{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T07:17:36Z","timestamp":1774595856193,"version":"3.50.1"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"The Graduate Student Innovation Fund of North China University of Science and Technology","award":["2025S02"],"award-info":[{"award-number":["2025S02"]}]},{"DOI":"10.13039\/501100003787","name":"Natural Science Foundation of Hebei Province","doi-asserted-by":"publisher","award":["D2024209006"],"award-info":[{"award-number":["D2024209006"]}],"id":[{"id":"10.13039\/501100003787","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science Research Project of Hebei Education Department","award":["QN2024147"],"award-info":[{"award-number":["QN2024147"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Real-Time Image Proc"],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1007\/s11554-025-01674-2","type":"journal-article","created":{"date-parts":[[2025,4,12]],"date-time":"2025-04-12T11:23:14Z","timestamp":1744456994000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Hcl-yolo: a lightweight and efficient underwater object detection algorithm"],"prefix":"10.1007","volume":"22","author":[{"given":"Xiuman","family":"Liang","sequence":"first","affiliation":[]},{"given":"Teng","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Haifeng","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Zhendong","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,4,12]]},"reference":[{"key":"1674_CR1","doi-asserted-by":"publisher","first-page":"110222","DOI":"10.1016\/j.patcog.2023.110222","volume":"149","author":"LH Dai","year":"2024","unstructured":"Dai, L.H., Liu, H., Song, P.H., Liu, M.Y.: A gated cross-domain collaborative network for underwater object detection. Pattern Recognit. 149, 110222 (2024)","journal-title":"Pattern Recognit."},{"key":"1674_CR2","doi-asserted-by":"publisher","first-page":"108926","DOI":"10.1016\/j.patcog.2022.108926","volume":"132","author":"L Chen","year":"2022","unstructured":"Chen, L., Zhou, F.X., Wang, S.K., Dong, J.Y., Li, N., Ma, H.P., Wang, X., Zhou, H.Y.: SWIPENET: object detection in noisy underwater scenes. Pattern Recognit. 132, 108926 (2022)","journal-title":"Pattern Recognit."},{"issue":"4","key":"1674_CR3","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1007\/s00530-024-01410-z","volume":"30","author":"L Deng","year":"2024","unstructured":"Deng, L., Luo, S.J., He, C.H., Xiao, H.P., Wu, H.: Underwater small and occlusion object detection with feature fusion and global context decoupling head-based YOLO. Multimed. Syst. 30(4), 208 (2024)","journal-title":"Multimed. Syst."},{"issue":"2","key":"1674_CR4","doi-asserted-by":"publisher","first-page":"2434","DOI":"10.1007\/s10489-022-03622-0","volume":"53","author":"HF Yu","year":"2023","unstructured":"Yu, H.F., Li, X.B., Feng, Y.K., Han, S.: Multiple attentional path aggregation network for ocean object detection. Appl. Intell. 53(2), 2434\u20132451 (2023)","journal-title":"Appl. Intell."},{"key":"1674_CR5","doi-asserted-by":"publisher","first-page":"122018","DOI":"10.1016\/j.eswa.2023.122018","volume":"238","author":"Y Liu","year":"2024","unstructured":"Liu, Y., An, D., Ren, Y.J., Zhao, J., Zhang, C., Cheng, J.H., Liu, J.C., Wei, Y.G.: DP-FishNet: dual-path pyramid vision transformer-based underwater fish detection network. Expert Syst. Appl. 238, 122018 (2024)","journal-title":"Expert Syst. Appl."},{"key":"1674_CR6","doi-asserted-by":"crossref","unstructured":"Cai, Z.W., Vasconcelos, N.: Cascade r-cnn: delving into high quality object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6154\u20136162 (2018)","DOI":"10.1109\/CVPR.2018.00644"},{"issue":"1","key":"1674_CR7","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1109\/JSTSP.2019.2899237","volume":"13","author":"R Diamant","year":"2019","unstructured":"Diamant, R., Kipnis, D., Bigal, E., Scheinin, A., Tchernov, D., Pinchasi, A.: An active acoustic track-before-detect approach for finding underwater mobile objects. IEEE J. Sel. Top. Signal Process. 13(1), 104\u2013119 (2019)","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"1674_CR8","doi-asserted-by":"publisher","first-page":"102022","DOI":"10.1016\/j.ecoinf.2023.102022","volume":"75","author":"XC Xu","year":"2023","unstructured":"Xu, X.C., Liu, Y., Lyu, L., Yan, P., Zhang, J.Y.: MAD-YOLO: a quantitative detection algorithm for dense small-scale ocean benthos. Ecol. Inform. 75, 102022 (2023)","journal-title":"Ecol. Inform."},{"key":"1674_CR9","doi-asserted-by":"publisher","first-page":"109471","DOI":"10.1016\/j.compeleceng.2024.109471","volume":"118","author":"XZ Yao","year":"2024","unstructured":"Yao, X.Z., Liang, X.M., Yu, H.F., Liu, Z.D., Zhao, Z.G.: GUCL: generalization of underwater color-line model for underwater image enhancement. Comput. Electr. Eng. 118, 109471 (2024)","journal-title":"Comput. Electr. Eng."},{"issue":"2","key":"1674_CR10","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1007\/s11554-024-01445-5","volume":"21","author":"SW Cai","year":"2024","unstructured":"Cai, S.W., Meng, H., Wu, J.B.: FE-YOLO: YOLO ship detection algorithm based on feature fusion and feature enhancement. J. Real-Time Image Process. 21(2), 61 (2024)","journal-title":"J. Real-Time Image Process."},{"issue":"1","key":"1674_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11554-024-01595-6","volume":"22","author":"JH Dai","year":"2025","unstructured":"Dai, J.H., Ren, J., Li, S.J.: PHL-YOLO: a real-time lightweight yarn inspection method. J. Real-Time Image Proc. 22(1), 1\u201314 (2025)","journal-title":"J. Real-Time Image Proc."},{"key":"1674_CR12","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 580\u2013587 (2014)","DOI":"10.1109\/CVPR.2014.81"},{"key":"1674_CR13","doi-asserted-by":"crossref","unstructured":"Girshick, R.: Fast r-cnn in Proceedings of the IEEE International Conference on Computer Vision (ICCV), pp. 1440\u20131448 (2015)","DOI":"10.1109\/ICCV.2015.169"},{"issue":"6","key":"1674_CR14","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"SQ Ren","year":"2016","unstructured":"Ren, S.Q., He, K.M., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans. Pattern Anal. Mach. Intell. 39(6), 1137\u20131149 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1674_CR15","doi-asserted-by":"crossref","unstructured":"He, K.M., Gkioxari, G., Doll\u00e1r, P., Grishck, R.: Mask r-cnn. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV), pp. 2961\u20132969 (2017)","DOI":"10.1109\/ICCV.2017.322"},{"issue":"4","key":"1674_CR16","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1007\/s11554-024-01519-4","volume":"21","author":"CL Ji","year":"2024","unstructured":"Ji, C.L., Yu, T., Gao, P., Wang, F., Yuan, R.Y.: An efficient and lightweight small object detection model based on YOLOv5. J. Real-Time Image Process. 21(4), 141 (2024)","journal-title":"J. Real-Time Image Process."},{"key":"1674_CR17","doi-asserted-by":"crossref","unstructured":"Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.Y., Berg, A.C.: Ssd: single shot multibox detector. In: 14th European Conference on Computer Vision(ECCV), vol. 9905, pp. 21\u201337. Springer International Publishing Ag, Cham (2016)","DOI":"10.1007\/978-3-319-46448-0_2"},{"issue":"7","key":"1674_CR18","doi-asserted-by":"publisher","first-page":"677","DOI":"10.3390\/machines11070677","volume":"11","author":"M Hussain","year":"2023","unstructured":"Hussain, M.: YOLO-v1 to YOLO-v8, the rise of YOLO and its complementary nature toward digital manufacturing and industrial defect detection. Machines 11(7), 677 (2023)","journal-title":"Machines"},{"key":"1674_CR19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TIM.2020.2991573","volume":"70","author":"X Cheng","year":"2020","unstructured":"Cheng, X., Yu, J.B.: RetinaNet with difference channel attention and adaptively spatial feature fusion for steel surface defect detection. IEEE Trans. Instrum. Meas. 70, 1\u201311 (2020)","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"1674_CR20","doi-asserted-by":"publisher","first-page":"107522","DOI":"10.1016\/j.compag.2022.107522","volume":"204","author":"W Ji","year":"2023","unstructured":"Ji, W., Peng, J.Q., Xu, B., Zhang, T.: Real-time detection of underwater river crab based on multi-scale pyramid fusion image enhancement and MobileCenterNet model. Comput. Electron. Agric. 204, 107522 (2023)","journal-title":"Comput. Electron. Agric."},{"key":"1674_CR21","doi-asserted-by":"publisher","first-page":"117235","DOI":"10.1109\/ACCESS.2022.3219592","volume":"10","author":"J Liu","year":"2022","unstructured":"Liu, J., Liu, S., Xu, S.J., Zhou, C.J.: Two-stage underwater object detection network using swin transformer. IEEE Access 10, 117235\u2013117247 (2022)","journal-title":"IEEE Access"},{"issue":"19","key":"1674_CR22","doi-asserted-by":"publisher","first-page":"3507","DOI":"10.3390\/w15193507","volume":"15","author":"ZX Yue","year":"2023","unstructured":"Yue, Z.X., Yan, B., Liu, H.Z., Chen, Z.: An effective method for underwater biological multi-object detection using mask region-based convolutional neural network. Water 15(19), 3507 (2023)","journal-title":"Water"},{"key":"1674_CR23","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1016\/j.neucom.2023.01.088","volume":"530","author":"PH Song","year":"2023","unstructured":"Song, P.H., Li, P.T., Dai, L.H., Wang, T., Chen, Z.: Reweighting R-CNN samples by RPN\u2019s error for underwater object detection. Neurocomputing 530, 150\u2013164 (2023)","journal-title":"Neurocomputing"},{"key":"1674_CR24","doi-asserted-by":"publisher","first-page":"115051","DOI":"10.1016\/j.eswa.2021.115051","volume":"178","author":"J Hu","year":"2021","unstructured":"Hu, J., Zhao, D.D., Zhang, Y.F., Zhou, C.Q., Chen, X.: Real-time nondestructive fish behavior detecting in mixed polyculture system using deep-learning and low-cost devices. Expert Syst. Appl. 178, 115051 (2021)","journal-title":"Expert Syst. Appl."},{"issue":"11","key":"1674_CR25","doi-asserted-by":"publisher","first-page":"6129","DOI":"10.1109\/TNNLS.2021.3072414","volume":"33","author":"C Yeh","year":"2021","unstructured":"Yeh, C., Lin, C.H., Kang, L.W., Huang, C., Lin, M.H., Chang, C.Y.: Lightweight deep neural network for joint learning of underwater object detection and color conversion. IEEE Trans. Neural Netw. Learn. Syst. 33(11), 6129\u20136143 (2021)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"1","key":"1674_CR26","doi-asserted-by":"publisher","first-page":"20220590","DOI":"10.1515\/geo-2022-0590","volume":"15","author":"JL Huo","year":"2023","unstructured":"Huo, J.L., Jiang, Q.: IG-YOLOv5-based underwater biological recognition and detection for ocean protection. Open Geosci. 15(1), 20220590 (2023)","journal-title":"Open Geosci."},{"issue":"6","key":"1674_CR27","first-page":"1178","volume":"11","author":"Y Sun","year":"2023","unstructured":"Sun, Y., Zheng, W.X., Du, X., Yan, Z.P.: Underwater small object detection based on yolox combined with mobilevit and double coordinate attention. J. Ocean Sci. Eng. 11(6), 1178 (2023)","journal-title":"J. Ocean Sci. Eng."},{"key":"1674_CR28","doi-asserted-by":"publisher","first-page":"102108","DOI":"10.1016\/j.ecoinf.2023.102108","volume":"75","author":"GY Yu","year":"2023","unstructured":"Yu, G.Y., Cai, R.L., Su, J.P., Huo, M.X., Deng, R.L.: U-YOLOv7: a network for underwater organism detection. Ecol. Inform. 75, 102108 (2023)","journal-title":"Ecol. Inform."},{"key":"1674_CR29","doi-asserted-by":"publisher","first-page":"102758","DOI":"10.1016\/j.ecoinf.2024.102758","volume":"82","author":"JF Feng","year":"2024","unstructured":"Feng, J.F., Jin, T.: CEH-YOLO: a composite enhanced YOLO-based model for underwater object detection. Ecol. Inform. 82, 102758 (2024)","journal-title":"Ecol. Inform."},{"key":"1674_CR30","doi-asserted-by":"publisher","first-page":"107766","DOI":"10.1016\/j.engappai.2023.107766","volume":"130","author":"HP Ma","year":"2024","unstructured":"Ma, H.P., Zhang, Y.J., Sun, S.Y., Zhang, W.J., Fei, M.R., Zhou, H.Y.: Weighted multi-error information entropy based you only look once network for underwater object detection. Eng. Appl. Artif. Intell. 130, 107766 (2024)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"1674_CR31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18293\/JVLC2024-n1-059","volume":"2024","author":"QC Cen","year":"2024","unstructured":"Cen, Q.C., Zhu, Q.G., Wang, Y.X., Chen, W.D., Liu, S.: YOLOv9-YX: lightweight algorithm for underwater object detection. Visual Comput. 2024, 1\u201313 (2024)","journal-title":"Visual Comput."},{"key":"1674_CR32","doi-asserted-by":"publisher","first-page":"102401","DOI":"10.1016\/j.ecoinf.2023.102401","volume":"79","author":"PZ Liu","year":"2024","unstructured":"Liu, P.Z., Qian, W.B., Wang, Y.L.: YWnet: a convolutional block attention-based fusion deep learning method for complex underwater small object detection. Ecol. Inform. 79, 102401 (2024)","journal-title":"Ecol. Inform."},{"key":"1674_CR33","doi-asserted-by":"publisher","first-page":"102680","DOI":"10.1016\/j.ecoinf.2024.102680","volume":"82","author":"H Zhou","year":"2024","unstructured":"Zhou, H., Kong, M.W., Yuan, H.X., Pan, Y.Y., Wang, X.R., Chen, R., Lu, W.H., Wang, R.Z., Yang, Q.H.: Real-time underwater object detection technology for complex underwater environments based on deep learning. Ecol. Inform. 82, 102680 (2024)","journal-title":"Ecol. Inform."},{"issue":"2","key":"1674_CR34","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1109\/JOE.2022.3223733","volume":"48","author":"JC Zhou","year":"2023","unstructured":"Zhou, J.C., Pang, L., Zhang, D.H., Zhang, W.S.: Underwater image enhancement method via multi-interval subhistogram perspective equalization. IEEE J. Ocean. Eng. 48(2), 474\u2013488 (2023)","journal-title":"IEEE J. Ocean. Eng."},{"issue":"9","key":"1674_CR35","doi-asserted-by":"publisher","first-page":"1204","DOI":"10.3390\/jmse10091204","volume":"10","author":"Z Liu","year":"2022","unstructured":"Liu, Z., Zhuang, Y.M., Jia, P.R., Wu, C.D., Xu, H.L., Liu, Z.L.: A novel underwater image enhancement algorithm and an improved underwater biological detection pipeline. J. Mar. Sci. Eng. 10(9), 1204 (2022)","journal-title":"J. Mar. Sci. Eng."},{"issue":"18","key":"1674_CR36","doi-asserted-by":"publisher","first-page":"3780","DOI":"10.3390\/electronics13183780","volume":"13","author":"C Yang","year":"2024","unstructured":"Yang, C., Xiang, J., Li, X.D., Xie, Y.J.: FishDet-YOLO: enhanced underwater fish detection with richer gradient flow and long-range dependency capture through Mamba-C2f. Electronics 13(18), 3780 (2024)","journal-title":"Electronics"},{"key":"1674_CR37","doi-asserted-by":"crossref","unstructured":"Liu, C.W., Li, H.J., Wang, S.C., Zhu, M., Wang, D., Fan, X.: A dataset and benchmark of underwater object detection for robot picking. In: IEEE International Conference on Multimedia Expo Workshops (ICMEW), pp.1\u20136 (2021)","DOI":"10.1109\/ICMEW53276.2021.9455997"},{"key":"1674_CR38","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.: Cbam: convolutional block attention module. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 3\u201319 (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"1674_CR39","doi-asserted-by":"crossref","unstructured":"Hou, Q.B., Zhou, D.Q., Feng, J.S.: Coordinate attention for efficient mobile network design. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 13713\u201313722 (2021)","DOI":"10.1109\/CVPR46437.2021.01350"},{"key":"1674_CR40","doi-asserted-by":"crossref","unstructured":"Wang, Q.L., Wu, B.G., Zhu, P.F., Li, P.H., Zuo, W.M., Hu, Q.H.: ECA-Net: efficient channel attention for deep convolutional neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition(CVPR), pp. 11534\u201311542 (2020)","DOI":"10.1109\/CVPR42600.2020.01155"},{"key":"1674_CR41","doi-asserted-by":"crossref","unstructured":"Misra, D., Nalamada, T., Arasanipalai, A.U., et al.: Rotate to attend: convolutional triplet attention module. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 3139\u20133148 (2021)","DOI":"10.1109\/WACV48630.2021.00318"},{"key":"1674_CR42","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7132\u20137141 (2018)","DOI":"10.1109\/CVPR.2018.00745"},{"key":"1674_CR43","doi-asserted-by":"crossref","unstructured":"Zhu, L., Wang, X.J., Ke, Z.H., Zhang, W., Lau, R.: Biformer: vision transformer with bi-level routing attention. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 10323\u201310333 (2023)","DOI":"10.1109\/CVPR52729.2023.00995"},{"key":"1674_CR44","unstructured":"Li, H.L., Li, J., Wei, H.B., Liu, Z., Zhan, Z.F., Ren, Q.L.: Slim-neck by GSConv: a better design paradigm of detector architectures for autonomous vehicles (2022). arXiv preprint arXiv:2206.02424"},{"key":"1674_CR45","doi-asserted-by":"crossref","unstructured":"Chen, J., Mai, H.S., Luo, L.B., Chen, X.Q., Wu, K.L.: Effective feature fusion network in BIFPN for small object detection. In: IEEE International Conference on Image Processing (ICIP), pp. 699\u2013703 (2021)","DOI":"10.1109\/ICIP42928.2021.9506347"},{"issue":"1","key":"1674_CR46","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s12145-024-01620-z","volume":"18","author":"XZ Yao","year":"2025","unstructured":"Yao, X.Z., Liang, X.M., Yu, H.F., Liu, Z.D.: Fast fusion-based underwater image enhancement with adaptive color correction and contrast enhancement. Earth Sci. Inf. 18(1), 1\u201314 (2025)","journal-title":"Earth Sci. Inf."}],"container-title":["Journal of Real-Time Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11554-025-01674-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11554-025-01674-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11554-025-01674-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,3]],"date-time":"2025-05-03T06:25:11Z","timestamp":1746253511000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11554-025-01674-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4]]},"references-count":46,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["1674"],"URL":"https:\/\/doi.org\/10.1007\/s11554-025-01674-2","relation":{},"ISSN":["1861-8200","1861-8219"],"issn-type":[{"value":"1861-8200","type":"print"},{"value":"1861-8219","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4]]},"assertion":[{"value":"8 February 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 March 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 April 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 conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"96"}}