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13,899 results on '"Yao Yu"'

410. Metabolic profiling reveals distinct variations linked to nicotine consumption in humans--first results from the KORA study.

Author

Rui Wang-Sattler, Yao Yu, Kirstin Mittelstrass, Eva Lattka, Elisabeth Altmaier, Christian Gieger, Karl H Ladwig, Norbert Dahmen, Klaus M Weinberger, Pei Hao, Lei Liu, Yixue Li, H-Erich Wichmann, Jerzy Adamski, Karsten Suhre, and Thomas Illig

Subjects
Medicine, Science
Abstract

Exposure to nicotine during smoking causes a multitude of metabolic changes that are poorly understood. We quantified and analyzed 198 metabolites in 283 serum samples from the human cohort KORA (Cooperative Health Research in the Region of Augsburg). Multivariate analysis of metabolic profiles revealed that the group of smokers could be clearly differentiated from the groups of former smokers and non-smokers. Moreover, 23 lipid metabolites were identified as nicotine-dependent biomarkers. The levels of these biomarkers are all up-regulated in smokers compared to those in former and non-smokers, except for three acyl-alkyl-phosphatidylcholines (e.g. plasmalogens). Consistently significant results were further found for the ratios of plasmalogens to diacyl-phosphatidylcolines, which are reduced in smokers and regulated by the enzyme alkylglycerone phosphate synthase (alkyl-DHAP) in both ether lipid and glycerophospholipid pathways. Notably, our metabolite profiles are consistent with the strong down-regulation of the gene for alkyl-DHAP (AGPS) in smokers that has been found in a study analyzing gene expression in human lung tissues. Our data suggest that smoking is associated with plasmalogen-deficiency disorders, caused by reduced or lack of activity of the peroxisomal enzyme alkyl-DHAP. Our findings provide new insight into the pathophysiology of smoking addiction. Activation of the enzyme alkyl-DHAP by small molecules may provide novel routes for therapy.

Published
2008
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417. Efficacy, safety and pharmacokinetics of Unecritinib (TQ-B3101) for patients with ROS1 positive advanced non-small cell lung cancer: a Phase I/II Trial

Author

Lu, Shun, Pan, Hongming, Wu, Lin, Yao, Yu, He, Jianxing, Wang, Yan, Wang, Xiuwen, Fang, Yong, Zhou, Zhen, Wang, Xicheng, Cai, Xiuyu, Yu, Yan, Ma, Zhiyong, Min, Xuhong, Yang, Zhixiong, Cao, Lejie, Yang, Huaping, Shu, Yongqian, Zhuang, Wu, Cang, Shundong, Fang, Jian, Li, Kai, Yu, Zhuang, Cui, Jiuwei, Zhang, Yang, Li, Man, Wen, Xinxuan, Zhang, Jie, Li, Weidong, Shi, Jianhua, Xu, Xingxiang, Zhong, Diansheng, Wang, Tao, and Zhu, Jiajia

Published
2023
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426. Inferring Black Hole Properties from Astronomical Multivariate Time Series with Bayesian Attentive Neural Processes

Author

Park, Ji Won, Villar, Ashley, Li, Yin, Jiang, Yan-Fei, Ho, Shirley, Lin, Joshua Yao-Yu, Marshall, Philip J., and Roodman, Aaron

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena, Computer Science - Machine Learning
Abstract

Among the most extreme objects in the Universe, active galactic nuclei (AGN) are luminous centers of galaxies where a black hole feeds on surrounding matter. The variability patterns of the light emitted by an AGN contain information about the physical properties of the underlying black hole. Upcoming telescopes will observe over 100 million AGN in multiple broadband wavelengths, yielding a large sample of multivariate time series with long gaps and irregular sampling. We present a method that reconstructs the AGN time series and simultaneously infers the posterior probability density distribution (PDF) over the physical quantities of the black hole, including its mass and luminosity. We apply this method to a simulated dataset of 11,000 AGN and report precision and accuracy of 0.4 dex and 0.3 dex in the inferred black hole mass. This work is the first to address probabilistic time series reconstruction and parameter inference for AGN in an end-to-end fashion., Comment: 6 pages, 4 figures, 1 table, written for non-astronomers, submitted to the ICML 2021 Time Series and Uncertainty and Robustness in Deep Learning Workshops. Comments welcome! Added affiliations and references for Fig 1

Published
2021

427. Coupling Intent and Action for Pedestrian Crossing Behavior Prediction

Author

Yao, Yu, Atkins, Ella, Roberson, Matthew Johnson, Vasudevan, Ram, and Du, Xiaoxiao

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Accurate prediction of pedestrian crossing behaviors by autonomous vehicles can significantly improve traffic safety. Existing approaches often model pedestrian behaviors using trajectories or poses but do not offer a deeper semantic interpretation of a person's actions or how actions influence a pedestrian's intention to cross in the future. In this work, we follow the neuroscience and psychological literature to define pedestrian crossing behavior as a combination of an unobserved inner will (a probabilistic representation of binary intent of crossing vs. not crossing) and a set of multi-class actions (e.g., walking, standing, etc.). Intent generates actions, and the future actions in turn reflect the intent. We present a novel multi-task network that predicts future pedestrian actions and uses predicted future action as a prior to detect the present intent and action of the pedestrian. We also designed an attention relation network to incorporate external environmental contexts thus further improve intent and action detection performance. We evaluated our approach on two naturalistic driving datasets, PIE and JAAD, and extensive experiments show significantly improved and more explainable results for both intent detection and action prediction over state-of-the-art approaches. Our code is available at: https://github.com/umautobots/pedestrian_intent_action_detection., Comment: 7pages, 4 figures, 3 tables. Accepted to IJCAI2021

Published
2021

428. Deterministic Assembly of Single Emitters in Sub-5 Nanometer Optical Cavity Formed by Gold Nanorod Dimers on Three-Dimensional DNA Origami

Author

Zhao, Zhi, Chen, Xiahui, Zuo, Jiawei, Basiri, Ali, Choi, Shinhyuk, Yao, Yu, Liu, Yan, and Wang, Chao

Subjects
Physics - Optics, Physics - Applied Physics
Abstract

Controllable strong interactions between a nanocavity and a single emitter is important to manipulating optical emission in a nanophotonic systems but challenging to achieve. Here a three-dimensional DNA origami, named as DNA rack (DR) is proposed and demonstrated to deterministically and precisely assemble single emitters within ultra-small plasmonic nanocavities formed by closely coupled gold nanorods (AuNRs). The DR uniquely possesses a saddle shape with two tubular grooves that geometrically allows a snug fit and linearly align two AuNRs with a bending angle <10{\deg}. It also includes a spacer at the saddle point to maintain the gap between AuNRs as small as 2-3 nm, forming a nanocavity estimated to be 20 nm3 and an experimentally measured Q factor of 7.3. A DNA docking strand is designed at the spacer to position a single fluorescent emitter at nanometer accuracy within the cavity. Using Cy5 as a model emitter, a ~30-fold fluorescence enhancement and a significantly reduced emission lifetime (from 1.6 ns to 670 ps) were experimentally verified, confirming significant emitter-cavity interactions. This DR-templated assembly method is capable of fitting AuNRs of variable length-to-width aspect ratios to form anisotropic nanocavities and deterministically incorporating different single emitters, thus enabling flexible design of both cavity resonance and emission wavelengths to tailor light-matter interactions at nanometer scale.

Published
2021
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437. Intelligent Perception Solution for Construction Machinery Based on Binocular Stereo Vision

Author

Lin, Fangfang, Lin, Tianliang, Li, Zhongshen, Chen, Qihuai, Wu, Jiangdong, Yao, Yu, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yang, Huayong, editor, Liu, Honghai, editor, Zou, Jun, editor, Yin, Zhouping, editor, Liu, Lianqing, editor, Yang, Geng, editor, Ouyang, Xiaoping, editor, and Wang, Zhiyong, editor

Published
2023
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438. Trajectory Inference Optimization Based on Improved DR Algorithm

Author

Yao-yu, Li, Fei, Hou, Wei, Ren, Man-hao, Ma, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Xu, Jinyang, Editorial Board Member, and Mo, John P.T., editor

Published
2023
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439. Flexible Resources Allocation in High-Penetration Renewable Energy System Based on Stochastic Programming

Author

Yao, Yu, Liu, Zhaoyu, Wang, Lei, Dai, Pan, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Zeng, Pingliang, editor, Zhang, Xiao-Ping, editor, Terzija, Vladimir, editor, Ding, Yi, editor, and Luo, Yunxia, editor

Published
2023
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440. Strong Gravitational Lensing Parameter Estimation with Vision Transformer

Author

Huang, Kuan-Wei, Chen, Geoff Chih-Fan, Chang, Po-Wen, Lin, Sheng-Chieh, Hsu, ChiaJung, Thengane, Vishal, Lin, Joshua Yao-Yu, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Karlinsky, Leonid, editor, Michaeli, Tomer, editor, and Nishino, Ko, editor

Published
2023
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450. Sunvozertinib for patients in China with platinum-pretreated locally advanced or metastatic non-small-cell lung cancer and EGFR exon 20 insertion mutation (WU-KONG6): single-arm, open-label, multicentre, phase 2 trial

Author

Wang, Mengzhao, Fan, Yun, Sun, Meili, Wang, Yongsheng, Zhao, Yanqiu, Jin, Bo, Hu, Ying, Han, Zhigang, Song, Xia, Liu, Anwen, Tang, Kejing, Ding, Cuimin, Liang, Li, Wu, Lin, Gao, Junzhen, Wang, Jianghong, Cheng, Ying, Zhou, Jianying, He, Yong, Dong, Xiaorong, Yao, Yu, Yu, Yan, Wang, Huijie, Sun, Si, Huang, Jianan, Fang, Jian, Li, Wen, Wang, Lin, Ren, Xiubao, Zhou, Chengzhi, Hu, Yanping, Zhao, Dahai, Yang, Runxiang, Xu, Fei, Huang, Yijiang, Pan, Yueyin, Cui, Jiuwei, Xu, Yan, Yang, Zhenfan, and Shi, Yuankai

Published
2024
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