{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T00:14:59Z","timestamp":1768522499009,"version":"3.49.0"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T00:00:00Z","timestamp":1731542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T00:00:00Z","timestamp":1731542400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Complex Intell. Syst."],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1007\/s40747-024-01667-x","type":"journal-article","created":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T13:30:43Z","timestamp":1731591043000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Two-stage deep reinforcement learning method for agile optical satellite scheduling problem"],"prefix":"10.1007","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2244-7367","authenticated-orcid":false,"given":"Zheng","family":"Liu","sequence":"first","affiliation":[]},{"given":"Wei","family":"Xiong","sequence":"additional","affiliation":[]},{"given":"Zhuoya","family":"Jia","sequence":"additional","affiliation":[]},{"given":"Chi","family":"Han","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,14]]},"reference":[{"issue":"6","key":"1667_CR1","doi-asserted-by":"publisher","first-page":"901","DOI":"10.3390\/rs12060901","volume":"12","author":"PP De Bem","year":"2020","unstructured":"De Bem PP, Carvalho Junior OA, Fontes Guimar\u00e3es R, Trancoso Gomes RA (2020) Change detection of deforestation in the Brazilian amazon using landsat data and convolutional neural networks. Remote Sens 12(6):901","journal-title":"Remote Sens"},{"key":"1667_CR2","doi-asserted-by":"crossref","unstructured":"Singh P, Pandey PC, Petropoulos GP, Pavlides A, Srivastava PK, Koutsias N, Deng KAK, Bao Y (2020) Hyperspectral remote sensing in precision agriculture: Present status, challenges, and future trends. In: Hyperspectral Remote Sensing, pp. 121\u2013 146. Elsevier","DOI":"10.1016\/B978-0-08-102894-0.00009-7"},{"issue":"6","key":"1667_CR3","doi-asserted-by":"publisher","first-page":"213","DOI":"10.3390\/ijgi7060213","volume":"7","author":"J Chen","year":"2018","unstructured":"Chen J, Liu H, Hou J, Yang M, Deng M (2018) Improving building change detection in VHR remote sensing imagery by combining coarse location and co-segmentation. ISPRS Int J Geo-Inform 7(6):213","journal-title":"ISPRS Int J Geo-Inform"},{"key":"1667_CR4","doi-asserted-by":"publisher","first-page":"1626","DOI":"10.23919\/JSEE.2023.000020","volume":"34","author":"H Chi","year":"2023","unstructured":"Chi H, Wei X, Minghui X, Zhen L (2023) Support vector regression-based operational effectiveness evaluation approach to reconnaissance satellite system. J Syst Eng Electron 34:1626\u20131644","journal-title":"J Syst Eng Electron"},{"issue":"2","key":"1667_CR5","doi-asserted-by":"publisher","first-page":"1921","DOI":"10.1109\/JSYST.2021.3072122","volume":"16","author":"Z Lu","year":"2021","unstructured":"Lu Z, Shen X, Li D, Chen Y, Li D (2021) A mission planning modeling method of multipoint target imaging within a single pass for super-agile earth observation satellite. IEEE Syst J 16(2):1921\u20131932","journal-title":"IEEE Syst J"},{"issue":"5","key":"1667_CR6","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1016\/S1270-9638(02)01173-2","volume":"6","author":"M Lema\u00eetre","year":"2002","unstructured":"Lema\u00eetre M, Verfaillie G, Jouhaud F, Lachiver J-M, Bataille N (2002) Selecting and scheduling observations of agile satellites. Aerosp Sci Technol 6(5):367\u2013381","journal-title":"Aerosp Sci Technol"},{"issue":"5","key":"1667_CR7","doi-asserted-by":"publisher","first-page":"3520","DOI":"10.1109\/TAES.2021.3088490","volume":"57","author":"T Stollenwerk","year":"2021","unstructured":"Stollenwerk T, Michaud V, Lobe E, Picard M, Basermann A, Botter T (2021) Agile earth observation satellite scheduling with a quantum annealer. IEEE Trans Aerosp Electron Syst 57(5):3520\u20133528","journal-title":"IEEE Trans Aerosp Electron Syst"},{"key":"1667_CR8","doi-asserted-by":"crossref","unstructured":"Chopra J, Kumar A, Aggarwal AK, Marwaha A ( 2018) An efficient watermarking for protecting signature biometric template. In: 2018 5th International Conference on Signal Processing and Integrated Networks (SPIN), pp. 413\u2013 418 . IEEE","DOI":"10.1109\/SPIN.2018.8474269"},{"key":"1667_CR9","doi-asserted-by":"crossref","unstructured":"Garg M, Ubhi JS, Aggarwal AK ( 2021) Deep learning for obstacle avoidance in autonomous driving. In: Autonomous Driving and Advanced Driver-assistance Systems (ADAS), pp. 233\u2013 246. CRC Press","DOI":"10.1201\/9781003048381-11"},{"key":"1667_CR10","doi-asserted-by":"crossref","unstructured":"Aggarwal AK (2021) Gps-based localization of autonomous vehicles. In: Autonomous Driving and Advanced Driver-Assistance Systems (ADAS), pp. 437\u2013 448. CRC Press","DOI":"10.1201\/9781003048381-24"},{"issue":"2","key":"1667_CR11","first-page":"199","volume":"10","author":"DS Maini","year":"2018","unstructured":"Maini DS, Aggarwal AK (2018) Camera position estimation using 2d image dataset. Int J Innov Eng Technol 10(2):199\u2013203","journal-title":"Int J Innov Eng Technol"},{"key":"1667_CR12","unstructured":"Nazari M, Oroojlooy A, Snyder L, Tak\u00e1c M (2018) Reinforcement learning for solving the vehicle routing problem. Adv Neur Inform Process Syst 31"},{"key":"1667_CR13","unstructured":"Kool W, Van\u00a0Hoof H, Welling M (2018) Attention, learn to solve routing problems! arXiv preprint arXiv:1803.08475"},{"key":"1667_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.114784","volume":"175","author":"CA Rigo","year":"2021","unstructured":"Rigo CA, Seman LO, Camponogara E, Morsch Filho E, Bezerra EA (2021) A nanosatellite task scheduling framework to improve mission value using fuzzy constraints. Expert Syst Appl 175:114784","journal-title":"Expert Syst Appl"},{"key":"1667_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2021.105626","volume":"139","author":"J Zhang","year":"2022","unstructured":"Zhang J, Xing L (2022) An improved genetic algorithm for the integrated satellite imaging and data transmission scheduling problem. Comput Oper Res 139:105626","journal-title":"Comput Oper Res"},{"key":"1667_CR16","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/j.eswa.2015.12.039","volume":"51","author":"R Xu","year":"2016","unstructured":"Xu R, Chen H, Liang X, Wang H (2016) Priority-based constructive algorithms for scheduling agile earth observation satellites with total priority maximization. Expert Syst Appl 51:195\u2013206","journal-title":"Expert Syst Appl"},{"issue":"4","key":"1667_CR17","doi-asserted-by":"publisher","first-page":"3162","DOI":"10.1109\/TAES.2020.2966902","volume":"56","author":"J Li","year":"2020","unstructured":"Li J, Li C, Wang F (2020) Automatic scheduling for earth observation satellite with temporal specifications. IEEE Trans Aerosp Electron Syst 56(4):3162\u20133169","journal-title":"IEEE Trans Aerosp Electron Syst"},{"key":"1667_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2023.04.003","volume":"636","author":"J Wu","year":"2023","unstructured":"Wu J, Yao F, Song Y, He L, Lu F, Du Y, Yan J, Chen Y, Xing L, Ou J (2023) Frequent pattern-based parallel search approach for time-dependent agile earth observation satellite scheduling. Inform Sci 636:118924","journal-title":"Inform Sci"},{"issue":"4","key":"1667_CR19","doi-asserted-by":"publisher","first-page":"3090","DOI":"10.1109\/TAES.2022.3146115","volume":"58","author":"A Chatterjee","year":"2022","unstructured":"Chatterjee A, Tharmarasa R (2022) Reward factor-based multiple agile satellites scheduling with energy and memory constraints. IEEE Trans Aerosp Electron Syst 58(4):3090\u20133103","journal-title":"IEEE Trans Aerosp Electron Syst"},{"key":"1667_CR20","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1016\/j.cor.2019.05.030","volume":"111","author":"G Peng","year":"2019","unstructured":"Peng G, Dewil R, Verbeeck C, Gunawan A, Xing L, Vansteenwegen P (2019) Agile earth observation satellite scheduling: An orienteering problem with time-dependent profits and travel times. Comput Oper Res 111:84\u201398","journal-title":"Comput Oper Res"},{"key":"1667_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2020.104946","volume":"120","author":"G Peng","year":"2020","unstructured":"Peng G, Song G, Xing L, Gunawan A, Vansteenwegen P (2020) An exact algorithm for agile earth observation satellite scheduling with time-dependent profits. Comput Oper Res 120:104946","journal-title":"Comput Oper Res"},{"key":"1667_CR22","first-page":"7345941","volume":"2017","author":"X Chu","year":"2017","unstructured":"Chu X, Chen Y, Xing L et al (2017) A branch and bound algorithm for agile earth observation satellite scheduling. Discrete Dynam Nat Soc 2017:7345941","journal-title":"Discrete Dynam Nat Soc"},{"issue":"11","key":"1667_CR23","first-page":"611","volume":"15","author":"D-H Cho","year":"2018","unstructured":"Cho D-H, Kim J-H, Choi H-L, Ahn J (2018) Optimization-based scheduling method for agile earth-observing satellite constellation. J Aerosp Inform Syst 15(11):611\u2013626","journal-title":"J Aerosp Inform Syst"},{"key":"1667_CR24","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1016\/j.ast.2017.11.009","volume":"72","author":"Y She","year":"2018","unstructured":"She Y, Li S, Zhao Y (2018) Onboard mission planning for agile satellite using modified mixed-integer linear programming. Aerosp Sci Technol 72:204\u2013216","journal-title":"Aerosp Sci Technol"},{"key":"1667_CR25","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1016\/j.chaos.2015.12.003","volume":"83","author":"X Wang","year":"2016","unstructured":"Wang X, Chen Z, Han C (2016) Scheduling for single agile satellite, redundant targets problem using complex networks theory. Chaos Solitons Fractals 83:125\u2013132","journal-title":"Chaos Solitons Fractals"},{"key":"1667_CR26","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.sysarc.2019.03.005","volume":"95","author":"Y He","year":"2019","unstructured":"He Y, Chen Y, Lu J, Chen C, Wu G (2019) Scheduling multiple agile earth observation satellites with an edge computing framework and a constructive heuristic algorithm. J Syst Archit 95:55\u201366","journal-title":"J Syst Archit"},{"issue":"6","key":"1667_CR27","first-page":"285","volume":"17","author":"J Kim","year":"2020","unstructured":"Kim J, Ahn J, Choi H-L, Cho D-H (2020) Task scheduling of agile satellites with transition time and stereoscopic imaging constraints. J Aerosp Inform Syst 17(6):285\u2013293","journal-title":"J Aerosp Inform Syst"},{"key":"1667_CR28","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1016\/j.actaastro.2017.04.027","volume":"137","author":"Z Zheng","year":"2017","unstructured":"Zheng Z, Guo J, Gill EKA (2017) Swarm satellite mission scheduling & planning using hybrid dynamic mutation genetic algorithm. Acta Astronautica 137:243\u2013253","journal-title":"Acta Astronautica"},{"key":"1667_CR29","doi-asserted-by":"publisher","first-page":"3837","DOI":"10.3233\/JIFS-212034","volume":"42","author":"B Yan","year":"2021","unstructured":"Yan B, Wang Y, Xia W, Hu X, Ma H, Jin P (2021) An improved method for satellite emergency mission scheduling scheme group decision-making incorporating pso and multimoora. J Intell Fuzzy Syst 42:3837\u20133853","journal-title":"J Intell Fuzzy Syst"},{"key":"1667_CR30","doi-asserted-by":"publisher","first-page":"531","DOI":"10.1016\/j.actaastro.2022.09.020","volume":"204","author":"X Wu","year":"2022","unstructured":"Wu X, Yang Y, Sun Y, Xie Y, Song X, Huang B (2022) Dynamic regional splitting planning of remote sensing satellite swarm using parallel genetic PSO algorithm. Acta Astronautica 204:531\u2013551","journal-title":"Acta Astronautica"},{"key":"1667_CR31","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/j.cor.2017.04.006","volume":"86","author":"X Liu","year":"2017","unstructured":"Liu X, Laporte G, Chen Y, He R (2017) An adaptive large neighborhood search metaheuristic for agile satellite scheduling with time-dependent transition time. Comput Oper Res 86:41\u201353","journal-title":"Comput Oper Res"},{"key":"1667_CR32","doi-asserted-by":"publisher","first-page":"1051","DOI":"10.1007\/s10845-019-01518-4","volume":"31","author":"L He","year":"2019","unstructured":"He L, Weerdt MD, Yorke-Smith N (2019) Time\/sequence-dependent scheduling: the design and evaluation of a general purpose tabu-based adaptive large neighbourhood search algorithm. J Intellig Manuf 31:1051\u20131078","journal-title":"J Intellig Manuf"},{"key":"1667_CR33","doi-asserted-by":"publisher","first-page":"1421","DOI":"10.1080\/0305215X.2019.1657113","volume":"52","author":"K Luo","year":"2020","unstructured":"Luo K (2020) A hybrid binary artificial bee colony algorithm for the satellite photograph scheduling problem. Eng Optimiz 52:1421\u20131440","journal-title":"Eng Optimiz"},{"key":"1667_CR34","doi-asserted-by":"publisher","first-page":"108823","DOI":"10.1016\/j.cie.2022.108823","volume":"174","author":"J Wu","year":"2022","unstructured":"Wu J, Song B, Zhang G, Ou J, Chen Y, Yao F, He L, Xing L (2022) A data-driven improved genetic algorithm for agile earth observation satellite scheduling with time-dependent transition time. Comput Ind Eng 174:108823","journal-title":"Comput Ind Eng"},{"key":"1667_CR35","first-page":"103211","volume":"117","author":"Z Lu","year":"2023","unstructured":"Lu Z, Shen X, Li DJ, Li D, Chen Y, Wang D, Shen S (2023) Multiple super-agile satellite collaborative mission planning for area target imaging. Int J Appl Earth Obs Geoinform 117:103211","journal-title":"Int J Appl Earth Obs Geoinform"},{"key":"1667_CR36","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.cor.2018.06.020","volume":"100","author":"L He","year":"2018","unstructured":"He L, Liu X, Laporte G, Chen YW, Chen Y (2018) An improved adaptive large neighborhood search algorithm for multiple agile satellites scheduling. Comput Oper Res 100:12\u201325","journal-title":"Comput Oper Res"},{"key":"1667_CR37","doi-asserted-by":"publisher","first-page":"40006","DOI":"10.1109\/ACCESS.2023.3269066","volume":"11","author":"Y Yang","year":"2023","unstructured":"Yang Y, Liu D (2023) A hybrid discrete artificial bee colony algorithm for imaging satellite mission planning. IEEE Access 11:40006\u201340017","journal-title":"IEEE Access"},{"issue":"3","key":"1667_CR38","doi-asserted-by":"publisher","first-page":"1463","DOI":"10.1109\/TSMC.2020.3020732","volume":"52","author":"Y He","year":"2020","unstructured":"He Y, Xing L, Chen Y, Pedrycz W, Wang L, Wu G (2020) A generic Markov decision process model and reinforcement learning method for scheduling agile earth observation satellites. IEEE Trans Syst Man Cybernet Syst 52(3):1463\u20131474","journal-title":"IEEE Trans Syst Man Cybernet Syst"},{"key":"1667_CR39","doi-asserted-by":"crossref","unstructured":"Chen M, Chen Y, Chen Y, Qi W ( 2019) Deep reinforcement learning for agile satellite scheduling problem. In: 2019 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 126\u2013 132 . IEEE","DOI":"10.1109\/SSCI44817.2019.9002957"},{"key":"1667_CR40","doi-asserted-by":"publisher","first-page":"107607","DOI":"10.1016\/j.asoc.2021.107607","volume":"110","author":"L Wei","year":"2021","unstructured":"Wei L, Chen Y, Chen M, Chen Y (2021) Deep reinforcement learning and parameter transfer based approach for the multi-objective agile earth observation satellite scheduling problem. Appl Soft Comput 110:107607","journal-title":"Appl Soft Comput"},{"key":"1667_CR41","doi-asserted-by":"publisher","first-page":"4503","DOI":"10.3390\/rs15184503","volume":"15","author":"W Huang","year":"2023","unstructured":"Huang W, Li Z, He X, Xiang J, Du X, Liang X (2023) Drl-based dynamic destroy approaches for agile-satellite mission planning. Remote Sens 15:4503","journal-title":"Remote Sens"},{"issue":"19","key":"1667_CR42","doi-asserted-by":"publisher","first-page":"4059","DOI":"10.3390\/math11194059","volume":"11","author":"J Chun","year":"2023","unstructured":"Chun J, Yang W, Liu X, Wu G, He L, Xing L (2023) Deep reinforcement learning for the agile earth observation satellite scheduling problem. Mathematics 11(19):4059","journal-title":"Mathematics"},{"issue":"7","key":"1667_CR43","first-page":"346","volume":"17","author":"X Zhao","year":"2020","unstructured":"Zhao X, Wang Z, Zheng G (2020) Two-phase neural combinatorial optimization with reinforcement learning for agile satellite scheduling. J Aerosp Inform Syst 17(7):346\u2013357","journal-title":"J Aerosp Inform Syst"},{"key":"1667_CR44","unstructured":"Vinyals O, Fortunato M, Jaitly N (2015) Pointer networks. Adv Neural Inform Process Syst 28"},{"key":"1667_CR45","doi-asserted-by":"crossref","unstructured":"Yue A, Feng B, Xueqin C, Yanjun D, Chaoyong EL (2019) Preparation of papers for IFAC conferences & symposia: autonomous distribution algorithm for formation satellites under emergent imaging requests. IFAC-PapersOnLine","DOI":"10.1016\/j.ifacol.2019.11.286"},{"key":"1667_CR46","unstructured":"Haarnoja T, Zhou A, Abbeel P, Levine S ( 2018) Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor. In: International Conference on Machine Learning, pp. 1861\u2013 1870 . PMLR"},{"key":"1667_CR47","unstructured":"Fujimoto S, Hoof H, Meger D (2018) Addressing function approximation error in actor-critic methods. In: International Conference on Machine Learning, pp. 1587\u2013 1596. PMLR"},{"key":"1667_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2023.101236","volume":"77","author":"Y Song","year":"2023","unstructured":"Song Y, Wei L, Yang Q, Wu J, Xing L, Chen Y (2023) RL-GA: a reinforcement learning-based genetic algorithm for electromagnetic detection satellite scheduling problem. Swarm Evolut Comput 77:101236","journal-title":"Swarm Evolut Comput"},{"key":"1667_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2022.108890","volume":"176","author":"Z Zhou","year":"2023","unstructured":"Zhou Z, Chen E, Wu F, Chang Z, Xing L (2023) Multi-satellite scheduling problem with marginal decreasing imaging duration: an improved adaptive ant colony algorithm. Comput Ind Eng 176:108890","journal-title":"Comput Ind Eng"},{"key":"1667_CR50","doi-asserted-by":"crossref","unstructured":"Wu X, Yang Y, Xie Y, Ma Q, Zhang Z (2023) Multi-region mission planning by satellite swarm using simulated annealing and neighborhood search. IEEE Trans Aerosp Electron Syst","DOI":"10.1109\/TAES.2023.3337066"},{"key":"1667_CR51","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2022.108823","volume":"174","author":"J Wu","year":"2022","unstructured":"Wu J, Song B, Zhang G, Ou J, Chen Y, Yao F, He L, Xing L (2022) A data-driven improved genetic algorithm for agile earth observation satellite scheduling with time-dependent transition time. Comput Ind Eng 174:108823","journal-title":"Comput Ind Eng"}],"container-title":["Complex &amp; Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-024-01667-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40747-024-01667-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-024-01667-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,30]],"date-time":"2025-01-30T20:16:24Z","timestamp":1738268184000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40747-024-01667-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,14]]},"references-count":51,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["1667"],"URL":"https:\/\/doi.org\/10.1007\/s40747-024-01667-x","relation":{},"ISSN":["2199-4536","2198-6053"],"issn-type":[{"value":"2199-4536","type":"print"},{"value":"2198-6053","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,14]]},"assertion":[{"value":"27 March 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 September 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 November 2024","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 that they have no competing interest, financial or non-financial, that could influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Approval of publication.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}],"article-number":"35"}}