{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T21:33:20Z","timestamp":1774474400891,"version":"3.50.1"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2025,1,21]],"date-time":"2025-01-21T00:00:00Z","timestamp":1737417600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,21]],"date-time":"2025-01-21T00:00:00Z","timestamp":1737417600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1007\/s10586-024-04927-0","type":"journal-article","created":{"date-parts":[[2025,1,21]],"date-time":"2025-01-21T06:29:35Z","timestamp":1737440975000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["V-shaped and S-shaped binary artificial protozoa optimizer (APO) algorithm for wrapper feature selection on biological data"],"prefix":"10.1007","volume":"28","author":[{"given":"Amir","family":"Seyyedabbasi","sequence":"first","affiliation":[]},{"given":"Gang","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Hisham A.","family":"Shehadeh","sequence":"additional","affiliation":[]},{"given":"Xiaopeng","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Peren Jerfi","family":"Canatalay","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,1,21]]},"reference":[{"key":"4927_CR1","doi-asserted-by":"publisher","DOI":"10.1093\/oso\/9780195131581.001.0001","volume-title":"Swarm Intelligence: From Natural to Artificial Systems","author":"E Bonabeau","year":"1999","unstructured":"Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, Oxford (1999)"},{"key":"4927_CR2","doi-asserted-by":"crossref","unstructured":"Seyyedabbasi, A., Tareq Tareq, W.Z., Bacanin, N.: An effective hybrid metaheuristic algorithm for solving global optimization algorithms. Multimed. Tools Appl. 1\u201336 (2024)","DOI":"10.1007\/s11042-024-19437-9"},{"key":"4927_CR3","doi-asserted-by":"crossref","unstructured":"Wang, X., Sn\u00e1\u0161el, V., Mirjalili, S., Pan, J.S., Kong, L., Shehadeh, H.A.: Artificial protozoa optimizer (APO): a novel bio-inspired metaheuristic algorithm for engineering optimization. Knowl. Based Syst. 111737 (2024)","DOI":"10.1016\/j.knosys.2024.111737"},{"key":"4927_CR4","doi-asserted-by":"crossref","unstructured":"Jia, H., Wen, Q., Wang, Y., Mirjalili, S.: Catch fish optimization algorithm: a new human behavior algorithm for solving clustering problems. Clust. Comput. 1\u201338 (2024)","DOI":"10.1007\/s10586-024-04618-w"},{"key":"4927_CR5","doi-asserted-by":"publisher","first-page":"1361","DOI":"10.11591\/ijeecs.v35.i3.pp1361-1369","volume":"35","author":"W Aribowo","year":"2024","unstructured":"Aribowo, W., Shehadeh, H.A.: Novel modified Chernobyl disaster optimizer for controlling DC motor. Indonesian J. Electr. Eng. Comput. Sci. 35, 1361\u20131369 (2024)","journal-title":"Indonesian J. Electr. Eng. Comput. Sci."},{"key":"4927_CR6","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1007\/978-3-319-93025-1_4","volume":"780","author":"S Mirjalili","year":"2019","unstructured":"Mirjalili, S.: Evolutionary algorithms and neural networks. Stud. Comput. Intell. 780, 43\u201353 (2019)","journal-title":"Stud. Comput. Intell."},{"issue":"4","key":"4927_CR7","doi-asserted-by":"publisher","first-page":"2627","DOI":"10.1007\/s00366-022-01604-x","volume":"39","author":"A Seyyedabbasi","year":"2023","unstructured":"Seyyedabbasi, A., Kiani, F.: Sand Cat swarm optimization: a nature-inspired algorithm to solve global optimization problems. Eng. Comput. 39(4), 2627\u20132651 (2023)","journal-title":"Eng. Comput."},{"key":"4927_CR8","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.swevo.2013.06.001","volume":"13","author":"I Fister","year":"2013","unstructured":"Fister, I., Fister, I., Jr., Yang, X.S., Brest, J.: A comprehensive review of firefly algorithms. Swarm Evol. Comput. 13, 34\u201346 (2013)","journal-title":"Swarm Evol. Comput."},{"issue":"2","key":"4927_CR9","doi-asserted-by":"publisher","first-page":"04015055","DOI":"10.1061\/(ASCE)IR.1943-4774.0000963","volume":"142","author":"HR Asgari","year":"2016","unstructured":"Asgari, H.R., Bozorg Haddad, O., Pazoki, M., Lo\u00e1iciga, H.A.: Weed optimization algorithm for optimal reservoir operation. J. Irrig. Drain. Eng. 142(2), 04015055 (2016)","journal-title":"J. Irrig. Drain. Eng."},{"issue":"3","key":"4927_CR10","first-page":"2023","volume":"15","author":"HA Shehadeh","year":"2023","unstructured":"Shehadeh, H.A., Jebril, I.H., Jaradat, G.M., Ibrahim, D., Sihwail, R., Al Hamad, H., et al.: Intelligent diagnostic prediction and classification system for Parkinson\u2019s disease by incorporating sperm swarm optimization (SSO) and density-based feature selection methods. Int. J. Adv. Soft Comput. Appl. 15(3), 2023 (2023)","journal-title":"Int. J. Adv. Soft Comput. Appl."},{"key":"4927_CR11","doi-asserted-by":"crossref","unstructured":"Esmin, A.A.A., Lambert-Torres, G., Alvarenga, G.B.: Hybrid evolutionary algorithm based on PSO and GA mutation. In: 2006 Sixth International Conference on Hybrid Intelligent Systems (HIS\u201906), pp. 57\u201357. IEEE, Rio de Janeiro (2006)","DOI":"10.1109\/HIS.2006.264940"},{"key":"4927_CR12","doi-asserted-by":"crossref","unstructured":"Niu, B., Li, L.: A novel PSO-DE-based hybrid algorithm for global optimization. In: International Conference on Intelligent Computing, pp. 156\u2013163. Springer, Berlin (2008)","DOI":"10.1007\/978-3-540-85984-0_20"},{"key":"4927_CR13","first-page":"2008","volume":"1\u201311","author":"N Holden","year":"2008","unstructured":"Holden, N., Freitas, A.A.: A hybrid PSO\/ACO algorithm for discovering classification rules in data mining. J. Artif. Evol. Appl. 1\u201311, 2008 (2008)","journal-title":"J. Artif. Evol. Appl."},{"key":"4927_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2023.100559","volume":"49","author":"M Nssibi","year":"2023","unstructured":"Nssibi, M., Manita, G., Korbaa, O.: Advances in nature-inspired metaheuristic optimization for feature selection problem: a comprehensive survey. Comput. Sci. Rev. 49, 100559 (2023)","journal-title":"Comput. Sci. Rev."},{"key":"4927_CR15","doi-asserted-by":"crossref","unstructured":"Neggaz, N., Seyyedabbasi, A., Hussien, A.G., Rahim, M., Be\u015fkirli, M.: Optimal nodes localization in wireless sensor networks using Nutcracker optimizer algorithms: Istanbul Area. IEEE Access (2024)","DOI":"10.1109\/ACCESS.2024.3400370"},{"issue":"6","key":"4927_CR16","doi-asserted-by":"publisher","first-page":"816","DOI":"10.1007\/s42979-023-02238-6","volume":"4","author":"N Gupta","year":"2023","unstructured":"Gupta, N., Kumar, S., Gupta, V., Vijh, S.: Novel automatic approach using modified differential evaluation to software module clustering problem. SN Comput. Sci. 4(6), 816 (2023)","journal-title":"SN Comput. Sci."},{"key":"4927_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121735","volume":"238","author":"AA Chaves","year":"2024","unstructured":"Chaves, A.A., Vianna, B.L., da Silva, T.T., Schenekemberg, C.M.: A parallel branch-and-cut and an adaptive metaheuristic to solve the family traveling salesman problem. Expert Syst. Appl. 238, 121735 (2024)","journal-title":"Expert Syst. Appl."},{"key":"4927_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2020.106946","volume":"151","author":"M Abdel-Basset","year":"2021","unstructured":"Abdel-Basset, M., Mohamed, R., Mirjalili, S.: A binary equilibrium optimization algorithm for 0\u20131 knapsack problems. Comput. Ind. Eng. 151, 106946 (2021)","journal-title":"Comput. Ind. Eng."},{"key":"4927_CR19","doi-asserted-by":"publisher","first-page":"310","DOI":"10.3390\/biomimetics8030310","volume":"8","author":"A Seyyedabbasi","year":"2023","unstructured":"Seyyedabbasi, A.: Binary sand cat swarm optimization algorithm for wrapper feature selection on biological data. Biomimetics 8, 310 (2023). https:\/\/doi.org\/10.3390\/biomimetics8030310","journal-title":"Biomimetics"},{"key":"4927_CR20","doi-asserted-by":"publisher","first-page":"1155","DOI":"10.1007\/s12065-022-00726-x","volume":"16","author":"D Chauhan","year":"2023","unstructured":"Chauhan, D., Yadav, A.: Binary artificial electric field algorithm. Evol. Intell. 16, 1155\u20131183 (2023). https:\/\/doi.org\/10.1007\/s12065-022-00726-x","journal-title":"Evol. Intell."},{"key":"4927_CR21","doi-asserted-by":"publisher","first-page":"2633","DOI":"10.1007\/s13042-023-01788-8","volume":"14","author":"L Sun","year":"2023","unstructured":"Sun, L., Si, S., Ding, W., et al.: BSSFS: binary sparrow search algorithm for feature selection. Int. J. Mach. Learn. Cyber. 14, 2633\u20132657 (2023). https:\/\/doi.org\/10.1007\/s13042-023-01788-8","journal-title":"Int. J. Mach. Learn. Cyber."},{"key":"4927_CR22","doi-asserted-by":"publisher","first-page":"1130","DOI":"10.3390\/electronics8101130","volume":"8","author":"J Too","year":"2019","unstructured":"Too, J., Abdullah, A.R., Mohd Saad, N.: A new quadratic binary Harris Hawk optimization for feature selection. Electronics 8, 1130 (2019). https:\/\/doi.org\/10.3390\/electronics8101130","journal-title":"Electronics"},{"issue":"16","key":"4927_CR23","doi-asserted-by":"publisher","first-page":"11395","DOI":"10.1007\/s00500-023-08274-x","volume":"27","author":"M Xu","year":"2023","unstructured":"Xu, M., Song, Q., Xi, M., Zhou, Z.: Binary arithmetic optimization algorithm for feature selection. Soft. Comput. 27(16), 11395\u201311429 (2023)","journal-title":"Soft. Comput."},{"issue":"2","key":"4927_CR24","doi-asserted-by":"publisher","first-page":"316","DOI":"10.1016\/j.jksuci.2019.11.007","volume":"34","author":"H Hichem","year":"2022","unstructured":"Hichem, H., Elkamel, M., Rafik, M., Mesaaoud, M.T., Ouahiba, C.: A new binary grasshopper optimization algorithm for feature selection problem. J. King Saud Univ. Comput. Inf. Sci. 34(2), 316\u2013328 (2022)","journal-title":"J. King Saud Univ. Comput. Inf. Sci."},{"issue":"10","key":"4927_CR25","doi-asserted-by":"publisher","first-page":"1821","DOI":"10.3390\/math8101821","volume":"8","author":"AG Hussien","year":"2020","unstructured":"Hussien, A.G., Oliva, D., Houssein, E.H., Juan, A.A., Yu, X.: Binary whale optimization algorithm for dimensionality reduction. Mathematics 8(10), 1821 (2020)","journal-title":"Mathematics"},{"issue":"9","key":"4927_CR26","doi-asserted-by":"publisher","first-page":"1161","DOI":"10.1016\/j.pnsc.2008.03.018","volume":"18","author":"S Lee","year":"2008","unstructured":"Lee, S., Soak, S., Oh, S., Pedrycz, W., Jeon, M.: Modified binary particle swarm optimization. Prog. Nat. Sci. 18(9), 1161\u20131166 (2008)","journal-title":"Prog. Nat. Sci."},{"key":"4927_CR27","doi-asserted-by":"publisher","first-page":"663","DOI":"10.1007\/s00521-013-1525-5","volume":"25","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili, S., Mirjalili, S.M., Yang, X.S.: Binary bat algorithm. Neural Comput. Appl. 25, 663\u2013681 (2014)","journal-title":"Neural Comput. Appl."},{"key":"4927_CR28","unstructured":"Tahir, M., Tubaishat, A., Al-Obeidat, F., Shah, B., Halim, Z., Waqas, M.: A novel binary chaotic genetic algorithm for feature selection and its utility in affective computing and healthcare. Neural Comput. Appl. 1\u201322 (2022)"},{"issue":"03","key":"4927_CR29","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1142\/S0218488523500241","volume":"31","author":"RK Eluri","year":"2023","unstructured":"Eluri, R.K., Devarakonda, N.: Chaotic binary pelican optimization algorithm for feature selection. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 31(03), 497\u2013530 (2023). https:\/\/doi.org\/10.1142\/S0218488523500241","journal-title":"Int. J. Uncertain. Fuzziness Knowl. Based Syst."},{"key":"4927_CR30","doi-asserted-by":"publisher","first-page":"26679","DOI":"10.1007\/s11042-023-15467-x","volume":"82","author":"RK Eluri","year":"2023","unstructured":"Eluri, R.K., Devarakonda, N.: Feature selection with a binary flamingo search algorithm and a genetic algorithm. Multimed. Tools Appl. 82, 26679\u201326730 (2023). https:\/\/doi.org\/10.1007\/s11042-023-15467-x","journal-title":"Multimed. Tools Appl."},{"key":"4927_CR31","doi-asserted-by":"publisher","unstructured":"Krishna, E.R., Devarakonda, N., Al-Shamri, M.Y.H., Revathi, D.: A novel hybrid clustering analysis based on combination of K-means and PSO algorithm. In: Jacob, I.J., Kolandapalayam Shanmugam, S., Bestak, R. (eds.) Data Intelligence and Cognitive Informatics. Algorithms for Intelligent Systems. Springer, Singapore (2022). https:\/\/doi.org\/10.1007\/978-981-16-6460-1_10","DOI":"10.1007\/978-981-16-6460-1_10"},{"key":"4927_CR32","doi-asserted-by":"crossref","unstructured":"Krishna, E.R., Devarakonda, N. (2023). Feature selection method based on GWO-PSO for coronary artery disease classification. In: 2023 Third International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), pp. 1\u20138. IEEE","DOI":"10.1109\/ICAECT57570.2023.10118351"},{"issue":"27","key":"4927_CR33","doi-asserted-by":"publisher","first-page":"20013","DOI":"10.1007\/s00521-023-08812-6","volume":"35","author":"MA Awadallah","year":"2023","unstructured":"Awadallah, M.A., Braik, M.S., Al-Betar, M.A., Abu Doush, I.: An enhanced binary artificial rabbits optimization for feature selection in medical diagnosis. Neural Comput. Appl. 35(27), 20013\u201320068 (2023)","journal-title":"Neural Comput. Appl."},{"issue":"23","key":"4927_CR34","doi-asserted-by":"publisher","first-page":"17833","DOI":"10.1007\/s00500-023-09062-3","volume":"27","author":"MS Braik","year":"2023","unstructured":"Braik, M.S., Hammouri, A.I., Awadallah, M.A., Al-Betar, M.A., Alzubi, O.A.: Improved versions of snake optimizer for feature selection in medical diagnosis: a real case COVID-19. Soft. Comput. 27(23), 17833\u201317865 (2023)","journal-title":"Soft. Comput."},{"key":"4927_CR35","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1016\/j.neucom.2023.02.010","volume":"532","author":"H Su","year":"2023","unstructured":"Su, H., Zhao, D., Heidari, A.A., Liu, L., Zhang, X., Mafarja, M., Chen, H.: RIME: A physics-based optimization. Neurocomputing 532, 183\u2013214 (2023)","journal-title":"Neurocomputing"},{"key":"4927_CR36","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/j.knosys.2018.08.030","volume":"163","author":"W Zhao","year":"2019","unstructured":"Zhao, W., Wang, L., Zhang, Z.: Atom search optimization and its application to solve a hydrogeologic parameter estimation problem. Knowl. Based Syst. 163, 283\u2013304 (2019)","journal-title":"Knowl. Based Syst."},{"issue":"15","key":"4927_CR37","doi-asserted-by":"publisher","first-page":"10733","DOI":"10.1007\/s00521-023-08261-1","volume":"35","author":"HA Shehadeh","year":"2023","unstructured":"Shehadeh, H.A.: Chernobyl disaster optimizer (CDO): a novel meta-heuristic method for global optimization. Neural Comput. Appl. 35(15), 10733\u201310749 (2023)","journal-title":"Neural Comput. Appl."},{"key":"4927_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.122147","volume":"238","author":"ESM El-Kenawy","year":"2024","unstructured":"El-Kenawy, E.S.M., Khodadadi, N., Mirjalili, S., Abdelhamid, A.A., Eid, M.M., Ibrahim, A.: Greylag goose optimization: nature-inspired optimization algorithm. Expert Syst. Appl. 238, 122147 (2024)","journal-title":"Expert Syst. Appl."},{"issue":"3","key":"4927_CR39","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1007\/s10462-023-10680-4","volume":"57","author":"MA Al-Betar","year":"2024","unstructured":"Al-Betar, M.A., Awadallah, M.A., Braik, M.S., Makhadmeh, S., Doush, I.A.: Elk herd optimizer: a novel nature-inspired metaheuristic algorithm. Artif. Intell. Rev. 57(3), 48 (2024)","journal-title":"Artif. Intell. Rev."},{"key":"4927_CR40","doi-asserted-by":"crossref","unstructured":"Mohammadzadeh, A., Mirjalili, S.: Eel and grouper optimizer: a nature-inspired optimization algorithm. Clust. Comput. 1\u201342 (2024)","DOI":"10.1007\/s10586-024-04545-w"},{"issue":"1","key":"4927_CR41","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1038\/scientificamerican0792-66","volume":"267","author":"JH Holland","year":"1992","unstructured":"Holland, J.H.: Genetic algorithms. Sci. Am. 267(1), 66\u201373 (1992)","journal-title":"Sci. Am."},{"key":"4927_CR42","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn, R., Price, K.: Differential evolution\u2014a simple and efficient heuristic for global optimization over continuous spaces. J. Glob. Optim. 11, 341\u2013359 (1997)","journal-title":"J. Glob. Optim."},{"issue":"1","key":"4927_CR43","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1109\/4235.585893","volume":"1","author":"DH Wolpert","year":"1997","unstructured":"Wolpert, D.H., Macready, W.G.: No free lunch theorems for optimization. IEEE Trans. Evol. Comput. 1(1), 67\u201382 (1997)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"4927_CR44","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.swevo.2012.09.002","volume":"9","author":"S Mirjalili","year":"2013","unstructured":"Mirjalili, S., Lewis, A.: S-shaped versus V-shaped transfer functions for binary particle swarm optimization. Swarm Evol. Comput. 9, 1\u201314 (2013)","journal-title":"Swarm Evol. Comput."},{"key":"4927_CR45","unstructured":"Dua, D., Graff, C.: Machine learning repository. University of California, Irvine, School of Information and Computer Sciences (2017). Available online at: http:\/\/archive.ics.uci.edu\/ml"},{"issue":"6","key":"4927_CR46","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3136625","volume":"50","author":"J Li","year":"2017","unstructured":"Li, J., Cheng, K., Wang, S., Morstatter, F., Trevino, R.P., Tang, J., Liu, H.: Feature selection: A data perspective. ACM Comput. Surv. (CSUR) 50(6), 1\u201345 (2017)","journal-title":"ACM Comput. Surv. (CSUR)"},{"issue":"3","key":"4927_CR47","doi-asserted-by":"publisher","first-page":"2844","DOI":"10.1007\/s11227-020-03378-9","volume":"77","author":"J Too","year":"2021","unstructured":"Too, J., Abdullah, A.R.: A new and fast rival genetic algorithm for feature selection. J. Supercomput. 77(3), 2844\u20132874 (2021)","journal-title":"J. Supercomput."},{"key":"4927_CR48","unstructured":"Too, J., Abdullah, A.R., Mohd Saad, N.: A new co-evolution binary particle swarm optimization with multiple inertia weight strategy for feature selection"},{"issue":"6","key":"4927_CR49","first-page":"2361","volume":"10","author":"RA Khurma","year":"2023","unstructured":"Khurma, R.A., Alhenawi, E., Braik, M., Hashim, F.A., Chhabra, A., Castillo, P.A.: A bio-medical snake optimizer system driven by logarithmic surviving global search for optimizing feature selection and its application for disorder recognition. J. Comput. Des. Eng. 10(6), 2361\u20132383 (2023)","journal-title":"J. Comput. Des. Eng."}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-024-04927-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-024-04927-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-024-04927-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,20]],"date-time":"2025-05-20T21:52:06Z","timestamp":1747777926000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-024-04927-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,21]]},"references-count":49,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,6]]}},"alternative-id":["4927"],"URL":"https:\/\/doi.org\/10.1007\/s10586-024-04927-0","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,21]]},"assertion":[{"value":"16 July 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 November 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 November 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 January 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All authors have no conflict of interest to report.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"163"}}