0000000001148061

AUTHOR

Anurag Singh

showing 10 related works from this author

Choosing Optimal Seed Nodes in Competitive Contagion.

2019

International audience; In recent years there has been a growing interest in simulating competitive markets to find out the efficient ways to advertise a product or spread an ideology. Along this line, we consider a binary competitive contagion process where two infections, A and B, interact with each other and diffuse simultaneously in a network. We investigate which is the best centrality measure to find out the seed nodes a company should adopt in the presence of rivals so that it can maximize its influence. These nodes can be used as the initial spreaders or advertisers by firms when two firms compete with each other. Each node is assigned a price tag to become an initial advertiser whi…

Big Datagame theoryComputer scienceProcess (engineering)01 natural sciencescompetitive contagionMicroeconomics010104 statistics & probabilityArtificial IntelligenceNode (computer science)Computer Science (miscellaneous)seed nodes0101 mathematicsOriginal ResearchSmall numbercentrality measures010102 general mathematicsStochastic game[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]complex networksComplex networkProduct (business)CentralityGame theorycompetitive marketingInformation SystemsFrontiers in big data
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Integrating Environmental Temperature Conditions into the SIR Model for Vector-Borne Diseases

2020

International audience; Nowadays, Complex networks are used to model and analyze various problems of real-life e.g. information diffusion in social networks, epidemic spreading in human population etc. Various epidemic spreading models are proposed for analyzing and understanding the spreading of infectious diseases in human contact networks. In classical epidemiological models, a susceptible person becomes infected after getting in contact with an infected person among the human population only. However, in vector-borne diseases, a human can be infected also by a living organism called a vector. The vector population that also help in spreading diseases is very sensitive to environmental f…

Computer sciencePopulationEpidemic dynamicsEpidemic SpreadingComplex NetworkContact networkMachine learningcomputer.software_genre01 natural sciences010305 fluids & plasmasEnvironmental temperature0103 physical sciences[INFO]Computer Science [cs]010306 general physicseducationeducation.field_of_studybusiness.industryTemperatureComplex network3. Good healthHomogeneousDy- namics on NetworkVector (epidemiology)Artificial intelligenceSIR modelEpidemic modelbusinesscomputer
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Centrality measures for networks with community structure

2016

Understanding the network structure, and finding out the influential nodes is a challenging issue in the large networks. Identifying the most influential nodes in the network can be useful in many applications like immunization of nodes in case of epidemic spreading, during intentional attacks on complex networks. A lot of research is done to devise centrality measures which could efficiently identify the most influential nodes in the network. There are two major approaches to the problem: On one hand, deterministic strategies that exploit knowledge about the overall network topology in order to find the influential nodes, while on the other end, random strategies are completely agnostic ab…

FOS: Computer and information sciencesStatistics and ProbabilityPhysics - Physics and SocietyExploitComplex networksFOS: Physical sciencesNetwork sciencePhysics and Society (physics.soc-ph)Network theoryMachine learningcomputer.software_genreNetwork topologyImmunization strategies01 natural sciences010305 fluids & plasmas0103 physical sciences010306 general physicsMathematicsSocial and Information Networks (cs.SI)Structure (mathematical logic)[PHYS.PHYS]Physics [physics]/Physics [physics]business.industryCommunity structureComputer Science - Social and Information NetworksComplex networkEpidemic dynamicsCondensed Matter Physics[ PHYS.PHYS ] Physics [physics]/Physics [physics]Community structureArtificial intelligenceData miningbusinessCentralitycomputer
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An Efficient Immunization Strategy Using Overlapping Nodes and Its Neighborhoods

2018

International audience; When an epidemic occurs, it is often impossible to vaccinate the entire population due to limited amount of resources. Therefore, it is of prime interest to identify the set of influential spreaders to immunize, in order to minimize both the cost of vaccine resource and the disease spreading. While various strategies based on the network topology have been introduced, few works consider the influence of the community structure in the epidemic spreading process. Nowadays, it is clear that many real-world networks exhibit an overlapping community structure, in which nodes are allowed to belong to more than one community. Previous work shows that the numbers of communit…

Connected componentSocial networkbusiness.industryComputer scienceCommunity structureOverlapping CommunitySLPANetwork topology01 natural sciencesPrime (order theory)010305 fluids & plasmasResource (project management)Betweenness centrality0103 physical sciencesNode (computer science)Largest Connected ComponentSocial NetworkImmunization[INFO]Computer Science [cs]010306 general physicsbusinessComputer network
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Effect of Topological Structure and Coupling Strength in Weighted Multiplex Networks

2018

Algebraic connectivity (second smallest eigenvalue of the supra-Laplacian matrix of the underlying multilayer network) and inter-layer coupling strength play an important role in the diffusion processes on the multiplex networks. In this work, we study the effect of inter-layer coupling strength, topological structure on algebraic connectivity in weighted multiplex networks. The results show a remarkable transition in the value of algebraic connectivity from classical cases where the inter-layer coupling strength is homogeneous. We investigate various topological structures in multiplex networks using configuration model, the Barabasi-Albert model (BA) and empirical data-set of multiplex ne…

PhysicsMatrix (mathematics)Work (thermodynamics)Algebraic connectivityStructure (category theory)MultiplexTopologyEigenvalues and eigenvectorsHeterogeneous networkClustering coefficient
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Community-based Immunization Strategies for Epidemic Control

2014

Understanding the epidemic dynamics, and finding out efficient techniques to control it, is a challenging issue. A lot of research has been done on targeted immunization strategies, exploiting various global network topological properties. However, in practice, information about the global structure of the contact network may not be available. Therefore, immunization strategies that can deal with a limited knowledge of the network structure are required. In this paper, we propose targeted immunization strategies that require information only at the community level. Results of our investigations on the SIR epidemiological model, using a realistic synthetic benchmark with controlled community…

Social and Information Networks (cs.SI)FOS: Computer and information sciencesPhysics - Physics and SocietyComputer scienceControl (management)Community structureFOS: Physical sciencesComputer Science - Social and Information NetworksPhysics and Society (physics.soc-ph)Immunization (finance)Targeted immunization strategiesRisk analysis (engineering)Global networkBenchmark (computing)CentralityEpidemic control
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Immunization Strategies Based on the Overlapping Nodes in Networks with Community Structure

2016

International audience; Understanding how the network topology affects the spread of an epidemic is a main concern in order to develop efficient immunization strategies. While there is a great deal of work dealing with the macroscopic topological properties of the networks, few studies have been devoted to the influence of the community structure. Furthermore, while in many real-world networks communities may overlap, in these studies non-overlapping community structures are considered. In order to gain insight about the influence of the overlapping nodes in the epidemic process we conduct an empirical evaluation of basic deterministic immunization strategies based on the overlapping nodes.…

FOS: Computer and information sciencesTheoretical computer science[ INFO ] Computer Science [cs]Computer scienceProcess (engineering)Epidemic02 engineering and technologyNetwork topology01 natural sciencesComplex NetworksDiffusion020204 information systems0103 physical sciencesNode (computer science)[INFO.INFO-SY]Computer Science [cs]/Systems and Control [cs.SY]0202 electrical engineering electronic engineering information engineeringOverlapping community[INFO]Computer Science [cs]010306 general physicsSocial and Information Networks (cs.SI)Connected componentWelfare economicsCommunity structureComputer Science - Social and Information NetworksAttackImmunization (finance)Complex networkDynamicsMembership number[ INFO.INFO-SY ] Computer Science [cs]/Systems and Control [cs.SY]ImmunizationEpidemic model
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Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition) 1

2021

Contains fulltext : 232759.pdf (Publisher’s version ) (Closed access) In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to…

0301 basic medicineProgrammed cell deathSettore BIO/06AutophagosomeAutolysosome[SDV]Life Sciences [q-bio]lnfectious Diseases and Global Health Radboud Institute for Molecular Life Sciences [Radboudumc 4]Autophagy-Related ProteinsReviewComputational biology[SDV.BC]Life Sciences [q-bio]/Cellular BiologyBiologySettore MED/0403 medical and health sciencesstressChaperone-mediated autophagyddc:570AutophagyLC3AnimalsHumanscancerSettore BIO/10Autophagosome; cancer; flux; LC3; lysosome; macroautophagy; neurodegeneration; phagophore; stress; vacuoleSet (psychology)Molecular Biologyvacuole.phagophore030102 biochemistry & molecular biologyvacuolebusiness.industryInterpretation (philosophy)AutophagyAutophagosomesneurodegenerationCell BiologyfluxMulticellular organismmacroautophagy030104 developmental biologyKnowledge baselysosomeAutophagosome; LC3; cancer; flux; lysosome; macroautophagy; neurodegeneration; phagophore; stress; vacuoleBiological AssayLysosomesbusinessBiomarkers[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
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Autophagy

2021

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide…

macroautophagy;autophagyAutophagosome[SDV]Life Sciences [q-bio]canceLC3 macroautophagyautophagosomeneurodegeneration;[SDV.BC]Life Sciences [q-bio]/Cellular BiologyAutophagy AutophagosomeNOstress vacuolestressautophagic processesstrerfluxLC3cancerguidelinesAutophagosome; cancer; flux; LC3; lysosome; macroautophagy; neurodegeneration; phagophore; stress; vacuoleSettore BIO/06 - Anatomia Comparata E Citologia[SDV.BC] Life Sciences [q-bio]/Cellular BiologyComputingMilieux_MISCELLANEOUSMedaka oryzias latipesphagophorevacuoleQHneurodegenerationAutophagosome cancer flux LC3 lysosome macroautophagy neurodegeneration phagophore stress vacuoleautophagy; autophagic processes; guidelines; autophagosome; cancer; flux; LC3; lysosome; macroautophagy; neurodegeneration; phagophore; stress; vacuolefluxmacroautophagystress.lysosomeAutophagosome; LC3; cancer; flux; lysosome; macroautophagy; neurodegeneration; phagophore; stress; vacuoleSettore BIO/17 - ISTOLOGIARC
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Optimal Local Routing Strategies for Community Structured Time Varying Communication Networks

2017

International audience; In time varying data communication networks (TVCN), traffic congestion, system utility maximization and network performance enhancement are the prominent issues. All these issues can be resolved either by optimizing the network structure or by selecting efficient routing approaches. In this paper, we focus on the design of a time varying network model and propose an algorithm to find efficient user route in this network. Centrality plays a very important role in finding congestion free routes. Indeed, the more a node is central, the more it can be congested by the flow coming from or going to its neighborhood. For that reason, classically, routes are chosen such that…

Mathematical optimization[INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI]Computer scienceNode (networking)Distributed computing[ INFO.INFO-NI ] Computer Science [cs]/Networking and Internet Architecture [cs.NI]Community structure01 natural sciencesTelecommunications network010305 fluids & plasmasCommunity structure[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]Data communication networks modelTraffic congestionBetweenness centrality0103 physical sciencesNetwork performanceSystem utilityRouting (electronic design automation)010306 general physicsCentralityCloseness and betweenness centrality
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