{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T21:07:23Z","timestamp":1765487243403,"version":"3.48.0"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"16","license":[{"start":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T00:00:00Z","timestamp":1761523200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T00:00:00Z","timestamp":1761523200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"the Key Science and Technology Program of Henan Province"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1007\/s10586-025-05795-y","type":"journal-article","created":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T18:20:21Z","timestamp":1761589221000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["TRCA with sparrow-optimized adaptive filter banks for SSVEP recognition"],"prefix":"10.1007","volume":"28","author":[{"given":"Jiaofen","family":"Nan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siyuan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Panpan","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaifan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Duan","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fubao","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanting","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongquan","family":"Xia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yinghui","family":"Meng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,10,27]]},"reference":[{"key":"5795_CR1","doi-asserted-by":"publisher","first-page":"2027","DOI":"10.1109\/TNSRE.2024.3404432","volume":"32","author":"S-Y Chen","year":"2024","unstructured":"Chen, S.-Y., Chang, C.-M., Chiang, K.-J., et al.: SSVEP-DAN: Cross-Domain Data Alignment for SSVEP-Based Brain-Computer Interfaces. IEEE Transactions on Neural Systems and Rehabilitation Engineering 32, 2027\u201337 (2024)","journal-title":"IEEE Transactions on Neural Systems and Rehabilitation Engineering"},{"key":"5795_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2024.106932","volume":"99","author":"T-J Luo","year":"2025","unstructured":"Luo, T.-J., Angadi, S., Elashiri, M.A.: Ensemble strategies exploration for the calibration data optimized spatial filters based SSVEP recognition algorithms [J]. Biomedical Signal Processing and Control 99, 106932 (2025)","journal-title":"Biomedical Signal Processing and Control"},{"issue":"1","key":"5795_CR3","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-84534-6","volume":"15","author":"Q Wei","year":"2025","unstructured":"Wei, Q., Li, C., Wang, Y., et al.: Enhancing the performance of SSVEP-based BCIs by combining task-related component analysis and deep neural network. Sci. Rep. 15(1), 365 (2025)","journal-title":"Sci. Rep."},{"issue":"9","key":"5795_CR4","doi-asserted-by":"publisher","first-page":"5565","DOI":"10.1109\/TCYB.2024.3390805","volume":"54","author":"J Jin","year":"2024","unstructured":"Jin, J., Xu, R., Daly, I., et al.: MOCNN: A Multiscale Deep Convolutional Neural Network for ERP-Based Brain-Computer Interfaces. IEEE Transactions on Cybernetics 54(9), 5565\u201376 (2024)","journal-title":"IEEE Transactions on Cybernetics"},{"key":"5795_CR5","doi-asserted-by":"publisher","first-page":"3271","DOI":"10.1109\/TNSRE.2025.3598795","volume":"33","author":"JA O\u2019Reilly","year":"2025","unstructured":"O\u2019Reilly, J.A., Sunthornwiriya-Amon, H., Aparprasith, N., et al.: Blind Source Separation of Event-Related Potentials Using Recurrent Neural Network. IEEE Transactions on Neural Systems and Rehabilitation Engineering 33, 3271\u20133280 (2025)","journal-title":"IEEE Transactions on Neural Systems and Rehabilitation Engineering"},{"issue":"1","key":"5795_CR6","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1007\/s11227-024-06627-3","volume":"81","author":"Y Tang","year":"2025","unstructured":"Tang, Y., Ma, Y., Xiao, C., et al.: Classification of EEG event-related potentials based on channel attention mechanism [J]. Journal of Supercomputing 81(1), 126 (2025)","journal-title":"Journal of Supercomputing"},{"issue":"3","key":"5795_CR7","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1080\/2326263X.2024.2372863","volume":"11","author":"DAB Mora","year":"2024","unstructured":"Mora, D.A.B., van Hoornweder, S., van Dun, K., et al.: Toward methodologies for motor imagery enhancement: a tDCS-BCI study [J]. Brain-Computer Interfaces 11(3), 110\u201324 (2024)","journal-title":"Brain-Computer Interfaces"},{"key":"5795_CR8","doi-asserted-by":"publisher","first-page":"527","DOI":"10.1109\/TNSRE.2024.3356916","volume":"32","author":"H Wu","year":"2024","unstructured":"Wu, H., Li, S., Wu, D.: Motor Imagery Classification for Asynchronous EEG-Based Brain-Computer Interfaces [J]. IEEE Trans. Neural Syst. Rehabil. Eng. 32, 527\u201336 (2024)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"5795_CR9","doi-asserted-by":"publisher","first-page":"2187","DOI":"10.1109\/TNSRE.2024.3409872","volume":"32","author":"S Yu","year":"2024","unstructured":"Yu, S., Mao, B., Zhou, Y., et al.: Large-Scale Cortical Network Analysis and Classification of MI-BCI Tasks Based on Bayesian Nonnegative Matrix Factorization [J]. IEEE Trans. Neural Syst. Rehabil. Eng. 32, 2187\u201397 (2024)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"1","key":"5795_CR10","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-79401-3","volume":"14","author":"P Tian","year":"2024","unstructured":"Tian, P., Xu, G., Han, C., et al.: A subjective and objective fusion visual fatigue assessment system for different hardware and software parameters in SSVEP-based BCI applications [J]. Sci. Rep. 14(1), 27872 (2024)","journal-title":"Sci. Rep."},{"key":"5795_CR11","doi-asserted-by":"publisher","first-page":"169557","DOI":"10.1109\/ACCESS.2024.3493134","volume":"12","author":"T Saichoo","year":"2024","unstructured":"Saichoo, T., Siribunyaphat, N., Aung, S.T., et al.: EEG-Based Brain-Computer Interface Using Visual Flicker Imagination for Assistive Communication System [J]. IEEE Access 12, 169557\u201366 (2024)","journal-title":"IEEE Access"},{"key":"5795_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2024.106063","volume":"91","author":"N Ban","year":"2024","unstructured":"Ban, N., Xie, S., Qu, C., et al.: Multifunctional robot based on multimodal brain-machine interface [J]. Biomed. Signal Process. Control 91, 106063 (2024)","journal-title":"Biomed. Signal Process. Control"},{"key":"5795_CR13","doi-asserted-by":"publisher","first-page":"1737","DOI":"10.1109\/TNSRE.2022.3185262","volume":"30","author":"N Guo","year":"2022","unstructured":"Guo, N., Wang, X., Duanmu, D., Huang, X., Li, X., Fan, Y., et al.: SSVEP-based brain computer interface controlled soft robotic glove for post-stroke hand function rehabilitation. IEEE Trans. Neural Syst. Rehabil. Eng. 30, 1737\u201344 (2022)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"5795_CR14","doi-asserted-by":"publisher","DOI":"10.3389\/fnagi.2022.870871","volume":"14","author":"L Li","year":"2022","unstructured":"Li, L., Zhang, Y., Huang, L., Zhao, J., Wang, J., Liu, T.: Robot Assisted Treatment of Hand Functional Rehabilitation Based on Visual Motor Imagination. Frontiers in Aging Neuroscience 14, 870871 (2022)","journal-title":"Frontiers in Aging Neuroscience"},{"issue":"6","key":"5795_CR15","doi-asserted-by":"publisher","first-page":"1922","DOI":"10.3390\/s24061922","volume":"24","author":"M Alban-Escobar","year":"2024","unstructured":"Alban-Escobar, M., Navarrete-Arroyo, P., De la Cruz-Guevara, D.R., et al.: Assistance Device Based on SSVEP-BCI Online to Control a 6-DOF Robotic Arm [J]. Sensors 24(6), 1922 (2024)","journal-title":"Sensors"},{"key":"5795_CR16","doi-asserted-by":"publisher","first-page":"2564","DOI":"10.1109\/TNSRE.2024.3425636","volume":"32","author":"R Li","year":"2024","unstructured":"Li, R., Bai, D., Li, Z., et al.: The SSHVEP Paradigm-Based Brain Controlled Method for Grasping Robot Using MVMD Combined CNN Model [J]. IEEE Trans. Neural Syst. Rehabil. Eng. 32, 2564\u201378 (2024)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"5795_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2023.105530","volume":"88","author":"X Mai","year":"2024","unstructured":"Mai, X., Ai, J., Ji, M., Zhu, X., Meng, J.: A hybrid BCI combining SSVEP and EOG and its application for continuous wheelchair control. Biomed. Signal Process. Control 88, 105530 (2024)","journal-title":"Biomed. Signal Process. Control"},{"issue":"4","key":"5795_CR18","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ac823e","volume":"19","author":"X Zhang","year":"2022","unstructured":"Zhang, X., Qiu, S., Zhang, Y., Wang, K., Wang, Y., He, H.: Bidirectional Siamese correlation analysis method for enhancing the detection of SSVEPs. J. Neural Eng. 19(4), 046027 (2022)","journal-title":"J. Neural Eng."},{"issue":"3","key":"5795_CR19","doi-asserted-by":"publisher","DOI":"10.3390\/brainsci13030483","volume":"13","author":"D Xu","year":"2023","unstructured":"Xu, D., Tang, F., Li, Y., Zhang, Q., Feng, X.: An Analysis of Deep Learning Models in SSVEP-Based BCI: A Survey. Brain Sciences 13(3), 483 (2023)","journal-title":"Brain Sciences"},{"issue":"6","key":"5795_CR20","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/aae5d8","volume":"15","author":"N Waytowich","year":"2018","unstructured":"Waytowich, N., Lawhern, V.J., Garcia, J.O., Cummings, J., Faller, J., Sajda, P., et al.: Compact convolutional neural networks for classification of asynchronous steady-state visual evoked potentials. J. Neural Eng. 15(6), 066031 (2018)","journal-title":"J. Neural Eng."},{"issue":"2","key":"5795_CR21","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ab6a67","volume":"17","author":"A Ravi","year":"2020","unstructured":"Ravi, A., Beni, N.H., Manuel, J., Jiang, N.: Comparing user-dependent and user-independent training of CNN for SSVEP BCI. J. Neural Eng. 17(2), 026028 (2020)","journal-title":"J. Neural Eng."},{"key":"5795_CR22","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1016\/j.neunet.2023.04.045","volume":"164","author":"J Chen","year":"2023","unstructured":"Chen, J., Zhang, Y., Pan, Y., Xu, P., Guan, C.: A transformer-based deep neural network model for SSVEP classification. Neural Netw. 164, 521\u201334 (2023)","journal-title":"Neural Netw."},{"issue":"6","key":"5795_CR23","doi-asserted-by":"publisher","first-page":"1172","DOI":"10.1109\/TBME.2006.889197","volume":"54","author":"Z Lin","year":"2007","unstructured":"Lin, Z., Zhang, C., Wu, W., Gao, X.: Frequency recognition based on canonical correlation analysis for SSVEP-based BCIs. IEEE Trans. Biomed. Eng. 54(6), 1172\u20136 (2007)","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"1","key":"5795_CR24","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1016\/j.jneumeth.2007.09.024","volume":"168","author":"GR M\u00fcller-Putz","year":"2008","unstructured":"M\u00fcller-Putz, G.R., Eder, E., Wriessnegger, S.C., Pfurtscheller, G.: Comparison of DFT and lock-in amplifier features and search for optimal electrode positions in SSVEP-based BCI. J. Neurosci. Methods 168(1), 174\u201381 (2008)","journal-title":"J. Neurosci. Methods"},{"issue":"4","key":"5795_CR25","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/12\/4\/046008","volume":"12","author":"X Chen","year":"2015","unstructured":"Chen, X., Wang, Y., Gao, S., Jung, T.-P., Gao, X.: Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain-computer interface. J. Neural Eng. 12(4), 046008 (2015)","journal-title":"J. Neural Eng."},{"issue":"1","key":"5795_CR26","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1109\/TBME.2017.2694818","volume":"65","author":"M Nakanishi","year":"2017","unstructured":"Nakanishi, M., Wang, Y., Chen, X., Wang, Y.-T., Gao, X., Jung, T.-P.: Enhancing detection of SSVEPs for a high-speed brain speller using task-related component analysis. IEEE Trans. Biomed. Eng. 65(1), 104\u201312 (2017)","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"5","key":"5795_CR27","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ad7f89","volume":"21","author":"X Wen","year":"2024","unstructured":"Wen, X., Jia, S., Han, D., et al.: Filter banks guided correlational convolutional neural network for SSVEPs based BCI classification. J. Neural Eng. 21(5), 056024 (2024)","journal-title":"J. Neural Eng."},{"issue":"5","key":"5795_CR28","doi-asserted-by":"publisher","first-page":"948","DOI":"10.1109\/TNSRE.2018.2826541","volume":"26","author":"Y Zhang","year":"2018","unstructured":"Zhang, Y., Guo, D., Li, F., Yin, E., Zhang, Y., Li, P., et al.: Correlated component analysis for enhancing the performance of SSVEP-based brain-computer interface. IEEE Trans. Neural Syst. Rehabil. Eng. 26(5), 948\u201356 (2018)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"5795_CR29","doi-asserted-by":"publisher","first-page":"2615","DOI":"10.1109\/TNSRE.2021.3132162","volume":"29","author":"W Ding","year":"2021","unstructured":"Ding, W., Shan, J., Fang, B., Wang, C., Sun, F., Li, X.: Filter Bank Convolutional Neural Network for Short Time-Window Steady-State Visual Evoked Potential Classification. IEEE Trans. Neural Syst. Rehabil. Eng. 29, 2615\u201324 (2021)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"5795_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2022.109674","volume":"379","author":"H Yao","year":"2022","unstructured":"Yao, H., Liu, K., Deng, X., Tang, X., Yu, H.: FB-EEGNet: A fusion neural network across multi-stimulus for SSVEP target detection. J. Neurosci. Methods 379, 109674 (2022)","journal-title":"J. Neurosci. Methods"},{"issue":"7","key":"5795_CR31","doi-asserted-by":"publisher","first-page":"10125","DOI":"10.1007\/s10586-024-04492-6","volume":"27","author":"J Nan","year":"2024","unstructured":"Nan, J., Zhang, S., Li, D., Zhang, K., Han, C., Meng, Y., et al.: Innovative combination of covariance analysis-based sliding time window and task-related component analysis for steady-state visual evoked potential recognition. Cluster Computing 27(7), 10125\u201339 (2024)","journal-title":"Cluster Computing"},{"issue":"1","key":"5795_CR32","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1177\/09544119221135714","volume":"237","author":"M Bhuvaneshwari","year":"2023","unstructured":"Bhuvaneshwari, M., Grace Mary Kanaga, E., George, S.T.: Classification of SSVEP-EEG signals using CNN and Red Fox Optimization for BCI applications. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 237(1), 134\u201343 (2023)","journal-title":"Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine"},{"key":"5795_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TIM.2023.3324345","volume":"72","author":"S Yadav","year":"2023","unstructured":"Yadav, S., Saha, S.K., Kar, R.: Evolutionary Algorithm-Based Optimal Wiener-Adaptive Filter Design: An Application on EEG Noise Mitigation. IEEE Trans. Instrum. Meas. 72, 1\u201312 (2023)","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"6","key":"5795_CR34","doi-asserted-by":"publisher","DOI":"10.3390\/s22062092","volume":"22","author":"ZAA Alyasseri","year":"2022","unstructured":"Alyasseri, Z.A.A., Alomari, O.A., Papa, J.P., Al-Betar, M.A., Abdulkareem, K.H., Mohammed, M.A., et al.: EEG Channel Selection Based User Identification via Improved Flower Pollination Algorithm. Sensors 22(6), 2092 (2022)","journal-title":"Sensors"},{"issue":"1","key":"5795_CR35","doi-asserted-by":"publisher","DOI":"10.3390\/bioengineering11010030","volume":"11","author":"S Wang","year":"2023","unstructured":"Wang, S., Luo, Z., Zhao, S., Zhang, Q., Liu, G., Wu, D., et al.: Classification of EEG Signals Based on Sparrow Search Algorithm-Deep Belief Network for Brain-Computer Interface. Bioengineering 11(1), 30 (2023)","journal-title":"Bioengineering"},{"issue":"1","key":"5795_CR36","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1080\/21642583.2019.1708830","volume":"8","author":"J Xue","year":"2020","unstructured":"Xue, J., Shen, B.: A novel swarm intelligence optimization approach: sparrow search algorithm. Systems Science & Control Engineering. 8(1), 22\u201334 (2020)","journal-title":"Systems Science & Control Engineering."},{"key":"5795_CR37","first-page":"64","volume":"40","author":"G Yang","year":"2021","unstructured":"Yang, G.: Research on optimized PID based on SSA in path tracking of mobile robot. Foreign Electron Meas Technol. 40, 64\u20139 (2021)","journal-title":"Foreign Electron Meas Technol."},{"issue":"10","key":"5795_CR38","doi-asserted-by":"publisher","first-page":"10867","DOI":"10.1007\/s10462-023-10435-1","volume":"56","author":"Y Yue","year":"2023","unstructured":"Yue, Y., Cao, L., Lu, D., Hu, Z., Xu, M., Wang, S., et al.: Review and empirical analysis of sparrow search algorithm. Artif. Intell. Rev. 56(10), 10867\u2013919 (2023)","journal-title":"Artif. Intell. Rev."},{"issue":"10","key":"5795_CR39","doi-asserted-by":"publisher","first-page":"1746","DOI":"10.1109\/TNSRE.2016.2627556","volume":"25","author":"Y Wang","year":"2017","unstructured":"Wang, Y., Chen, X., Gao, X., Gao, S.: A Benchmark Dataset for SSVEP-Based Brain-Computer Interfaces. IEEE Trans. Neural Syst. Rehabil. Eng. 25(10), 1746\u201352 (2017)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"5795_CR40","doi-asserted-by":"publisher","DOI":"10.1093\/gigascience\/giae041","volume":"13","author":"Y Sun","year":"2024","unstructured":"Sun, Y., Liang, L., Li, Y., Chen, X., Gao, X.: Dual-Alpha: a large EEG study for dual-frequency SSVEP brain-computer interface. Gigascience 13, giae041 (2024)","journal-title":"Gigascience"},{"key":"5795_CR41","doi-asserted-by":"publisher","first-page":"1606","DOI":"10.1109\/TNSRE.2024.3387283","volume":"32","author":"D Li","year":"2024","unstructured":"Li, D., Wang, X., Dou, M., Zhao, Y., Cui, X., Xiang, J., et al.: Multi-stimulus Least-squares Transformation with Online Adaptation Scheme to Reduce Calibration Effort for SSVEP-based BCIs. IEEE Trans. Neural Syst. Rehabil. Eng 32, 1606\u20131615 (2024)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng"},{"issue":"9","key":"5795_CR42","doi-asserted-by":"publisher","first-page":"6349","DOI":"10.1109\/TSMC.2025.3578533","volume":"55","author":"R Wei","year":"2025","unstructured":"Wei, R., Hua, C., Chen, J., et al.: Attention-Based Multiscale tCNN for SSVEP Classification and Its Application to Bionic Intelligent Soft Gripper Control [J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems 55(9), 6349\u201358 (2025)","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics: Systems"},{"issue":"6","key":"5795_CR43","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1016\/S1388-2457(02)00057-3","volume":"113","author":"JR Wolpaw","year":"2002","unstructured":"Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: Brain-computer interfaces for communication and control. Clinical Neurophysiology 113(6), 767\u201391 (2002)","journal-title":"Clinical Neurophysiology"},{"issue":"10","key":"5795_CR44","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0140703","volume":"10","author":"M Nakanishi","year":"2015","unstructured":"Nakanishi, M., Wang, Y., Wang, Y.-T., et al.: A comparison study of canonical correlation analysis based methods for detecting steady-state visual evoked potentials. PloS one 10(10), e0140703 (2015)","journal-title":"PloS one"}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-025-05795-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-025-05795-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-025-05795-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T21:02:25Z","timestamp":1765486945000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-025-05795-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,27]]},"references-count":44,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["5795"],"URL":"https:\/\/doi.org\/10.1007\/s10586-025-05795-y","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"type":"print","value":"1386-7857"},{"type":"electronic","value":"1573-7543"}],"subject":[],"published":{"date-parts":[[2025,10,27]]},"assertion":[{"value":"12 January 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 September 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 October 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 October 2025","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":"Competing Interests"}},{"value":"This article does not contain studies with human participants or animals carried out by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}],"article-number":"1073"}}