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: "structurally optimized shells"
  Abstract: Shells, i.e., objects made of a thin layer of material following a surface, are among the most common structures in use. They are highly efficient, in terms of material required to maintain strength, but also prone to deformation and failure. We introduce an efficient method for reinforcing shells, that is, adding material to the shell to increase its resilience to external loads. Our goal is to produce a reinforcement structure of minimal weight. It has been demonstrated that optimal reinforcement structures may be qualitatively different, depending on external loads and surface shape. In some cases, it naturally consists of discrete protruding ribs; in other cases, a smooth shell thickness variation allows to save more material. #R##N#Most previously proposed solutions, starting from classical Michell trusses, are not able to handle a full range of shells (e.g., are restricted to self-supporting structures) or are unable to reproduce this range of behaviors, resulting in suboptimal structures. #R##N#We propose a new method that works for any input surface with any load configurations, taking into account both in-plane (tensile/compression) and out-of-plane (bending) forces. By using a more precise volume model, we are capable of producing optimized structures with the full range of qualitative behaviors. Our method includes new algorithms for determining the layout of reinforcement structure elements, and an efficient algorithm to optimize their shape, minimizing a non-linear non-convex functional at a fraction of the cost and with better optimality compared to standard solvers. #R##N#We demonstrate the optimization results for a variety of shapes, and the improvements it yields in the strength of 3D-printed objects.

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.GR(Graphics)