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: "designing molecular circuits for approximate maximum a posteriori demodulation of concentration modulated signals"
  Abstract: Motivated by the fact that living cells use molecular circuits (i.e., a set of chemical reactions) for information processing, this paper investigates the problem of designing molecular circuits for demodulation. In our earlier work, we use a Markovian approach to derive a demodulator for diffusion-based molecular communication. The demodulation filters take the form of an ordinary differential equation, which computes the log-posteriori probability of a transmission symbol being sent. This paper considers the realization of these demodulation filters using molecular circuits assuming the transmission symbols are rectangular pulses of the same duration but different amplitudes, i.e., concentration modulation. This paper makes a number of contributions. First, we use time-scale separation and renewal theory to analytically derive an approximation of the demodulation filter from our earlier work. Second, we present a method to turn this approximation into a molecular circuit. By using simulations, we show that the output of the derived molecular circuit is approximately equal to the log-posteriori probability calculated by the exact demodulation filter if the log-posteriori probability is positive. Third, we demonstrate that a biochemical circuit in yeast behaves similarly to the derived molecular demodulation filter and is therefore a candidate for implementing the derived filter.

Connected through hyperedge HE-1 (induced by source paper "a survey of biological building blocks for synthetic molecular communication systems"):
  with members:
    - "transmitter and receiver architectures for molecular communications a survey on physical design with modulation coding and detection techniques"
    - "index modulation for molecular communication via diffusion systems"
    - "diffusive molecular communications with reactive molecules channel modeling and signal design"
    - "channel modeling for diffusive molecular communication a tutorial review"
    - "a novel experimental platform for in vessel multi chemical molecular communications"
    - "diffusion based molecular communication principle key technologies and challenges"
    - "symbol synchronization for diffusion based molecular communications"
    - "applications of molecular communications to medicine a survey"

Connected through hyperedge HE-2 (induced by source paper "using spatial partitioning to reduce the bit error rate of diffusion based molecular communications"):
  with members:
    - "generalized solution for the demodulation of reaction shift keying signals in molecular communication networks"
    - "on the design of matched filters for molecule counting receivers"
    - "improving the capacity of molecular communication using enzymatic reaction cycles"
    - "on medium chemical reaction in diffusion based molecular communication a two way relaying example"
    - "convex optimization of distributed cooperative detection in multi receiver molecular communication"
    - "a comprehensive survey of recent advancements in molecular communication"
    - "a markovian approach to the optimal demodulation of diffusion based molecular communication networks"
    - "improving receiver performance of diffusive molecular communication with enzymes"

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.IT(Information Theory)