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: "from quantity to quality massive molecular dynamics simulation of nanostructures under plastic deformation in desktop and service grid distributed computing infrastructure"
  Abstract: The distributed computing infrastructure (DCI) on the basis of BOINC andEDGeS-bridge technologies for high-performance distributed computing is usedfor porting the sequential molecular dynamics (MD) application to its paral-lel version for DCI with Desktop Grids (DGs) and Service Grids (SGs). Theactual metrics of the working DG-SG DCI were measured, and the normal dis-tribution of host performances, and signs of log-normal distributions of othercharacteristics (CPUs, RAM, and HDD per host) were found. The practicalfeasibility and high eﬃciency of the MD simulations on the basis of DG-SG DCIwere demonstrated during the experiment with the massive MD simulations forthe large quantity of aluminum nanocrystals ( ∼ 102–103). Statistical analysis(Kolmogorov-Smirnov test, moment analysis, and bootstrapping analysis) ofthe defect density distribution over the ensemble of nanocrystals had shownthat change of plastic deformation mode is followed by the qualitative changeof defect density distribution type over ensemble of nanocrystals. Some limita-tions (ﬂuctuating performance, unpredictable availability of resources, etc.) ofthe typical DG-SG DCI were outlined, and some advantages (high eﬃciency,high speedup, and low cost) were demonstrated. Deploying on DG DCI al-lows to get new scientiﬁc quality from the simulated quantity of numerousconﬁgurations by harnessing suﬃcient computational power to undertake MDsimulations in a wider range of physical parameters (conﬁgurations) in a muchshorter timeframe.

Connected through hyperedge HE-1 (induced by source paper "synergy of volunteer measurements and volunteer computing for effective data collecting processing simulating and analyzing on a worldwide scale"):
  with members:
    - "imp science gateway from the portal to the hub of virtual experimental labs in materials science"
    - "complex workflow management and integration of distributed computing resources by science gateway portal for molecular dynamics simulations in materials science"
    - "the computational and storage potential of volunteer computing"
    - "auger xtremweb monte carlo computation on a global computing platform"

Connected through hyperedge HE-2 (induced by source paper "science gateway for distributed multiscale course management in e science and e learning use case for study and investigation of functionalized nanomaterials"):
  with members:
    - "opencourseware observatory does the quality of opencourseware live up to its promise"
    - "imp science gateway from the portal to the hub of virtual experimental labs in materials science"
    - "complex workflow management and integration of distributed computing resources by science gateway portal for molecular dynamics simulations in materials science"

Connected through hyperedge HE-3 (induced by source paper "imp science gateway from the portal to the hub of virtual experimental labs in materials science"):
  with members:
    - "complex workflow management and integration of distributed computing resources by science gateway portal for molecular dynamics simulations in materials science"

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.CE(Computational Engineering, Finance, and Science)