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: "single memristor logic gates from not to a full adder"
  Abstract: Memristors have been suggested as a novel route to neuromorphic computing based on the similarity between them and neurons (specifically synapses and ion pumps). The d.c. action of the memristor is a current spike which imparts a short-term memory to the device. Here it is demonstrated that this short-term memory works exactly like habituation (e.g. in \emph{Aplysia}). We elucidate the physical rules, based on energy conservation, governing the interaction of these current spikes: summation, `bounce-back', directionality and `diminishing returns'. Using these rules, we introduce 4 different logical systems to implement sequential logic in the memristor and demonstrate how sequential logic works by instantiating a NOT gate, an AND gate, an XOR gate and a Full Adder with a single memristor. The Full Adder makes use of the memristor's short-term memory to add together three binary values and outputs the sum, the carry digit and even the order they were input in. A memristor full adder also outputs the arithmetical sum of bits, allowing for a logically (but not physically) reversible system. Essentially, we can replace an input/output port with an extra time-step, allowing a single memristor to do a hither-to unexpectedly large amount of computation. This makes up for the memristor's slow operation speed and may relate to how neurons do a similarly-large computation with such slow operations speeds. We propose that using spiking logic, either in gates or as neuron-analogues, with plastic rewritable connections between them, would allow the building of a neuromorphic computer.

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)