{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T18:02:31Z","timestamp":1770228151114,"version":"3.49.0"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2023,2,14]],"date-time":"2023-02-14T00:00:00Z","timestamp":1676332800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,2,14]],"date-time":"2023-02-14T00:00:00Z","timestamp":1676332800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61573266"],"award-info":[{"award-number":["61573266"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Basic Research Program of Shaanxi","award":["2021JM-133"],"award-info":[{"award-number":["2021JM-133"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Comp. Appl. Math."],"published-print":{"date-parts":[[2023,3]]},"DOI":"10.1007\/s40314-023-02221-0","type":"journal-article","created":{"date-parts":[[2023,2,14]],"date-time":"2023-02-14T23:28:44Z","timestamp":1676417324000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A novel feature selection using Markov blanket representative set and Particle Swarm Optimization algorithm"],"prefix":"10.1007","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8275-9322","authenticated-orcid":false,"given":"Liqin","family":"Sun","sequence":"first","affiliation":[]},{"given":"Youlong","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Tong","family":"Ning","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,2,14]]},"reference":[{"key":"2221_CR1","unstructured":"Aliferis CF, Tsamardinos I, Statnikov AR (2003) HITON: a novel markov blanket algorithm for optimal variable selection[C]. In: AMIA 2003, American medical informatics association annual symposium, Washington, DC, USA, November, 8\u201312, 2003. http:\/\/knowledge.amia.org\/amia55142-a2003a-1.616734\/t-001-1.619623\/f-001-1.619624\/a-004-1.620090\/a-005-1.620087"},{"issue":"1","key":"2221_CR2","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1016\/0004-3702(91)90084-W","volume":"48","author":"SK Andersen","year":"1991","unstructured":"Andersen SK (1991) Judea pearl, probabilistic reasoning in intelligent systems: networks of plausible inference[J]. Artif Intell 48(1):117\u2013124","journal-title":"Artif Intell"},{"issue":"1","key":"2221_CR3","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1007\/s13042-019-00932-7","volume":"11","author":"S Bakhshandeh","year":"2020","unstructured":"Bakhshandeh S, Azmi R, Teshnehlab M (2020) Symmetric uncertainty class-feature association map for feature selection in microarray dataset[J]. Int J Mach Learn Cybern 11(1):15\u201332","journal-title":"Int J Mach Learn Cybern"},{"key":"2221_CR4","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1016\/j.ins.2017.05.013","volume":"409","author":"J Che","year":"2017","unstructured":"Che J, Yang Y, Li L, Bai X, Zhang S, Deng C (2017) Maximum relevance minimum common redundancy feature selection for nonlinear data[J]. Inf Sci 409:68\u201386","journal-title":"Inf Sci"},{"issue":"1","key":"2221_CR5","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1109\/TCYB.2018.2864107","volume":"50","author":"L Cheng","year":"2020","unstructured":"Cheng L, Zheng Chutao W, Zhiwen SY, Hausan W (2020) Multitask Feature Selection by Graph-Clustered Feature Sharing[J]. IEEE Trans Cybern 50(1):74\u201386","journal-title":"IEEE Trans Cybern"},{"issue":"13","key":"2221_CR6","doi-asserted-by":"publisher","first-page":"1794","DOI":"10.1016\/j.patrec.2012.05.019","volume":"33","author":"AJ Ferreira","year":"2012","unstructured":"Ferreira AJ, Figueiredo MAT (2012) Efficient feature selection filters for high-dimensional data[J]. Pattern Recogn Lett 33(13):1794\u20131804","journal-title":"Pattern Recogn Lett"},{"key":"2221_CR7","doi-asserted-by":"publisher","first-page":"356","DOI":"10.1016\/j.eswa.2018.08.021","volume":"115","author":"J Gou","year":"2019","unstructured":"Gou J, Ma H, Ou W, Zeng S, Rao Y, Yang H (2019) A generalized mean distance-based k-nearest neighbor classifier[J]. Expert Syst Appl 115:356\u2013372","journal-title":"Expert Syst Appl"},{"key":"2221_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-84858-7","volume-title":"The elements of statistical learning: data mining, inference, and prediction[M]","author":"T Hastie","year":"2009","unstructured":"Hastie T, Tibshirani R, Friedman JH, Friedman JH (2009) The elements of statistical learning: data mining, inference, and prediction[M], 2nd edn. Springer, New York","edition":"2"},{"issue":"3\u20134","key":"2221_CR9","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1016\/j.mcm.2011.10.045","volume":"58","author":"J Jia","year":"2013","unstructured":"Jia J, Yang N, Zhang C, Yue A, Yang J, Zhu D (2013) Object-oriented feature selection of high spatial resolution images using an improved Relief algorithm[J]. Math Comput Model 58(3\u20134):619\u2013626","journal-title":"Math Comput Model"},{"issue":"3","key":"2221_CR10","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1162\/089976601300014493","volume":"13","author":"SS Keerthi","year":"2001","unstructured":"Keerthi SS, Shevade SK, Bhattacharyya C, Murthy KRK (2001) Improvements to Platt\u2019s SMO algorithm for SVM classifier design[J]. Neural Comput 13(3):637\u2013649","journal-title":"Neural Comput"},{"key":"2221_CR11","first-page":"1060","volume":"34","author":"UM Khaire","year":"2019","unstructured":"Khaire UM, Dhanalakshmi R (2019) Stability of feature selection algorithm: a review[J]. J King Saud Univ Comput Inf Sci 34:1060\u20131073","journal-title":"J King Saud Univ Comput Inf Sci"},{"key":"2221_CR12","unstructured":"Koller D, Sahami M (1996) Toward optimal feature selection[R]. Stanford InfoLab"},{"issue":"3","key":"2221_CR13","doi-asserted-by":"publisher","first-page":"211","DOI":"10.6029\/smartcr.2014.03.007","volume":"4","author":"V Kumar","year":"2014","unstructured":"Kumar V, Minz S (2014) Feature selection: a literature review[J]. SmartCR 4(3):211\u2013229","journal-title":"SmartCR"},{"key":"2221_CR14","doi-asserted-by":"publisher","first-page":"11854","DOI":"10.1109\/ACCESS.2019.2892063","volume":"7","author":"L Li","year":"2019","unstructured":"Li L, Zhang Y, Chen W, Bose SK, Zukerman M, Shen G (2019) Na\u00efve Bayes classifier-assisted least loaded routing for circuit-switched networks[J]. IEEE Access 7:11854\u201311867","journal-title":"IEEE Access"},{"issue":"3","key":"2221_CR15","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s00530-015-0494-1","volume":"23","author":"G Lianli","year":"2017","unstructured":"Lianli G, Jingkuan S, Xingyi L, Junming S, Jiajun L, Jie S (2017) Learning in high-dimensional multimedia data: the state of the art[J]. Multimedia Syst 23(3):303\u2013313","journal-title":"Multimedia Syst"},{"issue":"5","key":"2221_CR16","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1016\/S0167-4048(02)00514-X","volume":"21","author":"Y Liao","year":"2002","unstructured":"Liao Y, Vemuri VR (2002) Use of k-nearest neighbor classifier for intrusion detection[J]. Comput Secur 21(5):439\u2013448","journal-title":"Comput Secur"},{"key":"2221_CR17","unstructured":"Lichman M (2007) UCI machine learning repository[Online]. http:\/\/archive.ics.uci.edu\/ml"},{"key":"2221_CR18","unstructured":"Liu J, Wang G (2010) A hybrid feature selection method for data sets of thousands of variables[C]. In: 2010 2nd International conference on advanced computer control , vol 2, pp 288\u2013291"},{"key":"2221_CR19","volume-title":"Feature extraction and image processing for computer vision[M]","author":"M Nixon","year":"2019","unstructured":"Nixon M, Aguado A (2019) Feature extraction and image processing for computer vision[M]. Academic Press, New York"},{"key":"2221_CR20","unstructured":"Pedersen MEH (2010). Good parameters for particle swarm optimization[J]. Hvass Lab., Copenhagen, Denmark, Tech. Rep, HL1001, pp 1551\u20133203"},{"key":"2221_CR21","doi-asserted-by":"publisher","unstructured":"Pe\u00f1a JM, Bj\u00f6rkegren J, Tegn\u00e9r J (2005) Scalable, efficient and correct learning of markov boundaries under the faithfulness assumption. In: Symbolic and quantitative approaches to reasoning with uncertainty, 8th European Conference, ECSQARU 2005, Barcelona, Spain, July 6\u20138, 2005, Proceedings, pp 136\u2013147. https:\/\/doi.org\/10.1007\/1151865513","DOI":"10.1007\/1151865513"},{"issue":"2","key":"2221_CR22","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1016\/j.ijar.2006.06.008","volume":"45","author":"JM Pe\u00f1a","year":"2007","unstructured":"Pe\u00f1a JM, Nilsson R, Bj\u00f6rkegren J, Tegn\u00e9r J (2007) Towards scalable and data efficient learning of markov boundaries[J]. Int J Approx Reason 45(2):211\u2013232. https:\/\/doi.org\/10.1016\/j.ijar.2006.06.008","journal-title":"Int J Approx Reason"},{"issue":"1","key":"2221_CR23","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1007\/s11721-007-0002-0","volume":"1","author":"R Poli","year":"2007","unstructured":"Poli R, Kennedy J, Blackwell T (2007) Particle swarm optimization[J]. Swarm Intell 1(1):33\u201357","journal-title":"Swarm Intell"},{"issue":"5","key":"2221_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.17485\/ijst\/2017\/v10i5\/103233","volume":"10","author":"RM Rakholia","year":"2017","unstructured":"Rakholia RM, Saini JR (2017) Classification of Gujarati documents using Na\u00efve Bayes classifier[J]. Indian J Sci Technol 10(5):1\u20139","journal-title":"Indian J Sci Technol"},{"issue":"6062","key":"2221_CR25","doi-asserted-by":"publisher","first-page":"1518","DOI":"10.1126\/science.1205438","volume":"334","author":"DN Reshef","year":"2011","unstructured":"Reshef DN, Reshef YA, Finucane HK, Grossman SR, Gilean MV, Turnbaugh PJ, Lander ES, Michael M, Sabeti PC (2011) Detecting novel associations in large data sets[J]. Science 334(6062):1518","journal-title":"Science"},{"issue":"6062","key":"2221_CR26","doi-asserted-by":"publisher","first-page":"1518","DOI":"10.1126\/science.1205438","volume":"334","author":"DN Reshef","year":"2011","unstructured":"Reshef DN, Reshef YA, Finucane HK, Grossman SR, McVean G, Turnbaugh PJ et al (2011) Detecting novel associations in large data sets[J]. Science 334(6062):1518\u20131524","journal-title":"Science"},{"key":"2221_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2021.104210","volume":"100","author":"M Rostami","year":"2021","unstructured":"Rostami M, Berahmand K, Nasiri E, Forouzandeh S (2021) Review of swarm intelligence-based feature selection methods[J]. Eng Appl Artif Intell 100:104210","journal-title":"Eng Appl Artif Intell"},{"issue":"22","key":"2221_CR28","doi-asserted-by":"publisher","first-page":"24457","DOI":"10.1007\/s11042-016-4110-y","volume":"76","author":"VB Semwal","year":"2017","unstructured":"Semwal VB, Singha J, Sharma PK, Chauhan A, Behera B (2017) An optimized feature selection technique based on incremental feature analysis for bio-metric gait data classification[J]. Multimedia Tools Appl 76(22):24457\u201324475","journal-title":"Multimedia Tools Appl"},{"key":"2221_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2019.105302","volume":"188","author":"L Siying","year":"2020","unstructured":"Siying L, Runtong Z, Xiaopu S, Weizi L (2020) Analysis for warning factors of type 2 diabetes mellitus complications with Markov blanket based on a Bayesian network model[J]. Comput Methods Programs Biomed 188:105302","journal-title":"Comput Methods Programs Biomed"},{"key":"2221_CR30","first-page":"9573","volume":"9","author":"XF Song","year":"2021","unstructured":"Song XF, Zhang Y, Gong DW, Gao XZ (2021) A fast hybrid feature selection based on correlation-guided clustering and particle swarm optimization for high-dimensional data[J]. IEEE Trans Cybern 9:9573\u20139586","journal-title":"IEEE Trans Cybern"},{"issue":"1","key":"2221_CR31","first-page":"499","volume":"14","author":"A Statnikov","year":"2013","unstructured":"Statnikov A, Lytkin NI, Lemeire J, Aliferis CF (2013) Algorithms for discovery of multiple markov boundaries[J]. J Mach Learn Res Jmlr 14(1):499\u2013566","journal-title":"J Mach Learn Res Jmlr"},{"key":"2221_CR32","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1016\/j.future.2018.05.060","volume":"89","author":"GL Sun","year":"2018","unstructured":"Sun GL, Li JB, Dai J et al (2018) Feature selection for IoT based on maximal information coefficient[J]. Feature Gen Comput Syst 89:606\u2013616","journal-title":"Feature Gen Comput Syst"},{"issue":"3","key":"2221_CR33","doi-asserted-by":"publisher","first-page":"1269","DOI":"10.1007\/s10115-019-01335-4","volume":"61","author":"A Tharwat","year":"2019","unstructured":"Tharwat A (2019) Parameter investigation of support vector machine classifier with kernel functions[J]. Knowl Inf Syst 61(3):1269\u20131302","journal-title":"Knowl Inf Syst"},{"key":"2221_CR34","unstructured":"Tsamardinos I, Aliferis CF (2003) Towards principled feature selection: relevancy, filters and wrappers[C]. In: Proceedings of the ninth international workshop on artificial intelligence and statistics, AISTATS 2003, Key West, Florida, USA, January, 3\u20136, 2003. http:\/\/research.microsoft.com\/enus\/um\/cambridge\/events\/aistats2003\/proceedings\/133.pdf"},{"key":"2221_CR35","unstructured":"Tsamardinos I, Aliferis CF, Statnikov AR (2003) Algorithms for large scale markov blanket discovery[C]. In: Proceedings of the sixteenth international Florida artificial intelligence research society conference, May, 12\u201314, 2003, St. Augustine, Florida, USA, pp 376\u2013381. http:\/\/www.aaai.org\/Library\/FLAIRS\/2003\/flairs03--073.php"},{"key":"2221_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113873","volume":"164","author":"M Tubishat","year":"2021","unstructured":"Tubishat M, Ja\u2019afar S, Alswaitti M, Mirjalili S, Idris N, Ismail MA, Omar MS (2021) Dynamic salp swarm algorithm for feature selection[J]. Expert Syst Appl 164:113873","journal-title":"Expert Syst Appl"},{"issue":"1","key":"2221_CR37","first-page":"3","volume":"19","author":"B Venkatesh","year":"2019","unstructured":"Venkatesh B, Anuradha J (2019) A review of feature selection and its methods[J]. Cybern Inf Technol 19(1):3\u201326","journal-title":"Cybern Inf Technol"},{"issue":"1","key":"2221_CR38","doi-asserted-by":"publisher","first-page":"151","DOI":"10.21629\/JSEE.2017.01.17","volume":"28","author":"Y Wang","year":"2017","unstructured":"Wang Y, Wang J, Liao H, Chen H (2017) Unsupervised feature selection based on Markov blanket and particle swarm optimization[J]. J Syst Eng Electron 28(1):151\u2013161","journal-title":"J Syst Eng Electron"},{"key":"2221_CR39","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1016\/j.patcog.2016.08.011","volume":"61","author":"Y Wang","year":"2017","unstructured":"Wang Y, Wang J, Liao H, Chen H (2017) An efficient semi-supervised representatives feature selection algorithm based on information theory[J]. Pattern Recogn 61:511\u2013523","journal-title":"Pattern Recogn"},{"issue":"10","key":"2221_CR40","doi-asserted-by":"publisher","first-page":"5019","DOI":"10.1109\/TIP.2017.2726188","volume":"26","author":"R Wang","year":"2017","unstructured":"Wang R, Nie F, Hong R, Chang X, Yang X, Yu W (2017) Fast and orthogonal locality preserving projections for dimensionality reduction[J]. IEEE Trans Image Process 26(10):5019\u20135030","journal-title":"IEEE Trans Image Process"},{"key":"2221_CR41","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1016\/j.ins.2019.09.010","volume":"509","author":"H Wang","year":"2020","unstructured":"Wang H, Ling Z, Yu K, Wu X (2020) Towards efficient and effective discovery of Markov blankets for feature selection[J]. Inf Sci 509:227\u2013242","journal-title":"Inf Sci"},{"issue":"12","key":"2221_CR42","doi-asserted-by":"publisher","first-page":"4983","DOI":"10.1109\/TCYB.2019.2940509","volume":"50","author":"X Wu","year":"2019","unstructured":"Wu X, Jiang B, Yu K, Chen H (2019) Accurate markov boundary discovery for causal feature selection[J]. IEEE Trans Cybern 50(12):4983\u20134996","journal-title":"IEEE Trans Cybern"},{"key":"2221_CR43","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1007\/978-981-10-5041-1_57","volume-title":"Advanced multimedia and ubiquitous engineering","author":"S Xu","year":"2017","unstructured":"Xu S, Li Y, Wang Z (2017) Bayesian multinomial Na\u00efve Bayes classifier to text classification[M]. Advanced multimedia and ubiquitous engineering. Springer, Singapore, pp 347\u2013352"},{"issue":"4","key":"2221_CR44","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1109\/TEVC.2015.2504420","volume":"20","author":"B Xue","year":"2015","unstructured":"Xue B, Zhang M, Browne WN, Yao X (2015) A survey on evolutionary computation approaches to feature selection[J]. IEEE Trans Evol Comput 20(4):606\u2013626","journal-title":"IEEE Trans Evol Comput"},{"key":"2221_CR45","unstructured":"Yang Y, Li J, Yang Y (2015) The research of the fast SVM classifier method[C]. In: 2015 12th international computer conference on wavelet active media technology and information processing (ICCWAMTIP), p 121124"},{"key":"2221_CR46","doi-asserted-by":"crossref","unstructured":"Yu K, Wu X, Zhang Z, Mu Y, Wang H, Ding W (2013) Markov blanket feature selection with non-faithful data distributions[C]. In: 2013 IEEE 13th International conference on data mining, pp 857\u2013866","DOI":"10.1109\/ICDM.2013.154"},{"issue":"6","key":"2221_CR47","doi-asserted-by":"publisher","first-page":"1263","DOI":"10.1109\/TCYB.2015.2443857","volume":"46","author":"Z Yu","year":"2015","unstructured":"Yu Z, Chen H, Liu J, You J, Leung H, Han G (2015) Hybrid $$ k $$-nearest neighbor classifier[J]. IEEE Trans Cybern 46(6):1263\u20131275","journal-title":"IEEE Trans Cybern"},{"issue":"11","key":"2221_CR48","doi-asserted-by":"publisher","first-page":"2775","DOI":"10.1109\/TNNLS.2016.2602365","volume":"28","author":"K Yu","year":"2017","unstructured":"Yu K, Wu X, Ding W, Mu Y, Wang H (2017) Markov blanket feature selection using representative sets[J]. IEEE Trans Neural Netw Learn Syst 28(11):2775\u20132788","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"2221_CR49","unstructured":"Zhao Z, Morstatter F, Sharma S, Anand A, Liu H (2016) Advancing feature selection research-asu feature selection repository. http:\/\/citeseerx.ist.psu.edu\/viewdoc\/summary?doi=10.1.1.642.5862"},{"issue":"5","key":"2221_CR50","doi-asserted-by":"publisher","first-page":"5457","DOI":"10.1007\/s10489-021-02524-x","volume":"52","author":"H Zhou","year":"2022","unstructured":"Zhou H, Wang X, Zhu R (2022) Feature selection based on mutual information with correlation coefficient[J]. Appl Intell 52(5):5457\u20135474","journal-title":"Appl Intell"},{"issue":"11","key":"2221_CR51","doi-asserted-by":"publisher","first-page":"3236","DOI":"10.1016\/j.patcog.2007.02.007","volume":"40","author":"Z Zhu","year":"2007","unstructured":"Zhu Z, Ong YS, Dash M (2007) Markov blanket embedded genetic algorithm for gene selection[J]. Pattern Recogn 40(11):3236\u20133248","journal-title":"Pattern Recogn"}],"container-title":["Computational and Applied Mathematics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40314-023-02221-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40314-023-02221-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40314-023-02221-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,9]],"date-time":"2023-03-09T11:18:21Z","timestamp":1678360701000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40314-023-02221-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,14]]},"references-count":51,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,3]]}},"alternative-id":["2221"],"URL":"https:\/\/doi.org\/10.1007\/s40314-023-02221-0","relation":{},"ISSN":["2238-3603","1807-0302"],"issn-type":[{"value":"2238-3603","type":"print"},{"value":"1807-0302","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,14]]},"assertion":[{"value":"28 July 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 December 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 January 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 February 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"81"}}