{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T19:52:22Z","timestamp":1783540342721,"version":"3.55.0"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2024,9,27]],"date-time":"2024-09-27T00:00:00Z","timestamp":1727395200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,9,27]],"date-time":"2024-09-27T00:00:00Z","timestamp":1727395200000},"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":["SIViP"],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1007\/s11760-024-03529-y","type":"journal-article","created":{"date-parts":[[2024,9,27]],"date-time":"2024-09-27T15:02:44Z","timestamp":1727449364000},"page":"9051-9066","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["An adaptable physics-informed fault diagnosis approach via hybrid signal processing and transferable feature learning for structural\/machinery health monitoring"],"prefix":"10.1007","volume":"18","author":[{"given":"Milad","family":"Zarchi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Majid","family":"Shahgholi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kong Fah","family":"Tee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,9,27]]},"reference":[{"key":"3529_CR1","doi-asserted-by":"publisher","DOI":"10.1177\/1077546321997600","author":"H Abolhassanpour","year":"2021","unstructured":"Abolhassanpour, H., Ashenai Ghasemi, F., Shahgholi, M., Mohamadi, A.: Stability and vibration analysis of an axially moving thin-walled conical shell. J. Vib. Control (2021). https:\/\/doi.org\/10.1177\/1077546321997600","journal-title":"J. Vib. Control"},{"issue":"6","key":"3529_CR2","doi-asserted-by":"publisher","first-page":"1001","DOI":"10.1177\/1077546315587611","volume":"23","author":"S Bab","year":"2017","unstructured":"Bab, S., Khadem, S., Mahdiabadi, M., Shahgholi, M.: Vibration mitigation of a rotating beam under external periodic force using a nonlinear energy sink (NES). J. Vib. Control 23(6), 1001\u20131025 (2017)","journal-title":"J. Vib. Control"},{"key":"3529_CR3","doi-asserted-by":"publisher","DOI":"10.1177\/1077546321993585","author":"A Fasihi","year":"2021","unstructured":"Fasihi, A., Shahgholi, M., Ghahremani, S.: The effects of nonlinear energy sink and piezoelectric energy harvester on aeroelastic instability of an airfoil. J. Vib. Control (2021). https:\/\/doi.org\/10.1177\/1077546321993585","journal-title":"J. Vib. Control"},{"issue":"12","key":"3529_CR4","doi-asserted-by":"publisher","first-page":"1873","DOI":"10.1177\/1077546315603270","volume":"23","author":"S Mehrdad Pourkiaee","year":"2017","unstructured":"Mehrdad Pourkiaee, S., Khadem, S.E., Shahgholi, M.: Nonlinear vibration and stability analysis of an electrically actuated piezoelectric nanobeam considering surface effects and intermolecular interactions. J. Vib. Control 23(12), 1873\u20131889 (2017)","journal-title":"J. Vib. Control"},{"key":"3529_CR5","doi-asserted-by":"publisher","first-page":"833","DOI":"10.1007\/s13349-021-00483-y","volume":"11","author":"PG Hubbard","year":"2021","unstructured":"Hubbard, P.G., Xu, J., Zhang, S., et al.: Dynamic structural health monitoring of a model wind turbine tower using distributed acoustic sensing (DAS). J Civil Struct Health Monit 11, 833\u2013849 (2021). https:\/\/doi.org\/10.1007\/s13349-021-00483-y","journal-title":"J Civil Struct Health Monit"},{"key":"3529_CR6","doi-asserted-by":"publisher","first-page":"294","DOI":"10.1016\/j.ymssp.2017.12.009","volume":"105","author":"A Moshrefzadeh","year":"2018","unstructured":"Moshrefzadeh, A., Fasana, A.: The autogram: an effective approach for selecting the optimal demodulation band in rolling element bearings diagnosis. Mech. Syst. Signal Process. 105, 294\u2013318 (2018). https:\/\/doi.org\/10.1016\/j.ymssp.2017.12.009","journal-title":"Mech. Syst. Signal Process."},{"key":"3529_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2020.107908","author":"Z Zheng","year":"2020","unstructured":"Zheng, Z., Li, X., Zhu, Y.: Feature extraction of the hydraulic pump fault based on improved autogram. Measurement (2020). https:\/\/doi.org\/10.1016\/j.measurement.2020.107908","journal-title":"Measurement"},{"key":"3529_CR8","doi-asserted-by":"publisher","first-page":"106891","DOI":"10.1016\/j.ymssp.2020.106891","volume":"144","author":"A Mauricio","year":"2020","unstructured":"Mauricio, A., Smith, W.A., Randall, R.B., Antoni, J., Gryllias, K.: Improved Envelope Spectrum via Feature Optimisation-gram (IESFOgram): a novel tool for rolling element bearing diagnostics under non-stationary operating conditions. Mech. Syst. Signal Process. 144, 106891 (2020). https:\/\/doi.org\/10.1016\/j.ymssp.2020.106891","journal-title":"Mech. Syst. Signal Process."},{"key":"3529_CR9","doi-asserted-by":"publisher","first-page":"10852","DOI":"10.1016\/j.ymssp.2021.108524","volume":"167","author":"J Park","year":"2022","unstructured":"Park, J., Kim, Y., Na, K., Youn, B.D., Chen, Y., Zuo, M.J., Bae, Y.-C.: An image-based feature extraction method for fault diagnosis of variable-speed rotating machinery. Mech. Syst. Signal Process. 167, 10852 (2022). https:\/\/doi.org\/10.1016\/j.ymssp.2021.108524","journal-title":"Mech. Syst. Signal Process."},{"issue":"12","key":"3529_CR10","doi-asserted-by":"publisher","first-page":"e2839","DOI":"10.1002\/stc.2839","volume":"28","author":"J Tian","year":"2021","unstructured":"Tian, J., Yi, G.-W., Fei, C.-W., Zhou, J., Ai, Y.-T., Zhang, F.-L.: Quantum entropy-based hierarchical strategy for inter-shaft bearing fault detection. Struct. Control. Health Monit. 28(12), e2839 (2021). https:\/\/doi.org\/10.1002\/stc.2839","journal-title":"Struct. Control. Health Monit."},{"key":"3529_CR11","doi-asserted-by":"publisher","first-page":"e2686","DOI":"10.1002\/stc.2686","volume":"28","author":"CG Krishnanunni","year":"2021","unstructured":"Krishnanunni, C.G., Rao, B.N.: Indirect health monitoring of bridges using Tikhonov regularization scheme and signal averaging technique. Struct. Control. Health Monit. 28, e2686 (2021). https:\/\/doi.org\/10.1002\/stc.2686","journal-title":"Struct. Control. Health Monit."},{"key":"3529_CR12","doi-asserted-by":"publisher","first-page":"e2299","DOI":"10.1002\/stc.2299","volume":"26","author":"M Makki Alamdari","year":"2019","unstructured":"Makki Alamdari, M., Anaissi, A., Khoa, N.L.D., Mustapha, S.: Frequency domain decomposition-based multisensor data fusion for assessment of progressive damage in structures. Struct. Control. Health Monit. 26, e2299 (2019). https:\/\/doi.org\/10.1002\/stc.2299","journal-title":"Struct. Control. Health Monit."},{"key":"3529_CR13","doi-asserted-by":"publisher","first-page":"e2583","DOI":"10.1002\/stc.2583","volume":"27","author":"Z Zhang","year":"2020","unstructured":"Zhang, Z., Sun, C.: A numerical study on multi-site damage identification: a data-driven method via constrained independent component analysis. Struct. Control. Health Monit. 27, e2583 (2020). https:\/\/doi.org\/10.1002\/stc.2583","journal-title":"Struct. Control. Health Monit."},{"key":"3529_CR14","doi-asserted-by":"publisher","first-page":"e1960","DOI":"10.1002\/stc.1960","volume":"24","author":"K Lakshmi","year":"2017","unstructured":"Lakshmi, K., Rao, A.R.M., Gopalakrishnan, N.: Singular spectrum analysis combined with ARMAX model for structural damage detection. Struct. Control. Health Monit. 24, e1960 (2017). https:\/\/doi.org\/10.1002\/stc.1960","journal-title":"Struct. Control. Health Monit."},{"key":"3529_CR15","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1002\/stc.285","volume":"17","author":"A Moustafa","year":"2010","unstructured":"Moustafa, A., Mahadevan, S., Daigle, M., Biswas, G.: Structural and sensor damage identification using the bond graph approach. Struct. Control. Health Monit. 17, 178\u2013197 (2010). https:\/\/doi.org\/10.1002\/stc.285","journal-title":"Struct. Control. Health Monit."},{"key":"3529_CR16","doi-asserted-by":"publisher","first-page":"e2672","DOI":"10.1002\/stc.2672","volume":"28","author":"D Zhao","year":"2021","unstructured":"Zhao, D., Gelman, L., Chu, F., Ball, A.: Vibration health monitoring of rolling bearings under variable speed conditions by novel demodulation technique. Struct. Control. Health Monit. 28, e2672 (2021). https:\/\/doi.org\/10.1002\/stc.2672","journal-title":"Struct. Control. Health Monit."},{"key":"3529_CR17","doi-asserted-by":"publisher","first-page":"107334","DOI":"10.1016\/j.ymssp.2020.107334","volume":"151","author":"AR Bastami","year":"2021","unstructured":"Bastami, A.R., Vahid, S.: A comprehensive evaluation of the effect of defect size in rolling element bearings on the statistical features of the vibration signal. Mech. Syst. Signal Process. 151, 107334 (2021). https:\/\/doi.org\/10.1016\/j.ymssp.2020.107334","journal-title":"Mech. Syst. Signal Process."},{"key":"3529_CR18","doi-asserted-by":"publisher","first-page":"107767","DOI":"10.1016\/j.measurement.2020.107767","volume":"159","author":"AR Bastami","year":"2020","unstructured":"Bastami, A.R., Vahid, S.: Estimating the size of naturally generated defects in the outer ring and roller of a tapered roller bearing based on autoregressive model combined with envelope analysis and discrete wavelet transform. Measurement 159, 107767 (2020). https:\/\/doi.org\/10.1016\/j.measurement.2020.107767","journal-title":"Measurement"},{"issue":"18","key":"3529_CR19","doi-asserted-by":"publisher","first-page":"3224","DOI":"10.1177\/0954406217734885","volume":"232","author":"M Behzad","year":"2018","unstructured":"Behzad, M., Arghand, H.A., Rohani, B.A.: Remaining useful life prediction of ball-bearings based on high-frequency vibration features. Proc. Inst. Mech. Eng. C J. Mech. Eng. Sci. 232(18), 3224\u20133234 (2018). https:\/\/doi.org\/10.1177\/0954406217734885","journal-title":"Proc. Inst. Mech. Eng. C J. Mech. Eng. Sci."},{"issue":"3","key":"3529_CR20","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1177\/0954408911422635","volume":"226","author":"M Behzad","year":"2012","unstructured":"Behzad, M., Bastami, A.R., Mba, D.: Rolling bearing fault detection by short-time statistical features. Proc. Inst. Mech. Eng. Part E J. Process Mech. Eng. 226(3), 229\u2013237 (2012). https:\/\/doi.org\/10.1177\/0954408911422635","journal-title":"Proc. Inst. Mech. Eng. Part E J. Process Mech. Eng."},{"issue":"4","key":"3529_CR21","doi-asserted-by":"publisher","first-page":"041011","DOI":"10.1115\/1.4003595","volume":"133","author":"M Behzad","year":"2011","unstructured":"Behzad, M., Bastami, A.R., Mba, D.: a new model for estimating vibrations generated in the defective rolling element bearings. ASME. J. Vib. Acoust. 133(4), 041011 (2011). https:\/\/doi.org\/10.1115\/1.4003595","journal-title":"ASME. J. Vib. Acoust."},{"issue":"3\u20134","key":"3529_CR22","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1177\/1077546319877702","volume":"26","author":"A Rohani Bastami","year":"2020","unstructured":"Rohani Bastami, A., Bashari, A.: Rolling element bearing diagnosis using spectral kurtosis based on optimized impulse response wavelet. J. Vib. Control 26(3\u20134), 175\u2013185 (2020). https:\/\/doi.org\/10.1177\/1077546319877702","journal-title":"J. Vib. Control"},{"key":"3529_CR23","doi-asserted-by":"publisher","DOI":"10.1177\/10775463221138172","author":"M Zarchi","year":"2022","unstructured":"Zarchi, M., Shahgholi, M.: A novel information fusion approach using weighted neural networks for intelligent multi-class diagnostics of rotating machinery with unseen working conditions. J. Vib. Control (2022). https:\/\/doi.org\/10.1177\/10775463221138172","journal-title":"J. Vib. Control"},{"key":"3529_CR24","doi-asserted-by":"publisher","DOI":"10.1007\/s42417-022-00702-w","author":"M Zarchi","year":"2022","unstructured":"Zarchi, M., Shahgholi, M.: An expert condition monitoring system via fusion of signal processing for vibration of industrial rotating machinery with unseen operational conditions. J. Vib. Eng. Technol. (2022). https:\/\/doi.org\/10.1007\/s42417-022-00702-w","journal-title":"J. Vib. Eng. Technol."},{"key":"3529_CR25","doi-asserted-by":"publisher","first-page":"595","DOI":"10.1007\/s13349-020-00404-5","volume":"10","author":"L Chiriatti","year":"2020","unstructured":"Chiriatti, L., Fran\u00e7ois, P., Mercado-Mendoza, H., et al.: Monitoring of the rebar-concrete bond structural health through ultrasonic measurements: application to recycled aggregate concrete. J Civil Struct Health Monit 10, 595\u2013607 (2020). https:\/\/doi.org\/10.1007\/s13349-020-00404-5","journal-title":"J Civil Struct Health Monit"},{"key":"3529_CR26","doi-asserted-by":"publisher","first-page":"741","DOI":"10.1007\/s13349-019-00364-5","volume":"9","author":"M Jahangiri","year":"2019","unstructured":"Jahangiri, M., Hadianfard, M.A.: Vibration-based structural health monitoring using symbiotic organism search based on an improved objective function. J Civil Struct Health Monit 9, 741\u2013755 (2019). https:\/\/doi.org\/10.1007\/s13349-019-00364-5","journal-title":"J Civil Struct Health Monit"},{"key":"3529_CR27","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1007\/s13349-019-00322-1","volume":"9","author":"RC dos Santos","year":"2019","unstructured":"dos Santos, R.C., Larocca, A.P.C., de Ara\u00fajo Neto, J.O., et al.: Detection of a curved bridge deck vibration using robotic total stations for structural health monitoring. J Civil Struct Health Monit 9, 63\u201376 (2019). https:\/\/doi.org\/10.1007\/s13349-019-00322-1","journal-title":"J Civil Struct Health Monit"},{"key":"3529_CR28","doi-asserted-by":"publisher","first-page":"845","DOI":"10.1007\/s13349-020-00421-4","volume":"10","author":"A Entezami","year":"2020","unstructured":"Entezami, A., Sarmadi, H., Saeedi Razavi, B.: An innovative hybrid strategy for structural health monitoring by modal flexibility and clustering methods. J Civil Struct Health Monit 10, 845\u2013859 (2020). https:\/\/doi.org\/10.1007\/s13349-020-00421-4","journal-title":"J Civil Struct Health Monit"},{"key":"3529_CR29","doi-asserted-by":"publisher","DOI":"10.1007\/s13349-022-00565-5","author":"P Gardner","year":"2022","unstructured":"Gardner, P., Bull, L.A., Dervilis, N., et al.: Domain-adapted Gaussian mixture models for population-based structural health monitoring. J Civil Struct Health Monit (2022). https:\/\/doi.org\/10.1007\/s13349-022-00565-5","journal-title":"J Civil Struct Health Monit"},{"key":"3529_CR30","doi-asserted-by":"publisher","DOI":"10.1007\/s13349-022-00566-4","author":"E Favarelli","year":"2022","unstructured":"Favarelli, E., Testi, E., Giorgetti, A.: The impact of sensing parameters on data management and anomaly detection in structural health monitoring. J Civil Struct Health Monit (2022). https:\/\/doi.org\/10.1007\/s13349-022-00566-4","journal-title":"J Civil Struct Health Monit"},{"key":"3529_CR31","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1007\/s13349-021-00547-z","volume":"12","author":"TH Kwon","year":"2022","unstructured":"Kwon, T.H., Park, S.H., Park, S.I., et al.: Correction to: Building information modeling-based bridge health monitoring for anomaly detection under complex loading conditions using artificial neural networks. J Civil Struct Health Monit 12, 483 (2022). https:\/\/doi.org\/10.1007\/s13349-021-00547-z","journal-title":"J Civil Struct Health Monit"},{"key":"3529_CR32","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1007\/s13349-020-00466-5","volume":"11","author":"MH Daneshvar","year":"2021","unstructured":"Daneshvar, M.H., Gharighoran, A., Zareei, S.A., et al.: Structural health monitoring using high-dimensional features from time series modeling by innovative hybrid distance-based methods. J Civil Struct Health Monit 11, 537\u2013557 (2021). https:\/\/doi.org\/10.1007\/s13349-020-00466-5","journal-title":"J Civil Struct Health Monit"},{"key":"3529_CR33","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1007\/s13349-021-00530-8","volume":"12","author":"BT Svendsen","year":"2022","unstructured":"Svendsen, B.T., Fr\u00f8seth, G.T., \u00d8iseth, O., et al.: A data-based structural health monitoring approach for damage detection in steel bridges using experimental data. J Civil Struct Health Monit 12, 101\u2013115 (2022). https:\/\/doi.org\/10.1007\/s13349-021-00530-8","journal-title":"J Civil Struct Health Monit"},{"key":"3529_CR34","doi-asserted-by":"publisher","first-page":"809","DOI":"10.1007\/s13349-018-0307-2","volume":"8","author":"SK Samantaray","year":"2018","unstructured":"Samantaray, S.K., Mittal, S.K., Mahapatra, P., et al.: An impedance-based structural health monitoring approach for looseness identification in bolted joint structure. J Civil Struct Health Monit 8, 809\u2013822 (2018). https:\/\/doi.org\/10.1007\/s13349-018-0307-2","journal-title":"J Civil Struct Health Monit"},{"key":"3529_CR35","doi-asserted-by":"publisher","first-page":"1813","DOI":"10.1007\/s00158-018-2135-8","volume":"59","author":"M Zarchi","year":"2019","unstructured":"Zarchi, M., Attaran, B.: Improved design of an active landing gear for a passenger aircraft using multi-objective optimization technique. Struct Multidisc Optim. 59, 1813\u20131833 (2019). https:\/\/doi.org\/10.1007\/s00158-018-2135-8","journal-title":"Struct Multidisc Optim."},{"issue":"11","key":"3529_CR36","doi-asserted-by":"publisher","first-page":"1905","DOI":"10.1080\/0305215X.2017.1278757","volume":"49","author":"M Zarchi","year":"2017","unstructured":"Zarchi, M., Attaran, B.: Performance improvement of an active vibration absorber subsystem for an aircraft model using a bees algorithm based on multi-objective intelligent optimization. Eng. Optimiz. 49(11), 1905\u20131921 (2017). https:\/\/doi.org\/10.1080\/0305215X.2017.1278757","journal-title":"Eng. Optimiz."},{"key":"3529_CR37","doi-asserted-by":"publisher","DOI":"10.1109\/.2018.2877090.10.1109\/TIE.2018.2877090","author":"L Guo","year":"2018","unstructured":"Guo, L., Lei, Y., Xing, S., Yan, T., Li, N.: Deep convolutional transfer learning network: a new method for intelligent fault diagnosis of machines with unlabeled data. IEEE Trans. Ind. Electron. (2018). https:\/\/doi.org\/10.1109\/.2018.2877090.10.1109\/TIE.2018.2877090","journal-title":"IEEE Trans. Ind. Electron."},{"key":"3529_CR38","doi-asserted-by":"publisher","unstructured":"Yang B, Lei Y, Jia F, Xing S: An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings. Mechanical Systems and Signal Processing. doi.org\/https:\/\/doi.org\/10.1016\/.2018.12.051.","DOI":"10.1016\/.2018.12.051"},{"key":"3529_CR39","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1007\/s13349-017-0252-5","volume":"7","author":"AC Neves","year":"2017","unstructured":"Neves, A.C., Gonz\u00e1lez, I., Leander, J., et al.: Structural health monitoring of bridges: a model-free ANN-based approach to damage detection. J Civil Struct Health Monit 7, 689\u2013702 (2017). https:\/\/doi.org\/10.1007\/s13349-017-0252-5","journal-title":"J Civil Struct Health Monit"}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03529-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-024-03529-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03529-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,4]],"date-time":"2024-11-04T07:28:17Z","timestamp":1730705297000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-024-03529-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,27]]},"references-count":39,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2024,12]]}},"alternative-id":["3529"],"URL":"https:\/\/doi.org\/10.1007\/s11760-024-03529-y","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"value":"1863-1703","type":"print"},{"value":"1863-1711","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,27]]},"assertion":[{"value":"29 November 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 April 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 August 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 September 2024","order":4,"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":"The authors consent for publication.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors demonstrate that they have adhered to the accepted ethical standards of a genuine research study. They consent to participate.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}}]}}