{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T16:58:32Z","timestamp":1784912312924,"version":"3.55.0"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T00:00:00Z","timestamp":1727654400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T00:00:00Z","timestamp":1727654400000},"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":["Vis Comput"],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1007\/s00371-024-03631-9","type":"journal-article","created":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T16:02:56Z","timestamp":1727712176000},"page":"3785-3800","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Hierarchical wavelet-guided diffusion model for single image deblurring"],"prefix":"10.1007","volume":"41","author":[{"given":"Xiaopan","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiqian","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shoulie","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sos","family":"Agaian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,9,30]]},"reference":[{"issue":"4","key":"3631_CR1","doi-asserted-by":"publisher","first-page":"955","DOI":"10.1109\/TCSVT.2019.2901629","volume":"30","author":"B Sheng","year":"2020","unstructured":"Sheng, B., Li, P., Fang, X., Tan, P., Wu, E.: Depth-aware motion deblurring using loopy belief propagation. IEEE Trans. Circuits Syst. Video Technol. 30(4), 955\u2013969 (2020)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"3631_CR2","doi-asserted-by":"publisher","first-page":"6142","DOI":"10.1109\/TIP.2021.3092814","volume":"30","author":"Y Wen","year":"2021","unstructured":"Wen, Y., Chen, J., Sheng, B., Chen, Z., Li, P., Tan, P., Lee, T.-Y.: Structure-aware motion deblurring using multi-adversarial optimized cyclegan. IEEE Trans. Image Process. 30, 6142\u20136155 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"3631_CR3","doi-asserted-by":"crossref","unstructured":"Chen, L., Fang, F., Wang, T., Zhang, G.: Blind image deblurring with local maximum gradient prior. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1742\u20131750 (2019)","DOI":"10.1109\/CVPR.2019.00184"},{"issue":"1","key":"3631_CR4","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1007\/s10851-023-01161-y","volume":"66","author":"X Li","year":"2024","unstructured":"Li, X., Wu, S., Xie, S., Agaian, S.: Dynamic-clustering extreme intensity prior based blind image deblurring. J. Math. Imaging Vision 66(1), 22\u201336 (2024)","journal-title":"J. Math. Imaging Vision"},{"issue":"9","key":"3631_CR5","doi-asserted-by":"publisher","first-page":"5478","DOI":"10.1007\/s00034-023-02365-8","volume":"42","author":"X Feng","year":"2023","unstructured":"Feng, X., Tan, J., Ge, X., Liu, J., Hu, D.: Blind image deblurring via weighted dark channel prior. Circuits Syst. Signal Process. 42(9), 5478\u20135499 (2023)","journal-title":"Circuits Syst. Signal Process."},{"key":"3631_CR6","doi-asserted-by":"crossref","unstructured":"Cho, S.-J., Ji, S.-W., Hong, J.-P., Jung, S.-W., Ko, S.-J.: Rethinking coarse-to-fine approach in single image deblurring. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4641\u20134650 (2021)","DOI":"10.1109\/ICCV48922.2021.00460"},{"key":"3631_CR7","doi-asserted-by":"crossref","unstructured":"Zhang, H., Dai, Y., Li, H., Koniusz, P.: Deep stacked hierarchical multi-patch network for image deblurring. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5978\u20135986 (2019)","DOI":"10.1109\/CVPR.2019.00613"},{"key":"3631_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/s00371-024-03315-4","author":"Z Feng","year":"2024","unstructured":"Feng, Z., Zhang, J., Ran, X., Li, D., Zhang, C.: Ghost-unet: multi-stage network for image deblurring via lightweight subnet learning. Visual Comput. (2024). https:\/\/doi.org\/10.1007\/s00371-024-03315-4","journal-title":"Visual Comput."},{"key":"3631_CR9","doi-asserted-by":"crossref","unstructured":"Tsai, F.-J., Peng, Y.-T., Lin, Y.-Y., Tsai, C.-C., Lin, C.-W.: Stripformer: Strip transformer for fast image deblurring. In: Proceedings of the European Conference on Computer Vision, pp. 146\u2013162 (2022)","DOI":"10.1007\/978-3-031-19800-7_9"},{"key":"3631_CR10","doi-asserted-by":"crossref","unstructured":"Kong, L., Dong, J., Ge, J., Li, M., Pan, J.: Efficient frequency domain-based transformers for high-quality image deblurring. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5886\u20135895 (2023)","DOI":"10.1109\/CVPR52729.2023.00570"},{"key":"3631_CR11","doi-asserted-by":"crossref","unstructured":"Zamir, S.W., Arora, A., Khan, S., Hayat, M., Khan, F.S., Yang, M.-H.: Restormer: Efficient transformer for high-resolution image restoration. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5728\u20135739 (2022)","DOI":"10.1109\/CVPR52688.2022.00564"},{"key":"3631_CR12","doi-asserted-by":"crossref","unstructured":"Kupyn, O., Budzan, V., Mykhailych, M., Mishkin, D., Matas, J.: Deblurgan: Blind motion deblurring using conditional adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8183\u20138192 (2018)","DOI":"10.1109\/CVPR.2018.00854"},{"key":"3631_CR13","doi-asserted-by":"crossref","unstructured":"Kupyn, O., Martyniuk, T., Wu, J., Wang, Z.: Deblurgan-v2: Deblurring (orders-of-magnitude) faster and better. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 8878\u20138887 (2019)","DOI":"10.1109\/ICCV.2019.00897"},{"issue":"6","key":"3631_CR14","first-page":"1","volume":"42","author":"H Jiang","year":"2023","unstructured":"Jiang, H., Luo, A., Fan, H., Han, S., Liu, S.: Low-light image enhancement with wavelet-based diffusion models. ACM Trans. Graph. 42(6), 1\u201314 (2023)","journal-title":"ACM Trans. Graph."},{"issue":"9","key":"3631_CR15","doi-asserted-by":"publisher","first-page":"10850","DOI":"10.1109\/TPAMI.2023.3261988","volume":"45","author":"F-A Croitoru","year":"2023","unstructured":"Croitoru, F.-A., Hondru, V., Ionescu, R.T., Shah, M.: Diffusion models in vision: A survey. IEEE Trans. Pattern Anal. Mach. Intell. 45(9), 10850\u201310869 (2023)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3631_CR16","unstructured":"Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. In: Proceedings of the Advances in Neural Information Processing Systems, pp. 6840\u20136851 (2020)"},{"key":"3631_CR17","doi-asserted-by":"publisher","DOI":"10.1007\/s00371-024-03317-2","author":"X Lu","year":"2024","unstructured":"Lu, X., Liu, F., Rong, Y., Chen, Y., Xiong, S.: Makeupdiffuse: a double image-controlled diffusion model for exquisite makeup transfer. Visual Comput. (2024). https:\/\/doi.org\/10.1007\/s00371-024-03317-2","journal-title":"Visual Comput."},{"key":"3631_CR18","doi-asserted-by":"crossref","unstructured":"Jin, P., Li, H., Cheng, Z., Li, K., Ji, X., Liu, C., Yuan, L., Chen, J.: Diffusionret: Generative text-video retrieval with diffusion model. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 2470\u20132481 (2023)","DOI":"10.1109\/ICCV51070.2023.00234"},{"issue":"2s","key":"3631_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3538749","volume":"18","author":"X Xu","year":"2022","unstructured":"Xu, X., Yuan, X., Wang, Z., Zhang, K., Hu, R.: Rank-in-rank loss for person re-identification. ACM Trans. Multimed. Comput. Commun. Appl. 18(2s), 1\u201321 (2022)","journal-title":"ACM Trans. Multimed. Comput. Commun. Appl."},{"key":"3631_CR20","doi-asserted-by":"crossref","unstructured":"Shang, S., Shan, Z., Liu, G., Zhang, J.: Resdiff: Combining CNN and diffusion model for image super-resolution. arXiv preprint arXiv:2303.08714 (2023)","DOI":"10.1609\/aaai.v38i8.28746"},{"key":"3631_CR21","doi-asserted-by":"crossref","unstructured":"Whang, J., Delbracio, M., Talebi, H., Saharia, C., Dimakis, A.G., Milanfar, P.: Deblurring via stochastic refinement. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 16293\u201316303 (2022)","DOI":"10.1109\/CVPR52688.2022.01581"},{"key":"3631_CR22","doi-asserted-by":"crossref","unstructured":"Ren, M., Delbracio, M., Talebi, H., Gerig, G., Milanfar, P.: Multiscale structure guided diffusion for image deblurring. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10721\u201310733 (2023)","DOI":"10.1109\/ICCV51070.2023.00984"},{"key":"3631_CR23","doi-asserted-by":"crossref","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 10684\u201310695 (2022)","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"3631_CR24","unstructured":"Wang, L., Yang, Q., Wang, C., Wang, W., Pan, J., Su, Z.: Learning a coarse-to-fine diffusion transformer for image restoration. arXiv preprint arXiv:2308.08730 (2023)"},{"key":"3631_CR25","doi-asserted-by":"crossref","unstructured":"Niu, A., Zhang, K., Pham, T.X., Sun, J., Zhu, Y., Kweon, I.S., Zhang, Y.: Cdpmsr: Conditional diffusion probabilistic models for single image super-resolution. In: 2023 IEEE International Conference on Image Processing, pp. 615\u2013619 (2023). IEEE","DOI":"10.1109\/ICIP49359.2023.10222191"},{"key":"3631_CR26","doi-asserted-by":"crossref","unstructured":"Liu, P., Zhang, H., Zhang, K., Lin, L., Zuo, W.: Multi-level wavelet-cnn for image restoration. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 773\u2013782 (2018)","DOI":"10.1109\/CVPRW.2018.00121"},{"key":"3631_CR27","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2024.3359769","author":"Y Huang","year":"2024","unstructured":"Huang, Y., Huang, J., Liu, J., Yan, M., Dong, Y., Lyu, J., Chen, C., Chen, S.: Wavedm: wavelet-based diffusion models for image restoration. IEEE Trans. Multimed. (2024). https:\/\/doi.org\/10.1109\/TMM.2024.3359769","journal-title":"IEEE Trans. Multimed."},{"key":"3631_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2024.106378","volume":"177","author":"J Li","year":"2024","unstructured":"Li, J., Cheng, B., Chen, Y., Gao, G., Shi, J., Zeng, T.: Ewt: Efficient wavelet-transformer for single image denoising. Neural Netw. 177, 106378 (2024)","journal-title":"Neural Netw."},{"key":"3631_CR29","doi-asserted-by":"crossref","unstructured":"Mao, X., Liu, Y., Liu, F., Li, Q., Shen, W., Wang, Y.: Intriguing findings of frequency selection for image deblurring. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, pp. 1905\u20131913 (2023)","DOI":"10.1609\/aaai.v37i2.25281"},{"key":"3631_CR30","doi-asserted-by":"publisher","first-page":"2890","DOI":"10.1109\/TMM.2021.3090206","volume":"24","author":"Y Liu","year":"2021","unstructured":"Liu, Y., Fang, F., Wang, T., Li, J., Sheng, Y., Zhang, G.: Multi-scale grid network for image deblurring with high-frequency guidance. IEEE Trans. Multimed. 24, 2890\u20132901 (2021)","journal-title":"IEEE Trans. Multimed."},{"key":"3631_CR31","doi-asserted-by":"crossref","unstructured":"Nah, S., Hyun\u00a0Kim, T., Mu\u00a0Lee, K.: Deep multi-scale convolutional neural network for dynamic scene deblurring. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3883\u20133891 (2017)","DOI":"10.1109\/CVPR.2017.35"},{"key":"3631_CR32","doi-asserted-by":"crossref","unstructured":"Tao, X., Gao, H., Shen, X., Wang, J., Jia, J.: Scale-recurrent network for deep image deblurring. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8174\u20138182 (2018)","DOI":"10.1109\/CVPR.2018.00853"},{"key":"3631_CR33","doi-asserted-by":"crossref","unstructured":"Ji, S.-W., Lee, J., Kim, S.-W., Hong, J.-P., Baek, S.-J., Jung, S.-W., Ko, S.-J.: Xydeblur: divide and conquer for single image deblurring. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 17421\u201317430 (2022)","DOI":"10.1109\/CVPR52688.2022.01690"},{"key":"3631_CR34","doi-asserted-by":"crossref","unstructured":"Chen, L., Chu, X., Zhang, X., Sun, J.: Simple baselines for image restoration. In: Proceedings of the European Conference on Computer Vision, pp. 17\u201333 (2022)","DOI":"10.1007\/978-3-031-20071-7_2"},{"key":"3631_CR35","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., et al.: An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020)"},{"key":"3631_CR36","doi-asserted-by":"crossref","unstructured":"Wang, Z., Cun, X., Bao, J., Zhou, W., Liu, J., Li, H.: Uformer: A general u-shaped transformer for image restoration. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 17683\u201317693 (2022)","DOI":"10.1109\/CVPR52688.2022.01716"},{"key":"3631_CR37","doi-asserted-by":"crossref","unstructured":"Xia, B., Zhang, Y., Wang, S., Wang, Y., Wu, X., Tian, Y., Yang, W., Van\u00a0Gool, L.: Diffir: Efficient diffusion model for image restoration. arXiv preprint arXiv:2303.09472 (2023)","DOI":"10.1109\/ICCV51070.2023.01204"},{"key":"3631_CR38","unstructured":"Chen, Z., Zhang, Y., Liu, D., Gu, J., Kong, L., Yuan, X., et al: Hierarchical integration diffusion model for realistic image deblurring. In: Proceedings of the Advances in Neural Information Processing Systems, pp. 1\u201312 (2024)"},{"issue":"8","key":"3631_CR39","doi-asserted-by":"publisher","first-page":"10346","DOI":"10.1109\/TPAMI.2023.3238179","volume":"45","author":"O \u00d6zdenizci","year":"2023","unstructured":"\u00d6zdenizci, O., Legenstein, R.: Restoring vision in adverse weather conditions with patch-based denoising diffusion models. IEEE Trans. Pattern Anal. Mach. Intell. 45(8), 10346\u201310357 (2023)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3631_CR40","doi-asserted-by":"publisher","first-page":"69242","DOI":"10.1109\/ACCESS.2018.2880279","volume":"6","author":"C Min","year":"2018","unstructured":"Min, C., Wen, G., Li, B., Fan, F.: Blind deblurring via a novel recursive deep cnn improved by wavelet transform. IEEE Access 6, 69242\u201369252 (2018)","journal-title":"IEEE Access"},{"key":"3631_CR41","doi-asserted-by":"crossref","unstructured":"Zou, W., Jiang, M., Zhang, Y., Chen, L., Lu, Z., Wu, Y.: Sdwnet: A straight dilated network with wavelet transformation for image deblurring. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1895\u20131904 (2021)","DOI":"10.1109\/ICCVW54120.2021.00216"},{"key":"3631_CR42","unstructured":"Song, J., Meng, C., Ermon, S.: Denoising diffusion implicit models. arXiv preprint arXiv:2010.02502 (2020)"},{"key":"3631_CR43","unstructured":"Chung, H., Kim, J., Mccann, M.T., Klasky, M.L., Ye, J.C.: Diffusion posterior sampling for general noisy inverse problems. arXiv preprint arXiv:2209.14687 (2022)"},{"key":"3631_CR44","doi-asserted-by":"crossref","unstructured":"Shen, Z., Wang, W., Lu, X., Shen, J., Ling, H., Xu, T., Shao, L.: Human-aware motion deblurring. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 5572\u20135581 (2019)","DOI":"10.1109\/ICCV.2019.00567"},{"key":"3631_CR45","doi-asserted-by":"crossref","unstructured":"Zhang, K., Luo, W., Zhong, Y., Ma, L., Stenger, B., Liu, W., Li, H.: Deblurring by realistic blurring. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2737\u20132746 (2020)","DOI":"10.1109\/CVPR42600.2020.00281"},{"key":"3631_CR46","doi-asserted-by":"crossref","unstructured":"Zamir, S.W., Arora, A., Khan, S., Hayat, M., Khan, F.S., Yang, M.-H., Shao, L.: Multi-stage progressive image restoration. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 14821\u201314831 (2021)","DOI":"10.1109\/CVPR46437.2021.01458"},{"key":"3631_CR47","doi-asserted-by":"crossref","unstructured":"Mou, C., Wang, Q., Zhang, J.: Deep generalized unfolding networks for image restoration. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 17399\u201317410 (2022)","DOI":"10.1109\/CVPR52688.2022.01688"},{"key":"3631_CR48","doi-asserted-by":"crossref","unstructured":"Chen, L., Lu, X., Zhang, J., Chu, X., Chen, C.: Hinet: Half instance normalization network for image restoration. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 182\u2013192 (2021)","DOI":"10.1109\/CVPRW53098.2021.00027"},{"key":"3631_CR49","unstructured":"Ruan, L., Bemana, M., Seidel, H.-p., Myszkowski, K., Chen, B.: Revisiting image deblurring with an efficient convnet. arXiv preprint arXiv:2302.02234 (2023)"},{"key":"3631_CR50","unstructured":"Luo, Z., Gustafsson, F.K., Zhao, Z., Sj\u00f6lund, J., Sch\u00f6n, T.B.: Image restoration with mean-reverting stochastic differential equations. arXiv preprint arXiv:2301.11699 (2023)"},{"key":"3631_CR51","doi-asserted-by":"crossref","unstructured":"Rim, J., Lee, H., Won, J., Cho, S.: Real-world blur dataset for learning and benchmarking deblurring algorithms. In: Proceedings of the European Conference on Computer Vision, pp. 184\u2013201 (2020). Springer","DOI":"10.1007\/978-3-030-58595-2_12"},{"issue":"4","key":"3631_CR52","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process."},{"key":"3631_CR53","doi-asserted-by":"crossref","unstructured":"Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 586\u2013595 (2018)","DOI":"10.1109\/CVPR.2018.00068"},{"key":"3631_CR54","unstructured":"Loshchilov, I., Hutter, F.: Sgdr: Stochastic gradient descent with warm restarts. In: Proceedings of the International Conference on Learning Representations, pp. 1\u201316 (2017)"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-024-03631-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-024-03631-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-024-03631-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,16]],"date-time":"2025-04-16T10:22:09Z","timestamp":1744798929000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-024-03631-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,30]]},"references-count":54,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["3631"],"URL":"https:\/\/doi.org\/10.1007\/s00371-024-03631-9","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,30]]},"assertion":[{"value":"1 September 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 September 2024","order":2,"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"}}]}}