human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "received signal strength for randomly distributed molecular nanonodes"):
  Abstract: We consider nanonodes randomly distributed in a circular area and characterize the received signal strength when a pair of these nodes employ molecular communication. Two communication methods are investigated, namely free diffusion and diffusion with drift. Since the nodes are randomly distributed, the distance between them can be represented as a random variable, which results in a stochastic process representation of the received signal strength. We derive the probability density function of this process for both molecular communication methods. Specifically for the case of free diffusion we also derive the cumulative distribution function, which can be used to derive transmission success probabilities. The presented work constitutes a first step towards the characterization of the signal to noise ratio in the considered setting for a number of molecular communication methods.

Includes members:
  Member "a comprehensive survey of recent advancements in molecular communication":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "transmitter and receiver architectures for molecular communications a survey on physical design with modulation coding and detection techniques")
  Member "molecular communications channel model and physical layer techniques":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a survey of biological building blocks for synthetic molecular communication systems")
  Member "channel and noise models for nonlinear molecular communication systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "transmitter and receiver architectures for molecular communications a survey on physical design with modulation coding and detection techniques")
  Member "molecular communication in fluid media the additive inverse gaussian noise channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "transmitter and receiver architectures for molecular communications a survey on physical design with modulation coding and detection techniques")
  Member "nanoscale communication with brownian motion":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a novel time based modulation scheme in time asynchronous channels for molecular communications")

Question: Please tell me which class the source paper 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)