{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T00:34:01Z","timestamp":1760402041216,"version":"build-2065373602"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"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":["Earth Sci Inform"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1007\/s12145-025-01978-8","type":"journal-article","created":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T09:55:55Z","timestamp":1755597355000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Sustainable water quality prediction using adaptive spider monkey optimization with Bi-LSTM"],"prefix":"10.1007","volume":"18","author":[{"given":"D. Justin","family":"Jose","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"C. Helen","family":"Sulochana","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"I. Jessy","family":"Mol","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,8,19]]},"reference":[{"issue":"4","key":"1978_CR1","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1061\/(ASCE)HE.1943-5584.0000322","volume":"16","author":"S Abudu","year":"2011","unstructured":"Abudu S, King JP, Bawazir AS (2011) Forecasting monthly streamflow of spring-summer runoff season in Rio Grande headwaters basin using stochastic hybrid modeling approach. J Hydrol Eng 16(4):384\u2013390","journal-title":"J Hydrol Eng"},{"key":"1978_CR2","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1007\/s00477-014-0907-2","volume":"29","author":"FK Arya","year":"2015","unstructured":"Arya FK, Zhang L (2015) Time series analysis of water quality parameters at Stillaguamish River using order series method. Stoch Env Res Risk Assess 29:227\u2013239","journal-title":"Stoch Env Res Risk Assess"},{"issue":"2","key":"1978_CR3","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1007\/s00477-020-01776-2","volume":"34","author":"R Barzegar","year":"2020","unstructured":"Barzegar R, Aalami MT, Adamowski J (2020) Short-term water quality variable prediction using a hybrid CNN\u2013LSTM deep learning model. Stoch Env Res Risk Assess 34(2):415\u2013433","journal-title":"Stoch Env Res Risk Assess"},{"key":"1978_CR4","first-page":"1","volume":"238","author":"J Bi","year":"2023","unstructured":"Bi J, Chen Z, Yuan H, Zhang J (2023) Accurate water quality prediction with attention-based bidirectional LSTM and encoder\u2013decoder. Expert Syst Appl 238:1\u201331","journal-title":"Expert Syst Appl"},{"key":"1978_CR5","doi-asserted-by":"crossref","first-page":"125168","DOI":"10.1016\/j.eswa.2024.125168","volume":"258","author":"X Cai","year":"2024","unstructured":"Cai X, Zhang Y, Li M, Wu L, Zhang W, Chen J (2024) Dynamic deadline constrained multi-objective workflow scheduling in multi-cloud environments. Expert Syst Appl 258:125168","journal-title":"Expert Syst Appl"},{"issue":"18","key":"1978_CR6","doi-asserted-by":"crossref","first-page":"6835","DOI":"10.1080\/03067319.2021.1963713","volume":"103","author":"P Chawla","year":"2023","unstructured":"Chawla P, Cao X, Fu Y, Hu CM, Wang M, Wang S, Gao JZ (2023) Water quality prediction of salt on sea using machine learning and big data techniques. Int J Environ Anal Chem 103(18):6835\u20136858","journal-title":"Int J Environ Anal Chem"},{"key":"1978_CR7","doi-asserted-by":"crossref","first-page":"106659","DOI":"10.1016\/j.compbiomed.2023.106659","volume":"155","author":"Y Chen","year":"2023","unstructured":"Chen Y, Feng L, Zheng C, Zhou T, Liu L, Liu P, Chen Y (2023a) LDANet: automatic lung parenchyma segmentation from CT images. Comput Biol Med 155:106659","journal-title":"Comput Biol Med"},{"key":"1978_CR8","doi-asserted-by":"crossref","first-page":"109882","DOI":"10.1016\/j.ecolind.2023.109882","volume":"146","author":"L Chen","year":"2023","unstructured":"Chen L, Wu T, Wang Z, Lin X, Cai Y (2023b) A novel hybrid BPNN model based on adaptive evolutionary artificial bee colony algorithm for water quality index prediction. Ecol Indic 146:109882","journal-title":"Ecol Indic"},{"issue":"1-3","key":"1978_CR9","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/S0304-3800(00)00395-1","volume":"138","author":"I Chubarenko","year":"2001","unstructured":"Chubarenko I, Tchepikova I (2001) Modelling of man-made contribution to salinity increase into the Vistula Lagoon (Baltic Sea). Ecol Model 138(1\u20133):87\u2013100","journal-title":"Ecol Model"},{"key":"1978_CR10","doi-asserted-by":"crossref","first-page":"124662","DOI":"10.1016\/j.eswa.2024.124662","volume":"255","author":"Z Cui","year":"2024","unstructured":"Cui Z, Shi Z, Li Q, Zhao T, Zhang W, Chen J (2024) Cooperative interference to achieve interval many-objective evolutionary algorithm for association privacy secure computing migration. Expert Syst Appl 255:124662","journal-title":"Expert Syst Appl"},{"issue":"2","key":"1978_CR11","doi-asserted-by":"crossref","first-page":"2917","DOI":"10.1109\/TNNLS.2024.3350085","volume":"36","author":"W Cui","year":"2025","unstructured":"Cui W, Xiang Y, Wang Y, Yu T, Liao X, Hu B (2025) Deep multiview module adaption transfer network for subject-specific EEG recognition. IEEE Trans Neural Netw Learn 36(2):2917\u20132930","journal-title":"IEEE Trans Neural Netw Learn"},{"issue":"10","key":"1978_CR12","doi-asserted-by":"crossref","first-page":"2611","DOI":"10.2166\/wst.2023.357","volume":"88","author":"J Dong","year":"2023","unstructured":"Dong J, Wang Z, Wu J, Huang J, Zhang C (2023) A water quality prediction model based on signal decomposition and ensemble deep learning techniques. Water Sci Technol 88(10):2611\u20132632","journal-title":"Water Sci Technol"},{"issue":"19","key":"1978_CR13","doi-asserted-by":"crossref","first-page":"8491","DOI":"10.1080\/03067319.2023.2206022","volume":"104","author":"JC Egbueri","year":"2024","unstructured":"Egbueri JC, Agbasi JC, Ikwuka CF, Chiaghanam OI, Khan MI, Khan MY, Khan N, Uwajingba HC (2024) Nitrate health risk and geochemical characteristics of water in a semi-urban: implications from graphical plots and statistical computing. Int J Environ Anal Chem 104(19):8491\u20138511","journal-title":"Int J Environ Anal Chem"},{"issue":"1","key":"1978_CR14","first-page":"13","volume":"4","author":"H Henderi","year":"2021","unstructured":"Henderi H, Wahyuningsih T, Rahwanto E (2021) Comparison of Min-Max normalization and Z-score normalization in the K-nearest neighbor (kNN) Algorithm to test the accuracy of types of breast cancer. Int J Informatics Inf Syst 4(1):13\u201320","journal-title":"Int J Informatics Inf Syst"},{"issue":"8","key":"1978_CR15","doi-asserted-by":"crossref","first-page":"4259","DOI":"10.3390\/su13084259","volume":"13","author":"M Hmoud Al-Adhaileh","year":"2021","unstructured":"Hmoud Al-Adhaileh M, Waselallah Alsaade F (2021) Modelling and prediction of water quality by using artificial intelligence. Sustainability 13(8):4259","journal-title":"Sustainability"},{"issue":"14","key":"1978_CR16","doi-asserted-by":"crossref","first-page":"6371","DOI":"10.1016\/j.eswa.2014.04.019","volume":"41","author":"N Hoque","year":"2014","unstructured":"Hoque N, Bhattacharyya DK, Kalita JK (2014) MIFS-ND: a mutual information-based feature selection method. Expert Syst Appl 41(14):6371\u20136385","journal-title":"Expert Syst Appl"},{"key":"1978_CR17","doi-asserted-by":"publisher","unstructured":"Hussien AG, Houssein EH, Hassanien AE (2017) A binary whale optimization algorithm with hyperbolic tangent fitness function for feature selection. In 2017 Eighth international conference on intelligent computing and information systems (ICICIS)\u00a0(pp. 166-172). IEEE, Cairo, Egypt, 05-07 December 2017. https:\/\/doi.org\/10.1109\/INTELCIS.2017.8260031","DOI":"10.1109\/INTELCIS.2017.8260031"},{"issue":"7","key":"1978_CR18","doi-asserted-by":"crossref","first-page":"5271","DOI":"10.1007\/s00521-024-10878-9","volume":"37","author":"DJ Jose","year":"2025","unstructured":"Jose DJ, Sulochana CH (2025) Chicken moth flame optimization and region-based convolution neural network for water quality prediction. Neural Comput Appl 37(7):5271\u20135288","journal-title":"Neural Comput Appl"},{"issue":"2","key":"1978_CR19","doi-asserted-by":"crossref","first-page":"431","DOI":"10.2166\/wcc.2023.403","volume":"15","author":"K Karthick","year":"2024","unstructured":"Karthick K, Krishnan S, Manikandan R (2024) Water quality prediction: a data-driven approach exploiting advanced machine learning algorithms with data augmentation. J Water Clim Change 15(2):431\u2013452","journal-title":"J Water Clim Change"},{"key":"1978_CR20","doi-asserted-by":"crossref","first-page":"8091","DOI":"10.1007\/s11042-020-10139-6","volume":"80","author":"S Katoch","year":"2021","unstructured":"Katoch S, Chauhan SS, Kumar V (2021) A review on genetic algorithm: past, present, and future. Multimed Tools Appl 80:8091\u20138126","journal-title":"Multimed Tools Appl"},{"issue":"03","key":"1978_CR21","doi-asserted-by":"crossref","first-page":"2450009","DOI":"10.1142\/S2382624X24500097","volume":"10","author":"TH Kim","year":"2024","unstructured":"Kim TH (2024) The impact of a coastal water quality policy in South Korea: evidence from the total pollution load management program. Water Econ Policy 10(03):2450009","journal-title":"Water Econ Policy"},{"issue":"7","key":"1978_CR22","doi-asserted-by":"crossref","first-page":"1322","DOI":"10.3390\/ijerph15071322","volume":"15","author":"S Lee","year":"2018","unstructured":"Lee S, Lee D (2018) Improved prediction of harmful algal blooms in four Major South Korea\u2019s Rivers using deep learning models. Int J Environ Res Public Health 15(7):1322","journal-title":"Int J Environ Res Public Health"},{"issue":"19","key":"1978_CR23","doi-asserted-by":"crossref","first-page":"19879","DOI":"10.1007\/s11356-019-05116-y","volume":"26","author":"L Li","year":"2019","unstructured":"Li L, Jiang P, Xu H, Lin G, Guo D, Wu H (2019) Water quality prediction based on recurrent neural network and improved evidence theory: a case study of Qiantang River, China. Environ Sci Pollut Res 26(19):19879\u201319896","journal-title":"Environ Sci Pollut Res"},{"key":"1978_CR24","doi-asserted-by":"crossref","first-page":"39471","DOI":"10.1007\/s11356-021-13276-z","volume":"28","author":"Y Li","year":"2021","unstructured":"Li Y, Chiu YH, Li Y, Cen H, Lin TY (2021a) Dynamic analysis of residential and enterprise water supply and leakage efficiencies. Environ Sci Pollut Res 28:39471\u201339492","journal-title":"Environ Sci Pollut Res"},{"issue":"11","key":"1978_CR25","doi-asserted-by":"crossref","first-page":"12189","DOI":"10.1109\/TCYB.2021.3071860","volume":"52","author":"Y Li","year":"2021","unstructured":"Li Y, Liu Y, Guo YZ, Liao XF, Hu B, Yu T (2021b) Spatio-Temporal-Spectral Hierarchical Graph Convolutional Network with Semisupervised Active Learning for Patient-Specific Seizure Prediction. IEEE Trans Cybern 52(11):12189\u201312204","journal-title":"IEEE Trans Cybern"},{"key":"1978_CR26","doi-asserted-by":"crossref","first-page":"24784","DOI":"10.1109\/ACCESS.2020.2971253","volume":"8","author":"J Liu","year":"2020","unstructured":"Liu J, Yu C, Hu Z, Zhao Y, Bai Y, Xie M, Luo J (2020) Accurate prediction scheme of water quality in smart mariculture with deep Bi-S-SRU learning network. IEEE Access 8:24784\u201324798","journal-title":"IEEE Access"},{"key":"1978_CR27","doi-asserted-by":"publisher","unstructured":"Liu J, Yu C, Hu Z, Zhao Y, Xia X, Tu Z, Li R (2018) Automatic and accurate prediction of key water quality parameters based on SRU deep learning in mariculture. In\u00a02018 IEEE International conference on advanced manufacturing (ICAM)\u00a0(pp. 437-440). IEEE, Yunlin, Taiwan, 16-18 November 2018. https:\/\/doi.org\/10.1109\/AMCON.2018.8615048","DOI":"10.1109\/AMCON.2018.8615048"},{"key":"1978_CR28","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1016\/j.neucom.2021.08.030","volume":"463","author":"W Lu","year":"2021","unstructured":"Lu W, Zhao H, He Q, Huang H, Jin X (2021) Category-consistent deep network learning for accurate vehicle logo recognition. Neurocomputing 463:623\u2013636","journal-title":"Neurocomputing"},{"key":"1978_CR29","doi-asserted-by":"crossref","first-page":"104349","DOI":"10.1016\/j.jwpe.2023.104349","volume":"56","author":"H Moeinzadeh","year":"2023","unstructured":"Moeinzadeh H, Jegakumaran P, Yong KT, Withana A (2023) Efficient water quality prediction by synthesizing seven heavy metal parameters using deep neural network. J Water Process Eng 56:104349","journal-title":"J Water Process Eng"},{"issue":"1","key":"1978_CR30","doi-asserted-by":"crossref","first-page":"7520","DOI":"10.1038\/s41598-024-56775-y","volume":"14","author":"MK Nallakaruppan","year":"2024","unstructured":"Nallakaruppan MK, Gangadevi E, Shri ML, Balusamy B, Bhattacharya S, Selvarajan S (2024) Reliable water quality prediction and parametric analysis using explainable AI models. Scientific Rep 14(1):7520","journal-title":"Scientific Rep"},{"issue":"1-3","key":"1978_CR31","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/0304-3800(95)00126-3","volume":"89","author":"SS Park","year":"1996","unstructured":"Park SS, Lee YS (1996) A multiconstituent moving segment model for water quality predictions in steep and shallow streams. Ecol Model 89(1\u20133):121\u2013131","journal-title":"Ecol Model"},{"issue":"1","key":"1978_CR32","doi-asserted-by":"crossref","first-page":"24534","DOI":"10.1038\/s41598-024-74881-9","volume":"14","author":"S Qu","year":"2024","unstructured":"Qu S, Liu H, Xu Y, Wang L, Liu Y, Zhang L, Song J, Li Z (2024) Application of spiral enhanced whale optimization algorithm in solving optimization problems. Scientific Rep 14(1):24534","journal-title":"Scientific Rep"},{"key":"1978_CR33","doi-asserted-by":"crossref","first-page":"101049","DOI":"10.1016\/j.gsd.2023.101049","volume":"23","author":"AM Sajib","year":"2023","unstructured":"Sajib AM, Diganta MTM, Rahman A, Dabrowski T, Olbert AI, Uddin MG (2023) Developing a novel tool for assessing the groundwater incorporating water quality index and machine learning approach. Groundw Sustain Dev 23:101049","journal-title":"Groundw Sustain Dev"},{"key":"1978_CR34","doi-asserted-by":"publisher","unstructured":"Shafi U, Mumtaz R, Anwar H, Qamar AM, Khurshid H (2018) Surface water pollution detection using internet of things. In\u00a02018 15th international conference on smart cities: improving quality of life using ICT & IoT (HONET-ICT)\u00a0(pp. 92-96). IEEE, Islamabad, Pakistan, 08-10 October 2018. https:\/\/doi.org\/10.1109\/HONET.2018.8551341","DOI":"10.1109\/HONET.2018.8551341"},{"issue":"12","key":"1978_CR35","doi-asserted-by":"crossref","first-page":"35307","DOI":"10.1007\/s11042-023-16737-4","volume":"83","author":"MY Shams","year":"2024","unstructured":"Shams MY, Elshewey AM, El-Kenawy ESM, Ibrahim A, Talaat FM, Tarek Z (2024) Water quality prediction using machine learning models based on grid search method. Multimed Tools Appl 83(12):35307\u201335334","journal-title":"Multimed Tools Appl"},{"key":"1978_CR36","first-page":"43","volume-title":"Evolutionary and swarm intelligence algorithms","author":"H Sharma","year":"2019","unstructured":"Sharma H, Hazrati G, Bansal JC (2019) Spider monkey optimization algorithm. Evolutionary and swarm intelligence algorithms. Springer International Publishing, Cham, pp 43\u201359"},{"key":"1978_CR37","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.neucom.2019.12.083","volume":"385","author":"R Su","year":"2020","unstructured":"Su R, Liu T, Sun C, Jin Q, Jennane R, Wei L (2020) Fusing convolutional neural network features with hand-crafted features for osteoporosis diagnoses. Neurocomputing 385:300\u2013309","journal-title":"Neurocomputing"},{"issue":"5","key":"1978_CR38","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1007\/s10661-024-12603-4","volume":"196","author":"K Swarnkar","year":"2024","unstructured":"Swarnkar K, Gupta K, Nikam V (2024) Water quality monitoring and modeling for an urban storm drainage channel in Thane, India. Environ Monit Assess 196(5):440","journal-title":"Environ Monit Assess"},{"issue":"03","key":"1978_CR39","doi-asserted-by":"crossref","first-page":"2240005","DOI":"10.1142\/S2382624X22400057","volume":"9","author":"K Swedberg","year":"2023","unstructured":"Swedberg K, Boyle KJ, Stachelek J, Ward NK, Weng W, Cobourn KM (2023) Examining implicit price variation for lake water quality. Water Econ Policy 9(03):2240005","journal-title":"Water Econ Policy"},{"issue":"2","key":"1978_CR40","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1007\/s10661-024-12365-z","volume":"196","author":"F Teixeira de Mello","year":"2024","unstructured":"Teixeira de Mello F, Sierra P, Moi DA, Alonso J, Lucas C, Su\u00e1rez B, Alvareda E, Alvarez J, Andrade MS, Arimon L, Urtado L (2024) Effects of urbanization and accessibility to sanitation services on water quality in urban streams in Uruguay. Environ Monit Assess 196(2):185","journal-title":"Environ Monit Assess"},{"key":"1978_CR41","doi-asserted-by":"crossref","first-page":"128081","DOI":"10.1016\/j.jhydrol.2022.128081","volume":"612","author":"H Wan","year":"2022","unstructured":"Wan H, Xu R, Zhang M, Cai Y, Li J, Shen X (2022) A novel model for water quality prediction caused by non-point sources pollution based on deep learning and feature extraction methods. J Hydrol 612:128081","journal-title":"J Hydrol"},{"key":"1978_CR42","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1007\/s00500-016-2474-6","volume":"22","author":"D Wang","year":"2018","unstructured":"Wang D, Tan D, Liu L (2018) Particle swarm optimization algorithm: an overview. Soft Comput 22:387\u2013408","journal-title":"Soft Comput"},{"key":"1978_CR43","unstructured":"Water Quality Prediction database is taken from (2024) https:\/\/www.kaggle.com\/code\/imakash3011\/water-quality-prediction-7-model\/notebook. Accessed on January 2024"},{"issue":"4","key":"1978_CR44","doi-asserted-by":"crossref","first-page":"610","DOI":"10.3390\/w14040610","volume":"14","author":"J Wu","year":"2022","unstructured":"Wu J, Wang Z (2022) A hybrid model for water quality prediction based on an artificial neural network, wavelet transform, and long short-term memory. Water 14(4):610","journal-title":"Water"},{"key":"1978_CR45","doi-asserted-by":"crossref","first-page":"119410","DOI":"10.1016\/j.eswa.2022.119410","volume":"215","author":"L Wu","year":"2023","unstructured":"Wu L, Huang X, Cui J, Liu C, Xiao W (2023) Modified adaptive ant colony optimization algorithm and its application for solving path planning of mobile robot. Expert Syst Appl 215:119410","journal-title":"Expert Syst Appl"},{"key":"1978_CR46","doi-asserted-by":"publisher","unstructured":"Xue H, Huynh DQ, Reynolds M (2017) Bi-prediction: Pedestrian trajectory prediction based on bidirectional LSTM classification. In 2017 International conference on digital image computing: techniques and applications (DICTA)\u00a0(pp. 1-8). IEEE, Sydney, NSW, Australia, 29 November 2017 - 01 December 2017. https:\/\/doi.org\/10.1109\/DICTA.2017.8227412","DOI":"10.1109\/DICTA.2017.8227412"}],"container-title":["Earth Science Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12145-025-01978-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12145-025-01978-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12145-025-01978-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:24:27Z","timestamp":1760361867000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12145-025-01978-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,19]]},"references-count":46,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["1978"],"URL":"https:\/\/doi.org\/10.1007\/s12145-025-01978-8","relation":{},"ISSN":["1865-0473","1865-0481"],"issn-type":[{"type":"print","value":"1865-0473"},{"type":"electronic","value":"1865-0481"}],"subject":[],"published":{"date-parts":[[2025,8,19]]},"assertion":[{"value":"19 December 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 August 2025","order":3,"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":"Conflict of interest"}},{"value":"Not Applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Not Applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}],"article-number":"500"}}