{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T15:21:21Z","timestamp":1772119281894,"version":"3.50.1"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"16","license":[{"start":{"date-parts":[[2021,7,10]],"date-time":"2021-07-10T00:00:00Z","timestamp":1625875200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,7,10]],"date-time":"2021-07-10T00:00:00Z","timestamp":1625875200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100009051","name":"Universidad T\u00e9cnica Federico Santa Mar\u00eda","doi-asserted-by":"publisher","award":["PIIC"],"award-info":[{"award-number":["PIIC"]}],"id":[{"id":"10.13039\/100009051","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Soft Comput"],"published-print":{"date-parts":[[2021,8]]},"DOI":"10.1007\/s00500-021-06016-5","type":"journal-article","created":{"date-parts":[[2021,7,10]],"date-time":"2021-07-10T09:02:56Z","timestamp":1625907776000},"page":"10851-10862","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Forecasting inflation in Latin American countries using a SARIMA\u2013LSTM combination"],"prefix":"10.1007","volume":"25","author":[{"given":"Rodrigo","family":"Peirano","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5878-072X","authenticated-orcid":false,"given":"Werner","family":"Kristjanpoller","sequence":"additional","affiliation":[]},{"given":"Marcel C.","family":"Minutolo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,7,10]]},"reference":[{"issue":"2\u20134","key":"6016_CR1","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1080\/07474930701220543","volume":"26","author":"M Adolfson","year":"2007","unstructured":"Adolfson M, Lind\u00e9 J, Villani M (2007) Forecasting performance of an open economy dsge model. Econ Rev 26(2\u20134):289\u2013328","journal-title":"Econ Rev"},{"issue":"1","key":"6016_CR2","first-page":"2","volume":"25","author":"A Atkeson","year":"2001","unstructured":"Atkeson A, Ohanian LE et al (2001) Are Phillips curves useful for forecasting inflation? Federal Reser Bank Minneapolis Quar Rev 25(1):2\u201311","journal-title":"Federal Reser Bank Minneapolis Quar Rev"},{"key":"6016_CR3","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1016\/j.fss.2016.09.008","volume":"319","author":"F Bacani","year":"2017","unstructured":"Bacani F, de Barros LC (2017) Application of prediction models using fuzzy sets: a Bayesian inspired approach. Fuzzy Sets Syst 319:104\u2013116","journal-title":"Fuzzy Sets Syst"},{"key":"6016_CR4","unstructured":"Box GE, Jenkins GM (1976) Time series analysis: forecasting and control, revised. Holden-Day"},{"issue":"3","key":"6016_CR5","doi-asserted-by":"publisher","first-page":"1424","DOI":"10.1016\/j.econmod.2011.02.009","volume":"28","author":"C Broto","year":"2011","unstructured":"Broto C (2011) Inflation targeting in Latin America: empirical analysis using GARCH models. Econ Modell 28(3):1424\u20131434","journal-title":"Econ Modell"},{"issue":"4","key":"6016_CR6","doi-asserted-by":"publisher","first-page":"1770","DOI":"10.1016\/j.ijforecast.2018.12.001","volume":"35","author":"M Cai","year":"2019","unstructured":"Cai M, Del Negro M, Giannoni MP, Gupta A, Li P, Moszkowski E (2019) Dsge forecasts of the lost recovery. Int J Forecast 35(4):1770\u20131789","journal-title":"Int J Forecast"},{"issue":"1","key":"6016_CR7","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/S0167-7152(98)00195-3","volume":"42","author":"W-S Chan","year":"1999","unstructured":"Chan W-S (1999) A comparison of some of pattern identification methods for order determination of mixed ARMA models. Stat Prob Lett 42(1):69\u201379","journal-title":"Stat Prob Lett"},{"issue":"1","key":"6016_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/S0165-0114(96)00138-8","volume":"90","author":"P-T Chang","year":"1997","unstructured":"Chang P-T (1997) Fuzzy seasonality forecasting. Fuzzy Sets Syst 90(1):1\u201310","journal-title":"Fuzzy Sets Syst"},{"issue":"3","key":"6016_CR9","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1016\/0165-0114(95)00220-0","volume":"81","author":"S-M Chen","year":"1996","unstructured":"Chen S-M (1996) Forecasting enrollments based on fuzzy time series. Fuzzy Sets Syst 81(3):311\u2013319","journal-title":"Fuzzy Sets Syst"},{"issue":"3","key":"6016_CR10","doi-asserted-by":"publisher","first-page":"267","DOI":"10.3233\/IFS-1994-2306","volume":"2","author":"SL Chiu","year":"1994","unstructured":"Chiu SL (1994) Fuzzy model identification based on cluster estimation. J Intell Fuzzy Syst 2(3):267\u2013278","journal-title":"J Intell Fuzzy Syst"},{"issue":"5","key":"6016_CR11","doi-asserted-by":"publisher","first-page":"2101","DOI":"10.1257\/aer.98.5.2101","volume":"98","author":"T Cogley","year":"2008","unstructured":"Cogley T, Sbordone AM (2008) Trend inflation, indexation, and inflation persistence in the new keynesian phillips curve. Am Econ Rev 98(5):2101\u201326","journal-title":"Am Econ Rev"},{"issue":"2","key":"6016_CR12","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1109\/72.279188","volume":"5","author":"JT Connor","year":"1994","unstructured":"Connor JT, Martin RD, Atlas LE (1994) Recurrent neural networks and robust time series prediction. IEEE Trans Neural Netw 5(2):240\u2013254","journal-title":"IEEE Trans Neural Netw"},{"issue":"7","key":"6016_CR13","doi-asserted-by":"publisher","first-page":"1371","DOI":"10.1002\/jae.2504","volume":"31","author":"Cuaresma Jesus","year":"2016","unstructured":"Jesus Cuaresma, Cresp FM, Huber F (2016) Forecasting with global vector autoregressive models: a Bayesian approach. J Appl Econ 31(7):1371\u20131391","journal-title":"J Appl Econ"},{"key":"6016_CR14","unstructured":"D\u2019Amato L, Garegnani L, Blanco E (2008) Forecasting inflation in Argentina: Individual models or forecast pooling? Technical report, Working Paper, Central Bank of Argentina (BCRA)"},{"issue":"3","key":"6016_CR15","first-page":"59","volume":"4","author":"FN de Simona","year":"2001","unstructured":"de Simona FN (2001) Proyecci\u00f3n de la Inflaci\u00f3n en Chile. Econom\u00eda Chilena 4(3):59\u201385","journal-title":"Econom\u00eda Chilena"},{"issue":"2","key":"6016_CR16","doi-asserted-by":"publisher","first-page":"151","DOI":"10.15294\/edaj.v8i2.29074","volume":"8","author":"FI Estiko","year":"2019","unstructured":"Estiko FI, Wahyuddin S (2019) Analysis of indonesia\u2019s inflation using arima and artificial neural network. Econ Dev Anal J 8(2):151\u2013162","journal-title":"Econ Dev Anal J"},{"key":"6016_CR17","doi-asserted-by":"crossref","unstructured":"Faust J, Wright JH (2013) Forecasting inflation, volume\u00a02 of Handbook of Economic Forecasting, pages 2\u201356. Elsevier","DOI":"10.1016\/B978-0-444-53683-9.00001-3"},{"key":"6016_CR18","volume-title":"Algorithms, applications, and programming techniques","author":"JA Freeman","year":"1991","unstructured":"Freeman JA, Skapura DM (1991) Algorithms, applications, and programming techniques. Addison-Wesley Publishing Company, USA"},{"key":"6016_CR19","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/S0304-3932(99)00023-9","volume":"44","author":"J Gal\u00e1","year":"1999","unstructured":"Gal\u00e1 J, Gertler M (1999) Inflation dynamics: a structural econometric approach. J Monetary Econ 44:195\u2013222","journal-title":"J Monetary Econ"},{"key":"6016_CR20","unstructured":"Gamboa JCB (2017) Deep Learning for Time-Series Analysis. arXiv preprint arXiv:1701.01887"},{"key":"6016_CR21","doi-asserted-by":"crossref","unstructured":"Graves A, Fern\u00e1ndez S, Gomez F, Schmidhuber J (2006) Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks. In Proceedings of the 23rd international conference on Machine learning, pages 369\u2013376. ACM","DOI":"10.1145\/1143844.1143891"},{"issue":"10","key":"6016_CR22","doi-asserted-by":"publisher","first-page":"2222","DOI":"10.1109\/TNNLS.2016.2582924","volume":"28","author":"K Greff","year":"2017","unstructured":"Greff K, Srivastava RK, Koutn\u00edk J, Steunebrink BR, Schmidhuber J (2017) LSTM: a search space odyssey. IEEE Trans Neural Netw Learn Syst 28(10):2222\u20132232","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"4","key":"6016_CR23","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1198\/073500105000000063","volume":"23","author":"PR Hansen","year":"2005","unstructured":"Hansen PR (2005) A test for superior predictive ability. J Bus Econ Stat 23(4):365\u2013380","journal-title":"J Bus Econ Stat"},{"key":"6016_CR24","unstructured":"Hebb D (1949) Theorganization of behavior. New York"},{"issue":"8","key":"6016_CR25","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735\u20131780","journal-title":"Neural Comput"},{"issue":"4","key":"6016_CR26","first-page":"84","volume":"9","author":"E I\u015f\u0131\u011f\u0131\u00e7ok","year":"2020","unstructured":"I\u015f\u0131\u011f\u0131\u00e7ok E, \u00d6z R, Tarkun S (2020) Forecasting and technical comparison of inflation in turkey with box-jenkins (arima) models and the artificial neural network. Int J Energy Opt Eng (IJEOE) 9(4):84\u2013103","journal-title":"Int J Energy Opt Eng (IJEOE)"},{"issue":"3","key":"6016_CR27","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1109\/21.256541","volume":"23","author":"J-S Jang","year":"1993","unstructured":"Jang J-S (1993) ANFIS: adaptive-network-based fuzzy inference system. IEEE Trans Syst Man Cybern 23(3):665\u2013685","journal-title":"IEEE Trans Syst Man Cybern"},{"issue":"7","key":"6016_CR28","doi-asserted-by":"publisher","first-page":"769","DOI":"10.1016\/j.fss.2007.10.011","volume":"159","author":"M Khashei","year":"2008","unstructured":"Khashei M, Hejazi SR, Bijari M (2008) A new hybrid artificial neural networks and fuzzy regression model for time series forecasting. Fuzzy Sets Syst 159(7):769\u2013786","journal-title":"Fuzzy Sets Syst"},{"issue":"1688","key":"6016_CR29","first-page":"397","volume":"348","author":"B LeBaron","year":"1994","unstructured":"LeBaron B (1994) Chaos and nonlinear forecastability in economics and finance. Philos Trans Royal Soc London A Math Phys Eng Sci 348(1688):397\u2013404","journal-title":"Philos Trans Royal Soc London A Math Phys Eng Sci"},{"key":"6016_CR30","unstructured":"Lipton ZC, Berkowitz J, Elkan C (2015) A critical review of recurrent neural networks for sequence learning. arXiv preprint arXiv:1506.00019"},{"key":"6016_CR31","volume-title":"Forecasting and time series analysis using the SCA statistical system","author":"L-M Liu","year":"1992","unstructured":"Liu L-M, Hudak GB, Box GE, Muller ME, Tiao GC (1992) Forecasting and time series analysis using the SCA statistical system, vol 1. Scientific Computing Associates DeKalb, IL"},{"key":"6016_CR32","unstructured":"Luis J, H\u00e9ctor J, et\u00a0al. (2013) Forecasting Mexican inflation using neural networks. In Electronics, Communications and Computing (CONIELECOMP), 2013 International Conference on, pages 32\u201335. IEEE"},{"issue":"1","key":"6016_CR33","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1080\/07474939408800276","volume":"13","author":"E Maasoumi","year":"1994","unstructured":"Maasoumi E, Khotanzed A, Abaye A (1994) Artificial neural networks for some macroeconomic series: a first report. Econ Rev 13(1):105\u2013122","journal-title":"Econ Rev"},{"issue":"6","key":"6016_CR34","doi-asserted-by":"publisher","first-page":"669","DOI":"10.1016\/S0020-7373(76)80028-4","volume":"8","author":"EH Mamdani","year":"1976","unstructured":"Mamdani EH (1976) Advances in the linguistic synthesis of fuzzy controllers. Int J Man-Mach Stud 8(6):669\u2013678","journal-title":"Int J Man-Mach Stud"},{"key":"6016_CR35","unstructured":"Manning C, Socher R, Fang GG, Mundra R (2017) CS224n: Natural Language Processing with Deep Learning1"},{"issue":"4","key":"6016_CR36","first-page":"115","volume":"5","author":"WS McCulloch","year":"1943","unstructured":"McCulloch WS, Pitts W (1943) A logical calculus of the ideas immanent in nervous activity. Bull Math Biol 5(4):115\u2013133","journal-title":"Bull Math Biol"},{"key":"6016_CR37","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1016\/j.econmod.2019.08.011","volume":"87","author":"S McKnight","year":"2020","unstructured":"McKnight S, Mihailov A, Rumler F (2020) Inflation forecasting using the New Keynesian Phillips Curve with a time-varying trend. Econ Modell 87:383\u2013393","journal-title":"Econ Modell"},{"key":"6016_CR38","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1002\/(SICI)1099-131X(200004)19:3<201::AID-FOR753>3.0.CO;2-4","volume":"19","author":"S Moshiri","year":"2000","unstructured":"Moshiri S, Cameron N (2000) Econometrics versus ANN models in forecasting inflation. J Forecast 19:201\u2013217","journal-title":"J Forecast"},{"issue":"4","key":"6016_CR39","doi-asserted-by":"publisher","first-page":"642","DOI":"10.1016\/j.ijforecast.2009.08.007","volume":"25","author":"MH Pesaran","year":"2009","unstructured":"Pesaran MH, Schuermann T, Smith LV (2009) Forecasting economic and financial variables with global VARs. Int J Forecast 25(4):642\u2013675","journal-title":"Int J Forecast"},{"issue":"313","key":"6016_CR40","doi-asserted-by":"publisher","first-page":"85","DOI":"10.20430\/ete.v79i313.56","volume":"79","author":"P Pincheira","year":"2012","unstructured":"Pincheira P, Garc\u00eda \u00c1 (2012) En busca de un buen marco de referencia predictivo para la inflaci\u00f3n en Chile. El trimestre econ\u00f3mico 79(313):85\u2013123","journal-title":"El trimestre econ\u00f3mico"},{"issue":"3","key":"6016_CR41","doi-asserted-by":"publisher","first-page":"981","DOI":"10.1007\/s00181-015-1041-9","volume":"51","author":"P Pincheira","year":"2016","unstructured":"Pincheira P, Gatty A (2016) Forecasting Chilean inflation with international factors. Emp Econ 51(3):981\u20131010","journal-title":"Emp Econ"},{"key":"6016_CR42","unstructured":"Qi CR, Su H, Mo K, Guibas LJ (2017) Pointnet: Deep learning on point sets for 3D classification and segmentation. Proc. Computer Vision and Pattern Recognition (CVPR), IEEE, 1(2):4"},{"issue":"4","key":"6016_CR43","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1016\/j.neucom.2007.07.018","volume":"71","author":"I Rojas","year":"2008","unstructured":"Rojas I, Valenzuela O, Rojas F, Guill\u00e9n A, Herrera LJ, Pomares H, Marquez L, Pasadas M (2008) Soft-computing techniques and ARMA model for time series prediction. Neurocomputing 71(4):519\u2013537","journal-title":"Neurocomputing"},{"issue":"6","key":"6016_CR44","doi-asserted-by":"publisher","first-page":"386","DOI":"10.1037\/h0042519","volume":"65","author":"F Rosenblatt","year":"1958","unstructured":"Rosenblatt F (1958) The perceptron: a probabilistic model for information storage and organization in the brain. Psychol Rev 65(6):386","journal-title":"Psychol Rev"},{"key":"6016_CR45","doi-asserted-by":"crossref","unstructured":"Rumelhart DE, Hinton GE, Williams RJ (1985) Learning internal representations by error propagation. Technical report, California Univ San Diego La Jolla Inst for Cognitive Science","DOI":"10.21236\/ADA164453"},{"issue":"3","key":"6016_CR46","first-page":"1","volume":"5","author":"DE Rumelhart","year":"1988","unstructured":"Rumelhart DE, Hinton GE, Williams RJ et al (1988) Learning representations by back-propagating errors. Cognit Model 5(3):1","journal-title":"Cognit Model"},{"issue":"1","key":"6016_CR47","first-page":"77","volume":"29","author":"JC Santana","year":"2006","unstructured":"Santana JC (2006) Predicci\u00f3n de series temporales con redes neuronales: una aplicaci\u00f3n a la inflaci\u00f3n colombiana. Revista Colombiana de Estad\u00edstica 29(1):77\u201392","journal-title":"Revista Colombiana de Estad\u00edstica"},{"issue":"1","key":"6016_CR48","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1002\/for.2698","volume":"40","author":"T \u0160estanovi\u0107","year":"2021","unstructured":"\u0160estanovi\u0107 T, Arneri\u0107 J (2021) Neural network structure identification in inflation forecasting. J Forecast 40(1):62\u201379","journal-title":"J Forecast"},{"key":"6016_CR49","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1146\/annurev-bioeng-071516-044442","volume":"19","author":"D Shen","year":"2017","unstructured":"Shen D, Wu G, Suk H-I (2017) Deep learning in medical image analysis. Ann Revf Biomed Eng 19:221\u2013248","journal-title":"Ann Revf Biomed Eng"},{"key":"6016_CR50","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1111\/j.1538-4616.2007.00014.x","volume":"39","author":"JH Stock","year":"2007","unstructured":"Stock JH, Watson MW (2007) Why has US inflation become harder to forecast? J Money Credit Bank 39:3\u201334","journal-title":"J Money Credit Bank"},{"issue":"13","key":"6016_CR51","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/S1474-6670(17)62005-6","volume":"16","author":"T Takagi","year":"1983","unstructured":"Takagi T, Sugeno M (1983) Derivation of fuzzy control rules from human operator\u2019s control actions. IFAC Proc Vol 16(13):55\u201360","journal-title":"IFAC Proc Vol"},{"issue":"1","key":"6016_CR52","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1007\/s40503-014-0008-0","volume":"23","author":"M\u00c1 Tinoco-Zerme\u00f1o","year":"2014","unstructured":"Tinoco-Zerme\u00f1o M\u00c1, Venegas-Mart\u00ednez F, Torres-Preciado VH (2014) Growth, bank credit, and inflation in Mexico: evidence from an ARDL-bounds testing approach. Latin Am Econ Rev 23(1):8","journal-title":"Latin Am Econ Rev"},{"issue":"1","key":"6016_CR53","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/S0169-2070(00)00063-7","volume":"17","author":"G Tkacz","year":"2001","unstructured":"Tkacz G (2001) Neural network forecasting of Canadian GDP growth. Int J Forecast 17(1):57\u201369","journal-title":"Int J Forecast"},{"issue":"7","key":"6016_CR54","doi-asserted-by":"publisher","first-page":"769","DOI":"10.1016\/j.fss.2006.10.026","volume":"158","author":"E Vercher","year":"2007","unstructured":"Vercher E, Berm\u00fadez JD, Segura JV (2007) Fuzzy portfolio optimization under downside risk measures. Fuzzy Sets Syst 158(7):769\u2013782","journal-title":"Fuzzy Sets Syst"},{"key":"6016_CR55","unstructured":"Wang B, Yin P, Bertozzi AL, Brantingham PJ, Osher SJ, Xin J (2017) Deep Learning for Real-Time Crime Forecasting and its Ternarization. arXiv preprint arXiv:1711.08833"},{"key":"6016_CR56","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/j.eswa.2018.10.013","volume":"118","author":"Q Xu","year":"2019","unstructured":"Xu Q, Zhuo X, Jiang C, Liu Y (2019) An artificial neural network for mixed frequency data. Exp Syst Appl 118:127\u2013139","journal-title":"Exp Syst Appl"},{"key":"6016_CR57","doi-asserted-by":"crossref","unstructured":"Young T, Hazarika D, Poria S, Cambria E (2017) Recent trends in deep learning based natural language processing. arXiv preprint arXiv:1708.02709","DOI":"10.1109\/MCI.2018.2840738"}],"container-title":["Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-021-06016-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00500-021-06016-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-021-06016-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,4]],"date-time":"2023-02-04T22:06:43Z","timestamp":1675548403000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00500-021-06016-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,10]]},"references-count":57,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2021,8]]}},"alternative-id":["6016"],"URL":"https:\/\/doi.org\/10.1007\/s00500-021-06016-5","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-607554\/v1","asserted-by":"object"}]},"ISSN":["1432-7643","1433-7479"],"issn-type":[{"value":"1432-7643","type":"print"},{"value":"1433-7479","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,10]]},"assertion":[{"value":"28 June 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 July 2021","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.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}