Haiyan Zhou [3]Haiyang Zhou [1]
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  1.  39
    Self-Reference Emerges Earlier Than Emotion During an Implicit Self-Referential Emotion Processing Task: Event-Related Potential Evidence.Haiyan Zhou, Jialiang Guo, Xiaomeng Ma, Minghui Zhang, Liqing Liu, Lei Feng, Jie Yang, Zhijiang Wang, Gang Wang & Ning Zhong - 2017 - Frontiers in Human Neuroscience 11.
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    Revisiting the L-Dopa Response as a Predictor of Motor Outcomes After Deep Brain Stimulation in Parkinson’s Disease.Zhengyu Lin, Xiaoxiao Zhang, Linbin Wang, Yingying Zhang, Haiyan Zhou, Qingfang Sun, Bomin Sun, Peng Huang & Dianyou Li - 2021 - Frontiers in Human Neuroscience 15.
    Objective: To investigate the correlation between preoperative response to the L-dopa challenge test and efficacy of deep brain stimulation on motor function in Parkinson’s disease.Methods: We retrospectively reviewed the data of 38 patients with idiopathic PD who underwent DBS surgery with a median follow-up duration of 7 months. Twenty underwent bilateral globus pallidus interna DBS, and 18 underwent bilateral subthalamic nucleus DBS. The Movement Disorder Society Unified Parkinson Disease Rating Scale-Motor Part was assessed before surgery and at the last follow-up (...)
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    Hydrostatic Pressure Driven Spin, Volume and Band Gap Collapses in SmFeO3: A GGA + U Study.Yujiao Sun, Wei Ren, Shixun Cao, Haiyang Zhou, Hong Jian Zhao, Hailong Xu & Hongwei Zhao - 2016 - Philosophical Magazine 96 (15):1613-1622.
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    Predicting Risk Propensity Through Player Behavior in DOTA 2: A Cross-Sectional Study.Sihua Lyu, Nan Zhao, Yichuan Zhang, Wenwen Chen, Haiyan Zhou & Tingshao Zhu - 2022 - Frontiers in Psychology 13.
    As traditional methods such as questionnaires for measuring risk propensity are not applicable in some scenarios, a nonintrusive method that could automatically identify individuals' risk propensity could be valuable. This study utilized Defense of the Ancients 2 single match data and historical statistics to train predictive models to identify risk propensity by machine learning methods. Self-reported risk propensity scores from 218 DOTA 2 players were paired with their behavioral metrics. The best-performing model occurred with Gaussian process regression. The root mean (...)
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