human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "queuing models for abstracting interactions in bacterial communities"
  Abstract: Microbial communities play a significant role in bioremediation,plant growth,human and animal digestion,global elemental cycles including the carbon-cycle,and water treatment.They are also posed to be the engines of renewable energy via microbial fuel cells which can reverse the process of electrosynthesis.Microbial communication regulates many virulence mechanisms used by bacteria.Thus,it is of fundamental importance to understand interactions in microbial communities and to develop predictive tools that help control them,in order to aid the design of systems exploiting bacterial capabilities.This position paper explores how abstractions from communications,networking and information theory can play a role in understanding and modeling bacterial interactions.In particular,two forms of interactions in bacterial systems will be examined:electron transfer and quorum sensing.While the diffusion of chemical signals has been heavily studied,electron transfer occurring in living cells and its role in cell-cell interaction is less understood.Recent experimental observations open up new frontiers in the design of microbial systems based on electron transfer,which may coexist with the more well-known interaction strategies based on molecular diffusion.In quorum sensing,the concentration of certain signature chemical compounds emitted by the bacteria is used to estimate the bacterial population size,so as to activate collective behaviors.In this position paper,queuing models for electron transfer are summarized and adapted to provide new models for quorum sensing.These models are stochastic,and thus capture the inherent randomness exhibited by cell colonies in nature.It is shown that queuing models allow the characterization of the state of a single cell as a function of interactions with other cells and the environment,while being amenable to complexity reduction.

Connected through hyperedge HE-1 (induced by source paper "capacity of systems with queue length dependent service quality"):
  with members:
    - "work capacity of freelance markets fundamental limits and decentralized schemes"
    - "on the age of information in status update systems with packet management"
    - "reliable crowdsourcing for multi class labeling using coding theory"
    - "bits through bufferless queues"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.ET(Emerging Technologies)