Target layer state estimation in multi-layer complex dynamical networks considering nonlinear node dynamics

In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method.

The Effect of Key Nodes on theMalware Dynamics in the Industrial Control Network

As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security accidents.This paper proposes a model for the industrial control network.It includes a malware containment strategy that integrates intrusion detection,quarantine,and monitoring.Basedonthismodel,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment strategy.In addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction number.Moreover,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is optimized.In otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control systems.The earlier the immunization of key nodes,the better.Once the time exceeds the threshold,immunizing key nodes is almost ineffective.The analysis provides a better way to contain the malware in the industrial control network.

Research on the evolution law of dynamic performance of CR400BF EMU train based on stochastic dynamics simulation

Purpose–This paper aims to obtain the evolution law of dynamic performance of CR400BF electric multiple unit(EMU).Design/methodology/approach–Using the dynamic simulation based on field test,stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers were tested.Stiffness,damping coefficient,friction coefficient,track gauge were taken as random variables,the stochastic dynamics simulation method was constructed and applied to research the evolution law with running mileage of dynamic index of CR400BF EMU.Findings–The results showed that stiffness and damping coefficient subjected to normal distribution,the mean and variance were computed and the evolution law of stiffness and damping coefficient with running mileage was obtained.Originality/value–Firstly,based on the field test we found that stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers subjected to normal distribution,and the evolution law of stiffness and damping coefficient with running mileage was proposed.Secondly stiffness,damping coefficient,friction coefficient,track gauge were taken as random variables,the stochastic dynamics simulation method was constructed and applied to the research to the evolution law with running mileage of dynamic index of CR400BF EMU.

Application of CD34 expression combined with three-phase dynamic contrast-enhanced computed tomography scanning in preoperative staging of gastric cancer

BACKGROUND Accurate preoperative staging of gastric cancer(GC),a common malignant tumor worldwide,is critical for appropriate treatment plans and prognosis.Dynamic three-phase enhanced computed tomography(CT)scanning for preoperative staging of GC has limitations in evaluating tumor angiogenesis.CD34,a marker on vascular endothelial cell surfaces,is promising in evaluating tumor angiogenesis.We explored the value of their combination for preoperative staging of GC to improve the efficacy and prognosis of patients with GC.Medical records of 106 patients with GC treated at the First People's Hospital of Lianyungang between February 2021 and January 2023 were retrospectively studied.All patients underwent three-phase dynamic contrast-enhanced CT scanning before surgery,and CD34 was detected in gastroscopic biopsy specimens.Using surgical and pathological results as the gold standard,the diagnostic results of three-phase dynamic contrast-enhanced CT scanning at different T and N stages were analyzed,and the expression of CD34-marked microvessel density(MVD)at different T and N stages was determined.The specificity and sensitivity of three-phase dynamic contrast-enhanced CT and CD34 in T and N staging were calculated;those of the combined diagnosis of the two were evaluated in parallel.Independent factors affecting lymph node metastasis were analyzed using multiple logistic regression.RESULTS The accuracy of three-phase dynamic contrast-enhanced CT scanning in diagnosing stages T1,T2,T3 and T4 were 68.00%,75.00%,79.41%,and 73.68%,respectively,and for diagnosing stages N0,N1,N2,and N3 were 75.68%,74.07%,85.00%,and 77.27%,respectively.CD34-marked MVD expression increased with increasing T and N stages.Specificity and sensitivity of three-phase dynamic contrast-enhanced CT in T staging were 86.79%and 88.68%;for N staging,89.06%and 92.86%;for CD34 in T staging,64.15%and 88.68%;and for CD34 in N staging,84.38%and 78.57%,respectively.Specificity and sensitivity of joint diagnosis in T staging were 55.68%and 98.72%,and N staging were 75.15%and 98.47%,respectively,with the area under the curve for diagnosis improving accordingly.According to multivariate analysis,a longer tumor diameter,higher pathological T stage,lower differ-entiation degree,and higher expression of CD34-marked MVD were independent risk factors for lymph node metastasis in patients with GC.CONCLUSION With high accuracy in preoperatively determining the invasion depth and lymph node metastasis of GC,CD34 expression and three-phase dynamic contrast-enhanced CT can provide a reliable basis for surgical resection.

Discrimination of Metastatic from Non-metastatic Mesorectal Lymph Nodes in Rectal Cancer Using Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging

Preoperative detection of lymph nodes（LNs） metastasis is always highly challenging for radiologists nowadays. The utility of quantitative dynamic contrast-enhanced magnetic resonance imaging（QDCE-MRI） in identifying LNs metastasis is not well understood. In the present study, 59 patients with histologically proven rectal carcinoma underwent preoperative QDCE-MRI. The short axis diameter ratio, long axis diameter ratio, short-to-long axis diameter ratio and QDEC-MRI parameters（Ktrans, Kep, fPV and Ve） values were compared between the non-metastatic（n=44） and metastatic（n=35） LNs groups based on pathological examination. Compared with the non-metastatic group, the metastatic group exhibited significantly higher short axis diameter（7.558±0.668 mm vs. 5.427±0.285 mm）, Ktrans（0.483±0.198 min-1 vs. 0.218±0.116 min^-1） and Ve（0.399±0.118 vs. 0.203±0.096） values（all P〈0.05）. The short-to-long axis diameter ratio, long axis diameter ratio, Kep and fPV values did not show significant differences between the two groups. In conclusion, our results showed that for LNs larger than 5 mm in rectal cancer, there are distinctive differences in the Ktrans and Ve values between the metastatic and non-metastatic LNs, suggesting that QDCE-MRI may be potentially helpful in identifying LNs status.

A method to simulate multilayer welding process： Node dynamic relaxation method

A new method called node dynamic relaxation is proposed to simulate multilayer welding. A two dimensional plane strain model for multilayer welding is simulated and the results show that mesh distortion can be decreased, and it is also found that the node dynamic relaxation is a kind of method to calculate welding deformation accurately by comparing experiment results with simulation results.

Evolutionary dynamics analysis of complex network with fusion nodes and overlap edges

Multiple complex networks, each with different properties and mutually fused, have the problems that the evolving process is time varying and non-equilibrium, network structures are layered and interlacing, and evolving characteristics are difficult to be measured. On that account, a dynamic evolving model of complex network with fusion nodes and overlap edges（CNFNOEs） is proposed. Firstly, we define some related concepts of CNFNOEs, and analyze the conversion process of fusion relationship and hierarchy relationship. According to the property difference of various nodes and edges, fusion nodes and overlap edges are subsequently split, and then the CNFNOEs is transformed to interlacing layered complex networks（ILCN）. Secondly,the node degree saturation and attraction factors are defined. On that basis, the evolution algorithm and the local world evolution model for ILCN are put forward. Moreover, four typical situations of nodes evolution are discussed, and the degree distribution law during evolution is analyzed by means of the mean field method.Numerical simulation results show that nodes unreached degree saturation follow the exponential distribution with an error of no more than 6%; nodes reached degree saturation follow the distribution of their connection capacities with an error of no more than 3%; network weaving coefficients have a positive correlation with the highest probability of new node and initial number of connected edges. The results have verified the feasibility and effectiveness of the model, which provides a new idea and method for exploring CNFNOE＇s evolving process and law. Also, the model has good application prospects in structure and dynamics research of transportation network, communication network, social contact network,etc.

Impulsive synchronization of two coupled complex networks with time-delayed dynamical nodes

In this paper, we investigate the impulsive synchronization between two coupled complex networks with time- delayed dynamical nodes. Based on the Lyapunov stability, the linear feedback control and the impulsive control theories, the linear feedback and the impulsive controllers are designed separately. By using the generalized Barbalat＇s lemma, the global asymptotic impulsive synchronization of the drive-response complex networks is derived and some corresponding sufficient conditions are also obtained. Numerical examples are presented to verify the effectiveness and the correctness of the synchronization criteria.

Collective Dynamics for Network-Organized Identical Excitable Nodes

We investigate the collective dynamics of network-organized identical excitable nodes. We theoretically analyze the stability of the rest state and propose that there are two different transition paths： the stationary path and the oscillatory path. We find that, although the onset of collective dynamics strongly depend on the network topology, the local dynamics and how local nodes interact with each other decide the transition path and the involved bifurcation.

Research on Dynamic Clustering Routing Considering Node Load for Wireless Sensor Networks

Aiming at the problem that node load is rarely considered in existing clustering routing algorithm for Wireless Sensor Networks (WSNs), a dynamic clustering routing algorithm for WSN is presented in this paper called DCRCL (Dynamic Clustering Routing Considering Load). This algorithm is comprised of three phases including cluster head (CH) selection, cluster setup and inter-cluster routing. First, the CHs are selected based on residual energy and node load. Then the non-CH nodes choose a cluster by comparing the cost function of its neighbor CHs. At last, each CH communicates with base station by using multi-hop communication. The simulation results show that comparing with the existing one, the techniques life cycle and date volume of the network are increased by 30.7 percent and 29.8 percent respectively by using the proposed algorithm DCRCL.

Determination of Metastatic Axillary Lymph Node in Breast Cancer: Differentiation with Dynamic MRI Examination by Signal Intensity-Time Curves

Purpose: We aimed to evaluate the role of dynamic magnetic resonance imaging (MRI) in the detection of axillary lymph node metastasis based on the signal intensity-time curves. Materials and Methods: The data of 120 patients (benign patients, n = 91;malignant patients, n = 29) who underwent dynamic breast MRI were reviewed. The lymph nodes with the strongest criteria for malignancy (morphological-dynamic properties) were included in the analysis. Signal intensity-time curves were plotted by the software. Results: Of 29 patients with breast cancer, axillary lymph nodes were involved in 21 and not involved in the remaining 8. There was no significant difference between benign and malignant cases in terms of the distributions of Type Ia, Type Ib and Type IV curves (p = 0.12), whereas a significant difference was found between benign and malignant cases in terms of the distributions of Type II and III curves (p Conclusion: On dynamic MRI studies, benign and metastatic lymph nodes display different signal intensity-time curves.

Behavior analysis of malicious sensor nodes based on optimal response dynamics

Wireless sensor networks are extremely vulnerable to various security threats.The intrusion detection method based on game theory can effectively balance the detection rate and energy consumption of the system.The accurate analysis of the attack behavior of malicious sensor nodes can help to configure intrusion detection system,reduce unnecessary system consumption and improve detection efficiency.However,the completely rational assumption of the traditional game model will cause the established model to be inconsistent with the actual attack and defense scenario.In order to formulate a reasonable and effective intrusion detection strategy,we introduce evolutionary game theory to establish an attack evolution game model based on optimal response dynamics,and then analyze the attack behavior of malicious sensor nodes.Theoretical analysis and simulation results show that the evolution trend of attacks is closely related to the number of malicious sensors in the network and the initial state of the strategy,and the attacker can set the initial strategy so that all malicious sensor nodes will eventually launch attacks.Our work is of great significance to guide the development of defense strategies for intrusion detection systems.

Adversarial attacks against dynamic graph neural networks via node injection

Dynamic graph neural networks(DGNNs)have demonstrated their extraordinary value in many practical applications.Nevertheless,the vulnerability of DNNs is a serious hidden danger as a small disturbance added to the model can markedly reduce its performance.At the same time,current adversarial attack schemes are implemented on static graphs,and the variability of attack models prevents these schemes from transferring to dynamic graphs.In this paper,we use the diffused attack of node injection to attack the DGNNs,and first propose the node injection attack based on structural fragility against DGNNs,named Structural Fragility-based Dynamic Graph Node Injection Attack(SFIA).SFIA firstly determines the target time based on the period weight.Then,it introduces a structural fragile edge selection strategy to establish the target nodes set and link them with the malicious node using serial inject.Finally,an optimization function is designed to generate adversarial features for malicious nodes.Experiments on datasets from four different fields show that SFIA is significantly superior to many comparative approaches.When the graph is injected with 1%of the original total number of nodes through SFIA,the link prediction Recall and MRR of the target DGNN link decrease by 17.4%and 14.3%respectively,and the accuracy of node classification decreases by 8.7%.

The elastic dynamics analysis of band saw tightening system

In this paper, the node movement analysis of the levers of band saw tightening system is developed. A group of theoretical displacement and distortion equations of levers are presented using the Lagrange’s equation. This could be the basis for the future research in the field of band saw’s tightening system dynamics analysis.

Dynamic Expression of Hyperpolarization-activated Cyclic Nucleotide-gated Cation Channel 4 Involved in Microwave Induced Pacemaker Cell Injuries

To investigate the mechanisms of microwave induced pacemaker cell injuries, Wistar rats and the primary pacemaker cells of newborn Wistar rats were exposed to microwave at average power density of 50 mW/cm2. Slower spontaneous beating rate, intercellular Ca2＋ aggregation and cell membrane perforation were detected immediately after the exposure. Moreover, hyperpolarizationactivated cyclic nucleotide-gated cation channel 4 （HCN4） was down-regulated immediately after the exposure and up-regulated at 12 h after the exposure. In the sinoatrial node （SAN） of the rats,

Dynamic analysis and regulation of the flexible pipe conveying fluid with a hard-magnetic soft segment

The recently developed hard-magnetic soft(HMS)materials can play a significant role in the actuation and control of medical devices,soft robots,flexible electronics,etc.To regulate the mechanical behaviors of the cantilevered pipe conveying fluid,the present work introduces a segment made of the HMS material located somewhere along the pipe length.Based on the absolute node coordinate formulation(ANCF),the governing equations of the pipe conveying fluid with an HMS segment are derived by the generalized Lagrange equation.By solving the derived equations with numerical methods,the static deformation,linear vibration characteristic,and nonlinear dynamic response of the pipe are analyzed.The result of the static deformation of the pipe shows that when the HMS segment is located in the middle of the pipe,the downstream portion of the pipe centerline will keep a straight shape,providing that the pipe is stable with a relatively low flow velocity.Therefore,it is possible to precisely regulate the ejection direction of the fluid flow by changing the magnetic and fluid parameters.It is also found that the intensity and direction of the external magnetic field greatly affect the stability and dynamic response of the pipe with an HMS segment.In most cases,the magnetic actuation increases the critical flow velocity for the flutter instability of the pipe system and suppresses the vibration amplitude of the pipe.

An Explicit-Implicit Mixed Staggered Asynchronous Step Integration Algorithm in Structural Dynamics

Many engineering applications need to analyse the system dynamics on the macro and micro level,which results in a larger computational effort.An explicit-implicit asynchronous step algorithm is introduced to solve the structural dynamics in multi-scale both the space domain and time domain.The discrete FEA model is partitioned into explicit and implicit parts using the nodal partition method.Multiple boundary node method is adopted to handle the interface coupled problem.In coupled region,the implicit Newmark coupled with an explicit predictor corrector Newmark whose predictive wave propagates into the implicit mesh.During the explicit subcycling process,the variables of boundary nodes are solved directly by dynamics equilibrium equation.The dissipation energy is dynamically determined in accordance with the energy balance checking.A cantilever beam and a building two numerical examples are proposed to verify that the method can greatly reduce the computing time while maintaining a high accuracy.

Optimization of Load Balancing Algorithm for Virtual Machine Dynamic Migration under Mobile Cloud Computing

As one of the key technologies of cloud computing,the virtualization technology can virtualize all kinds of resources and integrate them into the unified planning of the cloud computing management platform.The migration of virtual machines is one of the important technologies of virtual machine applications.However,there are still many deficiencies in the implementation of load balancing by virtual machine dynamic migration in cloud computing.Traditional triggering strategy thresholds are mostly fixed.If there is an instantaneous peak,it will cause migration,which will cause a waste of resources.In order to solve this problem,based on improving the dynamic migration framework,this paper proposes node selection optimization algorithm and node load balancing strategy and designs a prediction module,which uses a one-time smooth prediction to avoid the shortcoming of peak load moment.The simulation experiments and conclusions analysis results show that the fusion algorithm has performance advantages obvious.

Progress of magnetic resonance imaging radiomics in preoperative lymph node diagnosis of esophageal cancer

Esophageal cancer,also referred to as esophagus cancer,is a prevalent disease in the cardiothoracic field and is a leading cause of cancer-related mortality in China.Accurately determining the status of lymph nodes is crucial for developing treatment plans,defining the scope of intraoperative lymph node dissection,and ascertaining the prognosis of patients with esophageal cancer.Recent advances in diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging(MRI)have improved the effectiveness of MRI for assessing lymph node involvement,making it a beneficial tool for guiding personalized treatment plans for patients with esophageal cancer in a clinical setting.Radiomics is a recently developed imaging technique that transforms radiological image data from regions of interest into high-dimensional feature data that can be analyzed.The features,such as shape,texture,and waveform,are associated with the cancer phenotype and tumor microenvironment.When these features correlate with the clinical disease outcomes,they form the basis for specific and reliable clinical evidence.This study aimed to review the potential clinical applications of MRIbased radiomics in studying the lymph nodes affected by esophageal cancer.The combination of MRI and radiomics is a powerful tool for diagnosing and treating esophageal cancer,enabling a more personalized and effectual approach.

移动IP技术及Dynamics HUT Mobile IP应用研究

移动IP是一种解决因特网上节点移动性问题的技术,也是目前Internet技术的一个研究热点。文中从移动IP的基本概念和原理入手,对国内外移动IP在Linux操作系统和Windows操作系统上的实现状况做一概述,并对IPv4下的DynamicsHUTMobileIP系统在Linux平台上安装、配置和应用程序的测试作了详细的阐述,为进一步研究移动IP技术的各项技术打下基础。