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: "effective inter symbol interference mitigation with a limited amount of enzymes in molecular communications"
  Abstract: In molecular communication via diffusion (MCvD), the inter-symbol interference (ISI) is a well known severe problem that deteriorates both data rates and link reliability. ISI mainly occurs due to the slow and highly random propagation of the messenger molecules, which causes the emitted molecules from the previous symbols to interfere with molecules from the current symbol. An effective way to mitigate the ISI is using enzymes to degrade undesired molecules. Prior work on ISI mitigation by enzymes has assumed an infinite amount of enzymes randomly distributed around the molecular channel. Taking a different approach, this paper assumes an MCvD channel with a limited amount of enzymes. The main question this paper addresses is how to deploy these enzymes in an effective structure so that ISI mitigation is maximized. To find an effective MCvD channel environment, this study considers optimization of the shape of the transmitter node, the deployment location and structure, the size of the enzyme deployed area, and the half-lives of the enzymes. It also analyzes the dependence of the optimum size of the enzyme area on the distance and half-life.

Connected through hyperedge HE-1 (induced by source paper "effective enzyme deployment for degradation of interference molecules in molecular communication"):
  with members:
    - "molecular mimo from theory to prototype"
    - "a comprehensive survey of recent advancements in molecular communication"
    - "improving receiver performance of diffusive molecular communication with enzymes"
    - "effect of receptor density and size on signal reception in molecular communication via diffusion with an absorbing receiver"
    - "effect of degradation in molecular communication impairment or enhancement"
    - "symbol interval optimization for molecular communication with drift"
    - "channel and noise models for nonlinear molecular communication systems"
    - "novel modulation techniques using isomers as messenger molecules for nano communication networks via diffusion"

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)