{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T08:37:04Z","timestamp":1792831024912,"version":"4.5.0"},"reference-count":45,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T00:00:00Z","timestamp":1792800000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T00:00:00Z","timestamp":1792800000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01MH119222"],"award-info":[{"award-number":["R01MH119222"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01MH125860"],"award-info":[{"award-number":["R01MH125860"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01MH132610"],"award-info":[{"award-number":["R01MH132610"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000738","name":"U.S. Department of Veterans Affairs","doi-asserted-by":"publisher","award":["36C24E22C0027"],"award-info":[{"award-number":["36C24E22C0027"]}],"id":[{"id":"10.13039\/100000738","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance in Med"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Combining multi\u2010site diffusion MRI (dMRI) data is hindered by inter\u2010scanner variability, which confounds subsequent analysis. Previous harmonization methods require large, matched or traveling human subjects from multiple sites, which are impractical to acquire in many situations. This study aims to develop a deep learning\u2010based dMRI harmonization framework that eliminates the reliance on multi\u2010site in\u2010vivo traveling human data for training.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>HARP employs a voxel\u2010wise 1D neural network trained on an easily transportable diffusion phantom. The model learns relationships between spherical harmonics coefficients of different sites without memorizing spatial structures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>HARP reduced inter\u2010scanner variability levels significantly in various measures. Quantitatively, it decreased inter\u2010scanner variability as measured by standard error in FA (12%), MD (10%), and GFA (30%) with scan\u2010rescan standard error as the baseline, while preserving fiber orientations and tractography after harmonization.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We believe that HARP represents an important first step toward dMRI harmonization using only phantom data, thereby obviating the need for complex, matched in vivo multi\u2010site cohorts. This phantom\u2010only strategy substantially enhances the feasibility and scalability of quantitative dMRI for large\u2010scale clinical studies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mrm.70640","type":"journal-article","created":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T07:52:35Z","timestamp":1792828355000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["HARP: HARmonizing In\u2010Vivo Single\u2010Shell Diffusion MRI Using Phantom\u2010Only Training"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5711-4290","authenticated-orcid":false,"given":"Hwihun","family":"Jeong","sequence":"first","affiliation":[{"name":"Department of Psychiatry Brigham and Women's Hospital, Harvard Medical School  Boston, Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-6818-0115","authenticated-orcid":false,"given":"Qiang","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Psychiatry Brigham and Women's Hospital, Harvard Medical School  Boston, Massachusetts USA"},{"name":"College of Engineering Northeastern University  Boston, Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9070-5255","authenticated-orcid":false,"given":"Kathryn E.","family":"Keenan","sequence":"additional","affiliation":[{"name":"Physical Measurement Laboratory National Institute of Standards and Technology  Boulder, Colorado USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elisabeth A.","family":"Wilde","sequence":"additional","affiliation":[{"name":"Department of Neurology University of Utah School of Medicine  Salt Lake City, Utah USA"},{"name":"George E. Wahlen Veterans Affairs Medical Center  Salt Lake City, Utah USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Walter","family":"Schneider","sequence":"additional","affiliation":[{"name":"University of Pittsburgh  Pittsburgh, Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6669-2263","authenticated-orcid":false,"given":"Sudhir","family":"Pathak","sequence":"additional","affiliation":[{"name":"University of Pittsburgh  Pittsburgh, Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9067-4923","authenticated-orcid":false,"given":"Anthony","family":"Zuccolotto","sequence":"additional","affiliation":[{"name":"Psychology Software Tools  Pittsburgh, Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0197-7801","authenticated-orcid":false,"given":"Lauren J.","family":"O'Donnell","sequence":"additional","affiliation":[{"name":"Department of Radiology Brigham and Women's Hospital, Harvard Medical School  Boston, Massachusetts USA"},{"name":"Harvard\u2010MIT Health Sciences and Technology  Cambridge, Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4992-459X","authenticated-orcid":false,"given":"Lipeng","family":"Ning","sequence":"additional","affiliation":[{"name":"Department of Psychiatry Brigham and Women's Hospital, Harvard Medical School  Boston, Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9946-2314","authenticated-orcid":false,"given":"Yogesh","family":"Rathi","sequence":"additional","affiliation":[{"name":"Department of Psychiatry Brigham and Women's Hospital, Harvard Medical School  Boston, Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,10,24]]},"reference":[{"key":"e_1_2_9_2_1","volume-title":"Diffusion MRI: from quantitative measurement to in vivo neuroanatomy","author":"Johansen\u2010Berg H.","year":"2013"},{"issue":"5","key":"e_1_2_9_3_1","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1016\/j.neuron.2006.08.012","article-title":"Principles of Diffusion Tensor Imaging and Its Applications to Basic Neuroscience Research","volume":"51","author":"Mori S.","year":"2006","journal-title":"Neuron"},{"key":"e_1_2_9_4_1","first-page":"116","volume-title":"International Conference on Medical Image Computing and Computer\u2010Assisted Intervention","author":"Cetin Karayumak S.","year":"2018"},{"issue":"11","key":"e_1_2_9_5_1","doi-asserted-by":"crossref","DOI":"10.1002\/mp.70096","article-title":"Effect of a Consistent Reconstruction Algorithm on Inter\u2010Scanner Reproducibility in Diffusion MRI","volume":"52","author":"Liu Q.","year":"2025","journal-title":"Medical Physics"},{"issue":"1","key":"e_1_2_9_6_1","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1002\/mrm.30062","article-title":"Reduced Cross\u2010Scanner Variability Using Vendor\u2010Agnostic Sequences for Single\u2010Shell Diffusion MRI","volume":"92","author":"Liu Q.","year":"2024","journal-title":"Magnetic Resonance in Medicine"},{"key":"e_1_2_9_7_1","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2020.117128","article-title":"Cross\u2010Scanner and Cross\u2010Protocol Multi\u2010Shell Diffusion MRI Data Harmonization: Algorithms and Results","volume":"221","author":"Ning L.","year":"2020","journal-title":"NeuroImage"},{"key":"e_1_2_9_8_1","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.neuroimage.2019.01.077","article-title":"Cross\u2010Scanner and Cross\u2010Protocol Diffusion MRI Data Harmonisation: A Benchmark Database and Evaluation of Algorithms","volume":"195","author":"Tax C. M. W.","year":"2019","journal-title":"NeuroImage"},{"issue":"1","key":"e_1_2_9_9_1","doi-asserted-by":"crossref","DOI":"10.1038\/s41597-024-03058-w","article-title":"Harmonized Diffusion MRI Data and White Matter Measures From the Adolescent Brain Cognitive Development Study","volume":"11","author":"Cetin\u2010Karayumak S.","year":"2024","journal-title":"Scientific Data"},{"key":"e_1_2_9_10_1","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2021.118451","article-title":"Fiber Tractography Bundle Segmentation Depends on Scanner Effects, Vendor Effects, Acquisition Resolution, Diffusion Sampling Scheme, Diffusion Sensitization, and Bundle Segmentation Workflow","volume":"242","author":"Schilling K. G.","year":"2021","journal-title":"NeuroImage"},{"key":"e_1_2_9_11_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1162\/imag_a_00042","article-title":"A Resource for Development and Comparison of Multimodal Brain 3 T MRI Harmonisation Approaches","volume":"1","author":"Warrington S.","year":"2023","journal-title":"Imaging Neuroscience"},{"key":"e_1_2_9_12_1","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.neuroimage.2017.08.047","article-title":"Harmonization of Multi\u2010Site Diffusion Tensor Imaging Data","volume":"161","author":"Fortin J.\u2010P.","year":"2017","journal-title":"NeuroImage"},{"key":"e_1_2_9_13_1","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/j.neuroimage.2016.04.041","article-title":"Inter\u2010site and inter\u2010scanner diffusion MRI data harmonization","volume":"135","author":"Mirzaalian H.","year":"2016","journal-title":"NeuroImage"},{"key":"e_1_2_9_14_1","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.neuroimage.2018.08.073","article-title":"Retrospective Harmonization of Multi\u2010Site Diffusion MRI Data Acquired With Different Acquisition Parameters","volume":"184","author":"Karayumak S. C.","year":"2019","journal-title":"NeuroImage"},{"key":"e_1_2_9_15_1","first-page":"193","volume-title":"International Conference on Medical Image Computing and Computer\u2010Assisted Intervention","author":"Nath V.","year":"2019"},{"issue":"4","key":"e_1_2_9_16_1","doi-asserted-by":"crossref","first-page":"2174","DOI":"10.1002\/mrm.28243","article-title":"Scanner Invariant Representations for Diffusion MRI Harmonization","volume":"84","author":"Moyer D.","year":"2020","journal-title":"Magnetic Resonance in Medicine"},{"key":"e_1_2_9_17_1","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2019.116450","article-title":"Harmonization of Large MRI Datasets for the Analysis of Brain Imaging Patterns Throughout the Lifespan","volume":"208","author":"Pomponio R.","year":"2020","journal-title":"NeuroImage"},{"key":"e_1_2_9_18_1","doi-asserted-by":"crossref","DOI":"10.1002\/alz.083704","article-title":"Harmonization of Diffusion MRI Measures Is Crucial for White Matter Tract Normative Assessment in ADNI","volume":"20","author":"Descoteaux M.","year":"2024","journal-title":"Alzheimer's & Dementia"},{"issue":"7","key":"e_1_2_9_19_1","doi-asserted-by":"crossref","first-page":"1599","DOI":"10.1109\/TMI.2019.2895020","article-title":"Multi\u2010Site Harmonization of Diffusion MRI Data via Method of Moments","volume":"38","author":"Huynh K. M.","year":"2019","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"e_1_2_9_20_1","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.mri.2019.05.041","article-title":"DeepHarmony: A Deep Learning Approach to Contrast Harmonization Across Scanner Changes","volume":"64","author":"Dewey B. E.","year":"2019","journal-title":"Magnetic Resonance Imaging"},{"issue":"1","key":"e_1_2_9_21_1","doi-asserted-by":"crossref","DOI":"10.1038\/s44172-023-00140-w","article-title":"Learning Multi\u2010Site Harmonization of Magnetic Resonance Images Without Traveling Human Phantoms","volume":"3","author":"Liu S.","year":"2024","journal-title":"Communications Engineering"},{"key":"e_1_2_9_22_1","doi-asserted-by":"crossref","first-page":"1750","DOI":"10.1002\/mrm.30575","article-title":"Cross\u2010Site Harmonization of Diffusion MRI Data Without Matched Training Subjects","volume":"94","author":"De Luca A.","year":"2025","journal-title":"Magnetic Resonance in Medicine"},{"key":"e_1_2_9_23_1","first-page":"21129","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Jeong H.","year":"2023"},{"key":"e_1_2_9_24_1","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2025.103483","article-title":"Harmonizing Flows: Leveraging Normalizing Flows for Unsupervised and Source\u2010Free MRI Harmonization","volume":"101","author":"Beizaee F.","year":"2025","journal-title":"Medical Image Analysis"},{"issue":"1","key":"e_1_2_9_25_1","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1002\/jmri.23950","article-title":"A Phantom for Diffusion\u2010Weighted MRI (DW\u2010MRI)","volume":"38","author":"Lavdas I.","year":"2013","journal-title":"Journal of Magnetic Resonance Imaging"},{"issue":"10","key":"e_1_2_9_26_1","doi-asserted-by":"crossref","first-page":"1265","DOI":"10.1080\/02699052.2018.1494855","article-title":"Assessment of Quantitative Magnetic Resonance Imaging Metrics in the Brain Through the Use of a Novel Phantom","volume":"32","author":"Wilde E. A.","year":"2018","journal-title":"Brain Injury"},{"key":"e_1_2_9_27_1","unstructured":"B.AylwardandJ.McLean \u201cCalibration of ADC Values for Quantitative MRI. PhD Thesis Master's Thesis \u201dUniversity of Glasgow (2022)."},{"key":"e_1_2_9_28_1","first-page":"313","volume-title":"International Conference on Medical Image Computing and Computer\u2010Assisted Intervention","author":"Liu M.","year":"2021"},{"issue":"1","key":"e_1_2_9_29_1","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1002\/mrm.27355","article-title":"Assessment of the Generalization of Learned Image Reconstruction and the Potential for Transfer Learning","volume":"81","author":"Knoll F.","year":"2019","journal-title":"Magnetic Resonance in Medicine"},{"key":"e_1_2_9_30_1","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1016\/j.neuroimage.2019.03.060","article-title":"DeepQSM\u2010Using Deep Learning to Solve the Dipole Inversion for Quantitative Susceptibility Mapping","volume":"195","author":"Bollmann S.","year":"2019","journal-title":"NeuroImage"},{"key":"e_1_2_9_31_1","unstructured":"Psychology Software Tools \u201cUniversal Phantom \u201dhttps:\/\/pstnet.com\/products\/mri\u2010diffusion\u2010calibration\u2010phantom\/."},{"key":"e_1_2_9_32_1","unstructured":"CaliberMRI \u201cDiffusion Phantom \u201dhttps:\/\/qmri.com\/product\/diffusion\u2010phantom\/."},{"key":"e_1_2_9_33_1","doi-asserted-by":"crossref","first-page":"1063","DOI":"10.1016\/j.neuroimage.2015.10.019","article-title":"An Integrated Approach to Correction for Off\u2010Resonance Effects and Subject Movement in Diffusion MR Imaging","volume":"125","author":"Andersson J. L. R.","year":"2016","journal-title":"NeuroImage"},{"issue":"2","key":"e_1_2_9_34_1","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1006\/nimg.2002.1132","article-title":"Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images","volume":"17","author":"Jenkinson M.","year":"2002","journal-title":"NeuroImage"},{"issue":"3","key":"e_1_2_9_35_1","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1002\/hbm.10062","article-title":"Fast Robust Automated Brain Extraction","volume":"17","author":"Smith S. M.","year":"2002","journal-title":"Human Brain Mapping"},{"key":"e_1_2_9_36_1","doi-asserted-by":"crossref","DOI":"10.7717\/peerj.6918","article-title":"We Need to Talk About Reliability: Making Better Use of Test\u2010Retest Studies for Study Design and Interpretation","volume":"7","author":"Matheson G. J.","year":"2019","journal-title":"PeerJ"},{"issue":"2","key":"e_1_2_9_37_1","doi-asserted-by":"crossref","first-page":"554","DOI":"10.1002\/mrm.22365","article-title":"Reconstruction of the Orientation Distribution Function in Single\u2010and Multiple\u2010Shell q\u2010Ball Imaging Within Constant Solid Angle","volume":"64","author":"Aganj I.","year":"2010","journal-title":"Magnetic Resonance in Medicine"},{"key":"e_1_2_9_38_1","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.neuroimage.2018.01.046","article-title":"Evaluation of Standardized and Study\u2010Specific Diffusion Tensor Imaging Templates of the Adult Human Brain: Template Characteristics, Spatial Normalization Accuracy, and Detection of Small Inter\u2010Group FA Differences","volume":"172","author":"Zhang S.","year":"2018","journal-title":"NeuroImage"},{"issue":"2","key":"e_1_2_9_39_1","first-page":"65","article-title":"A Simple Sequentially Rejective Multiple Test Procedure","volume":"6","author":"Holm S.","year":"1979","journal-title":"Scandinavian Journal of Statistics"},{"issue":"4","key":"e_1_2_9_40_1","doi-asserted-by":"crossref","first-page":"1459","DOI":"10.1016\/j.neuroimage.2007.02.016","article-title":"Robust Determination of the Fibre Orientation Distribution in Diffusion MRI: Non\u2010Negativity Constrained Super\u2010Resolved Spherical Deconvolution","volume":"35","author":"Tournier J.\u2010D.","year":"2007","journal-title":"NeuroImage"},{"key":"e_1_2_9_41_1","first-page":"894","volume-title":"International Conference on Medical Image Computing and Computer\u2010Assisted Intervention","author":"Malcolm J. G.","year":"2009"},{"issue":"11","key":"e_1_2_9_42_1","doi-asserted-by":"crossref","first-page":"1562","DOI":"10.1109\/TMI.2007.906785","article-title":"Automatic Tractography Segmentation Using a High\u2010Dimensional White Matter Atlas","volume":"26","author":"O'Donnell L. J.","year":"2007","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"e_1_2_9_43_1","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.neuroimage.2016.01.022","article-title":"Comparison of 3D Orientation Distribution Functions Measured With Confocal Microscopy and Diffusion MRI","volume":"129","author":"Schilling K.","year":"2016","journal-title":"NeuroImage"},{"issue":"10","key":"e_1_2_9_44_1","doi-asserted-by":"crossref","first-page":"3041","DOI":"10.1002\/hbm.24579","article-title":"Test\u2013Retest Reproducibility of White Matter Parcellation Using Diffusion MRI Tractography Fiber Clustering","volume":"40","author":"Zhang F.","year":"2019","journal-title":"Human Brain Mapping"},{"key":"e_1_2_9_45_1","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2020.116619","article-title":"Exploring Linearity of Deep Neural Network Trained QSM: QSMnet+","volume":"211","author":"Jung W.","year":"2020","journal-title":"NeuroImage"},{"key":"e_1_2_9_46_1","doi-asserted-by":"crossref","first-page":"177559","DOI":"10.1109\/ACCESS.2025.3620427","article-title":"A Fair Comparison in Deep Learning\u2010Based QSM Reconstruction","volume":"13","author":"Oh C.","year":"2025","journal-title":"IEEE Access"}],"container-title":["Magnetic Resonance in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mrm.70640","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/mrm.70640","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mrm.70640","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T07:52:42Z","timestamp":1792828362000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/mrm.70640"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,24]]},"references-count":45,"alternative-id":["10.1002\/mrm.70640"],"URL":"https:\/\/doi.org\/10.1002\/mrm.70640","archive":["Portico"],"relation":{},"ISSN":["0740-3194","1522-2594"],"issn-type":[{"value":"0740-3194","type":"print"},{"value":"1522-2594","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,24]]},"assertion":[{"value":"2026-02-03","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-10-11","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-10-24","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"mrm.70640"}}