{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T21:47:24Z","timestamp":1775857644435,"version":"3.50.1"},"reference-count":210,"publisher":"Association for Computing Machinery (ACM)","issue":"12","license":[{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62171260, 62272260, U21B2036"],"award-info":[{"award-number":["62171260, 62272260, U21B2036"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100020721","name":"Guoqiang Institute of Tsinghua University","doi-asserted-by":"crossref","award":["2023GQS0002"],"award-info":[{"award-number":["2023GQS0002"]}],"id":[{"id":"10.13039\/100020721","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Young Elite Scientists Sponsorship Program by CIC","award":["2021QNRC001"],"award-info":[{"award-number":["2021QNRC001"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Comput. Surv."],"published-print":{"date-parts":[[2024,12,31]]},"abstract":"<jats:p>Complex system simulation has been playing an irreplaceable role in understanding, predicting, and controlling diverse complex systems. In the past few decades, the multi-scale simulation technique has drawn increasing attention for its remarkable ability to overcome the challenges of complex system simulation with unknown mechanisms and expensive computational costs. In this survey, we will systematically review the literature on multi-scale simulation of complex systems from the perspective of knowledge and data. First, we will present background knowledge about simulating complex systems and the scales in complex systems. Then, we divide the main objectives of multi-scale modeling and simulation into five categories by considering scenarios with clear scale and scenarios with unclear scale, respectively. After summarizing the general methods for multi-scale simulation based on the clues of knowledge and data, we introduce the adopted methods to achieve different objectives. Finally, we introduce the applications of multi-scale simulation in typical matter systems and social systems.<\/jats:p>","DOI":"10.1145\/3654662","type":"journal-article","created":{"date-parts":[[2024,4,3]],"date-time":"2024-04-03T12:09:39Z","timestamp":1712146179000},"page":"1-38","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":29,"title":["Multi-scale Simulation of Complex Systems: A Perspective of Integrating Knowledge and Data"],"prefix":"10.1145","volume":"56","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6382-0861","authenticated-orcid":false,"given":"Huandong","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9626-5676","authenticated-orcid":false,"given":"Huan","family":"Yan","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5846-724X","authenticated-orcid":false,"given":"Can","family":"Rong","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1701-2588","authenticated-orcid":false,"given":"Yuan","family":"Yuan","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9912-9709","authenticated-orcid":false,"given":"Fenyu","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9634-7962","authenticated-orcid":false,"given":"Zhenyu","family":"Han","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8702-234X","authenticated-orcid":false,"given":"Hongjie","family":"Sui","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0419-5514","authenticated-orcid":false,"given":"Depeng","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5617-1659","authenticated-orcid":false,"given":"Yong","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2024,10]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/0009-2509(92)80235-5"},{"issue":"1","key":"e_1_3_1_3_2","first-page":"1","article-title":"Modeling the effect of exposure notification and non-pharmaceutical interventions on COVID-19 transmission in washington state","volume":"4","author":"Abueg Matthew","year":"2021","unstructured":"Matthew Abueg, Robert Hinch, Neo Wu, Luyang Liu, William Probert, Austin Wu, Paul Eastham, Yusef Shafi, Matt Rosencrantz, Michael Dikovsky et\u00a0al. 2021. Modeling the effect of exposure notification and non-pharmaceutical interventions on COVID-19 transmission in washington state. NPJ Dig. Med. 4, 1 (2021), 1\u201310.","journal-title":"NPJ Dig. Med."},{"issue":"11","key":"e_1_3_1_4_2","doi-asserted-by":"crossref","first-page":"1714","DOI":"10.1038\/s41591-020-1092-0","article-title":"Clustering and superspreading potential of SARS-CoV-2 infections in Hong Kong","volume":"26","author":"Adam Dillon C.","year":"2020","unstructured":"Dillon C. Adam, Peng Wu, Jessica Y. Wong, Eric H. Y. Lau, Tim K. Tsang, Simon Cauchemez, Gabriel M. Leung, and Benjamin J. Cowling. 2020. Clustering and superspreading potential of SARS-CoV-2 infections in Hong Kong. Nature Med. 26, 11 (2020), 1714\u20131719.","journal-title":"Nature Med."},{"issue":"10","key":"e_1_3_1_5_2","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1109\/MC.2020.3010549","article-title":"State of data privacy during COVID-19","volume":"53","author":"Ahmad Norita","year":"2020","unstructured":"Norita Ahmad and Preeti Chauhan. 2020. State of data privacy during COVID-19. Computer 53, 10 (2020), 119\u2013122.","journal-title":"Computer"},{"issue":"10","key":"e_1_3_1_6_2","doi-asserted-by":"crossref","first-page":"1901","DOI":"10.1142\/S0218202519500374","article-title":"Vehicular traffic, crowds, and swarms: From kinetic theory and multiscale methods to applications and research perspectives","volume":"29","author":"Albi Giacomo","year":"2019","unstructured":"Giacomo Albi, Nicola Bellomo, Luisa Fermo, S.-Y. Ha, J. Kim, Lorenzo Pareschi, David Poyato, and Juan Soler. 2019. Vehicular traffic, crowds, and swarms: From kinetic theory and multiscale methods to applications and research perspectives. Math. Models Methods Appl. Sci. 29, 10 (2019), 1901\u20132005.","journal-title":"Math. Models Methods Appl. Sci."},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41562-020-0931-9"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.trpro.2017.12.138"},{"issue":"69","key":"e_1_3_1_9_2","doi-asserted-by":"crossref","first-page":"39414","DOI":"10.1039\/C8RA07112H","article-title":"Application of DFT-based machine learning for developing molecular electrode materials in li-ion batteries","volume":"8","author":"Allam Omar","year":"2018","unstructured":"Omar Allam, Byung Woo Cho, Ki Chul Kim, and Seung Soon Jang. 2018. Application of DFT-based machine learning for developing molecular electrode materials in li-ion batteries. RSC Adv. 8, 69 (2018), 39414\u201339420.","journal-title":"RSC Adv."},{"key":"e_1_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.coche.2021.100752"},{"key":"e_1_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.trip.2021.100334"},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0906910106"},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2010.07.002"},{"key":"e_1_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.51.1035"},{"key":"e_1_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1814058116"},{"key":"e_1_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.1038\/nphys2741"},{"issue":"10","key":"e_1_3_1_17_2","doi-asserted-by":"crossref","first-page":"667","DOI":"10.1038\/nphys2727","article-title":"The extreme vulnerability of interdependent spatially embedded networks","volume":"9","author":"Bashan Amir","year":"2013","unstructured":"Amir Bashan, Yehiel Berezin, Sergey V. Buldyrev, and Shlomo Havlin. 2013. The extreme vulnerability of interdependent spatially embedded networks. Nature Phys. 9, 10 (2013), 667\u2013672.","journal-title":"Nature Phys."},{"key":"e_1_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41567-021-01371-4"},{"issue":"2","key":"e_1_3_1_19_2","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1006\/acha.1997.0226","article-title":"A multiresolution strategy for reduction of elliptic PDEs and eigenvalue problems","volume":"5","author":"Beylkin Gregory","year":"1998","unstructured":"Gregory Beylkin and Nicholas Coult. 1998. A multiresolution strategy for reduction of elliptic PDEs and eigenvalue problems. Appl. Comput. Harmon. Anal. 5, 2 (1998), 129\u2013155.","journal-title":"Appl. Comput. Harmon. Anal."},{"key":"e_1_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-021-00327-w"},{"issue":"1","key":"e_1_3_1_21_2","first-page":"1","article-title":"Noise-injected analog Ising machines enable ultrafast statistical sampling and machine learning","volume":"13","author":"B\u00f6hm Fabian","year":"2022","unstructured":"Fabian B\u00f6hm, Diego Alonso-Urquijo, Guy Verschaffelt, and Guy Van der Sande. 2022. Noise-injected analog Ising machines enable ultrafast statistical sampling and machine learning. Nature Commun. 13, 1 (2022), 1\u201313.","journal-title":"Nature Commun."},{"issue":"2","key":"e_1_3_1_22_2","doi-asserted-by":"crossref","first-page":"022204","DOI":"10.1103\/PhysRevE.102.022204","article-title":"Sparse identification of slow timescale dynamics","volume":"102","author":"Bramburger Jason J.","year":"2020","unstructured":"Jason J. Bramburger, Daniel Dylewsky, and J. Nathan Kutz. 2020. Sparse identification of slow timescale dynamics. Phys. Rev. E 102, 2 (2020), 022204.","journal-title":"Phys. Rev. E"},{"issue":"6520","key":"e_1_3_1_23_2","doi-asserted-by":"crossref","first-page":"eaaz3041","DOI":"10.1126\/science.aaz3041","article-title":"Protein storytelling through physics","volume":"370","author":"Brini Emiliano","year":"2020","unstructured":"Emiliano Brini, Carlos Simmerling, and Ken Dill. 2020. Protein storytelling through physics. Science 370, 6520 (2020), eaaz3041.","journal-title":"Science"},{"key":"e_1_3_1_24_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.1245200"},{"key":"e_1_3_1_25_2","doi-asserted-by":"publisher","DOI":"10.1002\/jcc.21287"},{"key":"e_1_3_1_26_2","doi-asserted-by":"crossref","unstructured":"Steven L. Brunton Marko Budi\u0161i\u0107 Eurika Kaiser and J. Nathan Kutz. 2021. Modern koopman theory for dynamical systems. Retrieved from https:\/\/arXiv:2102.12086","DOI":"10.1137\/21M1401243"},{"key":"e_1_3_1_27_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1517384113"},{"key":"e_1_3_1_28_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature08932"},{"key":"e_1_3_1_29_2","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.55.2471"},{"key":"e_1_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.commatsci.2018.07.064"},{"issue":"6","key":"e_1_3_1_31_2","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1080\/01441640802012813","article-title":"Microscopic analysis of cellular automata based traffic flow models and an improved model","volume":"28","author":"Chakroborty Partha","year":"2008","unstructured":"Partha Chakroborty and Akhilesh Kumar Maurya. 2008. Microscopic analysis of cellular automata based traffic flow models and an improved model. Transport Rev. 28, 6 (2008), 717\u2013734.","journal-title":"Transport Rev."},{"key":"e_1_3_1_32_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1906995116"},{"key":"e_1_3_1_33_2","doi-asserted-by":"publisher","DOI":"10.1137\/18M1188227"},{"key":"e_1_3_1_34_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2923-3"},{"key":"e_1_3_1_35_2","doi-asserted-by":"publisher","DOI":"10.1038\/s43588-022-00281-6"},{"key":"e_1_3_1_36_2","first-page":"1","article-title":"Strategic COVID-19 vaccine distribution can simultaneously elevate social utility and equity","author":"Chen Lin","year":"2022","unstructured":"Lin Chen, Fengli Xu, Zhenyu Han, Kun Tang, Pan Hui, James Evans, and Yong Li. 2022. Strategic COVID-19 vaccine distribution can simultaneously elevate social utility and equity. Nature Hum. Behav. (2022), 1\u201312.","journal-title":"Nature Hum. Behav."},{"key":"e_1_3_1_37_2","article-title":"Neural ordinary differential equations","volume":"31","author":"Chen Ricky T. Q.","year":"2018","unstructured":"Ricky T. Q. Chen, Yulia Rubanova, Jesse Bettencourt, and David K. Duvenaud. 2018. Neural ordinary differential equations. Adv. Neural Info. Process. Syst. 31 (2018).","journal-title":"Adv. Neural Info. Process. Syst."},{"issue":"1","key":"e_1_3_1_38_2","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.jtrangeo.2009.09.006","article-title":"Multi-scale and multi-modal GIS-T data model","volume":"19","author":"Chen Shaopei","year":"2011","unstructured":"Shaopei Chen, Jianjun Tan, Christophe Claramunt, and Cyril Ray. 2011. Multi-scale and multi-modal GIS-T data model. J. Transport Geogr. 19, 1 (2011), 147\u2013161.","journal-title":"J. Transport Geogr."},{"key":"e_1_3_1_39_2","doi-asserted-by":"publisher","DOI":"10.1002\/nme.1630"},{"key":"e_1_3_1_40_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.aba9757"},{"issue":"4","key":"e_1_3_1_41_2","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/S0370-1573(99)00117-9","article-title":"Statistical physics of vehicular traffic and some related systems","volume":"329","author":"Chowdhury Debashish","year":"2000","unstructured":"Debashish Chowdhury, Ludger Santen, and Andreas Schadschneider. 2000. Statistical physics of vehicular traffic and some related systems. Phys. Reports 329, 4-6 (2000), 199\u2013329.","journal-title":"Phys. Reports"},{"issue":"35","key":"e_1_3_1_42_2","doi-asserted-by":"crossref","first-page":"12647","DOI":"10.1073\/pnas.0805363105","article-title":"Chemical reaction dynamics","volume":"105","author":"Crim F Fleming","year":"2008","unstructured":"F Fleming Crim. 2008. Chemical reaction dynamics. Proc. Natl. Acad. Sci. U.S.A. 105, 35 (2008), 12647\u201312648.","journal-title":"Proc. Natl. Acad. Sci. U.S.A."},{"key":"e_1_3_1_43_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.camwa.2018.12.024"},{"issue":"1","key":"e_1_3_1_44_2","doi-asserted-by":"crossref","first-page":"8133","DOI":"10.1038\/ncomms9133","article-title":"Automated adaptive inference of phenomenological dynamical models","volume":"6","author":"Daniels Bryan C.","year":"2015","unstructured":"Bryan C. Daniels and Ilya Nemenman. 2015. Automated adaptive inference of phenomenological dynamical models. Nature Commun. 6, 1 (2015), 8133.","journal-title":"Nature Commun."},{"key":"e_1_3_1_45_2","first-page":"1","volume-title":"Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis","author":"Natale Francesco Di","year":"2019","unstructured":"Francesco Di Natale, Harsh Bhatia, Timothy S. Carpenter, Chris Neale, Sara Kokkila-Schumacher, Tomas Oppelstrup, Liam Stanton, Xiaohua Zhang, Shiv Sundram, Thomas R. W. Scogland et\u00a0al. 2019. A massively parallel infrastructure for adaptive multiscale simulations: Modeling RAS initiation pathway for cancer. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. 1\u201316."},{"key":"e_1_3_1_46_2","doi-asserted-by":"crossref","unstructured":"Domenico Di Sante Matija Medvidovi\u0107 Alessandro Toschi Giorgio Sangiovanni Cesare Franchini Anirvan M. Sengupta and Andrew J. Millis. 2022. Deep learning the functional renormalization group. Retrieved from https:\/\/arXiv:2202.13268","DOI":"10.1103\/PhysRevLett.129.136402"},{"key":"e_1_3_1_47_2","doi-asserted-by":"publisher","DOI":"10.1137\/110842545"},{"issue":"10","key":"e_1_3_1_48_2","doi-asserted-by":"crossref","first-page":"104105","DOI":"10.1103\/PhysRevB.95.104105","article-title":"High accuracy and transferability of a neural network potential through charge equilibration for calcium fluoride","volume":"95","author":"Faraji Somayeh","year":"2017","unstructured":"Somayeh Faraji, S. Alireza Ghasemi, Samare Rostami, Robabe Rasoulkhani, Bastian Schaefer, Stefan Goedecker, and Maximilian Amsler. 2017. High accuracy and transferability of a neural network potential through charge equilibration for calcium fluoride. Phys. Rev. B 95, 10 (2017), 104105.","journal-title":"Phys. Rev. B"},{"issue":"6","key":"e_1_3_1_49_2","doi-asserted-by":"crossref","first-page":"774","DOI":"10.1038\/s41563-020-00913-0","article-title":"Mesoscopic and multiscale modelling in materials","volume":"20","author":"Fish Jacob","year":"2021","unstructured":"Jacob Fish, Gregory J. Wagner, and Sinan Keten. 2021. Mesoscopic and multiscale modelling in materials. Nature Mater. 20, 6 (2021), 774\u2013786.","journal-title":"Nature Mater."},{"issue":"9","key":"e_1_3_1_50_2","doi-asserted-by":"crossref","first-page":"862","DOI":"10.1002\/nme.3201","article-title":"A nonintrusive stochastic multiscale solver","volume":"88","author":"Fish Jacob","year":"2011","unstructured":"Jacob Fish and Wei Wu. 2011. A nonintrusive stochastic multiscale solver. Int. J. Numer. Methods Eng. 88, 9 (2011), 862\u2013879.","journal-title":"Int. J. Numer. Methods Eng."},{"key":"e_1_3_1_51_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2405-7"},{"key":"e_1_3_1_52_2","unstructured":"Meire Fortunato Tobias Pfaff Peter Wirnsberger Alexander Pritzel and Peter Battaglia. 2022. Multiscale meshgraphnets. Retrieved from https:\/\/arXiv:2210.00612"},{"key":"e_1_3_1_53_2","doi-asserted-by":"publisher","DOI":"10.1063\/5.0020721"},{"key":"e_1_3_1_54_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature16948"},{"issue":"2","key":"e_1_3_1_55_2","doi-asserted-by":"crossref","first-page":"026105","DOI":"10.1103\/PhysRevE.76.026105","article-title":"Cellular-automaton model with velocity adaptation in the framework of kerner\u2019s three-phase traffic theory","volume":"76","author":"Gao Kun","year":"2007","unstructured":"Kun Gao, Rui Jiang, Shou-Xin Hu, Bing-Hong Wang, and Qing-Song Wu. 2007. Cellular-automaton model with velocity adaptation in the framework of kerner\u2019s three-phase traffic theory. Phys. Rev. E 76, 2 (2007), 026105.","journal-title":"Phys. Rev. E"},{"issue":"4","key":"e_1_3_1_56_2","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1140\/epjb\/e2007-00014-x","article-title":"Effect of looking backward on traffic flow in a cooperative driving car following model","volume":"54","author":"Ge H. X.","year":"2006","unstructured":"H. X. Ge, H. B. Zhu, and S. Q. Dai. 2006. Effect of looking backward on traffic flow in a cooperative driving car following model. Eur. Phys. J. B Cond. Matter Complex Syst. 54, 4 (2006), 503\u2013507.","journal-title":"Eur. Phys. J. B Cond. Matter Complex Syst."},{"issue":"18","key":"e_1_3_1_57_2","doi-asserted-by":"crossref","first-page":"3993","DOI":"10.1016\/S0009-2509(02)00234-8","article-title":"Physical mapping of fluidization regimes-the EMMS approach","volume":"57","author":"Ge Wei","year":"2002","unstructured":"Wei Ge and Jinghai Li. 2002. Physical mapping of fluidization regimes-the EMMS approach. Chem. Eng. Sci. 57, 18 (2002), 3993\u20134004.","journal-title":"Chem. Eng. Sci."},{"key":"e_1_3_1_58_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2019.112594"},{"key":"e_1_3_1_59_2","doi-asserted-by":"publisher","DOI":"10.1006\/acha.1997.0220"},{"key":"e_1_3_1_60_2","doi-asserted-by":"publisher","DOI":"10.1145\/3179993"},{"issue":"10","key":"e_1_3_1_61_2","doi-asserted-by":"crossref","first-page":"1416","DOI":"10.3390\/biom11101416","article-title":"Advanced sampling methods for multiscale simulation of disordered proteins and dynamic interactions","volume":"11","author":"Gong Xiping","year":"2021","unstructured":"Xiping Gong, Yumeng Zhang, and Jianhan Chen. 2021. Advanced sampling methods for multiscale simulation of disordered proteins and dynamic interactions. Biomolecules 11, 10 (2021), 1416.","journal-title":"Biomolecules"},{"key":"e_1_3_1_62_2","doi-asserted-by":"publisher","DOI":"10.1145\/3422622"},{"issue":"13","key":"e_1_3_1_63_2","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1016\/j.cma.2009.05.017","article-title":"An algebraic variational multiscale\u2013multigrid method for large eddy simulation of turbulent flow","volume":"199","author":"Gravemeier Volker","year":"2010","unstructured":"Volker Gravemeier, Michael W. Gee, Martin Kronbichler, and Wolfgang A. Wall. 2010. An algebraic variational multiscale\u2013multigrid method for large eddy simulation of turbulent flow. Comput. Methods Appl. Mech. Eng. 199, 13-16 (2010), 853\u2013864.","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"e_1_3_1_64_2","unstructured":"Ross Griebenow Brennan Klein and Erik Hoel. 2019. Finding the right scale of a network: Efficient identification of causal emergence through spectral clustering. Retrieved from https:\/\/arXiv:1908.07565"},{"issue":"6","key":"e_1_3_1_65_2","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1038\/s41562-020-0896-8","article-title":"Global supply-chain effects of COVID-19 control measures","volume":"4","author":"Guan Dabo","year":"2020","unstructured":"Dabo Guan, Daoping Wang, Stephane Hallegatte, Steven J Davis, Jingwen Huo, Shuping Li, Yangchun Bai, Tianyang Lei, Qianyu Xue, D\u2019Maris Coffman et\u00a0al. 2020. Global supply-chain effects of COVID-19 control measures. Nature Hum. Behav. 4, 6 (2020), 577\u2013587.","journal-title":"Nature Hum. Behav."},{"key":"e_1_3_1_66_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i1.16088"},{"issue":"8","key":"e_1_3_1_67_2","first-page":"1551","article-title":"Multi-scale simulation method for electroosmotic flows","volume":"225","author":"Guo Lin","year":"2016","unstructured":"Lin Guo, Shiyi Chen, and Mark O Robbins. 2016. Multi-scale simulation method for electroosmotic flows. Eur. Phys. J. Spec. Top. 225, 8 (2016), 1551\u20131582.","journal-title":"Eur. Phys. J. Spec. Top."},{"key":"e_1_3_1_68_2","article-title":"Electromagnetic modeling using an FDTD-equivalent recurrent convolution neural network: Accurate computing on a deep learning framework.","author":"Guo Liangshuai","year":"2021","unstructured":"Liangshuai Guo, Maokun Li, Shenheng Xu, Fan Yang, and Li Liu. 2021. Electromagnetic modeling using an FDTD-equivalent recurrent convolution neural network: Accurate computing on a deep learning framework. IEEE Anten. Prop. Mag. 65, 1 (2021), 93\u2013102.","journal-title":"IEEE Anten. Prop. Mag."},{"issue":"3","key":"e_1_3_1_69_2","doi-asserted-by":"crossref","first-page":"111","DOI":"10.3390\/fluids5030111","article-title":"Data-driven pulsatile blood flow physics with dynamic mode decomposition","volume":"5","author":"Habibi Milad","year":"2020","unstructured":"Milad Habibi, Scott T. M. Dawson, and Amirhossein Arzani. 2020. Data-driven pulsatile blood flow physics with dynamic mode decomposition. Fluids 5, 3 (2020), 111.","journal-title":"Fluids"},{"key":"e_1_3_1_70_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2021.110192"},{"key":"e_1_3_1_71_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10237-010-0222-x"},{"key":"e_1_3_1_72_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2020.110053"},{"key":"e_1_3_1_73_2","unstructured":"Jiequn Han Linfeng Zhang Roberto Car et\u00a0al. 2017. Deep potential: A general representation of a many-body potential energy surface. Retrieved from https:\/\/arXiv:1707.01478"},{"issue":"4","key":"e_1_3_1_74_2","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1038\/s43588-022-00233-0","article-title":"Optimizing social and economic activity while containing SARS-CoV-2 transmission using DAEDALUS","volume":"2","author":"Haw David J.","year":"2022","unstructured":"David J. Haw, Giovanni Forchini, Patrick Doohan, Paula Christen, Matteo Pianella, Robert Johnson, Sumali Bajaj, Alexandra B. Hogan, Peter Winskill, Marisa Miraldo et\u00a0al. 2022. Optimizing social and economic activity while containing SARS-CoV-2 transmission using DAEDALUS. Nature Comput. Sci. 2, 4 (2022), 223\u2013233.","journal-title":"Nature Comput. Sci."},{"key":"e_1_3_1_75_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"issue":"3","key":"e_1_3_1_76_2","doi-asserted-by":"crossref","first-page":"R2505","DOI":"10.1103\/PhysRevE.59.R2505","article-title":"Cellular automata simulating experimental properties of traffic flow","volume":"59","author":"Helbing Dirk","year":"1999","unstructured":"Dirk Helbing and Michael Schreckenberg. 1999. Cellular automata simulating experimental properties of traffic flow. Phys. Rev. E 59, 3 (1999), R2505.","journal-title":"Phys. Rev. E"},{"key":"e_1_3_1_77_2","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.58.133"},{"key":"e_1_3_1_78_2","doi-asserted-by":"publisher","DOI":"10.1063\/1.4901016"},{"key":"e_1_3_1_79_2","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.97.062412"},{"key":"e_1_3_1_80_2","doi-asserted-by":"publisher","DOI":"10.1016\/0022-5096(63)90036-X"},{"key":"e_1_3_1_81_2","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_1_82_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1314922110"},{"key":"e_1_3_1_83_2","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/1090.001.0001"},{"issue":"6615","key":"e_1_3_1_84_2","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1126\/science.abm7841","article-title":"Emergent phases of ecological diversity and dynamics mapped in microcosms","volume":"378","author":"Hu Jiliang","year":"2022","unstructured":"Jiliang Hu, Daniel R. Amor, Matthieu Barbier, Guy Bunin, and Jeff Gore. 2022. Emergent phases of ecological diversity and dynamics mapped in microcosms. Science 378, 6615 (2022), 85\u201389.","journal-title":"Science"},{"issue":"12","key":"e_1_3_1_85_2","doi-asserted-by":"crossref","first-page":"1679","DOI":"10.1002\/nme.5341","article-title":"An adaptive stochastic inverse solver for multiscale characterization of composite materials","volume":"109","author":"Hu Nan","year":"2017","unstructured":"Nan Hu, Jacob Fish, and Colin McAuliffe. 2017. An adaptive stochastic inverse solver for multiscale characterization of composite materials. Int. J. Numer. Methods Eng. 109, 12 (2017), 1679\u20131700.","journal-title":"Int. J. Numer. Methods Eng."},{"key":"e_1_3_1_86_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2022.111203"},{"key":"e_1_3_1_87_2","article-title":"Mesoscience: Exploring the common principle at mesoscales","author":"Huang Wenlai","year":"2018","unstructured":"Wenlai Huang, Jinghai Li, and Peter P. Edwards. 2018. Mesoscience: Exploring the common principle at mesoscales. Natl. Sci. Rev. 5, 3 (2018), 321\u2013326.","journal-title":"Natl. Sci. Rev."},{"key":"e_1_3_1_88_2","volume-title":"The Finite Element Method: Linear Static and Dynamic Finite Element Analysis","author":"Hughes Thomas J. R.","year":"2012","unstructured":"Thomas J. R. Hughes. 2012. The Finite Element Method: Linear Static and Dynamic Finite Element Analysis. Courier Corporation."},{"key":"e_1_3_1_89_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-10431-6"},{"key":"e_1_3_1_90_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11071-020-05854-6"},{"issue":"1","key":"e_1_3_1_91_2","doi-asserted-by":"crossref","first-page":"e2113297119","DOI":"10.1073\/pnas.2113297119","article-title":"Machine learning\u2013driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins","volume":"119","author":"Ing\u00f3lfsson Helgi I","year":"2022","unstructured":"Helgi I Ing\u00f3lfsson, Chris Neale, Timothy S Carpenter, Rebika Shrestha, Cesar A L\u00f3pez, Timothy H Tran, Tomas Oppelstrup, Harsh Bhatia, Liam G Stanton, Xiaohua Zhang et\u00a0al. 2022. Machine learning\u2013driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins. Proc. Natl. Acad. Sci. U.S.A. 119, 1 (2022), e2113297119.","journal-title":"Proc. Natl. Acad. Sci. U.S.A."},{"issue":"1","key":"e_1_3_1_92_2","first-page":"1","article-title":"It\u2019s complicated: Characterizing the time-varying relationship between cell phone mobility and COVID-19 spread in the US","volume":"4","author":"Jewell Sean","year":"2021","unstructured":"Sean Jewell, Joseph Futoma, Lauren Hannah, Andrew C. Miller, Nicholas J. Foti, and Emily B. Fox. 2021. It\u2019s complicated: Characterizing the time-varying relationship between cell phone mobility and COVID-19 spread in the US. NPJ Dig. Med. 4, 1 (2021), 1\u201311.","journal-title":"NPJ Dig. Med."},{"key":"e_1_3_1_93_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2284-y"},{"key":"e_1_3_1_94_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03819-2"},{"issue":"6","key":"e_1_3_1_95_2","doi-asserted-by":"crossref","first-page":"4616","DOI":"10.1109\/TVT.2017.2693235","article-title":"Multiscale modeling and control architecture for V2X enabled traffic streams","volume":"66","author":"Kachroo Pushkin","year":"2017","unstructured":"Pushkin Kachroo, Shaurya Agarwal, Benedetto Piccoli, and Kaan \u00d6zbay. 2017. Multiscale modeling and control architecture for V2X enabled traffic streams. IEEE Trans. Vehic. Technol. 66, 6 (2017), 4616\u20134626.","journal-title":"IEEE Trans. Vehic. Technol."},{"key":"e_1_3_1_96_2","doi-asserted-by":"publisher","DOI":"10.1038\/s42254-021-00314-5"},{"issue":"3","key":"e_1_3_1_97_2","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1038\/nrm2357","article-title":"Self-organization in cell biology: A brief history","volume":"9","author":"Karsenti Eric","year":"2008","unstructured":"Eric Karsenti. 2008. Self-organization in cell biology: A brief history. Nature Rev. Mol. Cell Biol. 9, 3 (2008), 255\u2013262.","journal-title":"Nature Rev. Mol. Cell Biol."},{"key":"e_1_3_1_98_2","doi-asserted-by":"publisher","DOI":"10.1088\/0305-4470\/35\/47\/303"},{"key":"e_1_3_1_99_2","unstructured":"Diederik P Kingma and Max Welling. 2013. Auto-encoding variational Bayes. Retrieved from https:\/\/arXiv:1312.6114"},{"key":"e_1_3_1_100_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00332-017-9437-7"},{"key":"e_1_3_1_101_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41567-018-0081-4"},{"key":"e_1_3_1_102_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2101784118"},{"key":"e_1_3_1_103_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.abb4218"},{"key":"e_1_3_1_104_2","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974508"},{"key":"e_1_3_1_105_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2293-x"},{"key":"e_1_3_1_106_2","doi-asserted-by":"publisher","DOI":"10.1002\/nme.4953"},{"key":"e_1_3_1_107_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2019.108973"},{"issue":"1","key":"e_1_3_1_108_2","doi-asserted-by":"crossref","first-page":"013141","DOI":"10.1063\/1.5126869","article-title":"Coarse-scale PDEs from fine-scale observations via machine learning","volume":"30","author":"Lee Seungjoon","year":"2020","unstructured":"Seungjoon Lee, Mahdi Kooshkbaghi, Konstantinos Spiliotis, Constantinos I. Siettos, and Ioannis G. Kevrekidis. 2020. Coarse-scale PDEs from fine-scale observations via machine learning. Chaos 30, 1 (2020), 013141.","journal-title":"Chaos"},{"key":"e_1_3_1_109_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2022.111539"},{"key":"e_1_3_1_110_2","doi-asserted-by":"publisher","DOI":"10.1038\/253694a0"},{"issue":"41","key":"e_1_3_1_111_2","first-page":"3225","article-title":"Generalized mathematical homogenization: from theory to practice","volume":"197","author":"Li Aiqin","year":"2008","unstructured":"Aiqin Li, Renge Li, and Jacob Fish. 2008. Generalized mathematical homogenization: from theory to practice. Comput. Methods Appl. Mech. Eng. 197, 41-42 (2008), 3225\u20133248.","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"e_1_3_1_112_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cej.2017.09.162"},{"key":"e_1_3_1_113_2","unstructured":"J. Li and M. Kwauk. 1994. Particle-Fluid Two-Phase Flow: The Energy-Minimization Multi-scale Method; Minimization Multi-Scale Method; Metallurg. https:\/\/scholar.googleusercontent.com\/scholar.bib?q=info:Is1dWljLh9oJ:scholar.google.com\/&output=citation&scisdr=ClGdSMJeEJHGy5thJeI:AFWwaeYAAAAAZitnPeKOiQQGLsqqdzQwTnwhxjI&scisig=AFWwaeYAAAAAZitnPSGOD5u96S5ZhxmPxs3T2p0&scisf=4&ct=citation&cd=-1&hl=zh-CN"},{"key":"e_1_3_1_114_2","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599858"},{"issue":"26","key":"e_1_3_1_115_2","doi-asserted-by":"crossref","first-page":"260601","DOI":"10.1103\/PhysRevLett.121.260601","article-title":"Neural network renormalization group","volume":"121","author":"Li Shuo-Hui","year":"2018","unstructured":"Shuo-Hui Li and Lei Wang. 2018. Neural network renormalization group. Phys. Rev. Lett. 121, 26 (2018), 260601.","journal-title":"Phys. Rev. Lett."},{"key":"e_1_3_1_116_2","doi-asserted-by":"publisher","DOI":"10.1098\/rsif.2017.0844"},{"key":"e_1_3_1_117_2","doi-asserted-by":"publisher","DOI":"10.1098\/rspa.1955.0089"},{"key":"e_1_3_1_118_2","unstructured":"Mario Lino Chris Cantwell Anil A. Bharath and Stathi Fotiadis. 2021. Simulating continuum mechanics with multi-scale graph neural networks. Retrieved from https:\/\/arXiv:2106.04900"},{"key":"e_1_3_1_119_2","unstructured":"Mario Lino Stati Fotiadis Anil A. Bharath and Chris Cantwell. 2022. REMuS-GNN: A rotation-equivariant model for simulating continuum dynamics. Retrieved from https:\/\/arXiv:2205.07852"},{"key":"e_1_3_1_120_2","unstructured":"Mario Lino Stathi Fotiadis Anil A. Bharath and Chris Cantwell. 2022. Towards fast simulation of environmental fluid mechanics with multi-scale graph neural networks. Retrieved from https:\/\/arXiv:2205.02637"},{"key":"e_1_3_1_121_2","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539397"},{"key":"e_1_3_1_122_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2016.04.004"},{"key":"e_1_3_1_123_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmps.2019.03.004"},{"key":"e_1_3_1_124_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2018.09.020"},{"key":"e_1_3_1_125_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature04153"},{"issue":"12","key":"e_1_3_1_126_2","doi-asserted-by":"crossref","first-page":"7930","DOI":"10.1021\/acs.jctc.1c00735","article-title":"GLIMPS: A machine learning approach to resolution transformation for multiscale modeling","volume":"17","author":"Louison Keverne A.","year":"2021","unstructured":"Keverne A. Louison, Ian L. Dryden, and Charles A. Laughton. 2021. GLIMPS: A machine learning approach to resolution transformation for multiscale modeling. J. Chem. Theory Comput. 17, 12 (2021), 7930\u20137937.","journal-title":"J. Chem. Theory Comput."},{"key":"e_1_3_1_127_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.abb4557"},{"issue":"2","key":"e_1_3_1_128_2","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1007\/s10494-019-00026-y","article-title":"Large eddy simulation of pre-chamber ignition in an internal combustion engine","volume":"103","author":"Mal\u00e9 Quentin","year":"2019","unstructured":"Quentin Mal\u00e9, Gabriel Staffelbach, Olivier Vermorel, Antony Misdariis, Fr\u00e9d\u00e9ric Ravet, and Thierry Poinsot. 2019. Large eddy simulation of pre-chamber ignition in an internal combustion engine. Flow, Turbul. Combust. 103, 2 (2019), 465\u2013483.","journal-title":"Flow, Turbul. Combust."},{"key":"e_1_3_1_129_2","doi-asserted-by":"publisher","DOI":"10.1109\/34.192463"},{"key":"e_1_3_1_130_2","doi-asserted-by":"publisher","DOI":"10.1137\/17M1162366"},{"issue":"11","key":"e_1_3_1_131_2","doi-asserted-by":"crossref","first-page":"3989","DOI":"10.1021\/bm201008b","article-title":"Observations of multiscale, stress-induced changes of collagen orientation in tendon by polarized Raman spectroscopy","volume":"12","author":"Masic Admir","year":"2011","unstructured":"Admir Masic, Luca Bertinetti, Roman Schuetz, Leonardo Galvis, Nadya Timofeeva, John W. C. Dunlop, Jong Seto, Markus A. Hartmann, and Peter Fratzl. 2011. Observations of multiscale, stress-induced changes of collagen orientation in tendon by polarized Raman spectroscopy. Biomacromolecules 12, 11 (2011), 3989\u20133996.","journal-title":"Biomacromolecules"},{"key":"e_1_3_1_132_2","doi-asserted-by":"publisher","DOI":"10.1063\/5.0039986"},{"key":"e_1_3_1_133_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.physd.2020.132368"},{"issue":"11","key":"e_1_3_1_134_2","doi-asserted-by":"crossref","first-page":"e003627","DOI":"10.1136\/bmjgh-2020-003627","article-title":"Incentivising wealthy nations to participate in the COVID-19 vaccine global access facility (COVAX): A game theory perspective","volume":"5","author":"McAdams David","year":"2020","unstructured":"David McAdams, Kaci Kennedy McDade, Osondu Ogbuoji, Matthew Johnson, Siddharth Dixit, and Gavin Yamey. 2020. Incentivising wealthy nations to participate in the COVID-19 vaccine global access facility (COVAX): A game theory perspective. BMJ Global Health 5, 11 (2020), e003627.","journal-title":"BMJ Global Health"},{"key":"e_1_3_1_135_2","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1214\/lnms\/1215455054","article-title":"Fitting diffusion models in finance","author":"McLeish Don L.","year":"1997","unstructured":"Don L. McLeish and Adam W. Kolkiewicz. 1997. Fitting diffusion models in finance. Lecture Notes-Monograph Series (1997), 327\u2013350.","journal-title":"Lecture Notes-Monograph Series"},{"issue":"3","key":"e_1_3_1_136_2","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1002\/nme.1554","article-title":"Wavelet galerkin method in multi-scale homogenization of heterogeneous media","volume":"66","author":"Mehraeen Shafigh","year":"2006","unstructured":"Shafigh Mehraeen and Jiun-Shyan Chen. 2006. Wavelet galerkin method in multi-scale homogenization of heterogeneous media. Int. J. Numer. Methods Eng. 66, 3 (2006), 381\u2013403.","journal-title":"Int. J. Numer. Methods Eng."},{"key":"e_1_3_1_137_2","unstructured":"Pankaj Mehta and David J. Schwab. 2014. An exact mapping between the variational renormalization group and deep learning. Retrieved from https:\/\/arXiv:1410.3831"},{"key":"e_1_3_1_138_2","doi-asserted-by":"publisher","DOI":"10.1002\/nme.1972"},{"key":"e_1_3_1_139_2","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2010-343"},{"key":"e_1_3_1_140_2","unstructured":"Volodymyr Mnih Koray Kavukcuoglu David Silver Alex Graves Ioannis Antonoglou Daan Wierstra and Martin Riedmiller. 2013. Playing Atari with deep reinforcement learning. Retrieved from https:\/\/arXiv:1312.5602"},{"key":"e_1_3_1_141_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.partic.2018.09.004"},{"issue":"4","key":"e_1_3_1_142_2","doi-asserted-by":"crossref","first-page":"043309","DOI":"10.1103\/PhysRevE.96.043309","article-title":"Reconstruction of three-dimensional porous media using generative adversarial neural networks","volume":"96","author":"Mosser Lukas","year":"2017","unstructured":"Lukas Mosser, Olivier Dubrule, and Martin J. Blunt. 2017. Reconstruction of three-dimensional porous media using generative adversarial neural networks. Phys. Rev. E 96, 4 (2017), 043309.","journal-title":"Phys. Rev. E"},{"issue":"1","key":"e_1_3_1_143_2","first-page":"1","article-title":"Deep learning of contagion dynamics on complex networks","volume":"12","author":"Murphy Charles","year":"2021","unstructured":"Charles Murphy, Edward Laurence, and Antoine Allard. 2021. Deep learning of contagion dynamics on complex networks. Nature Commun. 12, 1 (2021), 1\u201311.","journal-title":"Nature Commun."},{"issue":"1","key":"e_1_3_1_144_2","doi-asserted-by":"crossref","first-page":"016112","DOI":"10.1103\/PhysRevE.65.016112","article-title":"Effect of looking at the car that follows in an optimal velocity model of traffic flow","volume":"65","author":"Nakayama Akihiro","year":"2001","unstructured":"Akihiro Nakayama, Y\u016bki Sugiyama, and Katsuya Hasebe. 2001. Effect of looking at the car that follows in an optimal velocity model of traffic flow. Phys. Rev. E 65, 1 (2001), 016112.","journal-title":"Phys. Rev. E"},{"issue":"27","key":"e_1_3_1_145_2","doi-asserted-by":"crossref","first-page":"1598","DOI":"10.1103\/PhysRevLett.33.1598","article-title":"Renormalization-group approach to the solution of general ising models","volume":"33","author":"Nauenberg M.","year":"1974","unstructured":"M. Nauenberg and B. Nienhuis. 1974. Renormalization-group approach to the solution of general ising models. Phys. Rev. Lett. 33, 27 (1974), 1598.","journal-title":"Phys. Rev. Lett."},{"key":"e_1_3_1_146_2","doi-asserted-by":"publisher","DOI":"10.1287\/opre.9.2.209"},{"issue":"48","key":"e_1_3_1_147_2","doi-asserted-by":"crossref","first-page":"30285","DOI":"10.1073\/pnas.2014297117","article-title":"Network interventions for managing the COVID-19 pandemic and sustaining economy","volume":"117","author":"Nishi Akihiro","year":"2020","unstructured":"Akihiro Nishi, George Dewey, Akira Endo, Sophia Neman, Sage K. Iwamoto, Michael Y. Ni, Yusuke Tsugawa, Georgios Iosifidis, Justin D Smith, and Sean D. Young. 2020. Network interventions for managing the COVID-19 pandemic and sustaining economy. Proc. Natl. Acad. Sci. U.S.A. 117, 48 (2020), 30285\u201330294.","journal-title":"Proc. Natl. Acad. Sci. U.S.A."},{"key":"e_1_3_1_148_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sbi.2017.02.006"},{"key":"e_1_3_1_149_2","doi-asserted-by":"publisher","DOI":"10.1137\/110858616"},{"key":"e_1_3_1_150_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2017.08.040"},{"key":"e_1_3_1_151_2","doi-asserted-by":"publisher","DOI":"10.1002\/nme.2068"},{"issue":"6","key":"e_1_3_1_152_2","doi-asserted-by":"crossref","first-page":"1987","DOI":"10.1007\/s10237-019-01190-w","article-title":"Using machine learning to characterize heart failure across the scales","volume":"18","author":"Peirlinck Mathias","year":"2019","unstructured":"Mathias Peirlinck, F. Sahli Costabal, K. L. Sack, J. S. Choy, G. S. Kassab, J. M. Guccione, M. De Beule, Patrick Segers, and E. Kuhl. 2019. Using machine learning to characterize heart failure across the scales. Biomech. Model. Mechanobiol. 18, 6 (2019), 1987\u20132001.","journal-title":"Biomech. Model. Mechanobiol."},{"issue":"15","key":"e_1_3_1_153_2","doi-asserted-by":"crossref","first-page":"1694","DOI":"10.1016\/j.physleta.2010.02.020","article-title":"A dynamical model of car-following with the consideration of the multiple information of preceding cars","volume":"374","author":"Peng G. H.","year":"2010","unstructured":"G. H. Peng and D. H. Sun. 2010. A dynamical model of car-following with the consideration of the multiple information of preceding cars. Phys. Lett. A 374, 15-16 (2010), 1694\u20131698.","journal-title":"Phys. Lett. A"},{"issue":"3","key":"e_1_3_1_154_2","doi-asserted-by":"crossref","first-page":"1017","DOI":"10.1007\/s11831-020-09405-5","article-title":"Multiscale modeling meets machine learning: What can we learn?","volume":"28","author":"Peng Grace C. Y.","year":"2021","unstructured":"Grace C. Y. Peng, Mark Alber, Adrian Buganza Tepole, William R. Cannon, Suvranu De, Savador Dura-Bernal, Krishna Garikipati, George Karniadakis, William W. Lytton, Paris Perdikaris et\u00a0al. 2021. Multiscale modeling meets machine learning: What can we learn? Arch. Comput. Methods Eng. 28, 3 (2021), 1017\u20131037.","journal-title":"Arch. Comput. Methods Eng."},{"issue":"1","key":"e_1_3_1_155_2","first-page":"07B604_1","article-title":"Identification of slow molecular order parameters for markov model construction","volume":"139","author":"P\u00e9rez-Hern\u00e1ndez Guillermo","year":"2013","unstructured":"Guillermo P\u00e9rez-Hern\u00e1ndez, Fabian Paul, Toni Giorgino, Gianni De Fabritiis, and Frank No\u00e9. 2013. Identification of slow molecular order parameters for markov model construction. J. Chem. Phys. 139, 1 (2013), 07B604_1.","journal-title":"J. Chem. Phys."},{"key":"e_1_3_1_156_2","doi-asserted-by":"publisher","DOI":"10.1063\/1.1721265"},{"key":"e_1_3_1_157_2","doi-asserted-by":"publisher","DOI":"10.1137\/15M1013857"},{"issue":"1","key":"e_1_3_1_158_2","first-page":"1","article-title":"Scaling of contact networks for epidemic spreading in urban transit systems","volume":"11","author":"Qian Xinwu","year":"2021","unstructured":"Xinwu Qian, Lijun Sun, and Satish V. Ukkusuri. 2021. Scaling of contact networks for epidemic spreading in urban transit systems. Sci. Rep. 11, 1 (2021), 1\u201312.","journal-title":"Sci. Rep."},{"key":"e_1_3_1_159_2","first-page":"100083","article-title":"On-the-fly construction of surrogate constitutive models for concurrent multiscale mechanical analysis through probabilistic machine learning","volume":"9","author":"Rocha I. B. C. M.","year":"2021","unstructured":"I. B. C. M. Rocha, Pierre Kerfriden, and F. P. van der Meer. 2021. On-the-fly construction of surrogate constitutive models for concurrent multiscale mechanical analysis through probabilistic machine learning. J. Comput. Phys. X 9 (2021), 100083.","journal-title":"J. Comput. Phys. X"},{"issue":"638","key":"e_1_3_1_160_2","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1098\/rspa.1916.0007","article-title":"An application of the theory of probabilities to the study of a priori pathometry\u2014Part I","volume":"92","author":"Ross Ronald","year":"1916","unstructured":"Ronald Ross. 1916. An application of the theory of probabilities to the study of a priori pathometry\u2014Part I. Proc. Roy. Soc. London Ser. A 92, 638 (1916), 204\u2013230.","journal-title":"Proc. Roy. Soc. London Ser. A"},{"issue":"10","key":"e_1_3_1_161_2","doi-asserted-by":"crossref","first-page":"1168","DOI":"10.1515\/zna-1976-1006","article-title":"Chemical turbulence: Chaos in a simple reaction-diffusion system","volume":"31","author":"R\u00f6ssler Otto E","year":"1976","unstructured":"Otto E R\u00f6ssler. 1976. Chemical turbulence: Chaos in a simple reaction-diffusion system. Zeitschrift f\u00fcr Naturforschung A 31, 10 (1976), 1168\u20131172.","journal-title":"Zeitschrift f\u00fcr Naturforschung A"},{"issue":"1","key":"e_1_3_1_162_2","first-page":"1","article-title":"National interest may require distributing COVID-19 vaccines to other countries","volume":"11","author":"Rotesi Tiziano","year":"2021","unstructured":"Tiziano Rotesi, Paolo Pin, Maria Cucciniello, Amyn A. Malik, Elliott E. Paintsil, Scott E. Bokemper, Kathryn Willebrand, Gregory A. Huber, Alessia Melegaro, and Saad B. Omer. 2021. National interest may require distributing COVID-19 vaccines to other countries. Sci. Rep. 11, 1 (2021), 1\u20138.","journal-title":"Sci. Rep."},{"key":"e_1_3_1_163_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-85567-5_9"},{"key":"e_1_3_1_164_2","first-page":"8459","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Sanchez-Gonzalez Alvaro","year":"2020","unstructured":"Alvaro Sanchez-Gonzalez, Jonathan Godwin, Tobias Pfaff, Rex Ying, Jure Leskovec, and Peter Battaglia. 2020. Learning to simulate complex physics with graph networks. In Proceedings of the International Conference on Machine Learning. 8459\u20138468."},{"key":"e_1_3_1_165_2","doi-asserted-by":"publisher","DOI":"10.1017\/S0022112010001217"},{"key":"e_1_3_1_166_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00162-010-0203-9"},{"key":"e_1_3_1_167_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0905547106"},{"issue":"1","key":"e_1_3_1_168_2","first-page":"1","article-title":"Measuring the effect of non-pharmaceutical interventions (NPIs) on mobility during the COVID-19 pandemic using global mobility data","volume":"4","author":"Snoeijer Berber T.","year":"2021","unstructured":"Berber T. Snoeijer, Mariska Burger, Shaoxiong Sun, Richard J. B. Dobson, and Amos A. Folarin. 2021. Measuring the effect of non-pharmaceutical interventions (NPIs) on mobility during the COVID-19 pandemic using global mobility data. NPJ Dig. Med. 4, 1 (2021), 1\u201312.","journal-title":"NPJ Dig. Med."},{"key":"e_1_3_1_169_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-73949-6"},{"key":"e_1_3_1_170_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00466-015-1254-y"},{"issue":"15","key":"e_1_3_1_171_2","doi-asserted-by":"crossref","first-page":"158301","DOI":"10.1103\/PhysRevLett.127.158301","article-title":"Universal nonlinear infection kernel from heterogeneous exposure on higher-order networks","volume":"127","author":"St-Onge Guillaume","year":"2021","unstructured":"Guillaume St-Onge, Hanlin Sun, Antoine Allard, Laurent H\u00e9bert-Dufresne, and Ginestra Bianconi. 2021. Universal nonlinear infection kernel from heterogeneous exposure on higher-order networks. Phys. Rev. Lett. 127, 15 (2021), 158301.","journal-title":"Phys. Rev. Lett."},{"key":"e_1_3_1_172_2","doi-asserted-by":"publisher","DOI":"10.1021\/ct100569y"},{"issue":"8","key":"e_1_3_1_173_2","doi-asserted-by":"crossref","first-page":"2795","DOI":"10.1088\/0256-307X\/25\/8\/017","article-title":"Synchronized flow in a cellular automaton model with time headway dependent randomization","volume":"25","author":"Tao Chen","year":"2008","unstructured":"Chen Tao, Jia Bin, Li Xin-Gang, Jiang Rui, and Gao Zi-You. 2008. Synchronized flow in a cellular automaton model with time headway dependent randomization. Chinese Phys. Lett. 25, 8 (2008), 2795.","journal-title":"Chinese Phys. Lett."},{"key":"e_1_3_1_174_2","doi-asserted-by":"publisher","DOI":"10.1137\/090771648"},{"key":"e_1_3_1_175_2","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.62.1805"},{"key":"e_1_3_1_176_2","volume-title":"Dynamic Mode Decomposition: Theory and Applications","author":"Tu Jonathan H.","year":"2013","unstructured":"Jonathan H. Tu. 2013. Dynamic Mode Decomposition: Theory and Applications. Ph. D. Dissertation. Princeton University."},{"key":"e_1_3_1_177_2","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-022-00464-w"},{"key":"e_1_3_1_178_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jctc.1c00809"},{"issue":"6562","key":"e_1_3_1_179_2","first-page":"1","article-title":"Vaccine nationalism and the dynamics and control of SARS-CoV-2","volume":"373","author":"Wagner Caroline E.","year":"2021","unstructured":"Caroline E. Wagner, Chadi M. Saad-Roy, Sinead E. Morris, Rachel E. Baker, Michael J. Mina, Jeremy Farrar, Edward C. Holmes, Oliver G. Pybus, Andrea L. Graham, Ezekiel J. Emanuel et\u00a0al. 2021. Vaccine nationalism and the dynamics and control of SARS-CoV-2. Science 373, 6562 (2021), 1\u20138.","journal-title":"Science"},{"key":"e_1_3_1_180_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2018.11.026"},{"key":"e_1_3_1_181_2","volume-title":"Proceedings of the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","author":"Wang Mudan","year":"2023","unstructured":"Mudan Wang, Huan Yan, Huandong Wang, Yong Li, and Depeng Jin. 2023. Contagion process guided cross-scale spatio-temporal graph neural network for traffic congestion prediction. In Proceedings of the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems."},{"issue":"1","key":"e_1_3_1_182_2","first-page":"1","article-title":"Coarse-graining auto-encoders for molecular dynamics","volume":"5","author":"Wang Wujie","year":"2019","unstructured":"Wujie Wang and Rafael G\u00f3mez-Bombarelli. 2019. Coarse-graining auto-encoders for molecular dynamics. npj Comput. Mater. 5, 1 (2019), 1\u20139.","journal-title":"npj Comput. Mater."},{"key":"e_1_3_1_183_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2019.109071"},{"key":"e_1_3_1_184_2","doi-asserted-by":"publisher","DOI":"10.1038\/30918"},{"key":"e_1_3_1_185_2","doi-asserted-by":"publisher","DOI":"10.1063\/1.5011399"},{"key":"e_1_3_1_186_2","volume-title":"Principles of Multiscale Modeling","author":"Weinan E.","year":"2011","unstructured":"E. Weinan. 2011. Principles of Multiscale Modeling. Cambridge University Press."},{"key":"e_1_3_1_187_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.284.5420.1677"},{"issue":"8","key":"e_1_3_1_188_2","doi-asserted-by":"crossref","first-page":"532","DOI":"10.1038\/s43588-021-00115-x","article-title":"A machine learning-based multiscale model to predict bone formation in scaffolds","volume":"1","author":"Wu Chi","year":"2021","unstructured":"Chi Wu, Ali Entezari, Keke Zheng, Jianguang Fang, Hala Zreiqat, Grant P. Steven, Michael V. Swain, and Qing Li. 2021. A machine learning-based multiscale model to predict bone formation in scaffolds. Nature Comput. Sci. 1, 8 (2021), 532\u2013541.","journal-title":"Nature Comput. Sci."},{"key":"e_1_3_1_189_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30260-9"},{"key":"e_1_3_1_190_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2020.113234"},{"issue":"2","key":"e_1_3_1_191_2","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1016\/j.physa.2006.10.033","article-title":"The stability analysis of the full velocity and acceleration velocity model","volume":"375","author":"Xiaomei Zhao","year":"2007","unstructured":"Zhao Xiaomei and Gao Ziyou. 2007. The stability analysis of the full velocity and acceleration velocity model. Phys. A: Stat. Mech. Appl. 375, 2 (2007), 679\u2013686.","journal-title":"Phys. A: Stat. Mech. Appl."},{"issue":"4","key":"e_1_3_1_192_2","first-page":"899","article-title":"Stabilization of traffic flow based on the multiple information of preceding cars","volume":"3","author":"Xie D. F.","year":"2008","unstructured":"D. F. Xie, Z. Y. Gao, and X. M. Zhao. 2008. Stabilization of traffic flow based on the multiple information of preceding cars. Commun. Comput. Phys. 3, 4 (2008), 899\u2013912.","journal-title":"Commun. Comput. Phys."},{"key":"e_1_3_1_193_2","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.120.145301"},{"key":"e_1_3_1_194_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2021.103288"},{"key":"e_1_3_1_195_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2005.845141"},{"key":"e_1_3_1_196_2","doi-asserted-by":"publisher","DOI":"10.1145\/3295500.3356149"},{"key":"e_1_3_1_197_2","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.trpro.2017.05.007","article-title":"Multi-scale perimeter control approach in a connected-vehicle environment","volume":"23","author":"Yang Kaidi","year":"2017","unstructured":"Kaidi Yang, Nan Zheng, and Monica Menendez. 2017. Multi-scale perimeter control approach in a connected-vehicle environment. Transport. Res. Procedia 23 (2017), 101\u2013120.","journal-title":"Transport. Res. Procedia"},{"issue":"9","key":"e_1_3_1_198_2","doi-asserted-by":"crossref","first-page":"094117","DOI":"10.1063\/5.0015779","article-title":"When machine learning meets multiscale modeling in chemical reactions","volume":"153","author":"Yang Wuyue","year":"2020","unstructured":"Wuyue Yang, Liangrong Peng, Yi Zhu, and Liu Hong. 2020. When machine learning meets multiscale modeling in chemical reactions. J. Chem. Phys. 153, 9 (2020), 094117.","journal-title":"J. Chem. Phys."},{"issue":"11","key":"e_1_3_1_199_2","article-title":"Microstructural materials design via deep adversarial learning methodology","volume":"140","author":"Yang Zijiang","year":"2018","unstructured":"Zijiang Yang, Xiaolin Li, L. Catherine Brinson, Alok N. Choudhary, Wei Chen, and Ankit Agrawal. 2018. Microstructural materials design via deep adversarial learning methodology. J. Mech. Design 140, 11 (2018).","journal-title":"J. Mech. Design"},{"key":"e_1_3_1_200_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41562-022-01289-8"},{"key":"e_1_3_1_201_2","article-title":"Hierarchical graph representation learning with differentiable pooling","volume":"31","author":"Ying Zhitao","year":"2018","unstructured":"Zhitao Ying, Jiaxuan You, Christopher Morris, Xiang Ren, Will Hamilton, and Jure Leskovec. 2018. Hierarchical graph representation learning with differentiable pooling. Adv. Neural Info. Process. Syst. 31 (2018).","journal-title":"Adv. Neural Info. Process. Syst."},{"key":"e_1_3_1_202_2","volume-title":"Proceedings of the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","author":"Wang Yong Li Yinzhou Tang, Huandong","year":"2023","unstructured":"Yong Li Yinzhou Tang, Huandong Wang. 2023. Enhancing spatial spread prediction of infectious diseases through integrating multi-scale human mobility dynamics. In Proceedings of the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems."},{"key":"e_1_3_1_203_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0020-7683(02)00255-X"},{"issue":"21","key":"e_1_3_1_204_2","doi-asserted-by":"crossref","first-page":"2016","DOI":"10.1016\/j.cma.2008.12.038","article-title":"Multiple scale eigendeformation-based reduced order homogenization","volume":"198","author":"Yuan Zheng","year":"2009","unstructured":"Zheng Yuan and Jacob Fish. 2009. Multiple scale eigendeformation-based reduced order homogenization. Comput. Methods Appl. Mech. Eng. 198, 21-26 (2009), 2016\u20132038.","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"e_1_3_1_205_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2019.109165"},{"key":"e_1_3_1_206_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.abb8001"},{"issue":"22","key":"e_1_3_1_207_2","first-page":"E4334\u2013E4343","article-title":"Spread of zika virus in the americas","volume":"114","author":"Zhang Qian","year":"2017","unstructured":"Qian Zhang, Kaiyuan Sun, Matteo Chinazzi, Ana Pastore y Piontti, Natalie E. Dean, Diana Patricia Rojas, Stefano Merler, Dina Mistry, Piero Poletti, Luca Rossi et\u00a0al. 2017. Spread of zika virus in the americas. Proc. Natl. Acad. Sci. U.S.A. 114, 22 (2017), E4334\u2013E4343.","journal-title":"Proc. Natl. Acad. Sci. U.S.A."},{"issue":"1","key":"e_1_3_1_208_2","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1140\/epjb\/e2005-00304-3","article-title":"A new car-following model: Full velocity and acceleration difference model","volume":"47","author":"Zhao Xiao-Mei","year":"2005","unstructured":"Xiao-Mei Zhao and Zi-You Gao. 2005. A new car-following model: Full velocity and acceleration difference model. Eur. Phys. J. B Cond. Matter Complex Syst. 47, 1 (2005), 145\u2013150.","journal-title":"Eur. Phys. J. B Cond. Matter Complex Syst."},{"issue":"1","key":"e_1_3_1_209_2","first-page":"1","article-title":"Dissecting transition cells from single-cell transcriptome data through multiscale stochastic dynamics","volume":"12","author":"Zhou Peijie","year":"2021","unstructured":"Peijie Zhou, Shuxiong Wang, Tiejun Li, and Qing Nie. 2021. Dissecting transition cells from single-cell transcriptome data through multiscale stochastic dynamics. Nature Commun. 12, 1 (2021), 1\u201315.","journal-title":"Nature Commun."},{"issue":"8","key":"e_1_3_1_210_2","first-page":"e417\u2013e424","article-title":"Effects of human mobility restrictions on the spread of COVID-19 in shenzhen, China: A modelling study using mobile phone data","volume":"2","author":"Zhou Ying","year":"2020","unstructured":"Ying Zhou, Renzhe Xu, Dongsheng Hu, Yang Yue, Qingquan Li, and Jizhe Xia. 2020. Effects of human mobility restrictions on the spread of COVID-19 in shenzhen, China: A modelling study using mobile phone data. Lancet Dig. Health 2, 8 (2020), e417\u2013e424.","journal-title":"Lancet Dig. Health"},{"key":"e_1_3_1_211_2","first-page":"12904","article-title":"MixSeq: Connecting macroscopic time series forecasting with microscopic time series data","volume":"34","author":"Zhu Zhibo","year":"2021","unstructured":"Zhibo Zhu, Ziqi Liu, Ge Jin, Zhiqiang Zhang, Lei Chen, Jun Zhou, and Jianyong Zhou. 2021. MixSeq: Connecting macroscopic time series forecasting with microscopic time series data. Adv. Neural Info. Process. Syst. 34 (2021), 12904\u201312916.","journal-title":"Adv. Neural Info. Process. Syst."}],"container-title":["ACM Computing Surveys"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3654662","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3654662","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:06:10Z","timestamp":1750291570000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3654662"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10]]},"references-count":210,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2024,12,31]]}},"alternative-id":["10.1145\/3654662"],"URL":"https:\/\/doi.org\/10.1145\/3654662","relation":{},"ISSN":["0360-0300","1557-7341"],"issn-type":[{"value":"0360-0300","type":"print"},{"value":"1557-7341","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10]]},"assertion":[{"value":"2022-11-29","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-01-31","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-10-01","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}