Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectiv...Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.展开更多
Metabolomics covers a wide range of applications in life sciences,biomedicine,and phytology.Data acquisition(to achieve high coverage and efficiency)and analysis(to pursue good classification)are two key segments invo...Metabolomics covers a wide range of applications in life sciences,biomedicine,and phytology.Data acquisition(to achieve high coverage and efficiency)and analysis(to pursue good classification)are two key segments involved in metabolomics workflows.Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups.However,insufficient feature extraction,inappropriate feature selection,overfitting,or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused.Using two ginseng varieties,namely Panax japonicus(PJ)and Panax japonicus var.major(PJvm),containing the similar ginsenosides,we integrated pseudo-targeted metabolomics and deep neural network(DNN)modeling to achieve accurate species differentiation.A pseudo-targeted metabolomics approach was optimized through data acquisition mode,ion pairs generation,comparison between multiple reaction monitoring(MRM)and scheduled MRM(sMRM),and chromatographic elution gradient.In total,1980 ion pairs were monitored within 23 min,allowing for the most comprehensive ginseng metabolome analysis.The established DNN model demonstrated excellent classification performance(in terms of accuracy,precision,recall,F1 score,area under the curve,and receiver operating characteristic(ROC))using the entire metabolome data and feature-selection dataset,exhibiting superior advantages over random forest(RF),support vector machine(SVM),extreme gradient boosting(XGBoost),and multilayer perceptron(MLP).Moreover,DNNs were advantageous for automated feature learning,nonlinear modeling,adaptability,and generalization.This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples.This established approach holds promise for plant metabolomics and is not limited to ginseng.展开更多
Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhance...Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhanced networkmanagement capabilities than those of traditional networks.However,because SDN is designed to ensure high-level service availability,it faces additional challenges.One of themost critical challenges is ensuring efficient detection and recovery from link failures in the data plane.Such failures can significantly impact network performance and lead to service outages,making resiliency a key concern for the effective adoption of SDN.Since the recovery process is intrinsically dependent on timely failure detection,this research surveys and analyzes the current literature on both failure detection and recovery approaches in SDN.The survey provides a critical comparison of existing failure detection techniques,highlighting their advantages and disadvantages.Additionally,it examines the current failure recovery methods,categorized as either restoration-based or protection-based,and offers a comprehensive comparison of their strengths and limitations.Lastly,future research challenges and directions are discussed to address the shortcomings of existing failure recovery methods.展开更多
Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important a...Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.展开更多
Background:Insomnia is a prevalent clinical condition and Shangxia Liangji formula(SXLJF)is a well-established method of treatment.Nevertheless,the specific mechanism of action of SXLJF remains unclear.Methods:The mou...Background:Insomnia is a prevalent clinical condition and Shangxia Liangji formula(SXLJF)is a well-established method of treatment.Nevertheless,the specific mechanism of action of SXLJF remains unclear.Methods:The mouse model of insomnia was established by intraperitoneal injection of para-chlorophenylalanine.Forty-two mice were randomly divided into a negative control group,model group,SXLJF group(18.72 g/kg/day),and positive control group(diazepam,2 mg/kg)and treated with the corresponding drugs for 7 consecutive days.The open field test and pentobarbital-induced sleeping test were conducted.LC-MS-based untargeted metabolomics and network pharmacology were applied to explore the potential targets of SXLJF for treating insomnia.Finally,key targets were validated using RT-qPCR.Results:Behavioral tests demonstrated that SXLJF reduced the total distance,average velocity,central distance,and sleep latency,and prolonged sleep duration.Metabolomics and network pharmacology revealed potential targets,signaling pathways,metabolic pathways,and metabolites associated with the anti-insomnia effects of SXLJF.Specifically,tyrosine hydroxylase(TH)and tyrosine metabolism emerged as crucial metabolic pathways and targets,respectively.RT-qPCR results supported the role of TH in the mechanism of SXLJF in treating insomnia.Conclusion:In conclusion,TH and tyrosine metabolism may represent significant targets and pathways for SXLJF in treating insomnia.展开更多
Multi-agent systems often require good interoperability in the process of completing their assigned tasks.This paper first models the static structure and dynamic behavior of multiagent systems based on layered weight...Multi-agent systems often require good interoperability in the process of completing their assigned tasks.This paper first models the static structure and dynamic behavior of multiagent systems based on layered weighted scale-free community network and susceptible-infected-recovered(SIR)model.To solve the problem of difficulty in describing the changes in the structure and collaboration mode of the system under external factors,a two-dimensional Monte Carlo method and an improved dynamic Bayesian network are used to simulate the impact of external environmental factors on multi-agent systems.A collaborative information flow path optimization algorithm for agents under environmental factors is designed based on the Dijkstra algorithm.A method for evaluating system interoperability is designed based on simulation experiments,providing reference for the construction planning and optimization of organizational application of the system.Finally,the feasibility of the method is verified through case studies.展开更多
Friendship paradox states that individuals are likely to have fewer friends than their friends do,on average.Despite of its wide existence and appealing applications in real social networks,the mathematical understand...Friendship paradox states that individuals are likely to have fewer friends than their friends do,on average.Despite of its wide existence and appealing applications in real social networks,the mathematical understanding of friendship paradox is very limited.Only few works provide theoretical evidence of single-step and multi-step friendship paradoxes,given that the neighbors of interest are onehop and multi-hop away from the target node.However,they consider non-evolving networks,as opposed to the topology of real social networks that are constantly growing over time.We are thus motivated to present a first look into friendship paradox in evolving networks,where newly added nodes preferentially attach themselves to those with higher degrees.Our analytical verification of both single-step and multistep friendship paradoxes in evolving networks,along with comparison to the non-evolving counterparts,discloses that“friendship paradox is even more paradoxical in evolving networks”,primarily from three aspects:1)we demonstrate a strengthened effect of single-step friendship paradox in evolving networks,with a larger probability(more than 0.8)of a random node’s neighbors having higher average degree than the random node itself;2)we unravel higher effectiveness of multi-step friendship paradox in seeking for influential nodes in evolving networks,as the rate of reaching the max degree node can be improved by a factor of at least Θ(t^(2/3))with t being the network size;3)we empirically verify our findings through both synthetic and real datasets,which suggest high agreements of results and consolidate the reasonability of evolving model for real social networks.展开更多
Hyperuricemia(HUA)refers to a condition where fasting serum uric acid levels exceed 420μmol/L in men and 350μmol/L in women,affecting 17.4%of China’s general population,showing increasing prevalence among younger i...Hyperuricemia(HUA)refers to a condition where fasting serum uric acid levels exceed 420μmol/L in men and 350μmol/L in women,affecting 17.4%of China’s general population,showing increasing prevalence among younger individuals.Luteolin,a common flavonoid compound,exhibits multiple biological effects,including inhibition of tumor proliferation and inflammatory responses.It also suppresses the activity of urate transporter 1(URAT1),promoting uric acid excretion.This study is the first to integrate network toxicology and network pharmacology approaches to systematically analyze the multi-target mechanisms of adenine-induced HUA and luteolin-treated HUA,with molecular docking validation of interaction targets.We constructed compound-pathway-intersection gene networks and a dual-group PPI network to analyze the mechanisms of adenine-induced HUA and luteolin-treated HUA.The dual-group PPI network identified 7 shared targets,namely XDH,PYGL,IL10,PPARG,TNF,VEGFA,and MAOA,involving core intersecting pathways such as purine-xanthine metabolism and insulin resistance.Luteolin may activate PPARG to regulate inflammation and uric acid excretion modules in the adenine network.GO-KEGG analysis indicates that intersection genes for adenine pathogenesis involve diverse biological processes,cellular components,and molecular functions,with core target KEGG analysis revealing 15 signaling pathways.Luteolin’s therapeutic targets are associated with more entries,and its core target KEGG analysis identified 46 signaling pathways.Molecular docking shows TNF,PPARG,and PYGL bind to both luteolin and adenine with negative binding energies,and luteolin’s binding energies are all below 5 kJ/mol,confirming stable binding.Luteolin’s anti-HUA mechanism is characterized by inhibition of production,promotion of excretion,anti-inflammation and metabolic regulation,but interactions with gut microbiota metabolites require further study.展开更多
Cell-free networks can effectively reduce interference due to diversity gain.Two key technologies,access point(AP)clustering and transceiver design,play key roles in cell-free networks,and they are implemented at diff...Cell-free networks can effectively reduce interference due to diversity gain.Two key technologies,access point(AP)clustering and transceiver design,play key roles in cell-free networks,and they are implemented at different layers of the air interface.To address the issues and obtain global optimal results,this paper proposes an uplink joint AP clustering and receiver optimization algorithm,where a cross-layer optimization model is built based on graph neural networks(GNNs)with low computational complexity.Experimental results show that the proposed algorithm can activate fewer APs for each user with a small performance loss compared with conventional algorithms.展开更多
Zero Trust Network(ZTN)enhances network security through strict authentication and access control.However,in the ZTN,optimizing flow control to improve the quality of service is still facing challenges.Software Define...Zero Trust Network(ZTN)enhances network security through strict authentication and access control.However,in the ZTN,optimizing flow control to improve the quality of service is still facing challenges.Software Defined Network(SDN)provides solutions through centralized control and dynamic resource allocation,but the existing scheduling methods based on Deep Reinforcement Learning(DRL)are insufficient in terms of convergence speed and dynamic optimization capability.To solve these problems,this paper proposes DRL-AMIR,which is an efficient flow scheduling method for software defined ZTN.This method constructs a flow scheduling optimization model that comprehensively considers service delay,bandwidth occupation,and path hops.Additionally,it balances the differentiated requirements of delay-critical K-flows,bandwidth-intensive D-flows,and background B-flows through adaptiveweighting.Theproposed framework employs a customized state space comprising node labels,link bandwidth,delaymetrics,and path length.It incorporates an action space derived fromnode weights and a hybrid reward function that integrates both single-step and multi-step excitation mechanisms.Based on these components,a hierarchical architecture is designed,effectively integrating the data plane,control plane,and knowledge plane.In particular,the adaptive expert mechanism is introduced,which triggers the shortest path algorithm in the training process to accelerate convergence,reduce trial and error costs,and maintain stability.Experiments across diverse real-world network topologies demonstrate that DRL-AMIR achieves a 15–20%reduction in K-flow transmission delays,a 10–15%improvement in link bandwidth utilization compared to SPR,QoSR,and DRSIR,and a 30%faster convergence speed via adaptive expert mechanisms.展开更多
Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network lev...Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.展开更多
Accurate prediction of hydraulic fracture propagation is vital for Enhanced Geothermal System(EGS)design.We study the first hydraulic fracturing job at the GR1 well in the Gonghe Basin using field data,where the overa...Accurate prediction of hydraulic fracture propagation is vital for Enhanced Geothermal System(EGS)design.We study the first hydraulic fracturing job at the GR1 well in the Gonghe Basin using field data,where the overall direction of hydraulic fractures does not show a delineated shape parallel to the maximum principal stress orientation.A field-scale numerical model based on the distinct element method is set up to carry out a fully coupled hydromechanical simulation,with the explicit representation of natural fractures via the discrete fracture network(DFN)approach.The effects of injection parameters and in situ stress on hydraulic fracture patterns are then quantitatively assessed.The study reveals that shear-induced deformation primarily governs the fracturing morphology in the GR1 well,driven by smaller injection rates and viscosities that promote massive activation of natural fractures,ultimately dominating the direction of hydraulic fracturing.Furthermore,the increase of in situ differential stress may promote shear damage of natural fracture surfaces,with the exact influence pattern depending on the combination of specific discontinuity properties and in situ stress state.Finally,we provide recommendations for EGS fracturing based on the influence characteristics of multiple parameters.This study can serve as an effective basis and reference for the design and optimization of EGS in the Gonghe basin and other sites.展开更多
Background:This study investigated the impacts and mechanisms of yunweiling in the management of Functional Constipation(FC)using network pharmacology and experimental research.Methods:Using the Traditional Chinese Me...Background:This study investigated the impacts and mechanisms of yunweiling in the management of Functional Constipation(FC)using network pharmacology and experimental research.Methods:Using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP),Genecard,and Online Mendelian Inheritance in Man(OMIM)databases,a potential gene target for yunweiling in treating FC was found.A pharmacological network was built and viewed in Cytoscape.A protein interac-tion map was created with STRING and Cytoscape.‘clusterProfiler’helped uncover its mechanism.Molecular docking was done with AutoDock Vina.In a constipation mouse model,Western blot was used to assess yunweiling's effectiveness.Results:To investigate yunweiling's therapeutic effects on FC,we employed a loperamide-induced constipation model.Successful model establishment was con-firmed by first black stool time,reduced stool output,and impaired gastrointestinal motility.Yunweiling treatment,especially at high and medium doses,significantly al-leviated constipation symptoms by reducing first black stool time,increasing stool output,and enhancing gastrointestinal motility.HE staining revealed yunweiling's ability to restore colon tissue structure.Yunweiling modulated the expression of key proteins TP53,P-AKT,P-PI3K,RET,and Rai,implicating its involvement in the PI3K-Akt signaling pathway.Comparative analysis showed yunweiling to be more effective than its individual components(shionone,β-sitosterol,and daucosterol)in improving constipation.The combination of yunweiling with TP53 and PI3K-Akt inhibitors fur-ther enhanced its therapeutic effects,suggesting a synergistic mechanism.Conclusions:The integration of network pharmacology and experimental investiga-tions indicated the effectiveness of yunweiling in managing FC,offering essential theoretical support for clinical application.展开更多
A family of neural networks is proposed to solve linear complementarity problems(LCP).The neural networks are constructed from the novel equivalent model of LCP,which is reformulated by utilizing the modulus and smoot...A family of neural networks is proposed to solve linear complementarity problems(LCP).The neural networks are constructed from the novel equivalent model of LCP,which is reformulated by utilizing the modulus and smoothing technologies.Some important properties of the proposed novel equivalent model are summarized.In addition,the stability properties of the proposed steepest descent-based neural networks for LCP are analyzed.In order to illustrate the theoretical results,we provide some numerical simulations and compare the proposed neural networks with existing neural networks based on the NCP-functions.Numerical results indicate that the performance of the proposed neural networks is effective and robust.展开更多
Objective:To explore the mechanism of action of"Weilingxian-Guizhi"two drugs in the treatment of gout.Method:First obtain the 15 chemical components contained in the"Weilingxian-Guizhi"drug,predict...Objective:To explore the mechanism of action of"Weilingxian-Guizhi"two drugs in the treatment of gout.Method:First obtain the 15 chemical components contained in the"Weilingxian-Guizhi"drug,predict its target points through the database,and then construct the gout-related protein-protein interaction network(PPI),and then construct the"Weiling,"the"Xian,Guizhi"drug pair"active ingredient-predicted target"network,the construction of the gout-related"Weilingxian-Guizhi"drug pair"active ingredient-potential target"network,based on the Kyoto Encyclopedia of Genes and Genomes(KEGG)biological pathway enrichment analysis and gene ontology(GO)functional enrichment analysis,to study the mechanism of action of the two drugs"Weilingxian-Guizhi"in the treatment of gout.Results:The goutrelated"Weilingxian-Guizhi"drug pair"active ingredient-potential target"network contains 14 targets.KEGG pathway enrichment analysis yields 32 pathways,and GO functional enrichment analysis yields 517 GO entries.Among them,there are 468 items related to biological processes,21 items related to molecular functions,and 28 items related to cell composition.Conclusion:The results of this study initially verified and predicted the mechanism of the"Weilingxian-Cinnamon Stick"medicine on the treatment of gout,and laid a good foundation for further revealing its mechanism of action.展开更多
Wireless Sensor Networks(WSN)have gained significant attention over recent years due to their extensive applications in various domains such as environmentalmonitoring,healthcare systems,industrial automation,and smar...Wireless Sensor Networks(WSN)have gained significant attention over recent years due to their extensive applications in various domains such as environmentalmonitoring,healthcare systems,industrial automation,and smart cities.However,such networks are inherently vulnerable to different types of attacks because they operate in open environments with limited resources and constrained communication capabilities.Thepaper addresses challenges related to modeling and analysis of wireless sensor networks and their susceptibility to attacks.Its objective is to create versatile modeling tools capable of detecting attacks against network devices and identifying anomalies caused either by legitimate user errors or malicious activities.A proposed integrated approach for data collection,preprocessing,and analysis in WSN outlines a series of steps applicable throughout both the design phase and operation stage.This ensures effective detection of attacks and anomalies within WSNs.An introduced attackmodel specifies potential types of unauthorized network layer attacks targeting network nodes,transmitted data,and services offered by the WSN.Furthermore,a graph-based analytical framework was designed to detect attacks by evaluating real-time events from network nodes and determining if an attack is underway.Additionally,a simulation model based on sequences of imperative rules defining behaviors of both regular and compromised nodes is presented.Overall,this technique was experimentally verified using a segment of a WSN embedded in a smart city infrastructure,simulating a wormhole attack.Results demonstrate the viability and practical significance of the technique for enhancing future information security measures.Validation tests confirmed high levels of accuracy and efficiency when applied specifically to detecting wormhole attacks targeting routing protocols in WSNs.Precision and recall rates averaged above the benchmark value of 0.95,thus validating the broad applicability of the proposed models across varied scenarios.展开更多
Objective:To explore the potential mechanisms of a baicalin-geniposide combination against cerebral ischemia using a network pharmacology strategy.Method:We used network pharmacology integrating drug-target-disease in...Objective:To explore the potential mechanisms of a baicalin-geniposide combination against cerebral ischemia using a network pharmacology strategy.Method:We used network pharmacology integrating drug-target-disease interactions to identify key pathways which were validated in a rat middle cerebral artery occlusion model treated with baicalin(55 mg/kg),geniposide(5 mg/kg),or their 11:1 combination.Therapeutic efficacy and mechanistic insights were evaluated using triphenyltetrazolium chloride staining,Evans blue assay,enzyme-linked immunosorbent assay,and Western blot.Results:The results revealed that the nuclear factor-kappa B(NF-κB)signaling pathway is inhibited in combination treatment of cerebral ischemia.Ten targets were identified as key nodes in the protein-protein interaction network:interleukin 6(IL-6),interleukin-1β,interleukin 18,C-C motif ligand 2,C-C motif ligand 4,interleukin 10,interferon-γ-inducible protein 10,C-C motif ligand 3,tumor necrosis factor-α(TNF-α),interleukin-1α.The baicalin-geniposide combination significantly reduced infarct volume,improved neurological deficits,and alleviated brain edema/blood-brain barrier leakage compared with monotherapy.Additionally,it significantly inhibited toll-like receptor 4(TLR4)/NF-κB signaling and downregulated pro-inflammatory cytokines TNF-αand IL-6 levels.Conclusion:The baicalin-geniposide combination alleviated cerebral ischemia-reperfusion injury by synergistically suppressing the TLR4/NF-κB pathway and its downstream inflammatory factors.展开更多
Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and acc...Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and access control,their users do not have the control and the right over their data.Therefore,users cannot easily switch between similar platforms or transfer data from one platform to another.These issues imply,among other things,a threat to privacy since such users depend on the interests of the service provider responsible for administering OSNs.As a strategy for the decentralization of the OSNs and,consequently,as a solution to the privacy problems in these environments,the so-called decentralized online social networks(DOSNs)have emerged.Unlike OSNs,DOSNs are decentralized content management platforms because they do not use centralized service providers.Although DOSNs address some of the privacy issues encountered in OSNs,DOSNs also pose significant challenges to consider,for example,access control to user profile information with high granularity.This work proposes developing an ontological model and a service to support privacy in DOSNs.The model describes the main concepts of privacy access control in DOSNs and their relationships.In addition,the service will consume the model to apply access control according to the policies represented in the model.Our model was evaluated in two phases to verify its compliance with the proposed domain.Finally,we evaluated our service with a performance evaluation,and the results were satisfactory concerning the response time of access control requests.展开更多
Livestock transportation is a key factor that contributes to the spatial spread of brucellosis.To analyze the impact of sheep transportation on brucellosis transmission,we develop a human–sheep coupled brucellosis mo...Livestock transportation is a key factor that contributes to the spatial spread of brucellosis.To analyze the impact of sheep transportation on brucellosis transmission,we develop a human–sheep coupled brucellosis model within a metapopulation network framework.Theoretically,we examine the positively invariant set,the basic reproduction number,the existence,uniqueness,and stability of disease-free equilibrium and the existence of the endemic equilibrium of the model.For practical application,using Heilongjiang province as a case study,we simulate brucellosis transmission across 12 cities based on data using three network types:the BA network,the ER network,and homogeneous mixing network.The simulation results indicate that the network's average degree plays a role in the spread of brucellosis.For BA and ER networks,the basic reproduction number and cumulative incidence of brucellosis stabilize when the network's average degree reaches 4 or 5.In contrast,sheep transport in a homogeneous mixing network accelerates the cross-regional spread of brucellosis,whereas transportation in a BA network helps to control it effectively.Furthermore,the findings suggest that the movement of sheep is not always detrimental to controlling the spread of brucellosis.For cities with smaller sheep populations,such as Shuangyashan and Qitaihe,increasing the transport of sheep outward amplifies the spatial spread of the disease.In contrast,in cities with larger sheep populations,such as Qiqihar,Daqing,and Suihua,moderate sheep outflow can help reduce the spread.In addition,cities with large livestock populations play a dominant role in the overall transmission dynamics,underscoring the need for stricter supervision in these areas.展开更多
We study the influence of conformity on the evolution of cooperative behavior in games under the learning method of sampling on networks.A strategy update rule based on sampling is introduced into the stag hunt game,w...We study the influence of conformity on the evolution of cooperative behavior in games under the learning method of sampling on networks.A strategy update rule based on sampling is introduced into the stag hunt game,where agents draw samples from their neighbors and then update their strategies based on conformity or inference according to the situation in the sample.Based on these assumptions,we present the state transition equations in the dynamic evolution of population cooperation,conduct simulation analysis on lattice networks and scale-free networks,and discuss how this mechanism affects the evolution of cooperation and how cooperation evolves under different levels of conformity in the network.Our simulation results show that blindly imitating the strategies of neighbors does not necessarily lead to rapid consensus in the population.Instead,rational inference through samples can better promote the evolution of the same strategy among all agents in the population.Moreover,the simulation results also show that a smaller sample size cannot reflect the true situation of the neighbors,which has a large randomness,and the size of the benefits obtained in cooperation determines the direction of the entire population towards cooperation or defection.This work incorporates the conforming behavior of agents into the game,uses the method of sampling for strategy updates and enriches the theory of evolutionary games with a more realistic significance.展开更多
基金supported in part by the National Natural Science Foundation of China(62173255,62188101)Shenzhen Key Laboratory of Control Theory and Intelligent Systems(ZDSYS20220330161800001)
文摘Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.
基金supported by the National Key R&D Program of China(Grant No.:2022YFC3501805)the National Natural Science Foundation of China(Grant No.:82374030)+2 种基金the Science and Technology Program of Tianjin in China(Grant No.:23ZYJDSS00030)the Tianjin Outstanding Youth Fund,China(Grant No.:23JCJQJC00030)the China Postdoctoral Science Foundation-Tianjin Joint Support Program(Grant No.:2023T030TJ).
文摘Metabolomics covers a wide range of applications in life sciences,biomedicine,and phytology.Data acquisition(to achieve high coverage and efficiency)and analysis(to pursue good classification)are two key segments involved in metabolomics workflows.Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups.However,insufficient feature extraction,inappropriate feature selection,overfitting,or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused.Using two ginseng varieties,namely Panax japonicus(PJ)and Panax japonicus var.major(PJvm),containing the similar ginsenosides,we integrated pseudo-targeted metabolomics and deep neural network(DNN)modeling to achieve accurate species differentiation.A pseudo-targeted metabolomics approach was optimized through data acquisition mode,ion pairs generation,comparison between multiple reaction monitoring(MRM)and scheduled MRM(sMRM),and chromatographic elution gradient.In total,1980 ion pairs were monitored within 23 min,allowing for the most comprehensive ginseng metabolome analysis.The established DNN model demonstrated excellent classification performance(in terms of accuracy,precision,recall,F1 score,area under the curve,and receiver operating characteristic(ROC))using the entire metabolome data and feature-selection dataset,exhibiting superior advantages over random forest(RF),support vector machine(SVM),extreme gradient boosting(XGBoost),and multilayer perceptron(MLP).Moreover,DNNs were advantageous for automated feature learning,nonlinear modeling,adaptability,and generalization.This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples.This established approach holds promise for plant metabolomics and is not limited to ginseng.
文摘Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhanced networkmanagement capabilities than those of traditional networks.However,because SDN is designed to ensure high-level service availability,it faces additional challenges.One of themost critical challenges is ensuring efficient detection and recovery from link failures in the data plane.Such failures can significantly impact network performance and lead to service outages,making resiliency a key concern for the effective adoption of SDN.Since the recovery process is intrinsically dependent on timely failure detection,this research surveys and analyzes the current literature on both failure detection and recovery approaches in SDN.The survey provides a critical comparison of existing failure detection techniques,highlighting their advantages and disadvantages.Additionally,it examines the current failure recovery methods,categorized as either restoration-based or protection-based,and offers a comprehensive comparison of their strengths and limitations.Lastly,future research challenges and directions are discussed to address the shortcomings of existing failure recovery methods.
基金the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2024-9/1).
文摘Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.
基金Science Foundation of Hunan Province(2021JJ40510)General Guidance Project of Hunan Health Commission(202203074169)+1 种基金Clinical Medical Technology Innovation Guidance Project of Hunan Province(2021SK51901)and Key Guiding Projects of Hunan Health Commission(20201918)for supporting this study.
文摘Background:Insomnia is a prevalent clinical condition and Shangxia Liangji formula(SXLJF)is a well-established method of treatment.Nevertheless,the specific mechanism of action of SXLJF remains unclear.Methods:The mouse model of insomnia was established by intraperitoneal injection of para-chlorophenylalanine.Forty-two mice were randomly divided into a negative control group,model group,SXLJF group(18.72 g/kg/day),and positive control group(diazepam,2 mg/kg)and treated with the corresponding drugs for 7 consecutive days.The open field test and pentobarbital-induced sleeping test were conducted.LC-MS-based untargeted metabolomics and network pharmacology were applied to explore the potential targets of SXLJF for treating insomnia.Finally,key targets were validated using RT-qPCR.Results:Behavioral tests demonstrated that SXLJF reduced the total distance,average velocity,central distance,and sleep latency,and prolonged sleep duration.Metabolomics and network pharmacology revealed potential targets,signaling pathways,metabolic pathways,and metabolites associated with the anti-insomnia effects of SXLJF.Specifically,tyrosine hydroxylase(TH)and tyrosine metabolism emerged as crucial metabolic pathways and targets,respectively.RT-qPCR results supported the role of TH in the mechanism of SXLJF in treating insomnia.Conclusion:In conclusion,TH and tyrosine metabolism may represent significant targets and pathways for SXLJF in treating insomnia.
基金supported by the Key R&D Projects in Jiangsu Province(BE2021729)the Key Primary Research Project of Primary Strengthening Program(KYZYJKKCJC23001).
文摘Multi-agent systems often require good interoperability in the process of completing their assigned tasks.This paper first models the static structure and dynamic behavior of multiagent systems based on layered weighted scale-free community network and susceptible-infected-recovered(SIR)model.To solve the problem of difficulty in describing the changes in the structure and collaboration mode of the system under external factors,a two-dimensional Monte Carlo method and an improved dynamic Bayesian network are used to simulate the impact of external environmental factors on multi-agent systems.A collaborative information flow path optimization algorithm for agents under environmental factors is designed based on the Dijkstra algorithm.A method for evaluating system interoperability is designed based on simulation experiments,providing reference for the construction planning and optimization of organizational application of the system.Finally,the feasibility of the method is verified through case studies.
基金supported by NSF China(No.61960206002,62020106005,42050105,62061146002)Shanghai Pilot Program for Basic Research–Shanghai Jiao Tong University.
文摘Friendship paradox states that individuals are likely to have fewer friends than their friends do,on average.Despite of its wide existence and appealing applications in real social networks,the mathematical understanding of friendship paradox is very limited.Only few works provide theoretical evidence of single-step and multi-step friendship paradoxes,given that the neighbors of interest are onehop and multi-hop away from the target node.However,they consider non-evolving networks,as opposed to the topology of real social networks that are constantly growing over time.We are thus motivated to present a first look into friendship paradox in evolving networks,where newly added nodes preferentially attach themselves to those with higher degrees.Our analytical verification of both single-step and multistep friendship paradoxes in evolving networks,along with comparison to the non-evolving counterparts,discloses that“friendship paradox is even more paradoxical in evolving networks”,primarily from three aspects:1)we demonstrate a strengthened effect of single-step friendship paradox in evolving networks,with a larger probability(more than 0.8)of a random node’s neighbors having higher average degree than the random node itself;2)we unravel higher effectiveness of multi-step friendship paradox in seeking for influential nodes in evolving networks,as the rate of reaching the max degree node can be improved by a factor of at least Θ(t^(2/3))with t being the network size;3)we empirically verify our findings through both synthetic and real datasets,which suggest high agreements of results and consolidate the reasonability of evolving model for real social networks.
基金supported by the National College Student Innovation and Entrepreneurship Project.
文摘Hyperuricemia(HUA)refers to a condition where fasting serum uric acid levels exceed 420μmol/L in men and 350μmol/L in women,affecting 17.4%of China’s general population,showing increasing prevalence among younger individuals.Luteolin,a common flavonoid compound,exhibits multiple biological effects,including inhibition of tumor proliferation and inflammatory responses.It also suppresses the activity of urate transporter 1(URAT1),promoting uric acid excretion.This study is the first to integrate network toxicology and network pharmacology approaches to systematically analyze the multi-target mechanisms of adenine-induced HUA and luteolin-treated HUA,with molecular docking validation of interaction targets.We constructed compound-pathway-intersection gene networks and a dual-group PPI network to analyze the mechanisms of adenine-induced HUA and luteolin-treated HUA.The dual-group PPI network identified 7 shared targets,namely XDH,PYGL,IL10,PPARG,TNF,VEGFA,and MAOA,involving core intersecting pathways such as purine-xanthine metabolism and insulin resistance.Luteolin may activate PPARG to regulate inflammation and uric acid excretion modules in the adenine network.GO-KEGG analysis indicates that intersection genes for adenine pathogenesis involve diverse biological processes,cellular components,and molecular functions,with core target KEGG analysis revealing 15 signaling pathways.Luteolin’s therapeutic targets are associated with more entries,and its core target KEGG analysis identified 46 signaling pathways.Molecular docking shows TNF,PPARG,and PYGL bind to both luteolin and adenine with negative binding energies,and luteolin’s binding energies are all below 5 kJ/mol,confirming stable binding.Luteolin’s anti-HUA mechanism is characterized by inhibition of production,promotion of excretion,anti-inflammation and metabolic regulation,but interactions with gut microbiota metabolites require further study.
基金supported in part by National Natural Science Foundation of China under Grant No.62171474。
文摘Cell-free networks can effectively reduce interference due to diversity gain.Two key technologies,access point(AP)clustering and transceiver design,play key roles in cell-free networks,and they are implemented at different layers of the air interface.To address the issues and obtain global optimal results,this paper proposes an uplink joint AP clustering and receiver optimization algorithm,where a cross-layer optimization model is built based on graph neural networks(GNNs)with low computational complexity.Experimental results show that the proposed algorithm can activate fewer APs for each user with a small performance loss compared with conventional algorithms.
基金supported in part by Scientific Research Fund of Zhejiang Provincial Education Department under Grant Y202351110in part by Huzhou Science and Technology Plan Project under Grant 2024YZ23+1 种基金in part by Research Fund of National Key Laboratory of Advanced Communication Networks under Grant SCX23641X004in part by Postgraduate Research and Innovation Project of Huzhou University under Grant 2024KYCX50.
文摘Zero Trust Network(ZTN)enhances network security through strict authentication and access control.However,in the ZTN,optimizing flow control to improve the quality of service is still facing challenges.Software Defined Network(SDN)provides solutions through centralized control and dynamic resource allocation,but the existing scheduling methods based on Deep Reinforcement Learning(DRL)are insufficient in terms of convergence speed and dynamic optimization capability.To solve these problems,this paper proposes DRL-AMIR,which is an efficient flow scheduling method for software defined ZTN.This method constructs a flow scheduling optimization model that comprehensively considers service delay,bandwidth occupation,and path hops.Additionally,it balances the differentiated requirements of delay-critical K-flows,bandwidth-intensive D-flows,and background B-flows through adaptiveweighting.Theproposed framework employs a customized state space comprising node labels,link bandwidth,delaymetrics,and path length.It incorporates an action space derived fromnode weights and a hybrid reward function that integrates both single-step and multi-step excitation mechanisms.Based on these components,a hierarchical architecture is designed,effectively integrating the data plane,control plane,and knowledge plane.In particular,the adaptive expert mechanism is introduced,which triggers the shortest path algorithm in the training process to accelerate convergence,reduce trial and error costs,and maintain stability.Experiments across diverse real-world network topologies demonstrate that DRL-AMIR achieves a 15–20%reduction in K-flow transmission delays,a 10–15%improvement in link bandwidth utilization compared to SPR,QoSR,and DRSIR,and a 30%faster convergence speed via adaptive expert mechanisms.
基金supported by the National Natural Science Foundation of China,Nos.81871836(to MZ),82172554(to XH),and 81802249(to XH),81902301(to JW)the National Key R&D Program of China,Nos.2018YFC2001600(to JX)and 2018YFC2001604(to JX)+3 种基金Shanghai Rising Star Program,No.19QA1409000(to MZ)Shanghai Municipal Commission of Health and Family Planning,No.2018YQ02(to MZ)Shanghai Youth Top Talent Development PlanShanghai“Rising Stars of Medical Talent”Youth Development Program,No.RY411.19.01.10(to XH)。
文摘Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.
基金support from the National Natural Science Foundation of China(Grant Nos.42320104003,42177175,and 42077247)the Fundamental Research Funds for the Central Universities.
文摘Accurate prediction of hydraulic fracture propagation is vital for Enhanced Geothermal System(EGS)design.We study the first hydraulic fracturing job at the GR1 well in the Gonghe Basin using field data,where the overall direction of hydraulic fractures does not show a delineated shape parallel to the maximum principal stress orientation.A field-scale numerical model based on the distinct element method is set up to carry out a fully coupled hydromechanical simulation,with the explicit representation of natural fractures via the discrete fracture network(DFN)approach.The effects of injection parameters and in situ stress on hydraulic fracture patterns are then quantitatively assessed.The study reveals that shear-induced deformation primarily governs the fracturing morphology in the GR1 well,driven by smaller injection rates and viscosities that promote massive activation of natural fractures,ultimately dominating the direction of hydraulic fracturing.Furthermore,the increase of in situ differential stress may promote shear damage of natural fracture surfaces,with the exact influence pattern depending on the combination of specific discontinuity properties and in situ stress state.Finally,we provide recommendations for EGS fracturing based on the influence characteristics of multiple parameters.This study can serve as an effective basis and reference for the design and optimization of EGS in the Gonghe basin and other sites.
基金funded by the TCM Spleen and Stomach Discipline Leader Project of High-level Talents in Yunnan Province (no grant number)TCM Joint Project of Yunnan Provincial Science and Technology Department (grant number 202101AZ070001-209).
文摘Background:This study investigated the impacts and mechanisms of yunweiling in the management of Functional Constipation(FC)using network pharmacology and experimental research.Methods:Using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP),Genecard,and Online Mendelian Inheritance in Man(OMIM)databases,a potential gene target for yunweiling in treating FC was found.A pharmacological network was built and viewed in Cytoscape.A protein interac-tion map was created with STRING and Cytoscape.‘clusterProfiler’helped uncover its mechanism.Molecular docking was done with AutoDock Vina.In a constipation mouse model,Western blot was used to assess yunweiling's effectiveness.Results:To investigate yunweiling's therapeutic effects on FC,we employed a loperamide-induced constipation model.Successful model establishment was con-firmed by first black stool time,reduced stool output,and impaired gastrointestinal motility.Yunweiling treatment,especially at high and medium doses,significantly al-leviated constipation symptoms by reducing first black stool time,increasing stool output,and enhancing gastrointestinal motility.HE staining revealed yunweiling's ability to restore colon tissue structure.Yunweiling modulated the expression of key proteins TP53,P-AKT,P-PI3K,RET,and Rai,implicating its involvement in the PI3K-Akt signaling pathway.Comparative analysis showed yunweiling to be more effective than its individual components(shionone,β-sitosterol,and daucosterol)in improving constipation.The combination of yunweiling with TP53 and PI3K-Akt inhibitors fur-ther enhanced its therapeutic effects,suggesting a synergistic mechanism.Conclusions:The integration of network pharmacology and experimental investiga-tions indicated the effectiveness of yunweiling in managing FC,offering essential theoretical support for clinical application.
基金Supported by the National Natural Science Foundation of China(12371378,41725017,11901098).
文摘A family of neural networks is proposed to solve linear complementarity problems(LCP).The neural networks are constructed from the novel equivalent model of LCP,which is reformulated by utilizing the modulus and smoothing technologies.Some important properties of the proposed novel equivalent model are summarized.In addition,the stability properties of the proposed steepest descent-based neural networks for LCP are analyzed.In order to illustrate the theoretical results,we provide some numerical simulations and compare the proposed neural networks with existing neural networks based on the NCP-functions.Numerical results indicate that the performance of the proposed neural networks is effective and robust.
文摘Objective:To explore the mechanism of action of"Weilingxian-Guizhi"two drugs in the treatment of gout.Method:First obtain the 15 chemical components contained in the"Weilingxian-Guizhi"drug,predict its target points through the database,and then construct the gout-related protein-protein interaction network(PPI),and then construct the"Weiling,"the"Xian,Guizhi"drug pair"active ingredient-predicted target"network,the construction of the gout-related"Weilingxian-Guizhi"drug pair"active ingredient-potential target"network,based on the Kyoto Encyclopedia of Genes and Genomes(KEGG)biological pathway enrichment analysis and gene ontology(GO)functional enrichment analysis,to study the mechanism of action of the two drugs"Weilingxian-Guizhi"in the treatment of gout.Results:The goutrelated"Weilingxian-Guizhi"drug pair"active ingredient-potential target"network contains 14 targets.KEGG pathway enrichment analysis yields 32 pathways,and GO functional enrichment analysis yields 517 GO entries.Among them,there are 468 items related to biological processes,21 items related to molecular functions,and 28 items related to cell composition.Conclusion:The results of this study initially verified and predicted the mechanism of the"Weilingxian-Cinnamon Stick"medicine on the treatment of gout,and laid a good foundation for further revealing its mechanism of action.
基金the International Scientific Complex“Astana”was funded by the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan(Grant No.AP19680345).
文摘Wireless Sensor Networks(WSN)have gained significant attention over recent years due to their extensive applications in various domains such as environmentalmonitoring,healthcare systems,industrial automation,and smart cities.However,such networks are inherently vulnerable to different types of attacks because they operate in open environments with limited resources and constrained communication capabilities.Thepaper addresses challenges related to modeling and analysis of wireless sensor networks and their susceptibility to attacks.Its objective is to create versatile modeling tools capable of detecting attacks against network devices and identifying anomalies caused either by legitimate user errors or malicious activities.A proposed integrated approach for data collection,preprocessing,and analysis in WSN outlines a series of steps applicable throughout both the design phase and operation stage.This ensures effective detection of attacks and anomalies within WSNs.An introduced attackmodel specifies potential types of unauthorized network layer attacks targeting network nodes,transmitted data,and services offered by the WSN.Furthermore,a graph-based analytical framework was designed to detect attacks by evaluating real-time events from network nodes and determining if an attack is underway.Additionally,a simulation model based on sequences of imperative rules defining behaviors of both regular and compromised nodes is presented.Overall,this technique was experimentally verified using a segment of a WSN embedded in a smart city infrastructure,simulating a wormhole attack.Results demonstrate the viability and practical significance of the technique for enhancing future information security measures.Validation tests confirmed high levels of accuracy and efficiency when applied specifically to detecting wormhole attacks targeting routing protocols in WSNs.Precision and recall rates averaged above the benchmark value of 0.95,thus validating the broad applicability of the proposed models across varied scenarios.
基金supported by grants from the National Natural Science Foundation of China(U21A20400,81973789,82004327).
文摘Objective:To explore the potential mechanisms of a baicalin-geniposide combination against cerebral ischemia using a network pharmacology strategy.Method:We used network pharmacology integrating drug-target-disease interactions to identify key pathways which were validated in a rat middle cerebral artery occlusion model treated with baicalin(55 mg/kg),geniposide(5 mg/kg),or their 11:1 combination.Therapeutic efficacy and mechanistic insights were evaluated using triphenyltetrazolium chloride staining,Evans blue assay,enzyme-linked immunosorbent assay,and Western blot.Results:The results revealed that the nuclear factor-kappa B(NF-κB)signaling pathway is inhibited in combination treatment of cerebral ischemia.Ten targets were identified as key nodes in the protein-protein interaction network:interleukin 6(IL-6),interleukin-1β,interleukin 18,C-C motif ligand 2,C-C motif ligand 4,interleukin 10,interferon-γ-inducible protein 10,C-C motif ligand 3,tumor necrosis factor-α(TNF-α),interleukin-1α.The baicalin-geniposide combination significantly reduced infarct volume,improved neurological deficits,and alleviated brain edema/blood-brain barrier leakage compared with monotherapy.Additionally,it significantly inhibited toll-like receptor 4(TLR4)/NF-κB signaling and downregulated pro-inflammatory cytokines TNF-αand IL-6 levels.Conclusion:The baicalin-geniposide combination alleviated cerebral ischemia-reperfusion injury by synergistically suppressing the TLR4/NF-κB pathway and its downstream inflammatory factors.
基金Fundação de AmparoàPesquisa do Estado da Bahia(FAPESB),Coordenação de Aperfeiçoamento de Pessoal de Nível Superior(CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico(CNPq)organizations for supporting the Graduate Program in Computer Science at the Federal University of Bahia.
文摘Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and access control,their users do not have the control and the right over their data.Therefore,users cannot easily switch between similar platforms or transfer data from one platform to another.These issues imply,among other things,a threat to privacy since such users depend on the interests of the service provider responsible for administering OSNs.As a strategy for the decentralization of the OSNs and,consequently,as a solution to the privacy problems in these environments,the so-called decentralized online social networks(DOSNs)have emerged.Unlike OSNs,DOSNs are decentralized content management platforms because they do not use centralized service providers.Although DOSNs address some of the privacy issues encountered in OSNs,DOSNs also pose significant challenges to consider,for example,access control to user profile information with high granularity.This work proposes developing an ontological model and a service to support privacy in DOSNs.The model describes the main concepts of privacy access control in DOSNs and their relationships.In addition,the service will consume the model to apply access control according to the policies represented in the model.Our model was evaluated in two phases to verify its compliance with the proposed domain.Finally,we evaluated our service with a performance evaluation,and the results were satisfactory concerning the response time of access control requests.
基金Project supported by the National Natural Science Foundation of China(Grant No.12101443,12371493)the Natural Science Foundation of Shanxi Province(Grant Nos.20210302124260 and 202303021221024)。
文摘Livestock transportation is a key factor that contributes to the spatial spread of brucellosis.To analyze the impact of sheep transportation on brucellosis transmission,we develop a human–sheep coupled brucellosis model within a metapopulation network framework.Theoretically,we examine the positively invariant set,the basic reproduction number,the existence,uniqueness,and stability of disease-free equilibrium and the existence of the endemic equilibrium of the model.For practical application,using Heilongjiang province as a case study,we simulate brucellosis transmission across 12 cities based on data using three network types:the BA network,the ER network,and homogeneous mixing network.The simulation results indicate that the network's average degree plays a role in the spread of brucellosis.For BA and ER networks,the basic reproduction number and cumulative incidence of brucellosis stabilize when the network's average degree reaches 4 or 5.In contrast,sheep transport in a homogeneous mixing network accelerates the cross-regional spread of brucellosis,whereas transportation in a BA network helps to control it effectively.Furthermore,the findings suggest that the movement of sheep is not always detrimental to controlling the spread of brucellosis.For cities with smaller sheep populations,such as Shuangyashan and Qitaihe,increasing the transport of sheep outward amplifies the spatial spread of the disease.In contrast,in cities with larger sheep populations,such as Qiqihar,Daqing,and Suihua,moderate sheep outflow can help reduce the spread.In addition,cities with large livestock populations play a dominant role in the overall transmission dynamics,underscoring the need for stricter supervision in these areas.
基金Project supported by the National Natural Science Foundation of China(Grant No.72031009)the National Social Science Foundation of China(Grant No.20&ZD058)。
文摘We study the influence of conformity on the evolution of cooperative behavior in games under the learning method of sampling on networks.A strategy update rule based on sampling is introduced into the stag hunt game,where agents draw samples from their neighbors and then update their strategies based on conformity or inference according to the situation in the sample.Based on these assumptions,we present the state transition equations in the dynamic evolution of population cooperation,conduct simulation analysis on lattice networks and scale-free networks,and discuss how this mechanism affects the evolution of cooperation and how cooperation evolves under different levels of conformity in the network.Our simulation results show that blindly imitating the strategies of neighbors does not necessarily lead to rapid consensus in the population.Instead,rational inference through samples can better promote the evolution of the same strategy among all agents in the population.Moreover,the simulation results also show that a smaller sample size cannot reflect the true situation of the neighbors,which has a large randomness,and the size of the benefits obtained in cooperation determines the direction of the entire population towards cooperation or defection.This work incorporates the conforming behavior of agents into the game,uses the method of sampling for strategy updates and enriches the theory of evolutionary games with a more realistic significance.
