{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T01:43:35Z","timestamp":1784166215569,"version":"3.55.0"},"reference-count":71,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T00:00:00Z","timestamp":1618963200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61702240"],"award-info":[{"award-number":["61702240"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["lzujbky-2017-191"],"award-info":[{"award-number":["lzujbky-2017-191"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Community detection is of great significance in understanding the structure of the network. Label propagation algorithm (LPA) is a classical and effective method, but it has the problems of randomness and instability. An improved label propagation algorithm named LPA-MNI is proposed in this study by combining the modularity function and node importance with the original LPA. LPA-MNI first identify the initial communities according to the value of modularity. Subsequently, the label propagation is used to cluster the remaining nodes that have not been assigned to initial communities. Meanwhile, node importance is used to improve the node order of label updating and the mechanism of label selecting when multiple labels are contained by the maximum number of nodes. Extensive experiments are performed on twelve real-world networks and eight groups of synthetic networks, and the results show that LPA-MNI has better accuracy, higher modularity, and more reasonable community numbers when compared with other six algorithms. In addition, LPA-MNI is shown to be more robust than the traditional LPA algorithm.<\/jats:p>","DOI":"10.3390\/e23050497","type":"journal-article","created":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T21:25:10Z","timestamp":1619040310000},"page":"497","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["LPA-MNI: An Improved Label Propagation Algorithm Based on Modularity and Node Importance for Community Detection"],"prefix":"10.3390","volume":"23","author":[{"given":"Huan","family":"Li","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruisheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhili","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"026113","DOI":"10.1103\/PhysRevE.69.026113","article-title":"Finding and evaluating community structure in networks","volume":"69","author":"Newman","year":"2004","journal-title":"Phys. Rev. E Stat. Nonlinear Soft Matter Phys."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"40416","DOI":"10.1109\/ACCESS.2019.2897586","article-title":"Recommendation Based on Review Texts and Social Communities: A Hybrid Model","volume":"7","author":"Ji","year":"2019","journal-title":"IEEE Access"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1085","DOI":"10.1016\/j.physa.2018.08.045","article-title":"IMPC: Influence maximization based on multi-neighbor potential in community networks","volume":"512","author":"Shang","year":"2018","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"7821","DOI":"10.1073\/pnas.122653799","article-title":"Community structure in social and biological networks","volume":"99","author":"Girvan","year":"2002","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2658","DOI":"10.1073\/pnas.0400054101","article-title":"Defining and identifying communities in networks","volume":"101","author":"Radicchi","year":"2004","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"036104","DOI":"10.1103\/PhysRevE.74.036104","article-title":"Finding community structure in networks using the eigenvectors of matrices","volume":"74","author":"Newman","year":"2006","journal-title":"Phys. Rev. E Stat. Nonlinear Soft Matter Phys."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"8577","DOI":"10.1073\/pnas.0601602103","article-title":"Modularity and community structure in networks","volume":"103","author":"Newman","year":"2006","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.physrep.2009.11.002","article-title":"Community detection in graphs","volume":"486","author":"Fortunato","year":"2010","journal-title":"Phys. Rep."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"066111","DOI":"10.1103\/PhysRevE.70.066111","article-title":"Finding community structure in very large networks","volume":"70","author":"Clauset","year":"2004","journal-title":"Phys. Rev. E Stat. Nonlinear Soft Matter Phys."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1088\/1742-5468\/2008\/10\/P10008","article-title":"Fast unfolding of communities in large networks","volume":"2008","author":"Blondel","year":"2008","journal-title":"J. Stat. Mech."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"025101","DOI":"10.1103\/PhysRevE.70.025101","article-title":"Modularity from fluctuations in random graphs and complex networks","volume":"70","author":"Amaral","year":"2004","journal-title":"Phys. Rev. E Stat. Nonlinear Soft Matter Phys."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.physa.2018.01.025","article-title":"Overlapping communities detection based on spectral analysis of line graphs","volume":"498","author":"Gui","year":"2018","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"052808","DOI":"10.1103\/PhysRevE.92.052808","article-title":"Multiway spectral community detection in networks","volume":"92","author":"Zhang","year":"2015","journal-title":"Phys. Rev. E Stat. Nonlinear Soft Matter Phys."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1073\/pnas.0605965104","article-title":"Resolution limit in community detection","volume":"104","author":"Barthelemy","year":"2007","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1109\/TCSS.2014.2307458","article-title":"Community Detection via Maximization of Modularity and Its Variants","volume":"1","author":"Chen","year":"2014","journal-title":"IEEE Trans. Comput. Soc. Syst."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"016114","DOI":"10.1103\/PhysRevE.80.016114","article-title":"Analysis of community structure in networks of correlated data","volume":"80","author":"Jensen","year":"2009","journal-title":"Phys. Rev. E Stat. Nonlinear Soft Matter Phys."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"052802","DOI":"10.1103\/PhysRevE.88.052802","article-title":"Normalized modularity optimization method for community identification with degree adjustment","volume":"88","author":"Zhang","year":"2013","journal-title":"Phys. Rev. E Stat. Nonlinear Soft Matter Phys."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"107163","DOI":"10.1016\/j.csda.2020.107163","article-title":"Community detection via an efficient nonconvex optimization approach based on modularity","volume":"157","author":"Yuan","year":"2021","journal-title":"Comput. Stat. Data Anal."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Pons, P., and Latapy, M. (2005). Computing communities in large networks using random walks. International Symposium on Computer and Information Sciences, Springer.","DOI":"10.1007\/11569596_31"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1118","DOI":"10.1073\/pnas.0706851105","article-title":"Maps of Random Walks on Complex Networks Reveal Community Structure","volume":"105","author":"Rosvall","year":"2008","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_21","unstructured":"Van Dongen, S. (2000). Graph Clustering by Flow Simulation. [Ph.D. Thesis, University of Utrecht]."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Behera, R.K., Rath, S.K., Misra, S., Dama\u0161evi\u010dius, R., and Maskeli\u016bnas, R. (2017). Large Scale Community Detection Using a Small World Model. Appl. Sci., 7.","DOI":"10.3390\/app7111173"},{"key":"ref_23","unstructured":"Chang, H., Feng, Z., and Ren, Z. (2013, January 20\u201323). Community detection using Ant Colony Optimization. Proceedings of the 2013 IEEE Congress on Evolutionary Computation, Cancun, Mexico."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.neucom.2017.05.029","article-title":"Adaptive community detection in complex networks using genetic algorithms","volume":"266","author":"Guerrero","year":"2017","journal-title":"Neurocomputing"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.neunet.2014.04.006","article-title":"Discrete particle swarm optimization for identifying community structures in signed social networks","volume":"58","author":"Cai","year":"2014","journal-title":"Neural Netw."},{"key":"ref_26","unstructured":"Ali, E., Hafez, A.I., Hassanien, A.E., and Fahmy, A.A. (2015). A Discrete Bat Algorithm for the Community Detection Problem. Hybrid Artificial Intelligent Systems, Springer."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"122937","DOI":"10.1016\/j.physa.2019.122937","article-title":"WOCDA: A whale optimization based community detection algorithm","volume":"539","author":"Zhang","year":"2019","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_28","unstructured":"Hamilton, W.L., Ying, R., and Leskovec, J. (2017). Representation learning on graphs: Methods and applications. arXiv Preprint."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Yang, J., and Leskovec, J. (2013, January 4\u20138). Overlapping Community Detection at Scale: A Nonnegative Matrix Factorization Approach. Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, Rome, Italy.","DOI":"10.1145\/2433396.2433471"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"126012","DOI":"10.1016\/j.amc.2021.126012","article-title":"A weighted network community detection algorithm based on deep learning","volume":"401","author":"Li","year":"2021","journal-title":"Appl. Math. Comput."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"122050","DOI":"10.1016\/j.physa.2019.122050","article-title":"Modularized tri-factor nonnegative matrix factorization for community detection enhancement","volume":"533","author":"Yan","year":"2019","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"122904","DOI":"10.1016\/j.physa.2019.122904","article-title":"Modularized convex nonnegative matrix factorization for community detection in signed and unsigned networks","volume":"539","author":"Yan","year":"2020","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1016\/j.ins.2020.01.001","article-title":"Local community detection by the nearest nodes with greater centrality","volume":"517","author":"Luo","year":"2020","journal-title":"Inf. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"105626","DOI":"10.1016\/j.knosys.2020.105626","article-title":"Community detection in complex networks with an ambiguous structure using central node based link prediction","volume":"195","author":"Jiang","year":"2020","journal-title":"Knowl.-Based Syst."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"121552","DOI":"10.1016\/j.physa.2019.121552","article-title":"Communities detection in social network based on local edge centrality","volume":"531","author":"Li","year":"2019","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"122717","DOI":"10.1016\/j.physa.2019.122717","article-title":"A two-stage BFS local community detection algorithm based on node transfer similarity and Local Clustering Coefficient","volume":"537","author":"Liu","year":"2020","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Sheng, J., Liu, C., Chen, L., Wang, B., and Zhang, J. (2020). Research on Community Detection in Complex Networks Based on Internode Attraction. Entropy, 22.","DOI":"10.3390\/e22121383"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"100286","DOI":"10.1016\/j.cosrev.2020.100286","article-title":"Community detection in node-attributed social networks: A survey","volume":"37","author":"Chunaev","year":"2020","journal-title":"Comput. Sci. Rev."},{"key":"ref_39","unstructured":"Mercorio, F., Mezzanzanica, M., Moscato, V., Picariello, A., and Sperli, G. (2019). DICO: A Graph-DB Framework for Community Detection on Big Scholarly Data. IEEE Trans. Emerg. Top. Comput., 1."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"036106","DOI":"10.1103\/PhysRevE.76.036106","article-title":"Near linear time algorithm to detect community structures in large-scale networks","volume":"76","author":"Raghavan","year":"2007","journal-title":"Phys. Rev. E Stat. Nonlinear Soft Matter Phys."},{"key":"ref_41","first-page":"2803","article-title":"Learning from labeled and unlabeled data","volume":"3175","author":"Kothari","year":"2002","journal-title":"Int. Jt. Conf. Neural Netw."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.patrec.2017.12.018","article-title":"A community discovery algorithm based on boundary nodes and label propagation","volume":"109","author":"Gui","year":"2018","journal-title":"Pattern Recognit. Lett."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1750162","DOI":"10.1142\/S0217984917501627","article-title":"An improved label propagation algorithm based on node importance and random walk for community detection","volume":"31","author":"Ma","year":"2017","journal-title":"Mod. Phys. Lett. B"},{"key":"ref_44","first-page":"627581","article-title":"A Node Influence Based Label Propagation Algorithm for Community Detection in Networks","volume":"5","author":"Xing","year":"2014","journal-title":"Sci. World J."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2691","DOI":"10.1016\/j.physleta.2017.06.018","article-title":"Label propagation algorithm for community detection based on node importance and label influence","volume":"381","author":"Zhang","year":"2017","journal-title":"Phys. Lett. A"},{"key":"ref_46","first-page":"493","article-title":"A Stable Label Propagation Algorithm for Community Detection","volume":"4","author":"Zhao","year":"2013","journal-title":"J. Taiyuan Univ. Technol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"026129","DOI":"10.1103\/PhysRevE.80.026129","article-title":"Detecting network communities by propagating labels under constraints","volume":"80","author":"Barber","year":"2009","journal-title":"Phys. Rev. E Stat. Nonlinear Soft Matter Phys."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1493","DOI":"10.1016\/j.physa.2009.12.019","article-title":"Advanced modularity-specialized label propagation algorithm for detecting communities in networks","volume":"389","author":"Liu","year":"2012","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Xie, J., and Szymanski, B.K. (2011, January 22\u201324). Community Detection Using a Neighborhood Strength Driven Label Propagation Algorithm. Proceedings of the 2011 IEEE Network Science Workshop, IEEE Computer Society, West Point, NY, USA.","DOI":"10.1109\/NSW.2011.6004645"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Cordasco, G., and Gargano, L. (2011, January 15). Community detection via semi-synchronous label propagation algorithms. Proceedings of the IEEE International Workshop on Business Applications of Social Network Analysis, Bangalore, India.","DOI":"10.1109\/BASNA.2010.5730298"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1850011","DOI":"10.1142\/S0129183118500110","article-title":"LPA-CBD An Improved Label Propagation Algorithm Based on Community Belonging Degree for Community Detection","volume":"29","author":"Gui","year":"2018","journal-title":"Int. J. Mod. Phys. C"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"2011","DOI":"10.1088\/1367-2630\/12\/10\/103018","article-title":"Finding overlapping communities in networks by label propagation","volume":"12","author":"Gregory","year":"2010","journal-title":"New J. Phys."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Xie, J., Szymanski, B.K., and Liu, X. (2012, January 11). SLPA: Uncovering Overlapping Communities in Social Networks via a Speaker-Listener Interaction Dynamic Process. Proceedings of the IEEE International Conference on Data Mining Workshops, Vancouver, BC, Canada.","DOI":"10.1109\/ICDMW.2011.154"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1086\/jar.33.4.3629752","article-title":"An Information Flow Model for Conflict and Fission in Small Groups","volume":"33","author":"Zachary","year":"1977","journal-title":"J. Anthropol. Res."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1080\/0022250X.1972.9989806","article-title":"Factoring and weighting approaches to status scores and clique identification","volume":"2","author":"Bonacich","year":"1972","journal-title":"J. Math. Sociol."},{"key":"ref_56","first-page":"378","article-title":"Error and attack tolerance of complex networks","volume":"340","author":"Albert","year":"2004","journal-title":"Nature"},{"key":"ref_57","unstructured":"Burt, R.S., and Minor, M.J. (1983). Applied Network Analysis: A Methodological Introduction, SAGE Publications."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Li, P.Z., Huang, L., Wang, C.D., and Lai, J.H. (2019, January 4\u20138). EdMot: An Edge Enhancement Approach for Motif-Aware Community Detection. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Anchorage, AK, USA.","DOI":"10.1145\/3292500.3330882"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"09008","DOI":"10.1088\/1742-5468\/2005\/09\/P09008","article-title":"Comparing community structure identification","volume":"2005","author":"Danon","year":"2005","journal-title":"J. Stat. Mech."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Cherifi, H., Gaito, S., Mendes, J.F., Moro, E., and Rocha, L.M. (2020). Metrics Matter in Community Detection. Complex Networks and Their Applications VIII, Springer International Publishing.","DOI":"10.1007\/978-3-030-36687-2"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Chakraborty, T., Dalmia, A., Mukherjee, A., and Ganguly, N. (2017). Metrics for Community Analysis: A Survey. ACM Comput. Surv., 50.","DOI":"10.1145\/3091106"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"S186","DOI":"10.1098\/rsbl.2003.0057","article-title":"The emergent properties of a dolphin social network","volume":"270","author":"Lusseau","year":"2003","journal-title":"Proc. Biol. Sci."},{"key":"ref_63","unstructured":"Knuth, D.E. (1993). The Stanford GraphBase: A Platform for Combinatorial Computing, ACM."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1142\/S0219525903001067","article-title":"Community Structure in Jazz","volume":"6","author":"Gleiser","year":"2003","journal-title":"Adv. Complex Syst."},{"key":"ref_65","unstructured":"Glance, N., and Glance, N. (2005). The political blogosphere and the 2004 U.S. election: Divided they blog. Int. Workshop Link Discov., 36\u201343."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Rossi, R.A., and Ahmed, N.K. (2015, January 25\u201330). The network data repository with interactive graph analytics and visualization. Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, Austin, TX, USA.","DOI":"10.1609\/aaai.v29i1.9277"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1145\/1217299.1217301","article-title":"Graph evolution: Densification and shrinking diameters","volume":"1","author":"Leskovec","year":"2007","journal-title":"Acm Trans. Knowl. Discov. Data"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1073\/pnas.98.2.404","article-title":"The Structure of Scientific Collaboration Networks","volume":"98","author":"Newman","year":"2001","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"2741","DOI":"10.1016\/j.physa.2009.03.022","article-title":"A fast and efficient heuristic algorithm for detecting community structures in complex networks","volume":"388","author":"Chen","year":"2012","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1002\/j.1538-7305.1948.tb01338.x","article-title":"A mathematical theory of communication","volume":"27","author":"Shannon","year":"1948","journal-title":"Bell Syst. Tech. J."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"046110","DOI":"10.1103\/PhysRevE.78.046110","article-title":"Benchmark graphs for testing community detection algorithms","volume":"78","author":"Lancichinetti","year":"2008","journal-title":"Phys. Rev. E Stat. Nonlinear Soft Matter Phys."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/23\/5\/497\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:51:01Z","timestamp":1760161861000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/23\/5\/497"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,21]]},"references-count":71,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["e23050497"],"URL":"https:\/\/doi.org\/10.3390\/e23050497","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,21]]}}}