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Yinhui Yu on Muck Rack

Yinhui Yu

As seen in: Nature, Wiley Online Library, Frontiers, Taylor & Francis Online
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Articles

Physics-informed deep learning framework for vibration-based cylinder pressure reconstruction and heat release rate prediction in diesel engines

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By Jie Zhang, Yinhui Yu, Sumin Wu
| Frontiers
Abstract To address the cost and reliability issues of cylinder pressure sensors in engine digital twins, this study introduces a vibration-based, physics-informed deep learning method for reconstructing and predicting cylinder pressure and heat release rate (HRR). Coherence analysis confirmed a strong correlation (>0.8) within the 3,000–8,000 Hz band.
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Cortical Morphometric Similarity Network Gradient in Parkinson's Disease and its Association with Gene Expression Profiles

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By Tianqi Xu, Yinhui Yu, Zhihuai Deng
| Wiley Online Library Verified
Data availability statement All data supporting the findings of this study are available within the article and its Supplementary Information files. Supporting Information Filename Description mds70233-sup-0001-FigureS1.tifTIFF image, 28.7 MB Figure S1. Validation analysis of the morphometric similarity network (MSN) gradient. The brain maps of the MSN gradient based on (A) the Desikan–Killiany (DK)-1533 atlas and (B) the DK-308 atlas show similar spatial patterns.
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Development of a pre-discharge model for 1-year post-discharge all-cause mortality after endovascular treatment for aneurysmal subarachnoid haemorrhage using LASSO-Boruta feature selection: Neurological Research: Vol 0, No 0 - Get Access

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By Longxiang Ma, Bin Zhang, Xiangxin Li, Yinhui Yu
| Taylor & Francis Online
ABSTRACT Objective To develop a predischarge model for predicting 1-year post-discharge all-cause mortality in patients with aneurysmal subarachnoid haemorrhage (aSAH) following endovascular treatment (EVT). Methods We retrospectively analysed 947 patients with aSAH who were discharged alive between April 2021 and April 2023 from four neurointerventional centres in China as the training cohort.
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