{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T21:11:35Z","timestamp":1758057095215,"version":"3.44.0"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"14","license":[{"start":{"date-parts":[[2025,9,15]],"date-time":"2025-09-15T00:00:00Z","timestamp":1757894400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,15]],"date-time":"2025-09-15T00:00:00Z","timestamp":1757894400000},"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":["J Supercomput"],"DOI":"10.1007\/s11227-025-07518-x","type":"journal-article","created":{"date-parts":[[2025,9,15]],"date-time":"2025-09-15T17:52:30Z","timestamp":1757958750000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Prototype reduction method based on accelerated binary bare-bone particle swarm optimization for instance-based classifiers"],"prefix":"10.1007","volume":"81","author":[{"given":"Xing","family":"Huang","sequence":"first","affiliation":[]},{"given":"Kexin","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Junnan","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,9,15]]},"reference":[{"issue":"9","key":"7518_CR1","doi-asserted-by":"publisher","first-page":"2143","DOI":"10.1109\/TFUZZ.2019.2930942","volume":"28","author":"S Maldonado","year":"2020","unstructured":"Maldonado S, Merig\u00f3 J, Miranda J (2020) IOWA-SVM: a density-based weighting strategy for SVM classification via OWA operators. IEEE Trans Fuzzy Syst 28(9):2143\u20132150","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"6","key":"7518_CR2","first-page":"5563","volume":"35","author":"C Gong","year":"2023","unstructured":"Gong C, Su ZG, Wang PH, Wang Q, You Y (2023) A sparse reconstructive evidential K-nearest neighbor classifier for high-dimensional data. IEEE Trans Knowl Data Eng 35(6):5563\u20135576","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"7518_CR3","doi-asserted-by":"publisher","first-page":"116529","DOI":"10.1016\/j.eswa.2022.116529","volume":"194","author":"J Gou","year":"2022","unstructured":"Gou J, Sun L, Du L, Ma H, Xiong T, Ou W, Zhan Y (2022) A representation coefficient-based k-nearest centroid neighbor classifier. Expert Syst Appl 194:116529","journal-title":"Expert Syst Appl"},{"key":"7518_CR4","doi-asserted-by":"publisher","first-page":"117159","DOI":"10.1016\/j.eswa.2022.117159","volume":"201","author":"Y Ma","year":"2022","unstructured":"Ma Y, Huang R, Yan M, Li G, Wang T (2022) Attention-based Local mean K-nearest centroid neighbor classifier. Expert Syst Appl 201:117159","journal-title":"Expert Syst Appl"},{"key":"7518_CR5","doi-asserted-by":"publisher","first-page":"109010","DOI":"10.1016\/j.buildenv.2022.109010","volume":"216","author":"L Gao","year":"2022","unstructured":"Gao L, Li D, Liu X, Liu G (2022) Enhanced chiller faults detection and isolation method based on independent component analysis and k-nearest neighbors classifier. Build Environ 216:109010","journal-title":"Build Environ"},{"key":"7518_CR6","doi-asserted-by":"publisher","first-page":"1920","DOI":"10.1016\/j.istruc.2022.10.019","volume":"45","author":"A Ghiasi","year":"2022","unstructured":"Ghiasi A, Ng CT, Sheikh AH (2022) Damage detection of in-service steel railway bridges using a fine k-nearest neighbor machine learning classifier. Structures 45:1920\u20131935","journal-title":"Structures"},{"key":"7518_CR7","doi-asserted-by":"publisher","first-page":"120922","DOI":"10.1016\/j.eswa.2023.120922","volume":"232","author":"D Sisodia","year":"2023","unstructured":"Sisodia D, Sisodia DS (2023) A transfer learning framework towards identifying behavioral changes of fraudulent publishers in pay-per-click model of online advertising for click fraud detection. Expert Syst Appl 232:120922","journal-title":"Expert Syst Appl"},{"key":"7518_CR8","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1016\/j.neucom.2014.01.037","volume":"138","author":"F Li","year":"2014","unstructured":"Li F, Wang J, Tang B, Tian D (2014) Life grade recognition method based on supervised uncorrelated orthogonal locality preserving projection and K-nearest neighbor classifier. Neurocomputing 138:271\u2013282","journal-title":"Neurocomputing"},{"issue":"6","key":"7518_CR9","doi-asserted-by":"publisher","first-page":"1981","DOI":"10.1109\/TFUZZ.2022.3216990","volume":"31","author":"X Zhang","year":"2022","unstructured":"Zhang X, Mei C, Li J, Yang Y, Qian T (2022) Instance and feature selection using fuzzy rough sets: a bi-selection approach for data reduction. IEEE Trans Fuzzy Syst 31(6):1981\u20131994","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"8","key":"7518_CR10","doi-asserted-by":"publisher","first-page":"1840","DOI":"10.1109\/TFUZZ.2019.2921935","volume":"28","author":"NM Parthal\u00e1in","year":"2019","unstructured":"Parthal\u00e1in NM, Jensen R, Diao R (2019) Fuzzy-rough set bireducts for data reduction. IEEE Trans Fuzzy Syst 28(8):1840\u20131850. https:\/\/doi.org\/10.1109\/TFUZZ.2019.2921935","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"7518_CR11","doi-asserted-by":"publisher","first-page":"109190","DOI":"10.1016\/j.patcog.2022.109190","volume":"135","author":"JJ Valero-Mas","year":"2023","unstructured":"Valero-Mas JJ, Gallego AJ, Alonso-Jim\u00e9nez P, Serra X (2023) Multilabel prototype generation for data reduction in K-nearest neighbour classification. Pattern Recogn 135:109190","journal-title":"Pattern Recogn"},{"issue":"5","key":"7518_CR12","doi-asserted-by":"publisher","first-page":"467","DOI":"10.1007\/s13676-018-0132-0","volume":"8","author":"A Estes","year":"2019","unstructured":"Estes A, Lovell DJ, Ball MO (2019) Unsupervised prototype reduction for data exploration and an application to air traffic management initiatives. EURO J Transp Logist 8(5):467\u2013510","journal-title":"EURO J Transp Logist"},{"key":"7518_CR13","doi-asserted-by":"publisher","first-page":"1127","DOI":"10.1007\/s11709-022-0838-9","volume":"16","author":"A Ghannadiasl","year":"2022","unstructured":"Ghannadiasl A, Ghaemifard S (2022) Crack detection of the cantilever beam using new triple hybrid algorithms based on particle swarm optimization. Front Struct Civ Eng 16:1127\u20131140. https:\/\/doi.org\/10.1007\/s11709-022-0838-9","journal-title":"Front Struct Civ Eng"},{"key":"7518_CR14","doi-asserted-by":"publisher","DOI":"10.1155\/2024\/2054173","author":"S Ghaemifard","year":"2024","unstructured":"Ghaemifard S, Ghannadiasl A, Khajehzadeh MA (2024) Comparison of metaheuristic algorithms for structural optimization: performance and efficiency analysis. Adv Civ Eng. https:\/\/doi.org\/10.1155\/2024\/2054173","journal-title":"Adv Civ Eng"},{"issue":"22","key":"7518_CR15","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1016\/j.neucom.2016.12.040","volume":"230","author":"L Yang","year":"2017","unstructured":"Yang L, Zhu Q, Huang J, Cheng D (2017) Adaptive edited natural neighbor algorithm. Neurocomputing 230(22):427\u2013433","journal-title":"Neurocomputing"},{"key":"7518_CR16","doi-asserted-by":"publisher","first-page":"13235","DOI":"10.1007\/s00500-019-03865-z","volume":"23","author":"L Yang","year":"2019","unstructured":"Yang L, Zhu Q, Huang J, Cheng D, Wu Q, Hong X (2019) Constraint nearest neighbor for instance reduction. Soft Comput 23:13235\u201313245","journal-title":"Soft Comput"},{"issue":"17","key":"7518_CR17","doi-asserted-by":"publisher","first-page":"6894","DOI":"10.1016\/j.eswa.2013.06.053","volume":"40","author":"GDC Cavalcanti","year":"2013","unstructured":"Cavalcanti GDC, Ren TI, Pereira CL (2013) ATISA: adaptive threshold-based instance selection algorithm. Expert Syst Appl 40(17):6894\u20136900","journal-title":"Expert Syst Appl"},{"key":"7518_CR18","first-page":"997","volume":"9","author":"E Marchiori","year":"2008","unstructured":"Marchiori E (2008) Hit miss networks with applications to instance selection. J Mach Learn Res 9:997\u20131017","journal-title":"J Mach Learn Res"},{"key":"7518_CR19","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1016\/j.asoc.2018.05.029","volume":"70","author":"L Yang","year":"2018","unstructured":"Yang L, Zhu Q, Huang J, Cheng D, Wu Q, Hong X (2018) Natural neighborhood graph-based instance reduction algorithm without parameters. Appl Soft Comput 70:279\u2013287","journal-title":"Appl Soft Comput"},{"issue":"2","key":"7518_CR20","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/j.patrec.2009.09.022","volume":"31","author":"CG Vallejo","year":"2010","unstructured":"Vallejo CG, Troyano JR, Ortega FJ (2010) InstanceRank: bringing order to datasets. Pattern Recogn Lett 31(2):131\u2013142","journal-title":"Pattern Recogn Lett"},{"issue":"1","key":"7518_CR21","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1016\/j.patcog.2012.07.007","volume":"46","author":"P Hernandezleal","year":"2013","unstructured":"Hernandezleal P, Carrascoochoa JA, Mart\u00ednezTrinidad JF, Olveralopez JA (2013) Instancerank based on borders for instance selection. Pattern Recogn 46(1):365\u2013375","journal-title":"Pattern Recogn"},{"key":"7518_CR22","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1007\/s10044-014-0393-7","volume":"19","author":"S Ougiaroglou","year":"2016","unstructured":"Ougiaroglou S, Evangelidis G (2016) RHC: a non-parametric cluster-based data reduction for efficient k-NN classification. Pattern Anal Appl 19:93\u2013109","journal-title":"Pattern Anal Appl"},{"key":"7518_CR23","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1016\/j.ins.2018.10.029","volume":"477","author":"C Tsai","year":"2019","unstructured":"Tsai C, Lin W, Hu Y, Yao G (2019) Under-sampling class imbalanced datasets by combining clustering analysis and instance selection. Inf Sci 477:47\u201354","journal-title":"Inf Sci"},{"key":"7518_CR24","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1007\/s10489-019-01598-y","volume":"50","author":"J Li","year":"2020","unstructured":"Li J, Zhu Q, Wu Q (2020) A parameter-free hybrid instance selection algorithm based on local sets with natural neighbors. Appl Intell 50:1527\u20131541","journal-title":"Appl Intell"},{"key":"7518_CR25","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1016\/j.ins.2022.04.036","volume":"602","author":"S Saha","year":"2022","unstructured":"Saha S, Sarker PS, Saud AA, Shatabda S, Newton MAH (2022) Cluster-oriented instance selection for classification problems. Inf Sci 602:143\u2013158","journal-title":"Inf Sci"},{"key":"7518_CR26","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1016\/j.knosys.2013.04.021","volume":"49","author":"T Zhai","year":"2013","unstructured":"Zhai T, He Z (2013) Instance selection for time series classification based on immune binary particle swarm optimization. Knowl-Based Syst 49:106\u2013115","journal-title":"Knowl-Based Syst"},{"issue":"3","key":"7518_CR27","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1109\/TCYB.2013.2257480","volume":"44","author":"P Yang","year":"2014","unstructured":"Yang P, Yoo PD, Fernando J, Zhou BB, Zhang Z, Zomaya AY (2014) Sample subset optimization techniques for imbalanced and ensemble learning problems in bioinformatics applications. IEEE Trans Cybern 44(3):445\u2013455","journal-title":"IEEE Trans Cybern"},{"key":"7518_CR28","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1016\/j.asoc.2019.02.028","volume":"78","author":"S Susan","year":"2019","unstructured":"Susan S, Kumar A (2019) SSOMaj-SMOTE-SSOMin: three-step intelligent pruning of majority and minority samples for learning from imbalanced datasets. Appl Soft Comput 78:141\u2013149","journal-title":"Appl Soft Comput"},{"key":"7518_CR29","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.dss.2014.01.012","volume":"61","author":"C Tsai","year":"2014","unstructured":"Tsai C, Chen Z (2014) Towards high dimensional instance selection: an evolutionary approach. Decis Support Syst 61:79\u201392","journal-title":"Decis Support Syst"},{"key":"7518_CR30","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1016\/j.compind.2015.08.007","volume":"74","author":"Z Chen","year":"2015","unstructured":"Chen Z, Lin W, Ke S, Tsai C (2015) Evolutionary feature and instance selection for traffic sign recognition. Comput Ind 74:201\u2013211","journal-title":"Comput Ind"},{"issue":"1","key":"7518_CR31","first-page":"43","volume":"10","author":"S Ghaemifard","year":"2023","unstructured":"Ghaemifard S, Ghannadiasl A (2023) Optimization approaches for structural control. J Struct Constr Eng 10(1):43\u201375","journal-title":"J Struct Constr Eng"},{"issue":"8","key":"7518_CR32","first-page":"1","volume":"31","author":"P Li","year":"2021","unstructured":"Li P, Liu X, Chen H, Li B, Ma T, Jiang W (2021) Optimization of three-dimensional magnetic field in vacuum interrupter using particle swarm optimization algorithm. IEEE Trans Appl Supercond 31(8):1\u20134","journal-title":"IEEE Trans Appl Supercond"},{"issue":"9","key":"7518_CR33","first-page":"5","volume":"10","author":"A Ghannadiasl","year":"2023","unstructured":"Ghannadiasl A, Ghaemifard S (2023) An overview of damage and crack detection in structures using metaheuristic algorithms and artificial neural networks. J Struct Constr Eng 10(9):5\u201335","journal-title":"J Struct Constr Eng"},{"key":"7518_CR34","doi-asserted-by":"crossref","unstructured":"Kennedy J (2003) Bare bones particle swarms. In: Proceedings of the 2003 IEEE swarm intelligence symposium. SIS'03 (Cat. No.03EX706), Indianapolis, pp. 80\u201387.","DOI":"10.1109\/SIS.2003.1202251"},{"key":"7518_CR35","doi-asserted-by":"publisher","first-page":"120642","DOI":"10.1016\/j.eswa.2023.120642","volume":"230","author":"L Zhang","year":"2023","unstructured":"Zhang L, Lim CP, Liu C (2023) Enhanced bare-bones particle swarm optimization based evolving deep neural networks. Expert Syst Appl 230:120642","journal-title":"Expert Syst Appl"},{"issue":"10","key":"7518_CR36","doi-asserted-by":"publisher","first-page":"4454","DOI":"10.1109\/TCYB.2019.2937565","volume":"50","author":"X Zhang","year":"2020","unstructured":"Zhang X, Du KJ, Zhan ZH, Kwong S, Gu TL, Zhang J (2020) Cooperative coevolutionary bare-bones particle swarm optimization with function independent decomposition for large-scale supply chain network design with uncertainties. IEEE Trans Cybern 50(10):4454\u20134468","journal-title":"IEEE Trans Cybern"},{"key":"7518_CR37","doi-asserted-by":"publisher","first-page":"1337","DOI":"10.1007\/s00500-013-1147-y","volume":"18","author":"Y Zhang","year":"2014","unstructured":"Zhang Y, Gong D, Sun X, Geng N (2014) Adaptive bare-bones particle swarm optimization algorithm and its convergence analysis. Soft Comput 18:1337\u20131352","journal-title":"Soft Comput"},{"key":"7518_CR38","first-page":"106","volume":"238","author":"H Liu","year":"2014","unstructured":"Liu H, Ding G, Wang B (2014) Bare-bones particle swarm optimization with disruption operator. Appl Math Comput 238:106\u2013122","journal-title":"Appl Math Comput"},{"key":"7518_CR39","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1016\/j.knosys.2015.12.017","volume":"97","author":"M Campos","year":"2016","unstructured":"Campos M, Krohling RA (2016) Entropy-based bare bones particle swarm for dynamic constrained optimization. Knowl-Based Syst 97:203\u2013223","journal-title":"Knowl-Based Syst"},{"key":"7518_CR40","doi-asserted-by":"publisher","first-page":"405","DOI":"10.1016\/j.asoc.2017.03.024","volume":"56","author":"W Srisukkham","year":"2017","unstructured":"Srisukkham W, Zhang L, Neoh SC, Todryk S, Lim CP (2017) Intelligent leukaemia diagnosis with bare-bones PSO based feature optimization. Appl Soft Comput 56:405\u2013419","journal-title":"Appl Soft Comput"},{"key":"7518_CR41","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1016\/j.neucom.2012.09.049","volume":"148","author":"Y Zhang","year":"2015","unstructured":"Zhang Y, Gong D, Hu Y, Zhang W (2015) Feature selection algorithm based on bare bones particle swarm optimization. Neurocomputing 148:150\u2013157","journal-title":"Neurocomputing"},{"key":"7518_CR42","doi-asserted-by":"publisher","first-page":"107804","DOI":"10.1016\/j.patcog.2020.107804","volume":"112","author":"X Song","year":"2021","unstructured":"Song X, Zhang Y, Gong D, Sun X (2021) Feature selection using bare-bones particle swarm optimization with mutual information. Pattern Recogn 112:107804","journal-title":"Pattern Recogn"},{"issue":"5","key":"7518_CR43","first-page":"2179","volume":"33","author":"H Zhao","year":"2021","unstructured":"Zhao H, Xu X, Song Y, Lee DL, Chen Z, Gao H (2021) Ranking users in social networks with motif-based pagerank. IEEE Trans Knowl Data Eng 33(5):2179\u20132192","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"7518_CR44","doi-asserted-by":"publisher","DOI":"10.1007\/s41062-024-01583-6","author":"A Ghannadiasl","year":"2024","unstructured":"Ghannadiasl A, Ghaemifard S (2024) Meta-heuristic algorithms: an appropriate approach in crack detection. Innov Infrastruct Solut. https:\/\/doi.org\/10.1007\/s41062-024-01583-6","journal-title":"Innov Infrastruct Solut"},{"issue":"8","key":"7518_CR45","doi-asserted-by":"publisher","first-page":"107056","DOI":"10.1016\/j.knosys.2021.107056","volume":"223","author":"J Li","year":"2021","unstructured":"Li J, Zhu Q, Wu Q, Zhang Z, Gong Y, He Z, Zhu F (2021) SMOTE-NaN-DE: addressing the noisy and borderline examples problem in imbalanced classification by natural neighbors and differential evolution. Knowl-Based Syst 223(8):107056","journal-title":"Knowl-Based Syst"},{"key":"7518_CR46","doi-asserted-by":"publisher","first-page":"107302","DOI":"10.1016\/j.asoc.2021.107302","volume":"106","author":"AD Li","year":"2021","unstructured":"Li AD, Xue B, Zhang M (2021) Improved binary particle swarm optimization for feature selection with new initialization and search space reduction strategies. Appl Soft Comput 106:107302","journal-title":"Appl Soft Comput"},{"issue":"2","key":"7518_CR47","doi-asserted-by":"publisher","first-page":"489","DOI":"10.23919\/JSEE.2022.000048","volume":"33","author":"Z Wang","year":"2022","unstructured":"Wang Z, Hu Z, Yang X (2022) Multi-agent and ant colony optimization for ship integrated power system network reconfiguration. J Syst Eng Electron 33(2):489\u2013496","journal-title":"J Syst Eng Electron"},{"issue":"1","key":"7518_CR48","first-page":"1","volume":"7","author":"J Demiar","year":"2006","unstructured":"Demiar J, Schuurmans D (2006) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7(1):1\u201330","journal-title":"J Mach Learn Res"},{"key":"7518_CR49","doi-asserted-by":"publisher","first-page":"120374","DOI":"10.1016\/j.eswa.2023.120374","volume":"228","author":"Z Dai","year":"2023","unstructured":"Dai Z, Zhang Z, Chen M (2023) The home health care location-routing problem with a mixed fleet and battery swapping stations using a competitive simulated annealing algorithm. Expert Syst Appl 228:120374","journal-title":"Expert Syst Appl"},{"key":"7518_CR50","doi-asserted-by":"publisher","first-page":"25205","DOI":"10.1007\/s11042-022-12409-x","volume":"81","author":"ST Shishavan","year":"2022","unstructured":"Shishavan ST, Gharehchopogh FS (2022) An improved cuckoo search optimization algorithm with genetic algorithm for community detection in complex networks. Multimed Tools Appl 81:25205\u201325231","journal-title":"Multimed Tools Appl"},{"issue":"2","key":"7518_CR51","doi-asserted-by":"publisher","first-page":"17","DOI":"10.61186\/NMCE.2311.1036","volume":"9","author":"A Ghannadiasl","year":"2024","unstructured":"Ghannadiasl A, Ghaemifard S (2024) Parameter selection for PSO-based hybrid algorithms and its effect on crack detection in cantilever beams. Numer Methods Civ Eng 9(2):17\u201328","journal-title":"Numer Methods Civ Eng"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-07518-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-025-07518-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-07518-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,15]],"date-time":"2025-09-15T19:02:02Z","timestamp":1757962922000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-025-07518-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,15]]},"references-count":51,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2025,9]]}},"alternative-id":["7518"],"URL":"https:\/\/doi.org\/10.1007\/s11227-025-07518-x","relation":{},"ISSN":["1573-0484"],"issn-type":[{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,15]]},"assertion":[{"value":"27 May 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 September 2025","order":2,"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 no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"The authors declare that they have informed consent to publish and for the data used. This research is not applicable to both humans and\/or animals.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Our research does not include human or animal subjects.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human or animal rights"}}],"article-number":"1340"}}