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Xinyu Zhang
Researcher at University of California, San Diego
Publications - 169
Citations - 6006
Xinyu Zhang is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Wireless network & Wireless. The author has an hindex of 38, co-authored 140 publications receiving 4681 citations. Previous affiliations of Xinyu Zhang include Wisconsin Alumni Research Foundation & University of Toronto.
Papers
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Journal ArticleDOI
The infertile individual analysis based on whole-exome sequencing in chinese multi-ethnic groups
Qiongzhen Zhao,Yanqi Li,Qi Liang,Jie Zhao,Kai Kang,Meiling Hou,Xinyu Zhang,Renqian Du,Lingyin Kong,Bo Liang,Weidong Huang +10 more
TL;DR: This study establishes the genetics analysis of Northwest China and finds a candidate gene locus KNTC1 (rs7968222: G > T), which is one of the genetic susceptibility factors for male azoospermia.
Journal ArticleDOI
Direct insertion into the C–C bond of unactivated ketones with NaH-mediated aryne chemistry
Fa Luo,Chen-Long Li,Peng Ji,Yuxin Zhou,Jingjing Gui,Yuejia Yin,Xinyu Zhang,Yanwei Hu,Xiaobei Chen,Xue-Li Liu,Xiaodong Chen,Zhi-wei Yu,Wei Wang,Shilei Zhang +13 more
TL;DR: In this article , the authors proposed a NaH-mediated activation strategy for the generation of highly reactive aryne species in a controlled manner, which can efficiently participate in a C-C σ-bond insertion reaction with unactivated ketones, which is difficult to achieve by existing methods.
Proceedings ArticleDOI
Demo: A paper keyboard for mobile devices
TL;DR: UbiK, an alternative portable text-entry method that allows user to type on a piece of paper, placed on solid surfaces like wood desktop, leverages the microphones on a mobile device to accurately localize the keystrokes through fine-grained acoustic fingerprinting.
Patent
Hybrid learning method and device for improving interactive video transmission quality and equipment
TL;DR: In this paper, a hybrid learning method and device for improving interactive video transmission quality and electronic equipment is presented, which comprises the steps: obtaining a transmission parameter of a previous transmission time slot and an inter-packet delay sequence for a current transmission time slots; inputting the transmission parameter into a code rate prediction deep reinforcement learning model, and determining a first alternative transmission code rate; determining a network state identification value based on an interpackets delay trend represented by the interpacket delays sequence; determining the network state threshold of the current transmission timeslots; if the network