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 "capacity of electron based communication over bacterial cables the full csi case"):
  Abstract: Motivated by recent discoveries of microbial communities that transfer electrons across centimeter-length scales, this paper studies the information capacity of bacterial cables via electron transfer, which coexists with molecular communications, under the assumption of full causal channel state information (CSI). The bacterial cable is modeled as an electron queue that transfers electrons from the encoder at the electron donor source, which controls the desired input electron intensity, to the decoder at the electron acceptor sink. Clogging due to local ATP saturation along the cable is modeled. A discrete-time scheme is investigated, enabling the computation of an achievable rate. The regime of asymptotically small time-slot duration is analyzed, and the optimality of binary input distributions is proved, i.e., the encoder transmits at either maximum or minimum intensity, as dictated by the physical constraints of the cable. A dynamic programming formulation of the capacity is proposed, and the optimal binary signaling is determined via policy iteration. It is proved that the optimal signaling has smaller intensity than that given by the myopic policy, which greedily maximizes the instantaneous information rate but neglects its effect on the steady-state cable distribution. In contrast, the optimal scheme balances the tension between achieving high instantaneous information rate, and inducing a favorable steady-state distribution, such that those states characterized by high information rates are visited more frequently, thus revealing the importance of CSI. This work represents a first contribution towards the design of electron signaling schemes in complex microbial structures, e.g., bacterial cables and biofilms, where the tension between maximizing the transfer of information and guaranteeing the well-being of the overall bacterial community arises.

Includes members:
  Member "a stochastic model for electron transfer in bacterial cables":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "information theory of molecular communication directions and challenges")
  Member "diffusion based nanonetworking a new modulation technique and performance analysis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "simulation study and analysis of diffusive molecular communications with an apertured plane")
  Member "an information theoretic characterization of channels that die":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the throughput of channels that wear out")
  Member "capacity of discrete molecular diffusion channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "using spatial partitioning to reduce the bit error rate of diffusion based molecular communications")
  Member "the poisson channel with side information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "superposition coding is almost always optimal for the poisson broadcast channel")

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.IT(Information Theory)