及AMOS23.0软件进行信效度分析,运用结构方程模型验证关系假设。结果表明,协同创新网络规模、协同创新网络关系强度、网络开放性、知识管理均对创新绩效有显著正向影响,同时知识管理也可作为中介效应,协同创新通过知识管理对创新绩效产生正向影响。

基于耦合模型的特种设备安全风险预警研究

为提高特种设备安全监管水平,结合结构方程模型(SEM)、网络层次分析法(ANP)和云模型(CM),构建SEM-ANP-CM特种设备安全风险预警分析耦合模型,根据加权隶属度值将预警等级分为无警情、四级预警、三级预警、二级预警和一级预警5个等级。将耦合模型应用到华北地区特种设备安全风险预警分析中,结果显示:北京市、内蒙古自治区、天津市、河北省的加权隶属度值处于[1.5,2.5),属于四级预警状态,山西省的安全状态最差,加权隶属度值处于[2.5,3.5),属于三级预警状态。