{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T19:51:22Z","timestamp":1774381882637,"version":"3.50.1"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,1,16]],"date-time":"2025-01-16T00:00:00Z","timestamp":1736985600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,16]],"date-time":"2025-01-16T00:00:00Z","timestamp":1736985600000},"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":["Cogn Comput"],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1007\/s12559-024-10399-6","type":"journal-article","created":{"date-parts":[[2025,1,16]],"date-time":"2025-01-16T03:38:17Z","timestamp":1736998697000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Functional Connectivity Imbalance Between Positive and Negative Networks in Mild Cognitive Impairment via Feature Selection"],"prefix":"10.1007","volume":"17","author":[{"given":"Haifeng","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changlin","family":"Pu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,16]]},"reference":[{"issue":"3","key":"10399_CR1","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/j.jalz.2019.01.010","volume":"15","author":"A Association","year":"2019","unstructured":"Association A. 2019 Alzheimer\u2019s disease facts and figures. Alzheimers Dement. 2019;15(3):321\u201387.","journal-title":"Alzheimers Dement"},{"issue":"1","key":"10399_CR2","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.neurobiolaging.2004.12.010","volume":"27","author":"B Borroni","year":"2006","unstructured":"Borroni B, Anchisi D, Paghera B, et al. Combined 99mTc-ECD SPECT and neuropsychological studies in MCI for the assessment of conversion to AD. Neurobiol Aging. 2006;27(1):24\u201331.","journal-title":"Neurobiol Aging"},{"issue":"4","key":"10399_CR3","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1097\/00001504-200207000-00008","volume":"15","author":"M Zaudig","year":"2002","unstructured":"Zaudig M. Mild cognitive impairment in the elderly. Curr Opin Psychiatry. 2002;15(4):387\u201393.","journal-title":"Curr Opin Psychiatry"},{"key":"10399_CR4","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/j.neuroimage.2017.06.006","volume":"157","author":"M Pannunzi","year":"2017","unstructured":"Pannunzi M, Hindriks R, Bettinardi RG, et al. Resting-state fMRI correlations: from link-wise unreliability to whole brain stability. Neuroimage. 2017;157:250\u201362.","journal-title":"Neuroimage"},{"key":"10399_CR5","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1016\/j.pnpbp.2017.08.012","volume":"81","author":"S Wang","year":"2018","unstructured":"Wang S, Zhan Y, Zhang Y, et al. Abnormal long-and short-range functional connectivity in adolescent-onset schizophrenia patients: a resting-state fMRI study. Prog Neuropsychopharmacol Biol Psychiatry. 2018;81:445\u201351.","journal-title":"Prog Neuropsychopharmacol Biol Psychiatry"},{"issue":"10","key":"10399_CR6","doi-asserted-by":"crossref","first-page":"1907","DOI":"10.1016\/j.ejrad.2014.07.003","volume":"83","author":"W Zhang","year":"2014","unstructured":"Zhang W, Liu X, Zhang Y, et al. Disrupted functional connectivity of the hippocampus in patients with hyperthyroidism: evidence from resting-state fMRI. Eur J Radiol. 2014;83(10):1907\u201313.","journal-title":"Eur J Radiol"},{"key":"10399_CR7","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.neuroimage.2017.11.025","volume":"167","author":"F de Vos","year":"2018","unstructured":"de Vos F, Koini M, Schouten TM, et al. A comprehensive analysis of resting state fMRI measures to classify individual patients with Alzheimer\u2019s disease. Neuroimage. 2018;167:62\u201372.","journal-title":"Neuroimage"},{"issue":"24","key":"10399_CR8","doi-asserted-by":"crossref","first-page":"9868","DOI":"10.1073\/pnas.87.24.9868","volume":"87","author":"S Ogawa","year":"1990","unstructured":"Ogawa S, Lee TM, Kay AR, et al. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proceedings of the National Academy of Sciences. 1990;87(24):9868\u201372.","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"9","key":"10399_CR9","doi-asserted-by":"crossref","first-page":"700","DOI":"10.1038\/nrn2201","volume":"8","author":"MD Fox","year":"2007","unstructured":"Fox MD, Raichle ME. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci. 2007;8(9):700\u201311.","journal-title":"Nat Rev Neurosci"},{"key":"10399_CR10","doi-asserted-by":"crossref","first-page":"735","DOI":"10.1146\/annurev.physiol.66.082602.092845","volume":"66","author":"NK Logothetis","year":"2004","unstructured":"Logothetis NK, Wandell BA. Interpreting the BOLD signal. Annu Rev Physiol. 2004;66:735\u201369.","journal-title":"Annu Rev Physiol"},{"issue":"2","key":"10399_CR11","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1038\/nrn730","volume":"3","author":"DJ Heeger","year":"2002","unstructured":"Heeger DJ, Ress D. What does fMRI tell us about neuronal activity? Nat Rev Neurosci. 2002;3(2):142\u201351.","journal-title":"Nat Rev Neurosci"},{"issue":"7848","key":"10399_CR12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41586-021-03284-x","volume":"591","author":"CA Brittin","year":"2021","unstructured":"Brittin CA, Cook SJ, Hall DH, et al. A multi-scale brain map derived from whole-brain volumetric reconstructions. Nature. 2021;591(7848):1\u20136.","journal-title":"Nature"},{"key":"10399_CR13","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1016\/j.ebiom.2019.08.023","volume":"47","author":"W Yan","year":"2019","unstructured":"Yan W, Calhoun V, Song M, et al. Discriminating schizophrenia using recurrent neural networks applied on time courses of multi-site FMRI data. EBioMedicine. 2019;47:543\u201352.","journal-title":"EBioMedicine"},{"issue":"3","key":"10399_CR14","doi-asserted-by":"crossref","first-page":"2045","DOI":"10.1016\/j.neuroimage.2011.10.015","volume":"59","author":"CY Wee","year":"2012","unstructured":"Wee CY, Yap PT, Zhang D, et al. Identification of MCI individuals using structural and functional connectivity networks. Neuroimage. 2012;59(3):2045\u201356.","journal-title":"Neuroimage"},{"issue":"2","key":"10399_CR15","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1109\/TNB.2015.2403274","volume":"14","author":"X Zhang","year":"2015","unstructured":"Zhang X, Hu B, Ma X, et al. Resting-state whole-brain functional connectivity networks for MCI classification using L2-regularized logistic regression. IEEE Trans Nanobiosci. 2015;14(2):237\u201347.","journal-title":"IEEE Trans Nanobiosci"},{"issue":"40","key":"10399_CR16","doi-asserted-by":"crossref","first-page":"10222","DOI":"10.1523\/JNEUROSCI.2250-06.2006","volume":"26","author":"KA Celone","year":"2006","unstructured":"Celone KA, Calhoun VD, Dickerson BC, et al. Alterations in memory networks in mild cognitive impairment and Alzheimer\u2019s disease: an independent component analysis. J Neurosci. 2006;26(40):10222\u201331.","journal-title":"J Neurosci"},{"key":"10399_CR17","doi-asserted-by":"crossref","first-page":"9673","DOI":"10.1073\/pnas.0504136102","volume":"102","author":"MD Fox","year":"2005","unstructured":"Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, Raichle ME. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A. 2005;102:9673\u20138.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"10399_CR18","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1002\/hbm.20113","volume":"26","author":"P Fransson","year":"2005","unstructured":"Fransson P. Spontaneous low-frequency BOLD signal fluctuations: an fMRI investigation of the resting-state default mode of brain function hypothesis. Hum Brain Mapp. 2005;26:15\u201329.","journal-title":"Hum Brain Mapp"},{"issue":"1\u20133","key":"10399_CR19","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1016\/j.schres.2007.05.029","volume":"97","author":"Y Zhou","year":"2007","unstructured":"Zhou Y, Liang M, Tian L, et al. Functional disintegration in paranoid schizophrenia using resting-state fMRI. Schizophr Res. 2007;97(1\u20133):194\u2013205.","journal-title":"Schizophr Res"},{"issue":"3","key":"10399_CR20","first-page":"215","volume":"2","author":"H Shao","year":"2011","unstructured":"Shao H, Du X, Du X, et al. Research progress in the role of the posterior cingulate cortex\/cuneus as a key node in the resting state functional networks. Magn Reson Imaging. 2011;2(3):215\u20137.","journal-title":"Magn Reson Imaging"},{"key":"10399_CR21","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/B978-008045046-9.00435-6","volume":"8","author":"AK Barbey","year":"2009","unstructured":"Barbey AK, Barsalou LW. Reasoning and problem solving: models. Encyclopedia of Neuroscience. 2009;8:35\u201343.","journal-title":"Encyclopedia of Neuroscience"},{"key":"10399_CR22","doi-asserted-by":"crossref","first-page":"5932","DOI":"10.1109\/JSTARS.2021.3086151","volume":"14","author":"C Zhang","year":"2021","unstructured":"Zhang C, Ye M, Lei L, Qian Y. Feature selection for cross-scene hyperspectral image classification using cross-domain I-ReliefF. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2021;14:5932\u201349.","journal-title":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"},{"key":"10399_CR23","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.patrec.2018.08.021","volume":"112","author":"R Huang","year":"2018","unstructured":"Huang R, Jiang W, Sun G. Manifold-based constraint Laplacian score for multi-label feature selection. Pattern Recogn Lett. 2018;112:346\u201352.","journal-title":"Pattern Recogn Lett"},{"issue":"3","key":"10399_CR24","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1109\/TCSS.2020.2966910","volume":"7","author":"A Satorra","year":"2020","unstructured":"Satorra A, Bentler PM. Comparative analysis of feature selection algorithms for computational personality prediction from social media. IEEE Transactions on Computational Social Systems. 2020;7(3):587\u201399.","journal-title":"IEEE Transactions on Computational Social Systems"},{"key":"10399_CR25","doi-asserted-by":"crossref","unstructured":"Wu H, Kong L, Zeng Y, et al. Resting-state brain connectivity via multivariate EMD in mild cognitive impairment. IEEE Trans Cogn Dev Syst. 2021;14(2):552-64.","DOI":"10.1109\/TCDS.2021.3054504"},{"issue":"4","key":"10399_CR26","doi-asserted-by":"crossref","first-page":"e3752","DOI":"10.1002\/nbm.3752","volume":"32","author":"SN Sotiropoulos","year":"2019","unstructured":"Sotiropoulos SN, Zalesky A. Building connectomes using diffusion MRI: why, how and but. NMR Biomed. 2019;32(4): e3752.","journal-title":"NMR Biomed"},{"issue":"9","key":"10399_CR27","doi-asserted-by":"crossref","first-page":"2941","DOI":"10.1002\/hbm.25369","volume":"42","author":"B Ibrahim","year":"2021","unstructured":"Ibrahim B, Suppiah S, Ibrahim N, et al. Diagnostic power of resting-state fMRI for detection of networks connectivity in Alzheimer\u2019s disease and mild cognitive impairment: a systematic review[J]. Hum Brain Mapp. 2021;42(9):2941\u201368.","journal-title":"Hum Brain Mapp"},{"issue":"4","key":"10399_CR28","first-page":"16","volume":"36","author":"J Huang","year":"2021","unstructured":"Huang J, Biao J, Weiping D, et al. Brain network analysis methods and their applications[J]. Data Acquis Process. 2021;36(4):16.","journal-title":"Data Acquis Process."},{"key":"10399_CR29","doi-asserted-by":"crossref","first-page":"5","DOI":"10.3389\/fninf.2021.619557","volume":"15","author":"S Saetia","year":"2021","unstructured":"Saetia S, Yoshimura N, Koike Y. Constructing brain connectivity model using causal networks reconstruction approach. Front Neuroinform. 2021;15:5.","journal-title":"Front Neuroinform"},{"issue":"5","key":"10399_CR30","doi-asserted-by":"crossref","first-page":"e36838","DOI":"10.1371\/journal.pone.0036838","volume":"7","author":"Z Wang","year":"2012","unstructured":"Wang Z, Liang P, Jia X, et al. The baseline and longitudinal changes of PCC connectivity in mild cognitive impairment: a combined structure and resting-state fMRI study. PLoS ONE. 2012;7(5): e36838.","journal-title":"PLoS ONE"},{"issue":"7","key":"10399_CR31","doi-asserted-by":"crossref","first-page":"1997","DOI":"10.1007\/s13042-021-01501-7","volume":"13","author":"H Wu","year":"2022","unstructured":"Wu H, Luo J, Lu X, et al. 3D transfer learning networks for classification of Alzheimer\u2019s disease with MRI. Int J Mach Learn Cybern. 2022;13(7):1997\u20132011.","journal-title":"Int J Mach Learn Cybern"},{"key":"10399_CR32","doi-asserted-by":"crossref","first-page":"1095","DOI":"10.3389\/fpsyg.2015.01095","volume":"6","author":"L Farr\u00e0s-Permanyer","year":"2015","unstructured":"Farr\u00e0s-Permanyer L, Gu\u00e0rdia-Olmos J, Per\u00f3-Cebollero M. Mild cognitive impairment and fMRI studies of brain functional connectivity: the state of the art. Front Psychol. 2015;6:1095.","journal-title":"Front Psychol"},{"issue":"7","key":"10399_CR33","doi-asserted-by":"crossref","first-page":"e22153","DOI":"10.1371\/journal.pone.0022153","volume":"6","author":"P Liang","year":"2011","unstructured":"Liang P, Wang Z, Yang Y, et al. Functional disconnection and compensation in mild cognitive impairment: evidence from DLPFC connectivity using resting-state fMRI. PLoS ONE. 2011;6(7): e22153.","journal-title":"PLoS ONE"},{"key":"10399_CR34","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1109\/TCBB.2017.2776910","volume":"16","author":"R Ju","year":"2017","unstructured":"Ju R, Hu C, Li Q. Early diagnosis of Alzheimer\u2019s disease based on resting-state brain networks and deep learning. IEEE\/ACM Trans Comput Biol Bioinf. 2017;16:244\u201357.","journal-title":"IEEE\/ACM Trans Comput Biol Bioinf"},{"key":"10399_CR35","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1016\/j.neuroimage.2014.11.001","volume":"105","author":"EC Hansen","year":"2015","unstructured":"Hansen EC, Battaglia D, Spiegler A, Deco G, Jirsa VK. Functional connectivity dynamics: modeling the switching behavior of the resting state. NeuroImage. 2015;105:525\u201335.","journal-title":"NeuroImage"},{"issue":"8","key":"10399_CR36","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1016\/j.euroneuro.2010.03.008","volume":"20","author":"MP Van Den Heuvel","year":"2010","unstructured":"Van Den Heuvel MP, Pol HEH. Exploring the brain networks: a review on resting-state fMRI functional connectivity. Eur Neuropsychopharmacol. 2010;20(8):519\u201334.","journal-title":"Eur Neuropsychopharmacol"},{"key":"10399_CR37","doi-asserted-by":"crossref","first-page":"304","DOI":"10.3389\/fnagi.2018.00304","volume":"10","author":"T Yokoi","year":"2018","unstructured":"Yokoi T, Watanabe H, Yamaguchi H, et al. Involvement of the precuneus\/posterior cingulate cortex is significant for the development of Alzheimer\u2019s disease: a PET (THK5351, PiB) and resting fMRI study. Frontiers in Aging Neuroscience. 2018;10: 304.","journal-title":"Frontiers in Aging Neuroscience"},{"issue":"1","key":"10399_CR38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/ncomms11254","volume":"7","author":"N Yahata","year":"2016","unstructured":"Yahata N, Morimoto J, Hashimoto R, et al. A small number of abnormal brain connections predicts adult autism spectrum disorder. Nat Commun. 2016;7(1):1\u201312.","journal-title":"Nat Commun"},{"issue":"10","key":"10399_CR39","first-page":"1","volume":"31","author":"Y Zhang","year":"2010","unstructured":"Zhang Y, Huo Y, Lannan Wu, Dong Z. A review of dimension reduction techniques and methods. J Sichuan Ordnance Eng. 2010;31(10):1\u20137.","journal-title":"J Sichuan Ordnance Eng"},{"issue":"13","key":"10399_CR40","doi-asserted-by":"crossref","first-page":"2208","DOI":"10.1016\/j.ins.2009.02.014","volume":"179","author":"S Maldonado","year":"2009","unstructured":"Maldonado S, Weber R. A wrapper method for feature selection using support vector machines. Inf Sci. 2009;179(13):2208\u201317.","journal-title":"Inf Sci"},{"issue":"5","key":"10399_CR41","first-page":"671","volume":"45","author":"Ge Lei","year":"2009","unstructured":"Lei Ge, Guozheng Li, Mingyu Y. Embedded feature selection based on multi-label learning. J Nanjing Univ: Nat Sci. 2009;45(5):671\u20136.","journal-title":"J Nanjing Univ: Nat Sci"},{"issue":"3","key":"10399_CR42","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1007\/s12021-016-9299-4","volume":"14","author":"CG Yan","year":"2016","unstructured":"Yan CG, Wang XD, Zuo XN, et al. DPABI: data processing & analysis for (resting-state) brain imaging. Neuroinformatics. 2016;14(3):339\u201351.","journal-title":"Neuroinformatics"},{"key":"10399_CR43","doi-asserted-by":"crossref","first-page":"9112","DOI":"10.1523\/JNEUROSCI.1982-05.2005","volume":"25","author":"K Schon","year":"2005","unstructured":"Schon K, Atri A, Hasselmo ME, Tricarico MD, LoPresti ML, Stern CE. Scopolamine reduces persistent activity related to long-term encoding in the parahippocampal gyrus during delayed matching in humans. J Neurosci. 2005;25:9112\u201323.","journal-title":"J Neurosci"},{"issue":"12","key":"10399_CR44","doi-asserted-by":"publisher","first-page":"4396","DOI":"10.1109\/TPAMI.2020.3002843","volume":"43","author":"G Roffo","year":"2021","unstructured":"Roffo G, Melzi S, Castellani U, Vinciarelli A, Cristani M. Infinite feature selection: a graph-based feature filtering approach. IEEE Trans Pattern Anal Mach Intell. 2021;43(12):4396\u2013410. https:\/\/doi.org\/10.1109\/TPAMI.2020.3002843.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10399_CR45","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1016\/j.neuroimage.2015.02.039","volume":"111","author":"KC Fox","year":"2015","unstructured":"Fox KC, Spreng RN, Ellamil M, Andrews-Hanna JR, Christoff K. The wandering brain: meta-analysis of brain imaging and behavior functional neuroimaging studies of mind-wandering and related spontaneous thought processes. NeuroImage. 2015;111:611\u201321.","journal-title":"NeuroImage"},{"issue":"7","key":"10399_CR46","doi-asserted-by":"crossref","first-page":"3517","DOI":"10.1002\/hbm.22418","volume":"35","author":"X Lei","year":"2014","unstructured":"Lei X, Wang Y, Yuan H, Mantini D. Neuronal oscillations and functional interactions between resting state networks. Hum Brain Mapp. 2014;35(7):3517\u201328.","journal-title":"Hum Brain Mapp"},{"issue":"3","key":"10399_CR47","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1162\/jocn_a_00517","volume":"26","author":"XJ Chai","year":"2014","unstructured":"Chai XJ, Ofen N, Gabrieli JD, Whitfield-Gabrieli S. Selective development of anticorrelated networks in the intrinsic functional organization of the human brain. J Cogn Neurosci. 2014;26(3):501\u201313.","journal-title":"J Cogn Neurosci"}],"container-title":["Cognitive Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-024-10399-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12559-024-10399-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-024-10399-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T07:34:18Z","timestamp":1740814458000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12559-024-10399-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,16]]},"references-count":47,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,2]]}},"alternative-id":["10399"],"URL":"https:\/\/doi.org\/10.1007\/s12559-024-10399-6","relation":{},"ISSN":["1866-9956","1866-9964"],"issn-type":[{"value":"1866-9956","type":"print"},{"value":"1866-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,16]]},"assertion":[{"value":"19 October 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 December 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 January 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 competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interest"}}],"article-number":"45"}}