{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T01:04:06Z","timestamp":1778547846792,"version":"3.51.4"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2023,1,20]],"date-time":"2023-01-20T00:00:00Z","timestamp":1674172800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,20]],"date-time":"2023-01-20T00:00:00Z","timestamp":1674172800000},"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"],"published-print":{"date-parts":[[2023,6]]},"DOI":"10.1007\/s11227-023-05047-z","type":"journal-article","created":{"date-parts":[[2023,1,20]],"date-time":"2023-01-20T04:42:41Z","timestamp":1674189761000},"page":"9715-9770","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["TDMBBO: a novel three-dimensional migration model of biogeography-based optimization (case study: facility planning and benchmark problems)"],"prefix":"10.1007","volume":"79","author":[{"given":"Mehrdad","family":"Kaveh","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammad Saadi","family":"Mesgari","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Diego","family":"Mart\u00edn","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masoud","family":"Kaveh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,1,20]]},"reference":[{"key":"5047_CR1","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.cie.2014.03.008","volume":"72","author":"L Zhen","year":"2014","unstructured":"Zhen L, Wang K, Hu H, Chang D (2014) A simulation optimization framework for ambulance deployment and relocation problems. Comput Ind Eng 72:12\u201323","journal-title":"Comput Ind Eng"},{"issue":"4","key":"5047_CR2","doi-asserted-by":"crossref","first-page":"1000","DOI":"10.1016\/j.cie.2011.12.026","volume":"62","author":"SR Shariff","year":"2012","unstructured":"Shariff SR, Moin NH, Omar M (2012) Location allocation modeling for healthcare facility planning in Malaysia. Comput Ind Eng 62(4):1000\u20131010","journal-title":"Comput Ind Eng"},{"key":"5047_CR3","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.cie.2016.08.011","volume":"101","author":"YD Ko","year":"2016","unstructured":"Ko YD, Song BD, Hwang H (2016) Location, capacity and capability design of emergency medical centers with multiple emergency diseases. Comput Ind Eng 101:10\u201320","journal-title":"Comput Ind Eng"},{"key":"5047_CR4","doi-asserted-by":"crossref","first-page":"800","DOI":"10.1016\/j.cie.2019.06.058","volume":"135","author":"M Kaveh","year":"2019","unstructured":"Kaveh M, Mesgari MS (2019) Improved biogeography-based optimization using migration process adjustment: an approach for location-allocation of ambulances. Comput Ind Eng 135:800\u2013813","journal-title":"Comput Ind Eng"},{"key":"5047_CR5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/978-3-030-32177-2","volume-title":"Location science","author":"G Laporte","year":"2019","unstructured":"Laporte G, Nickel S, Saldanha-da-Gama F (2019) Introduction to location science. Location science. Springer, Cham, pp 1\u201321"},{"key":"5047_CR6","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.apacoust.2016.11.012","volume":"118","author":"M Khishe","year":"2017","unstructured":"Khishe M, Mosavi MR, Kaveh M (2017) Improved migration models of biogeography-based optimization for sonar dataset classification by using neural network. Appl Acoust 118:15\u201329","journal-title":"Appl Acoust"},{"issue":"3","key":"5047_CR7","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1287\/opre.13.3.462","volume":"13","author":"SL Hakimi","year":"1965","unstructured":"Hakimi SL (1965) Optimum distribution of switching centers in a communication network and some related graph theoretic problems. Oper Res 13(3):462\u2013475","journal-title":"Oper Res"},{"issue":"1","key":"5047_CR8","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1111\/j.1538-4632.1970.tb00142.x","volume":"2","author":"CS ReVelle","year":"1970","unstructured":"ReVelle CS, Swain RW (1970) Central facilities location. Geogr Anal 2(1):30\u201342","journal-title":"Geogr Anal"},{"issue":"2","key":"5047_CR9","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1016\/S0377-2217(96)00141-5","volume":"96","author":"E Rolland","year":"1997","unstructured":"Rolland E, Schilling DA, Current JR (1997) An efficient tabu search procedure for the p-median problem. Eur J Oper Res 96(2):329\u2013342","journal-title":"Eur J Oper Res"},{"issue":"2","key":"5047_CR10","doi-asserted-by":"crossref","first-page":"1540","DOI":"10.1016\/j.asoc.2008.03.015","volume":"11","author":"JM Cadenas","year":"2011","unstructured":"Cadenas JM, Can\u00f3s MJ, Garrido MC, Ivorra C, Liern V (2011) Soft-computing based heuristics for location on networks: the p-median problem. Appl Soft Comput 11(2):1540\u20131547","journal-title":"Appl Soft Comput"},{"key":"5047_CR11","doi-asserted-by":"crossref","first-page":"103674","DOI":"10.1016\/j.engappai.2020.103674","volume":"92","author":"O Gokalp","year":"2020","unstructured":"Gokalp O (2020) An iterated greedy algorithm for the obnoxious p-median problem. Eng Appl Artif Intell 92:103674","journal-title":"Eng Appl Artif Intell"},{"issue":"6","key":"5047_CR12","doi-asserted-by":"crossref","first-page":"4591","DOI":"10.1007\/s10462-021-10006-2","volume":"54","author":"\u0130M Elig\u00fczel","year":"2021","unstructured":"Elig\u00fczel \u0130M, \u00d6zceylan E (2021) Application of an improved discrete crow search algorithm with local search and elitism on a humanitarian relief case. Artif Intell Rev 54(6):4591\u20134617","journal-title":"Artif Intell Rev"},{"key":"5047_CR13","doi-asserted-by":"crossref","unstructured":"Kariv, O., & Hakimi, S. L. (1979). An algorithmic approach to network location problems. I: The p-centers.\u00a0SIAM Journal on Applied Mathematics,\u00a037(3), 513\u2013538.","DOI":"10.1137\/0137040"},{"key":"5047_CR14","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.compenvurbsys.2016.07.001","volume":"59","author":"W Zhang","year":"2016","unstructured":"Zhang W, Cao K, Liu S, Huang B (2016) A multi-objective optimization approach for health-care facility location-allocation problems in highly developed cities such as Hong Kong. Comput Environ Urban Syst 59:220\u2013230","journal-title":"Comput Environ Urban Syst"},{"key":"5047_CR15","doi-asserted-by":"crossref","unstructured":"ElKady SK, Abdelsalam HM (2016) A modified particle swarm optimization algorithm for solving capacitated maximal covering location problem in healthcare systems. In: Applications of intelligent optimization in biology and medicine, pp. 117\u2013133.","DOI":"10.1007\/978-3-319-21212-8_5"},{"key":"5047_CR16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.orhc.2016.08.001","volume":"11","author":"MA Zaffar","year":"2016","unstructured":"Zaffar MA, Rajagopalan HK, Saydam C, Mayorga M, Sharer E (2016) Coverage, survivability or response time: a comparative study of performance statistics used in ambulance location models via simulation\u2013optimization. Oper Res Health Care 11:1\u201312","journal-title":"Oper Res Health Care"},{"key":"5047_CR17","doi-asserted-by":"crossref","first-page":"107625","DOI":"10.1016\/j.knosys.2021.107625","volume":"235","author":"W Kaidi","year":"2022","unstructured":"Kaidi W, Khishe M, Mohammadi M (2022) Dynamic levy flight chimp optimization. Knowl-Based Syst 235:107625","journal-title":"Knowl-Based Syst"},{"issue":"6","key":"5047_CR18","doi-asserted-by":"crossref","first-page":"702","DOI":"10.1109\/TEVC.2008.919004","volume":"12","author":"D Simon","year":"2008","unstructured":"Simon D (2008) Biogeography-based optimization. IEEE Trans Evol Comput 12(6):702\u2013713","journal-title":"IEEE Trans Evol Comput"},{"issue":"6","key":"5047_CR19","doi-asserted-by":"crossref","first-page":"1052","DOI":"10.1016\/j.engappai.2011.04.012","volume":"24","author":"H Ma","year":"2011","unstructured":"Ma H, Simon D (2011) Analysis of migration models of biogeography-based optimization using Markov theory. Eng Appl Artif Intell 24(6):1052\u20131060","journal-title":"Eng Appl Artif Intell"},{"issue":"2","key":"5047_CR20","doi-asserted-by":"crossref","first-page":"1214","DOI":"10.1007\/s11227-020-03317-8","volume":"77","author":"MR Shirani","year":"2021","unstructured":"Shirani MR, Safi-Esfahani F (2021) Dynamic scheduling of tasks in cloud computing applying dragonfly algorithm, biogeography-based optimization algorithm and Mexican hat wavelet. J Supercomput 77(2):1214\u20131272","journal-title":"J Supercomput"},{"issue":"3","key":"5047_CR21","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1007\/s12518-020-00297-5","volume":"12","author":"M Kaveh","year":"2020","unstructured":"Kaveh M, Kaveh M, Mesgari MS, Paland RS (2020) Multiple criteria decision-making for hospital location-allocation based on improved genetic algorithm. Appl Geomat 12(3):291\u2013306","journal-title":"Appl Geomat"},{"key":"5047_CR22","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.matcom.2021.08.013","volume":"192","author":"FA Hashim","year":"2022","unstructured":"Hashim FA, Houssein EH, Hussain K, Mabrouk MS, Al-Atabany W (2022) Honey badger algorithm: new metaheuristic algorithm for solving optimization problems. Math Comput Simul 192:84\u2013110","journal-title":"Math Comput Simul"},{"issue":"5","key":"5047_CR23","doi-asserted-by":"crossref","first-page":"1297","DOI":"10.1007\/s12559-021-09933-7","volume":"13","author":"J Wang","year":"2021","unstructured":"Wang J, Khishe M, Kaveh M, Mohammadi H (2021) Binary chimp optimization algorithm (BChOA): a new binary meta-heuristic for solving optimization problems. Cogn Comput 13(5):1297\u20131316","journal-title":"Cogn Comput"},{"issue":"12","key":"5047_CR24","doi-asserted-by":"crossref","first-page":"4459","DOI":"10.3390\/s22124459","volume":"22","author":"S Baniasadi","year":"2022","unstructured":"Baniasadi S, Rostami O, Mart\u00edn D, Kaveh M (2022) A novel deep supervised learning-based approach for intrusion detection in IoT systems. Sensors 22(12):4459","journal-title":"Sensors"},{"key":"5047_CR25","doi-asserted-by":"crossref","first-page":"107408","DOI":"10.1016\/j.cie.2021.107408","volume":"158","author":"B Abdollahzadeh","year":"2021","unstructured":"Abdollahzadeh B, Gharehchopogh FS, Mirjalili S (2021) African vultures optimization algorithm: a new nature-inspired metaheuristic algorithm for global optimization problems. Comput Ind Eng 158:107408","journal-title":"Comput Ind Eng"},{"key":"5047_CR26","doi-asserted-by":"crossref","unstructured":"Kaveh M, Mesgari MS (2022) Application of meta-heuristic algorithms for training neural networks and deep learning architectures: a comprehensive review. Neural Process Lett 1\u2013104.","DOI":"10.1007\/s11063-022-11055-6"},{"issue":"3","key":"5047_CR27","doi-asserted-by":"crossref","first-page":"3998","DOI":"10.1007\/s11227-021-04015-9","volume":"78","author":"MJ Goldanloo","year":"2022","unstructured":"Goldanloo MJ, Gharehchopogh FS (2022) A hybrid OBL-based firefly algorithm with symbiotic organisms search algorithm for solving continuous optimization problems. J Supercomput 78(3):3998\u20134031","journal-title":"J Supercomput"},{"issue":"3","key":"5047_CR28","doi-asserted-by":"crossref","first-page":"911","DOI":"10.1007\/s10596-020-10030-1","volume":"25","author":"O Rostami","year":"2021","unstructured":"Rostami O, Kaveh M (2021) Optimal feature selection for SAR image classification using biogeography-based optimization (BBO), artificial bee colony (ABC) and support vector machine (SVM): a combined approach of optimization and machine learning. Comput Geosci 25(3):911\u2013930","journal-title":"Comput Geosci"},{"key":"5047_CR29","doi-asserted-by":"crossref","unstructured":"Azizi, M., Talatahari, S., & Gandomi, A. H. (2022). Fire hawk optimizer: a novel metaheuristic algorithm. Artif Intell Rev, 1\u201377.","DOI":"10.1007\/s10462-022-10173-w"},{"key":"5047_CR30","doi-asserted-by":"crossref","first-page":"100471","DOI":"10.1016\/j.sste.2021.100471","volume":"40","author":"N Kianfar","year":"2022","unstructured":"Kianfar N, Mesgari MS, Mollalo A, Kaveh M (2022) Spatio-temporal modeling of COVID-19 prevalence and mortality using artificial neural network algorithms. Spat Spatio-temporal Epidemiol 40:100471","journal-title":"Spat Spatio-temporal Epidemiol"},{"issue":"1","key":"5047_CR31","doi-asserted-by":"crossref","first-page":"751","DOI":"10.32604\/cmc.2023.031519","volume":"74","author":"F Sadeghi","year":"2023","unstructured":"Sadeghi F, Rostami O, Yi MK, Hwang SO (2023) A deep learning approach for detecting Covid-19 using the chest X-ray images. Cmc-Comput Mater Continua 74(1):751\u2013768","journal-title":"Cmc-Comput Mater Continua"},{"issue":"4","key":"5047_CR32","first-page":"453","volume":"33","author":"PK Giri","year":"2021","unstructured":"Giri PK, De SS, Dehuri S (2021) Adaptive neighbourhood for locally and globally tuned biogeography based optimization algorithm. J King Saud Univ Comput Inf Sci 33(4):453\u2013467","journal-title":"J King Saud Univ Comput Inf Sci"},{"key":"5047_CR33","doi-asserted-by":"crossref","first-page":"106869","DOI":"10.1016\/j.asoc.2020.106869","volume":"99","author":"Y An","year":"2021","unstructured":"An Y, Chen X, Li Y, Han Y, Zhang J, Shi H (2021) An improved non-dominated sorting biogeography-based optimization algorithm for the (hybrid) multi-objective flexible job-shop scheduling problem. Appl Soft Comput 99:106869","journal-title":"Appl Soft Comput"},{"key":"5047_CR34","doi-asserted-by":"crossref","first-page":"28810","DOI":"10.1109\/ACCESS.2019.2901849","volume":"7","author":"X Zhang","year":"2019","unstructured":"Zhang X, Wang D, Chen H (2019) Improved biogeography-based optimization algorithm and its application to clustering optimization and medical image segmentation. IEEE Access 7:28810\u201328825","journal-title":"IEEE Access"},{"issue":"1","key":"5047_CR35","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1002\/isaf.1486","volume":"28","author":"PK Giri","year":"2021","unstructured":"Giri PK, De SS, Dehuri S, Cho SB (2021) Biogeography based optimization for mining rules to assess credit risk. Intell Syst Account Financ Manag 28(1):35\u201351","journal-title":"Intell Syst Account Financ Manag"},{"key":"5047_CR36","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.swevo.2015.10.006","volume":"27","author":"V Garg","year":"2016","unstructured":"Garg V, Deep K (2016) Performance of laplacian biogeography-based optimization algorithm on CEC 2014 continuous optimization benchmarks and camera calibration problem. Swarm Evol Comput 27:132\u2013144","journal-title":"Swarm Evol Comput"},{"issue":"18","key":"5047_CR37","doi-asserted-by":"crossref","first-page":"3444","DOI":"10.1016\/j.ins.2010.05.035","volume":"180","author":"H Ma","year":"2010","unstructured":"Ma H (2010) An analysis of the equilibrium of migration models for biogeography-based optimization. Inf Sci 180(18):3444\u20133464","journal-title":"Inf Sci"},{"key":"5047_CR38","doi-asserted-by":"crossref","unstructured":"Garg V, Deep K (2015) A state-of-the-art review of biogeography-based optimization. In Proceedings of Fourth International Conference on Soft Computing for Problem Solving. Springer, New Delhi, pp. 533\u2013549","DOI":"10.1007\/978-81-322-2220-0_44"},{"issue":"1","key":"5047_CR39","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1109\/4235.585893","volume":"1","author":"DH Wolpert","year":"1997","unstructured":"Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1(1):67\u201382","journal-title":"IEEE Trans Evol Comput"},{"issue":"3\u20135","key":"5047_CR40","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/0270-0255(87)90473-8","volume":"9","author":"RW Saaty","year":"1987","unstructured":"Saaty RW (1987) The analytic hierarchy process\u2014what it is and how it is used. Math Model 9(3\u20135):161\u2013176","journal-title":"Math Model"},{"issue":"5","key":"5047_CR41","doi-asserted-by":"crossref","first-page":"7428","DOI":"10.1007\/s11227-021-04177-6","volume":"78","author":"J Li","year":"2022","unstructured":"Li J, Wu Y, Fong S, Tall\u00f3n-Ballesteros AJ, Yang XS, Mohammed S, Wu F (2022) A binary PSO-based ensemble under-sampling model for rebalancing imbalanced training data. J Supercomput 78(5):7428\u20137463","journal-title":"J Supercomput"},{"issue":"4","key":"5047_CR42","doi-asserted-by":"crossref","first-page":"4624","DOI":"10.1007\/s11227-021-04062-2","volume":"78","author":"S Nabi","year":"2022","unstructured":"Nabi S, Ahmed M (2022) PSO-RDAL: Particle swarm optimization-based resource-and deadline-aware dynamic load balancer for deadline constrained cloud tasks. J Supercomput 78(4):4624\u20134654","journal-title":"J Supercomput"},{"key":"5047_CR43","doi-asserted-by":"crossref","unstructured":"Ibrahim S, Jarboui B (2020) A general variable neighborhood search approach based on a p-median model for cellular manufacturing problems. Optim Lett 1\u201315.","DOI":"10.1007\/s11590-020-01662-4"},{"issue":"7","key":"5047_CR44","doi-asserted-by":"crossref","first-page":"2515","DOI":"10.1007\/s00521-020-05145-6","volume":"33","author":"M Braik","year":"2021","unstructured":"Braik M, Sheta A, Al-Hiary H (2021) A novel meta-heuristic search algorithm for solving optimization problems: capuchin search algorithm. Neural Comput Appl 33(7):2515\u20132547","journal-title":"Neural Comput Appl"},{"key":"5047_CR45","doi-asserted-by":"crossref","first-page":"113338","DOI":"10.1016\/j.eswa.2020.113338","volume":"149","author":"M Khishe","year":"2020","unstructured":"Khishe M, Mosavi MR (2020) Chimp optimization algorithm. Expert Syst Appl 149:113338","journal-title":"Expert Syst Appl"},{"key":"5047_CR46","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46\u201361","journal-title":"Adv Eng Softw"},{"issue":"1","key":"5047_CR47","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.swevo.2011.02.002","volume":"1","author":"J Derrac","year":"2011","unstructured":"Derrac J, Garc\u00eda S, Molina D, Herrera F (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evol Comput 1(1):3\u201318","journal-title":"Swarm Evol Comput"},{"key":"5047_CR48","unstructured":"Suganthan PN, Hansen N, Liang JJ, Deb K, Chen YP, Auger A, Tiwari S (2005) Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization. KanGAL Report, 2005"},{"key":"5047_CR49","doi-asserted-by":"crossref","unstructured":"Molina D, Moreno-Garc\u00eda F, Herrera F (2017) Analysis among winners of different IEEE CEC competitions on real-parameters optimization: Is there always improvement?. In: 2017 IEEE Congress on Evolutionary Computation (CEC), 805\u2013812","DOI":"10.1109\/CEC.2017.7969392"},{"key":"5047_CR50","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1016\/j.asoc.2015.10.036","volume":"56","author":"A Baykaso\u011flu","year":"2017","unstructured":"Baykaso\u011flu A, Akpinar \u015e (2017) Weighted Superposition Attraction (WSA): a swarm intelligence algorithm for optimization problems\u2013part 1: unconstrained optimization. Appl Soft Comput 56:520\u2013540","journal-title":"Appl Soft Comput"},{"issue":"3","key":"5047_CR51","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1007\/s10589-013-9566-3","volume":"56","author":"S Chetty","year":"2013","unstructured":"Chetty S, Adewumi AO (2013) Three new stochastic local search algorithms for continuous optimization problems. Comput Optim Appl 56(3):675\u2013721","journal-title":"Comput Optim Appl"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05047-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-023-05047-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05047-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,24]],"date-time":"2023-04-24T22:05:49Z","timestamp":1682373949000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-023-05047-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,20]]},"references-count":51,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2023,6]]}},"alternative-id":["5047"],"URL":"https:\/\/doi.org\/10.1007\/s11227-023-05047-z","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"value":"0920-8542","type":"print"},{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,20]]},"assertion":[{"value":"4 January 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 January 2023","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 that they have no conflict of interest. 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 interests"}},{"value":"This paper does not contain any studies with human participants or animals.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"The datasets generated during and\/or analyzed during the current study are available from the corresponding author on reasonable request.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Availability of data and material"}}]}}