{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T23:20:45Z","timestamp":1771024845920,"version":"3.50.1"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T00:00:00Z","timestamp":1745366400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T00:00:00Z","timestamp":1745366400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 62374135"],"award-info":[{"award-number":["No. 62374135"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Development Program of Shaanxi","award":["No.2023-YBGY-273"],"award-info":[{"award-number":["No.2023-YBGY-273"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Complex Intell. Syst."],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1007\/s40747-025-01848-2","type":"journal-article","created":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T10:05:58Z","timestamp":1745402758000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A few-shot learning-based dual-input neural network for complex spectrogram recognition system with millimeter-wave radar"],"prefix":"10.1007","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8305-9678","authenticated-orcid":false,"given":"Kaiyu","family":"Chen","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0230-2059","authenticated-orcid":false,"given":"Shaoxi","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Wei","family":"Li","sequence":"additional","affiliation":[]},{"given":"Yucheng","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Cunqian","family":"Feng","sequence":"additional","affiliation":[]},{"given":"Yannian","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Jian","family":"Cao","sequence":"additional","affiliation":[]},{"given":"Binfeng","family":"Zong","sequence":"additional","affiliation":[]},{"given":"Minming","family":"Gu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,4,23]]},"reference":[{"key":"1848_CR1","unstructured":"\u201cWorld population aging 2023.\u201d Jan. 2024. [Online]. Available: https:\/\/desapublications.un.org\/"},{"key":"1848_CR2","doi-asserted-by":"publisher","DOI":"10.4324\/9781003480280","volume-title":"China\u2019s Aging Population: Development and Policy Options","author":"\u201cChina Development Research Foundation","year":"2024","unstructured":"\u201cChina Development Research Foundation (2024) China\u2019s Aging Population: Development and Policy Options. Routledge, London. https:\/\/doi.org\/10.4324\/9781003480280"},{"issue":"7824","key":"1848_CR3","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1038\/s41586-020-2669-y","volume":"585","author":"A Haque","year":"2020","unstructured":"Haque A, Milstein A, Fei-Fei L (2020) Illuminating the dark spaces of healthcare with ambient intelligence. Nature 585(7824):193\u2013202","journal-title":"Nature"},{"issue":"506","key":"1848_CR4","first-page":"1","volume":"24","author":"A Bertolazzi","year":"2024","unstructured":"Bertolazzi A, Quaglia V, Bongelli R (2024) Barriers and facilitators to health technology adoption by older adults with chronic diseases: an integrative systematic review. BMC Public Health 24(506):1\u201317","journal-title":"BMC Public Health"},{"issue":"1","key":"1848_CR5","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1109\/TII.2022.3165875","volume":"19","author":"MAA Al-qaness","year":"2023","unstructured":"Al-qaness MAA, Dahou A, Abd Elaziz M, Helmi AM (2023) Multi-ResAtt: multilevel residual network with attention for human activity recognition using wearable sensors. IEEE Trans Industr Inf 19(1):144\u2013152","journal-title":"IEEE Trans Industr Inf"},{"issue":"805","key":"1848_CR6","first-page":"1","volume":"13","author":"S Yu","year":"2023","unstructured":"Yu S, Zhan H, Lian X (2023) A smartphone-based sEMG signal analysis system for human action recognition. Biosensors 13(805):1\u201316","journal-title":"Biosensors"},{"key":"1848_CR7","first-page":"2515313","volume":"73","author":"A Tripathi","year":"2024","unstructured":"Tripathi A, Gupta A, Prathosh AP, Muthukrishnan P, Kumar L (2024) NeuroAiR: deep learning framework for airwriting recognition from scalp-recorded neural signals. IEEE Trans Instr Measure 73:2515313","journal-title":"IEEE Trans Instr Measure"},{"issue":"13","key":"1848_CR8","doi-asserted-by":"crossref","first-page":"11761","DOI":"10.1109\/JIOT.2023.3243944","volume":"10","author":"C Yin","year":"2023","unstructured":"Yin C, Miao X, Chen J, Jiang H, Chen D, Tong Y, Zheng S (2023) Human activity recognition with low-resolution infrared array sensor using semi-supervise cross-domain neural networks for indoor environment. IEEE Internet Things J 10(13):11761\u201311772","journal-title":"IEEE Internet Things J"},{"issue":"6997","key":"1848_CR9","first-page":"1","volume":"23","author":"Y Jiang","year":"2023","unstructured":"Jiang Y, Jeong I, Heravi M, Sarkar S, Shin H, Ahn Y (2023) Multi-camera-based human activity recognition for human-robot collaboration in construction. Sensors 23(6997):1\u201320","journal-title":"Sensors"},{"issue":"3","key":"1848_CR10","doi-asserted-by":"crossref","first-page":"938","DOI":"10.1109\/JMW.2023.3264494","volume":"3","author":"I Ullmann","year":"2023","unstructured":"Ullmann I, Guendel R, Kruse N, Fioranelli F, Yarovoy A (2023) A survey on radar-based continuous human activity recognition. IEEE J Microw 3(3):938\u2013950","journal-title":"IEEE J Microw"},{"issue":"10","key":"1848_CR11","first-page":"7005304","volume":"8","author":"W Li","year":"2024","unstructured":"Li W, Liu J, Guo S, Jia Y (2024) Human activity recognition method based on scattering separation using multifrequency radar data. IEEE Sensor Letters 8(10):7005304","journal-title":"IEEE Sensor Letters"},{"issue":"22","key":"1848_CR12","doi-asserted-by":"crossref","first-page":"36287","DOI":"10.1109\/JSEN.2024.3452110","volume":"24","author":"S Ahmed","year":"2024","unstructured":"Ahmed S, Abdullah S, Cho S (2024) Advancements in radar point cloud processing for macro human movements in healthcare and assisted living domains: a review. IEEE Sens J 24(22):36287\u201336305","journal-title":"IEEE Sens J"},{"key":"1848_CR13","doi-asserted-by":"crossref","first-page":"700","DOI":"10.1109\/OJEMB.2024.3420747","volume":"5","author":"F Savvidou","year":"2024","unstructured":"Savvidou F, Tegos S, Diamantoulakis P, Karagiannidis G (2024) Passive radar sensing for human activity recognition: a survey. IEEE Open J Eng Med Biol 5:700\u2013706","journal-title":"IEEE Open J Eng Med Biol"},{"key":"1848_CR14","first-page":"5103112","volume":"60","author":"X Li","year":"2022","unstructured":"Li X, He Y, Fioranelli F, Jing X (2022) Semisupervised human activity recognition with radar micro-Doppler signatures. IEEE Trans Geosci Remote Sens 60:5103112","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"20","key":"1848_CR15","doi-asserted-by":"crossref","first-page":"25128","DOI":"10.1109\/JSEN.2023.3314407","volume":"23","author":"M Gu","year":"2023","unstructured":"Gu M, Chen Z, Chen K, Pan H (2023) IR-ST: a lightweight transformer network for human fall detection based on FMCW radar. IEEE Sens J 23(20):25128\u201325135","journal-title":"IEEE Sens J"},{"issue":"9","key":"1848_CR16","doi-asserted-by":"crossref","first-page":"8111","DOI":"10.1109\/JIOT.2022.3229462","volume":"10","author":"Z Ou","year":"2023","unstructured":"Ou Z, Ye W (2023) Lightweight deep learning model for radar-based fall detection with metric learning. IEEE Internet Things J 10(9):8111\u20138122","journal-title":"IEEE Internet Things J"},{"key":"1848_CR17","doi-asserted-by":"crossref","first-page":"22055","DOI":"10.1007\/s11042-023-15700-7","volume":"83","author":"X Zhou","year":"2024","unstructured":"Zhou X, Meng X, Zheng J, Fang G, Guo T (2024) Human body recognition based on the sparse point cloud data form MIMO millimeter-wave radar for smart home. Multimed Tools Appl 83:22055\u201322074","journal-title":"Multimed Tools Appl"},{"key":"1848_CR18","doi-asserted-by":"crossref","first-page":"2219","DOI":"10.1007\/s11760-023-02894-4","volume":"18","author":"M Gu","year":"2024","unstructured":"Gu M, Chen Z, Chen K (2024) RMPCT-Net: a multi-channel parallel CNN and transformer network model applied to HAR using FMCW radar. SIViP 18:2219\u20132229","journal-title":"SIViP"},{"key":"1848_CR19","doi-asserted-by":"crossref","first-page":"8001710","DOI":"10.1109\/TIM.2024.3366575","volume":"73","author":"H Raeis","year":"2024","unstructured":"Raeis H, Kazemi M, Shirmohammadi S (2024) CAE-MAS: convolutional autoencoder interference cancellation for multiperson activity sensing with FMCE microwave radar. IEEE Trans Instrum Meas 73:8001710","journal-title":"IEEE Trans Instrum Meas"},{"issue":"15","key":"1848_CR20","doi-asserted-by":"crossref","first-page":"17815","DOI":"10.1109\/JSEN.2023.3290565","volume":"23","author":"S Gong","year":"2023","unstructured":"Gong S, Shi H, Yan X et al (2023) Human activity recognition with FMCW radar using few-shot learning. IEEE Sens J 23(15):17815\u201317824","journal-title":"IEEE Sens J"},{"issue":"4060","key":"1848_CR21","first-page":"1","volume":"12","author":"J Zhou","year":"2023","unstructured":"Zhou J, Sun C, Jang K, Yang S, Kim Y (2023) Human activity recognition based on continuous-wave radar and bidirectional gate recurrent unit. Electronics 12(4060):1\u201314","journal-title":"Electronics"},{"issue":"7","key":"1848_CR22","doi-asserted-by":"crossref","first-page":"11750","DOI":"10.1109\/JIOT.2023.3330996","volume":"11","author":"X Li","year":"2023","unstructured":"Li X, Chen S, Zhang S et al (2023) Advancing IR-UWB radar human activity recognition with swin transformers and supervised contrastive learning. IEEE Internet Things J 11(7):11750\u201311766","journal-title":"IEEE Internet Things J"},{"issue":"12","key":"1848_CR23","doi-asserted-by":"crossref","first-page":"13522","DOI":"10.1109\/JSEN.2021.3068388","volume":"21","author":"Y Kim","year":"2021","unstructured":"Kim Y, Alnujaim I, Oh D (2021) Human activity classification based on point clouds measured by millimeter wave MIMO radar with deep recurrent neural networks. IEEE Sens J 21(12):13522\u201313529","journal-title":"IEEE Sens J"},{"issue":"9","key":"1848_CR24","doi-asserted-by":"crossref","first-page":"8648","DOI":"10.1109\/JSEN.2022.3156762","volume":"22","author":"F Abdu","year":"2022","unstructured":"Abdu F, Zhang Y, Deng Z (2022) Activity classification based on feature fusion of FMCW radar human motion micro-doppler signatures. IEEE Sens J 22(9):8648\u20138662","journal-title":"IEEE Sens J"},{"issue":"11","key":"1848_CR25","doi-asserted-by":"crossref","first-page":"10024","DOI":"10.1109\/JIOT.2023.3235808","volume":"10","author":"C Ding","year":"2023","unstructured":"Ding C, Zhang L, Chen H et al (2023) Sparsity-based human activity recognition with PointNet using a portable FMCW radar. IEEE Internet Things J 10(11):10024\u201310037","journal-title":"IEEE Internet Things J"},{"key":"1848_CR26","first-page":"5121117","volume":"60","author":"X Qiao","year":"2022","unstructured":"Qiao X, Feng Y, Liu S, Tao R (2022) Radar point clouds processing for human activity classification using convolutional multilinear subspace learning. IEEE Trans Geosci Remote Sens 60:5121117","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"1848_CR27","doi-asserted-by":"crossref","unstructured":"Chen H, Ding C, Zhang L, et al (2022) Human activity recognition using temporal 3DCNN based on FMCW radar. IEEE MTT-S International Microwave Biomedical Conference(IMBioC) 13 June: 245\u2013247","DOI":"10.1109\/IMBioC52515.2022.9790101"},{"key":"1848_CR28","first-page":"8500910","volume":"72","author":"D Rodrigues","year":"2023","unstructured":"Rodrigues D, Zeng L, Li C (2023) Multitarget physical activities monitoring and classification using a V-band FMCW radar. IEEE Trans Instrum Meas 72:8500910","journal-title":"IEEE Trans Instrum Meas"},{"key":"1848_CR29","first-page":"1002311","volume":"60","author":"W-Y Kim","year":"2022","unstructured":"Kim W-Y, Seo D-H (2022) Radar-based human activity recognition combining range-time-doppler maps and range-distributed-convolutional neural networks. IEEE Trans Geosci Remote Sens 60:1002311","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"7208","key":"1848_CR30","first-page":"1","volume":"23","author":"G Zhang","year":"2023","unstructured":"Zhang G, Li S, Zhang K, Lin Y-J (2023) Machine learning-based human posture identification from point cloud data acquisitioned by FMCW millimetre-wave radar. Sensors 23(7208):1\u201320","journal-title":"Sensors"},{"key":"1848_CR31","doi-asserted-by":"crossref","unstructured":"Wang B, Guo Y (2022) Soft fall detection using frequency modulated continuous wave radar and regional power burst curve. Proceeding of 2022 Asia-Pacific Microwave Conference, 09 January 2023, Yokohama, Japan: 240\u2013242.","DOI":"10.23919\/APMC55665.2022.9999763"},{"key":"1848_CR32","doi-asserted-by":"crossref","first-page":"7933","DOI":"10.1007\/s00521-022-06886-2","volume":"34","author":"S Shah","year":"2022","unstructured":"Shah S, Tahir A, Kernec J, Zoha A, Fioranelli F (2022) Data portability for activities of daily living and fall detection in different environments using radar micro-doppler. Neural Comput Appl 34:7933\u20137953","journal-title":"Neural Comput Appl"},{"issue":"9","key":"1848_CR33","doi-asserted-by":"crossref","first-page":"6821","DOI":"10.1109\/TGRS.2019.2908758","volume":"57","author":"C Ding","year":"2019","unstructured":"Ding C, Hong H, Zou Y et al (2019) Continuous human motion recognition with a dynamic range-doppler trajectory method based on FMCW radar. IEEE Trans Geosci Remote Sens 57(9):6821\u20136831","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"12","key":"1848_CR34","doi-asserted-by":"crossref","first-page":"10236","DOI":"10.1109\/JIOT.2023.3237494","volume":"10","author":"P Zhao","year":"2023","unstructured":"Zhao P, Lu C, Wang B, Trigoni N, Markham A (2023) CubeLearn: end-to-end learning for human motion recognition from raw mmWave radar signals. IEEE Internet Things J 10(12):10236\u201310249","journal-title":"IEEE Internet Things J"},{"key":"1848_CR35","doi-asserted-by":"crossref","unstructured":"Biswas S, Ayna C, Gurbuz S, Gurbuz A(2023) Complex SincNet for more interpretable radar based activity recognition. 2023 IEEE Radar Conference (RadarConf23), 21 June 2023, San Antonio, TX, USA: 1\u20136","DOI":"10.1109\/RadarConf2351548.2023.10149682"},{"issue":"2","key":"1848_CR36","doi-asserted-by":"crossref","first-page":"1000","DOI":"10.1109\/JBHI.2023.3339703","volume":"28","author":"C Wang","year":"2024","unstructured":"Wang C, Kumar T, Raedt W, Camps G, Hallez H, Vanrumste B (2024) Eat-radar: continuous fine-grained intake gesture detection using FMCW radar and 3D temporal convolutional network with attention. IEEE J Biomed Health Inform 28(2):1000\u20131011","journal-title":"IEEE J Biomed Health Inform"},{"issue":"6","key":"1848_CR37","doi-asserted-by":"crossref","first-page":"8289","DOI":"10.1109\/TAES.2024.3427101","volume":"60","author":"W Yin","year":"2024","unstructured":"Yin W, Shi L, Shi Y (2024) Continuous human action recognition by multiple-object-detection-based FMCW radar. IEEE Trans Aerosp Electron Syst 60(6):8289\u20138297","journal-title":"IEEE Trans Aerosp Electron Syst"},{"issue":"3","key":"1848_CR38","doi-asserted-by":"crossref","first-page":"4160","DOI":"10.1109\/TII.2023.3316164","volume":"20","author":"C Gianoglio","year":"2024","unstructured":"Gianoglio C, Mohanna A, Rizik A, Moroney L, Valle M (2024) On edge human action recognition using radar-based sensing and deep learning. IEEE Trans Industr Inf 20(3):4160\u20134172","journal-title":"IEEE Trans Industr Inf"},{"issue":"8","key":"1848_CR39","first-page":"1","volume":"19","author":"N Nguyen","year":"2024","unstructured":"Nguyen N, Pham M, Doan V-S, Le V (2024) Improving human activity classification based on micro-dopppler signatures of FMCW radar with the effect of noise. PLoS ONE 19(8):1\u201326","journal-title":"PLoS ONE"},{"issue":"3","key":"1848_CR40","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1109\/JSEN.2019.2946095","volume":"20","author":"H Li","year":"2020","unstructured":"Li H, Shrestha A, Heidari H, Kernec J, Fioranelli F (2020) Bi-LSTM network for multimodal continuous human activity recognition and fall detection. IEEE Sens J 20(3):1191\u20131201","journal-title":"IEEE Sens J"},{"issue":"5100","key":"1848_CR41","first-page":"1","volume":"23","author":"L Cao","year":"2023","unstructured":"Cao L, Liang S, Zhao Z, Wang D, Fu C, Du K (2023) Human activity recognition method based on FMCW radar sensor with multi-domain feature attention fusion network. Sensors 23(5100):1\u201315","journal-title":"Sensors"},{"key":"1848_CR42","doi-asserted-by":"crossref","first-page":"24509","DOI":"10.1109\/ACCESS.2022.3150838","volume":"10","author":"H Khalid","year":"2022","unstructured":"Khalid H, Gorji A, Bourdoux A, Pollin S, Sahli H (2022) Multi-view CNN-LSTM architecture for radar-based human activity recognition. IEEE Access 10:24509\u201324519","journal-title":"IEEE Access"},{"key":"1848_CR43","doi-asserted-by":"crossref","first-page":"1517","DOI":"10.1007\/s40747-023-01236-8","volume":"10","author":"M Gu","year":"2024","unstructured":"Gu M, Chen K, Chen Z (2024) RFDANet: an FMCW and TOF radar fusion approach for driver activity recognition using multi-level attention based CNN and LSTM network. Complex & Intell Syst 10:1517\u20131530","journal-title":"Complex & Intell Syst"},{"issue":"18","key":"1848_CR44","doi-asserted-by":"crossref","first-page":"22019","DOI":"10.1109\/JSEN.2023.3300357","volume":"23","author":"X Feng","year":"2023","unstructured":"Feng X, Wang Y, Li W, Chen P, Zheng H (2023) DAMUN: a domain adaptive human activity recognition network based on multimodal feature fusion. IEEE Sens J 23(18):22019\u201322030","journal-title":"IEEE Sens J"},{"key":"1848_CR45","doi-asserted-by":"publisher","DOI":"10.1109\/TMTT.2024.3441591","author":"X Yang","year":"2024","unstructured":"Yang X, Gao W, Qu X, Ma Z, Zhang H (2024) Through-the-wall radar human activity micro-doppler signature representation method based on joint boulic-sinusoidal pendulum model: 1\u201316. Early Access. https:\/\/doi.org\/10.1109\/TMTT.2024.3441591","journal-title":"Early Access"},{"key":"1848_CR46","doi-asserted-by":"crossref","unstructured":"Shah S, Fioranelli F (2019) Human activity recognition: preliminary results for dataset portability using FMCW radar. 2019 International Radar Conference (RADAR2019): 171307","DOI":"10.1109\/RADAR41533.2019.171307"},{"key":"1848_CR47","first-page":"28","volume":"420","author":"U Saeed","year":"2022","unstructured":"Saeed U, Alqahtani F, Baothman F et al (2022) Monitoring discrete activities of daily living of young and older adults using 5.8GHz frequency modulated continuous wave radar and ResNet algorithm. Body Area Netw: Smart IOT Big Data Intell Manage 420:28\u201338","journal-title":"Body Area Netw: Smart IOT Big Data Intell Manage"},{"issue":"10","key":"1848_CR48","doi-asserted-by":"crossref","first-page":"4750","DOI":"10.3390\/s23104750","volume":"23","author":"H Zhou","year":"2023","unstructured":"Zhou H, Zhao Y, Liu Y, Lu S, An X, Liu Q (2023) Multi-sensor data fusion and CNN-LSTM model for human activity recognition system. Sensors 23(10):4750","journal-title":"Sensors"},{"issue":"21","key":"1848_CR49","doi-asserted-by":"crossref","first-page":"24318","DOI":"10.1109\/JSEN.2021.3111187","volume":"21","author":"Y Sun","year":"2021","unstructured":"Sun Y, Xiong H, Tan D, Han T, Du R, Yang X, Ye T (2021) Moving target localization and activity\/gesture recognition for indoor radio frequency sensing applications. IEEE Sens J 21(21):24318\u201324326","journal-title":"IEEE Sens J"}],"container-title":["Complex &amp; Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-025-01848-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40747-025-01848-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-025-01848-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,17]],"date-time":"2025-05-17T11:22:31Z","timestamp":1747480951000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40747-025-01848-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,23]]},"references-count":49,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,6]]}},"alternative-id":["1848"],"URL":"https:\/\/doi.org\/10.1007\/s40747-025-01848-2","relation":{},"ISSN":["2199-4536","2198-6053"],"issn-type":[{"value":"2199-4536","type":"print"},{"value":"2198-6053","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,23]]},"assertion":[{"value":"7 November 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 March 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 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":"Corresponding authors declare on behalf of all authors that there is no conflict of interest. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The experiments were conducted under the guidance of Northwestern Polytechnical University.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"All procedures involving human research conformed to the ethical standards of Northwestern Polytechnical University and followed Declaration of Helsinki.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participant"}}],"article-number":"261"}}