{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T15:57:26Z","timestamp":1776700646031,"version":"3.51.2"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T00:00:00Z","timestamp":1757289600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T00:00:00Z","timestamp":1757289600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"Frontier Technology Research for Intelligent TBM Base","award":["KY202412-158"],"award-info":[{"award-number":["KY202412-158"]}]},{"name":"Funds for Talent Team Development in Double First-Class Universities"},{"name":"Independent Project of State Key Laboratory of Fluid Power and Mechatronic Systems","award":["SKLoFP_ZZ_2505"],"award-info":[{"award-number":["SKLoFP_ZZ_2505"]}]},{"name":"Pioneer and Leading Goose R&D Program of Zhejiang","award":["2025C01078"],"award-info":[{"award-number":["2025C01078"]}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2024YFF0505303"],"award-info":[{"award-number":["2024YFF0505303"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Complex Intell. Syst."],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1007\/s40747-025-02081-7","type":"journal-article","created":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T09:26:46Z","timestamp":1757410006000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Motion planning for hyper-redundant manipulator systems: combining path following and improved APF-RRT* Path finding"],"prefix":"10.1007","volume":"11","author":[{"given":"Hongcheng","family":"Ji","sequence":"first","affiliation":[]},{"given":"Cheng","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Chengzhen","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0977-8719","authenticated-orcid":false,"given":"Haibo","family":"Xie","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,9,8]]},"reference":[{"key":"2081_CR1","doi-asserted-by":"publisher","unstructured":"Du Z-C, Ouyang G-Y, Xue J, Yao Y-B (2020) A review on kinematic, workspace, trajectory planning and path planning of hyper-redundant manipulators. In: 2020 10th Institute of Electrical and Electronics Engineers international conference on cyber technology in automation, control, and intelligent systems (CYBER), pp 444\u2013449. https:\/\/doi.org\/10.1109\/CYBER50695.2020.9279171","DOI":"10.1109\/CYBER50695.2020.9279171"},{"key":"2081_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.fusengdes.2024.114334","volume":"202","author":"S Buonocore","year":"2024","unstructured":"Buonocore S, Zoppoli A, Gironimo GD (2024) An obstacle avoidance path planning algorithm to simulate hyper redundant manipulators for tokamaks maintenance. Fusion Eng Des 202:114334. https:\/\/doi.org\/10.1016\/j.fusengdes.2024.114334","journal-title":"Fusion Eng Des"},{"issue":"3","key":"2081_CR3","doi-asserted-by":"publisher","first-page":"4817","DOI":"10.32604\/cmc.2022.026845","volume":"72","author":"L Zhang","year":"2022","unstructured":"Zhang L, Huang S, Du Z, Ouyang G, Chen H (2022) Motion-planning algorithm for a hyper-redundant manipulator in narrow spaces. Comput Mater Continua 72(3):4817\u20134832. https:\/\/doi.org\/10.32604\/cmc.2022.026845","journal-title":"Comput Mater Continua"},{"issue":"5","key":"2081_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1115\/1.4055934","volume":"15","author":"Y Huang","year":"2023","unstructured":"Huang Y, Yan L, Yang T, Hu Z, Xu W (2023) Sensing design, trajectory planning, and motion control of a cable-driven redundant manipulator composed of quaternion joints. J Mech Robot 15(5):1\u201322. https:\/\/doi.org\/10.1115\/1.4055934","journal-title":"J Mech Robot"},{"issue":"2","key":"2081_CR5","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1109\/TMRB.2023.3269568","volume":"5","author":"Q Gao","year":"2023","unstructured":"Gao Q, Ji G, Sun Z (2023) Robust shape-distortion prediction for a wire-driven hyper-redundant manipulator with engaging rolling joints. IEEE Trans Med Robot Bionics 5(2):265\u2013277. https:\/\/doi.org\/10.1109\/TMRB.2023.3269568","journal-title":"IEEE Trans Med Robot Bionics"},{"issue":"4","key":"2081_CR6","doi-asserted-by":"publisher","first-page":"1693","DOI":"10.1109\/TMECH.2018.2842141","volume":"23","author":"W Xu","year":"2018","unstructured":"Xu W, Liu T, Li Y (2018) Kinematics, dynamics, and control of a cable-driven hyper-redundant manipulator. IEEE\/ASME Trans Mechatron 23(4):1693\u20131704. https:\/\/doi.org\/10.1109\/TMECH.2018.2842141","journal-title":"IEEE\/ASME Trans Mechatron"},{"key":"2081_CR7","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/j.actaastro.2017.06.015","volume":"139","author":"W Xu","year":"2017","unstructured":"Xu W, Mu Z, Liu T, Liang B (2017) A modified modal method for solving the mission-oriented inverse kinematics of hyper-redundant space manipulators for on-orbit servicing. Acta Astronaut 139:54\u201366. https:\/\/doi.org\/10.1016\/j.actaastro.2017.06.015","journal-title":"Acta Astronaut"},{"key":"2081_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2024.109402","volume":"138","author":"Y Sun","year":"2024","unstructured":"Sun Y, Tao H, Stojanovic V (2024) Autoregressive data generation method based on wavelet packet transform and cascaded stochastic quantization for bearing fault diagnosis under unbalanced samples. Eng Appl Artif Intell 138:109402. https:\/\/doi.org\/10.1016\/j.engappai.2024.109402","journal-title":"Eng Appl Artif Intell"},{"issue":"4","key":"2081_CR9","doi-asserted-by":"publisher","first-page":"6591","DOI":"10.1109\/TII.2023.3346993","volume":"20","author":"M Luo","year":"2024","unstructured":"Luo M, Tian Y, Li E, Chen M, Tan M (2024) A local obstacle avoidance and global planning method for the follow-the-leader motion of coiled hyper-redundant manipulators. IEEE Trans Ind Inf 20(4):6591\u20136602. https:\/\/doi.org\/10.1109\/TII.2023.3346993","journal-title":"IEEE Trans Ind Inf"},{"issue":"10","key":"2081_CR10","doi-asserted-by":"publisher","first-page":"3473","DOI":"10.1002\/acs.3885","volume":"38","author":"Z Peng","year":"2024","unstructured":"Peng Z, Song X, Song S, Stojanovic V (2024) Spatiotemporal fault estimation for switched nonlinear reaction\u2013diffusion systems via adaptive iterative learning. Int J Adapt Control Signal Process 38(10):3473\u20133483. https:\/\/doi.org\/10.1002\/acs.3885","journal-title":"Int J Adapt Control Signal Process"},{"key":"2081_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.mechmachtheory.2022.104967","volume":"176","author":"C Lauretti","year":"2022","unstructured":"Lauretti C, Grasso T, Marchi E, Grazioso S, Gironimo G (2022) A geometric approach to inverse kinematics of hyper-redundant manipulators for tokamaks maintenance. Mech Mach Theory 176:104967. https:\/\/doi.org\/10.1016\/j.mechmachtheory.2022.104967","journal-title":"Mech Mach Theory"},{"issue":"5","key":"2081_CR12","doi-asserted-by":"publisher","first-page":"1746","DOI":"10.1109\/TSMC.2017.2784828","volume":"50","author":"Z Mu","year":"2020","unstructured":"Mu Z, Yuan H, Xu W, Liu T, Liang B (2020) A segmented geometry method for kinematics and configuration planning of spatial hyper-redundant manipulators. IEEE Trans Syst Man Cybern Syst 50(5):1746\u20131756. https:\/\/doi.org\/10.1109\/TSMC.2017.2784828","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"issue":"5","key":"2081_CR13","doi-asserted-by":"publisher","first-page":"172988141987463","DOI":"10.1177\/1729881419874638","volume":"16","author":"H Xie","year":"2019","unstructured":"Xie H, Wang C, Li S, Hu L, Yang H (2019) A geometric approach for follow-the-leader motion of serpentine manipulator. Int J Adv Robot Syst 16(5):1729881419874638. https:\/\/doi.org\/10.1177\/1729881419874638","journal-title":"Int J Adv Robot Syst"},{"issue":"1","key":"2081_CR14","doi-asserted-by":"publisher","first-page":"172988142199614","DOI":"10.1177\/1729881421996148","volume":"18","author":"L Zhao","year":"2021","unstructured":"Zhao L, Jiang Z, Sun Y, Zhao J, Liu H (2021) Collision-free kinematics for hyper-redundant manipulators in dynamic scenes using optimal velocity obstacles. Int J Adv Robot Syst 18(1):1729881421996148. https:\/\/doi.org\/10.1177\/1729881421996148","journal-title":"Int J Adv Robot Syst"},{"issue":"9","key":"2081_CR15","doi-asserted-by":"publisher","first-page":"1251","DOI":"10.1177\/0278364914528132","volume":"33","author":"J Schulman","year":"2014","unstructured":"Schulman J, Duan Y, Ho J, Lee A, Awwal I, Bradlow H, Pan J, Patil S, Goldberg K, Abbeel P (2014) Motion planning with sequential convex optimization and convex collision checking. Int J Robot Res 33(9):1251\u20131270. https:\/\/doi.org\/10.1177\/0278364914528132","journal-title":"Int J Robot Res"},{"key":"2081_CR16","doi-asserted-by":"publisher","unstructured":"Wang J, Miao R, Ma J, Shi H (2024) Search-based motion planning with task-space motion primitives for hyper-redundant manipulators in cluttered environment. In: 2024 6th international conference on reconfigurable mechanisms and robots (ReMAR), pp 554\u2013559. https:\/\/doi.org\/10.1109\/ReMAR61031.2024.10618160","DOI":"10.1109\/ReMAR61031.2024.10618160"},{"issue":"7","key":"2081_CR17","doi-asserted-by":"publisher","first-page":"2388","DOI":"10.1017\/S0263574724000791","volume":"42","author":"R Ju","year":"2024","unstructured":"Ju R, Zhang D, Gai Y, Cao Z (2024) A local collision-free motion planning strategy for hyper-redundant manipulators based on dynamic safety envelopes. Robotica 42(7):2388\u20132402. https:\/\/doi.org\/10.1017\/S0263574724000791","journal-title":"Robotica"},{"issue":"4","key":"2081_CR18","doi-asserted-by":"publisher","first-page":"172988062211100","DOI":"10.1177\/17298806221110022","volume":"19","author":"Y Lin","year":"2022","unstructured":"Lin Y, Wang J, Xiao X, Qu J, Qin F (2022) A snake-inspired path planning algorithm based on reinforcement learning and self-motion for hyper-redundant manipulators. Int J Adv Robot Syst 19(4):17298806221110022. https:\/\/doi.org\/10.1177\/17298806221110022","journal-title":"Int J Adv Robot Syst"},{"issue":"8","key":"2081_CR19","doi-asserted-by":"publisher","first-page":"2677","DOI":"10.1017\/S0263574724001048","volume":"42","author":"D Zhang","year":"2024","unstructured":"Zhang D, Ju R, Cao Z (2024) DDPG-based path planning for cable-driven manipulators in multi-obstacle environments. Robotica 42(8):2677\u20132689. https:\/\/doi.org\/10.1017\/S0263574724001048","journal-title":"Robotica"},{"key":"2081_CR20","doi-asserted-by":"publisher","DOI":"10.3390\/math12233822","author":"H Xu","year":"2024","unstructured":"Xu H, Xue C, Chen Q, Yang J, Liang B (2024) Continuous multi-target approaching control of hyper-redundant manipulators based on reinforcement learning. Mathematics. https:\/\/doi.org\/10.3390\/math12233822","journal-title":"Mathematics"},{"issue":"15","key":"2081_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.jfranklin.2024.107112","volume":"361","author":"L Gao","year":"2024","unstructured":"Gao L, Zhuang Z, Tao H, Chen Y, Stojanovic V (2024) Non-lifted norm optimal iterative learning control for networked dynamical systems: a computationally efficient approach. J Franklin Inst 361(15):107112. https:\/\/doi.org\/10.1016\/j.jfranklin.2024.107112","journal-title":"J Franklin Inst"},{"key":"2081_CR22","doi-asserted-by":"publisher","unstructured":"Lee K, Koo JC, Choi HR, Moon H (2015) An RRT* path planning for kinematically constrained hyper-redundant inpipe robot. In: 2015 12th international conference on ubiquitous robots and ambient intelligence (URAI), pp 121\u2013128. https:\/\/doi.org\/10.1109\/URAI.2015.7358875","DOI":"10.1109\/URAI.2015.7358875"},{"key":"2081_CR23","doi-asserted-by":"publisher","unstructured":"Gammell JD, Srinivasa SS, Barfoot TD (2014) Informed RRT*: optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic. In: 2014 IEEE\/rsj international conference on intelligent robots and systems, pp 2997\u20133004. https:\/\/doi.org\/10.1109\/IROS.2014.6942976","DOI":"10.1109\/IROS.2014.6942976"},{"issue":"1","key":"2081_CR24","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1007\/s11370-017-0242-9","volume":"11","author":"M-C Kim","year":"2018","unstructured":"Kim M-C, Song J-B (2018) Informed RRT* with improved converging rate by adopting wrapping procedure. Intel Serv Robot 11(1):53\u201360. https:\/\/doi.org\/10.1007\/s11370-017-0242-9","journal-title":"Intel Serv Robot"},{"key":"2081_CR25","doi-asserted-by":"publisher","first-page":"19842","DOI":"10.1109\/ACCESS.2020.2969316","volume":"8","author":"R Mashayekhi","year":"2020","unstructured":"Mashayekhi R, Idris MYI, Anisi MH, Ahmedy I, Ali I (2020) Informed RRT*-connect: an asymptotically optimal single-query path planning method. IEEE Access 8:19842\u201319852. https:\/\/doi.org\/10.1109\/ACCESS.2020.2969316","journal-title":"IEEE Access"},{"issue":"11","key":"2081_CR26","doi-asserted-by":"publisher","first-page":"2033","DOI":"10.1007\/s12541-019-00224-8","volume":"20","author":"H Ryu","year":"2019","unstructured":"Ryu H, Park Y (2019) Improved informed RRT* using gridmap skeletonization for mobile robot path planning. Int J Precis Eng Manuf 20(11):2033\u20132039. https:\/\/doi.org\/10.1007\/s12541-019-00224-8","journal-title":"Int J Precis Eng Manuf"},{"key":"2081_CR27","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.eswa.2019.01.032","volume":"123","author":"I-B Jeong","year":"2019","unstructured":"Jeong I-B, Lee S-J, Kim J-H (2019) Quick-RRT*: triangular inequality-based implementation of RRT* with improved initial solution and convergence rate. Expert Syst Appl 123:82\u201390. https:\/\/doi.org\/10.1016\/j.eswa.2019.01.032","journal-title":"Expert Syst Appl"},{"key":"2081_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.robot.2015.02.007","volume":"68","author":"AH Qureshi","year":"2015","unstructured":"Qureshi AH, Ayaz Y (2015) Intelligent bidirectional rapidly-exploring random trees for optimal motion planning in complex cluttered environments. Robot Auton Syst 68:1\u201311. https:\/\/doi.org\/10.1016\/j.robot.2015.02.007","journal-title":"Robot Auton Syst"},{"issue":"6","key":"2081_CR29","doi-asserted-by":"publisher","first-page":"8273","DOI":"10.1007\/s40747-024-01576-z","volume":"10","author":"Y Zhou","year":"2024","unstructured":"Zhou Y, Lu Y, Lv L (2024) GVP-RRT: a grid based variable probability rapidly-exploring random tree algorithm for AGV path planning. Complex Intell Syst 10(6):8273\u20138286. https:\/\/doi.org\/10.1007\/s40747-024-01576-z","journal-title":"Complex Intell Syst"},{"issue":"12","key":"2081_CR30","doi-asserted-by":"publisher","first-page":"8128","DOI":"10.1109\/LRA.2023.3325716","volume":"8","author":"H Ji","year":"2023","unstructured":"Ji H, Xie H, Wang C, Yang H (2023) E-RRT*: path planning for hyper-redundant manipulators. IEEE Robot Autom Lett 8(12):8128\u20138135. https:\/\/doi.org\/10.1109\/LRA.2023.3325716","journal-title":"IEEE Robot Autom Lett"},{"issue":"6","key":"2081_CR31","doi-asserted-by":"publisher","first-page":"7249","DOI":"10.1007\/s40747-023-01111-6","volume":"9","author":"J Cong","year":"2023","unstructured":"Cong J, Hu J, Wang Y, He Z, Han L, Su M (2023) FF-RRT*: a sampling-improved path planning algorithm for mobile robots against concave cavity obstacle. Complex Intell Syst 9(6):7249\u20137267. https:\/\/doi.org\/10.1007\/s40747-023-01111-6","journal-title":"Complex Intell Syst"},{"issue":"10","key":"2081_CR32","doi-asserted-by":"publisher","first-page":"8587","DOI":"10.1109\/LRA.2024.3448198","volume":"9","author":"A Cohen","year":"2024","unstructured":"Cohen A, Sintov A, Zarrouk D (2024) Motion planning for minimally actuated serial robots. IEEE Robot Autom Lett 9(10):8587\u20138594. https:\/\/doi.org\/10.1109\/LRA.2024.3448198","journal-title":"IEEE Robot Autom Lett"},{"key":"2081_CR33","doi-asserted-by":"publisher","unstructured":"Wei H, Zheng Y, Gu G (2021) RRT-based path planning for follow-the-leader motion of hyper-redundant manipulators. In: 2021 IEEE\/RSJ international conference on intelligent robots and systems (IROS), pp 3198\u20133204. https:\/\/doi.org\/10.1109\/IROS51168.2021.9635876","DOI":"10.1109\/IROS51168.2021.9635876"},{"key":"2081_CR34","doi-asserted-by":"publisher","unstructured":"Deng J, Li Z, Zheng Y, Gu G (2022) An RRT-based motion planning method for hyper-redundant manipulators in confined spaces. In: 2022 IEEE international conference on robotics and biomimetics (ROBIO), pp 1067\u20131073. https:\/\/doi.org\/10.1109\/ROBIO55434.2022.10011650","DOI":"10.1109\/ROBIO55434.2022.10011650"},{"key":"2081_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.116379","volume":"193","author":"L Jia","year":"2022","unstructured":"Jia L, Huang Y, Chen T, Guo Y, Yin Y, Chen J (2022) MDA + RRT: a general approach for resolving the problem of angle constraint for hyper-redundant manipulator. Expert Syst Appl 193:116379. https:\/\/doi.org\/10.1016\/j.eswa.2021.116379","journal-title":"Expert Syst Appl"},{"issue":"1","key":"2081_CR36","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1109\/TMECH.2023.3289871","volume":"29","author":"L Zhang","year":"2024","unstructured":"Zhang L, Gao Y, Mu Z, Yan L, Li Z, Gao M (2024) A variable-stiffness planning method considering both the overall configuration and cable tension for hyper-redundant manipulators. IEEE\/ASME Trans Mechatron 29(1):659\u2013667. https:\/\/doi.org\/10.1109\/TMECH.2023.3289871","journal-title":"IEEE\/ASME Trans Mechatron"},{"key":"2081_CR37","doi-asserted-by":"publisher","unstructured":"Huang S (2021) Path planning based on mixed algorithm of RRT and artificial potential field method. In: 2021 4th international conference on intelligent robotics and control engineering (IRCE), pp 149\u2013155. https:\/\/doi.org\/10.1109\/IRCE53649.2021.9570910","DOI":"10.1109\/IRCE53649.2021.9570910"},{"key":"2081_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.119137","volume":"213","author":"J Fan","year":"2023","unstructured":"Fan J, Chen X, Liang X (2023) UAV trajectory planning based on bi-directional APF-RRT* algorithm with goal-biased. Expert Syst Appl 213:119137. https:\/\/doi.org\/10.1016\/j.eswa.2022.119137","journal-title":"Expert Syst Appl"},{"key":"2081_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.123571","volume":"249","author":"Z Feng","year":"2024","unstructured":"Feng Z, Zhou L, Qi J, Hong S (2024) DBVS-APF-RRT*: a global path planning algorithm with ultra-high speed generation of initial paths and high optimal path quality. Expert Syst Appl 249:123571. https:\/\/doi.org\/10.1016\/j.eswa.2024.123571","journal-title":"Expert Syst Appl"}],"container-title":["Complex & Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-025-02081-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40747-025-02081-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-025-02081-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T13:33:29Z","timestamp":1758807209000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40747-025-02081-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,8]]},"references-count":39,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2025,10]]}},"alternative-id":["2081"],"URL":"https:\/\/doi.org\/10.1007\/s40747-025-02081-7","relation":{},"ISSN":["2199-4536","2198-6053"],"issn-type":[{"value":"2199-4536","type":"print"},{"value":"2198-6053","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,8]]},"assertion":[{"value":"6 May 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 September 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 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 interest"}}],"article-number":"441"}}