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2,594 results on '"Li, Donghui"'

1. Harvesting Efficient On-Demand Order Pooling from Skilled Couriers: Enhancing Graph Representation Learning for Refining Real-time Many-to-One Assignments

Author

Liang, Yile, Zhao, Jiuxia, Li, Donghui, Feng, Jie, Zhang, Chen, Ding, Xuetao, Hao, Jinghua, and He, Renqing

Subjects
Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

The recent past has witnessed a notable surge in on-demand food delivery (OFD) services, offering delivery fulfillment within dozens of minutes after an order is placed. In OFD, pooling multiple orders for simultaneous delivery in real-time order assignment is a pivotal efficiency source, which may in turn extend delivery time. Constructing high-quality order pooling to harmonize platform efficiency with the experiences of consumers and couriers, is crucial to OFD platforms. However, the complexity and real-time nature of order assignment, making extensive calculations impractical, significantly limit the potential for order consolidation. Moreover, offline environment is frequently riddled with unknown factors, posing challenges for the platform's perceptibility and pooling decisions. Nevertheless, delivery behaviors of skilled couriers (SCs) who know the environment well, can improve system awareness and effectively inform decisions. Hence a SC delivery network (SCDN) is constructed, based on an enhanced attributed heterogeneous network embedding approach tailored for OFD. It aims to extract features from rich temporal and spatial information, and uncover the latent potential for order combinations embedded within SC trajectories. Accordingly, the vast search space of order assignment can be effectively pruned through scalable similarity calculations of low-dimensional vectors, making comprehensive and high-quality pooling outcomes more easily identified in real time. SCDN has now been deployed in Meituan dispatch system. Online tests reveal that with SCDN, the pooling quality and extent have been greatly improved. And our system can boost couriers'efficiency by 45-55% during noon peak hours, while upholding the timely delivery commitment., Comment: Accepted in KDD 2024 ADS Track

Published
2024

2. Genome-wide association study identifies high-impact susceptibility loci for HCC in North America.

Author

Hassan, Manal, Li, Donghui, Han, Younghun, Byun, Jinyoung, Hatia, Rikita, Long, Erping, Choi, Jiyeon, Kelley, Robin, Cleary, Sean, Lok, Anna, Bracci, Paige, Permuth, Jennifer, Bucur, Roxana, Yuan, Jian-Min, Singal, Amit, Jalal, Prasun, Ghobrial, R, Santella, Regina, Kono, Yuko, Shah, Dimpy, Nguyen, Mindie, Liu, Geoffrey, Parikh, Neehar, Kim, Richard, Wu, Hui-Chen, El-Serag, Hashem, Chang, Ping, Li, Yanan, Chun, Yun, Lee, Sunyoung, Gu, Jian, Hawk, Ernest, Sun, Ryan, Huff, Chad, Rashid, Asif, Amin, Hesham, Beretta, Laura, Wolff, Robert, Antwi, Samuel, Patt, Yehuda, Hwang, Lu-Yu, Klein, Alison, Zhang, Karen, Schmidt, Mikayla, White, Donna, Goss, John, Khaderi, Saira, Marrero, Jorge, Cigarroa, Francisco, Shah, Pankil, Kaseb, Ahmed, Roberts, Lewis, and Amos, Christopher

Subjects
Humans, Genome-Wide Association Study, Liver Neoplasms, Genetic Predisposition to Disease, Carcinoma, Hepatocellular, Male, Female, Middle Aged, North America, Case-Control Studies, Polymorphism, Single Nucleotide, Aged, Genetic Loci, White People
Abstract

BACKGROUND AND AIMS: Despite the substantial impact of environmental factors, individuals with a family history of liver cancer have an increased risk for HCC. However, genetic factors have not been studied systematically by genome-wide approaches in large numbers of individuals from European descent populations (EDP). APPROACH AND RESULTS: We conducted a 2-stage genome-wide association study (GWAS) on HCC not affected by HBV infections. A total of 1872 HCC cases and 2907 controls were included in the discovery stage, and 1200 HCC cases and 1832 controls in the validation. We analyzed the discovery and validation samples separately and then conducted a meta-analysis. All analyses were conducted in the presence and absence of HCV. The liability-scale heritability was 24.4% for overall HCC. Five regions with significant ORs (95% CI) were identified for nonviral HCC: 3p22.1, MOBP , rs9842969, (0.51, [0.40-0.65]); 5p15.33, TERT , rs2242652, (0.70, (0.62-0.79]); 19q13.11, TM6SF2 , rs58542926, (1.49, [1.29-1.72]); 19p13.11 MAU2 , rs58489806, (1.53, (1.33-1.75]); and 22q13.31, PNPLA3 , rs738409, (1.66, [1.51-1.83]). One region was identified for HCV-induced HCC: 6p21.31, human leukocyte antigen DQ beta 1, rs9275224, (0.79, [0.74-0.84]). A combination of homozygous variants of PNPLA3 and TERT showing a 6.5-fold higher risk for nonviral-related HCC compared to individuals lacking these genotypes. This observation suggests that gene-gene interactions may identify individuals at elevated risk for developing HCC. CONCLUSIONS: Our GWAS highlights novel genetic susceptibility of nonviral HCC among European descent populations from North America with substantial heritability. Selected genetic influences were observed for HCV-positive HCC. Our findings indicate the importance of genetic susceptibility to HCC development.

Published
2024

6. Genetic Susceptibility to Nonalcoholic Fatty Liver Disease and Risk for Pancreatic Cancer: Mendelian Randomization.

Author

Canzian, Federico, Du, Mengmeng, Gallinger, Steven, Giles, Graham, Goodman, Phyllis, Haiman, Christopher, Kogevinas, Manolis, Kooperberg, Charles, LeMarchand, Loic, Neale, Rachel, Visvanathan, Kala, White, Emily, Albanes, Demetrius, Andreotti, Gabriella, Babic, Ana, Berndt, Sonja, Brais, Lauren, Brennan, Paul, Buring, Julie, Rabe, Kari, Bamlet, William, Chanock, Stephen, Fuchs, Charles, Gaziano, J, Giovannucci, Edward, Hackert, Thilo, Hassan, Manal, Katzke, Verena, Kurtz, Robert, Lee, I-Min, Malats, Núria, Murphy, Neil, Oberg, Ann, Orlow, Irene, Porta, Miquel, Real, Francisco, Rothman, Nathaniel, Sesso, Howard, Silverman, Debra, Thompson, Ian, Wactawski-Wende, Jean, Wang, Xiaoliang, Wentzensen, Nicolas, Yu, Herbert, Zeleniuch-Jacquotte, Anne, Yu, Kai, Wolpin, Brian, Duell, Eric, Li, Donghui, Hung, Rayjean, Perdomo, Sandra, McCullough, Marjorie, Freedman, Neal, Patel, Alpa, Peters, Ulrike, Riboli, Elio, Sund, Malin, Tjønneland, Anne, Zhong, Jun, Van Den Eeden, Stephen, Kraft, Peter, Risch, Harvey, Amundadottir, Laufey, Klein, Alison, Stolzenberg-Solomon, Rachael, Antwi, Samuel, King, Sontoria, Veliginti, Swathi, Brouwers, Martijn, Ren, Zhewen, Zheng, Wei, Setiawan, Veronica, Wilkens, Lynne, Shu, Xiao-Ou, Arslan, Alan, Beane Freeman, Laura, and Bracci, Paige

Subjects
Humans, Non-alcoholic Fatty Liver Disease, Genetic Predisposition to Disease, Genome-Wide Association Study, Mendelian Randomization Analysis, Pancreatic Neoplasms, Obesity, Polymorphism, Single Nucleotide
Abstract

BACKGROUND: There are conflicting data on whether nonalcoholic fatty liver disease (NAFLD) is associated with susceptibility to pancreatic cancer. Using Mendelian randomization (MR), we investigated the relationship between genetic predisposition to NAFLD and risk for pancreatic cancer. METHODS: Data from genome-wide association studies (GWAS) within the Pancreatic Cancer Cohort Consortium (PanScan; cases n = 5,090, controls n = 8,733) and the Pancreatic Cancer Case Control Consortium (PanC4; cases n = 4,163, controls n = 3,792) were analyzed. We used data on 68 genetic variants with four different MR methods [inverse variance weighting (IVW), MR-Egger, simple median, and penalized weighted median] separately to predict genetic heritability of NAFLD. We then assessed the relationship between each of the four MR methods and pancreatic cancer risk, using logistic regression to calculate ORs and 95% confidence intervals (CI), adjusting for PC risk factors, including obesity and diabetes. RESULTS: No association was found between genetically predicted NAFLD and pancreatic cancer risk in the PanScan or PanC4 samples [e.g., PanScan, IVW OR, 1.04; 95% confidence interval (CI), 0.88-1.22; MR-Egger OR, 0.89; 95% CI, 0.65-1.21; PanC4, IVW OR, 1.07; 95% CI, 0.90-1.27; MR-Egger OR, 0.93; 95% CI, 0.67-1.28]. None of the four MR methods indicated an association between genetically predicted NAFLD and pancreatic cancer risk in either sample. CONCLUSIONS: Genetic predisposition to NAFLD is not associated with pancreatic cancer risk. IMPACT: Given the close relationship between NAFLD and metabolic conditions, it is plausible that any association between NAFLD and pancreatic cancer might reflect host metabolic perturbations (e.g., obesity, diabetes, or metabolic syndrome) and does not necessarily reflect a causal relationship between NAFLD and pancreatic cancer.

Published
2023

8. Scientific Software Citation Intent Classification Using Large Language Models

Author

Istrate, Ana-Maria, Fisher, Joshua, Yang, Xinyu, Moraw, Kara, Li, Kai, Li, Donghui, Klein, Martin, Goos, Gerhard, Series 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, Rehm, Georg, editor, Dietze, Stefan, editor, Schimmler, Sonja, editor, and Krüger, Frank, editor

Published
2024
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9. Research on the Dynamic Characteristics of Hot Die Forging Press Controlled by Combined Wet Clutch-Brake

Author

Zhang, Lingqing, Cui, Hongwei, Mei, Bizhou, Li, Donghui, Cui, Long, Li, Qi, Ceccarelli, Marco, Series Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, Agrawal, Sunil K., Advisory Editor, Tan, Jianrong, editor, Liu, Yu, editor, Huang, Hong-Zhong, editor, Yu, Jingjun, editor, and Wang, Zequn, editor

Published
2024
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14. A large dataset of software mentions in the biomedical literature

Author

Istrate, Ana-Maria, Li, Donghui, Taraborelli, Dario, Torkar, Michaela, Veytsman, Boris, and Williams, Ivana

Subjects
Computer Science - Digital Libraries, Quantitative Biology - Other Quantitative Biology
Abstract

We describe the CZ Software Mentions dataset, a new dataset of software mentions in biomedical papers. Plain-text software mentions are extracted with a trained SciBERT model from several sources: the NIH PubMed Central collection and from papers provided by various publishers to the Chan Zuckerberg Initiative. The dataset provides sources, context and metadata, and, for a number of mentions, the disambiguated software entities and links. We extract 1.12 million unique string software mentions from 2.4 million papers in the NIH PMC-OA Commercial subset, 481k unique mentions from the NIH PMC-OA Non-Commercial subset (both gathered in October 2021) and 934k unique mentions from 3 million papers in the Publishers' collection. There is variation in how software is mentioned in papers and extracted by the NER algorithm. We propose a clustering-based disambiguation algorithm to map plain-text software mentions into distinct software entities and apply it on the NIH PubMed Central Commercial collection. Through this methodology, we disambiguate 1.12 million unique strings extracted by the NER model into 97600 unique software entities, covering 78% of all software-paper links. We link 185000 of the mentions to a repository, covering about 55% of all software-paper links. We describe in detail the process of building the datasets, disambiguating and linking the software mentions, as well as opportunities and challenges that come with a dataset of this size. We make all data and code publicly available as a new resource to help assess the impact of software (in particular scientific open source projects) on science.

Published
2022

15. A Dual-fusion Semantic Segmentation Framework With GAN For SAR Images

Author

Li, Donghui, Liu, Jia, Liu, Fang, Zhang, Wenhua, Zhang, Andi, Gao, Wenfei, and Shi, Jiao

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Deep learning based semantic segmentation is one of the popular methods in remote sensing image segmentation. In this paper, a network based on the widely used encoderdecoder architecture is proposed to accomplish the synthetic aperture radar (SAR) images segmentation. With the better representation capability of optical images, we propose to enrich SAR images with generated optical images via the generative adversative network (GAN) trained by numerous SAR and optical images. These optical images can be used as expansions of original SAR images, thus ensuring robust result of segmentation. Then the optical images generated by the GAN are stitched together with the corresponding real images. An attention module following the stitched data is used to strengthen the representation of the objects. Experiments indicate that our method is efficient compared to other commonly used methods, Comment: 4 pages,4 figures, 2022 IEEE International Geoscience and Remote Sensing Symposium

Published
2022

19. Research on Nonlinear Bearing Characteristics of Conical Deformation Friction Pairs in the Hydro-viscous Cluth Considering the Influence of Structural Parameters

Author

Sun Hao, Cui Hongwei, Mei Bizhou, Li Donghui, Suo Yiran, and Zhang Lingqing

Subjects
Hydro-viscous clutch, Conical deformation, Structural parameter, Bearing characteristics, Mechanical engineering and machinery, TJ1-1570
Abstract

In purpose of getting the influence of different structural parameters on the bearing characteristics of the conical deformation friction pair, the equivalent contact model of the conical deformation friction pair under different structural parameters is established. The buckling deformation simulation is carried out by Ansys Workbench, and combined with the analysis of the Matlab numerical model, the variation law of the oil film thickness of the friction pair under different structural parameters is obtained. Based on the oil film pressure and micro-convex peak rough contact model, the variation law of the maximum total contact pressure during 10 s soft start is found, and the method of selecting the optimal structural parameters of the friction pair under the actual operating conditions is summarized. The results show that the axial deformation and the increase of the thickness of the steel sheet can make the deformation of the middle diameter of the steel sheet more difficult, and lead to the increase of the maximum total contact pressure of the friction pair. At the same time, it leads to non-uniform contact and non-uniform distribution of contact pressure, and different ratios of inner diameter to outer diameter can only affect the distribution location of the maximum total contact pressure of the friction pair, without having any great influence on its variation law and value. The research results provide a basis for the study of torque characteristics of conical deformation friction pairs under different structural parameters.

Published
2024
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25. Association of social determinants, lifestyle, and metabolic factors with mortality in Chinese adults: A nationwide 10-year prospective cohort study

Author

Lu, Jieli, Li, Mian, He, Jiang, Xu, Yu, Zheng, Ruizhi, Zheng, Jie, Qin, Guijun, Qin, Yingfen, Chen, Yuhong, Tang, Xulei, Ye, Zhen, Xu, Min, Wang, Tiange, Shi, Lixin, Su, Qing, Yu, Xuefeng, Yan, Li, Zhao, Zhiyun, Wan, Qin, Chen, Gang, Gao, Zhengnan, Wang, Guixia, Shen, Feixia, Gu, Xuejiang, Luo, Zuojie, Chen, Li, Hou, Xinguo, Huo, Yanan, Li, Qiang, Qiao, Hong, Zhang, Yinfei, Zeng, Tianshu, Hu, Chunyan, Cao, Qiuyu, Jia, Xiaojing, Liu, Chao, Wang, Youmin, Wu, Shengli, Yang, Tao, Deng, Huacong, Qi, Hongyan, Wu, Xueyan, Zhang, Di, Dai, Meng, Li, Donghui, Lai, Shenghan, Chen, Lulu, Zhao, Jiajun, Mu, Yiming, Hu, Weiguo, Ning, Guang, Hu, Ruying, Bi, Yufang, and Wang, Weiqing

Published
2024
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28. Association of circulating long-chain free fatty acids and incident diabetes risk among normoglycemic Chinese adults: a prospective nested case–control study

Author

Wang, Shuangyuan, Hu, Chunyan, Lin, Hong, Jia, Xiaojing, Hu, Ruying, Zheng, Ruizhi, Li, Mian, Xu, Yu, Xu, Min, Zheng, Jie, Zhao, Xinjie, Li, Yanli, Chen, Lulu, Zeng, Tianshu, Ye, Zhen, Shi, Lixin, Su, Qing, Chen, Yuhong, Yu, Xuefeng, Yan, Li, Wang, Tiange, Zhao, Zhiyun, Qin, Guijun, Wan, Qin, Chen, Gang, Dai, Meng, Zhang, Di, Qiu, Bihan, Zhu, Xiaoyan, Liu, Ruixin, Wang, Xiao, Tang, Xulei, Gao, Zhengnan, Shen, Feixia, Gu, Xuejiang, Luo, Zuojie, Qin, Yingfen, Chen, Li, Hou, Xinguo, Huo, Yanan, Li, Qiang, Wang, Guixia, Zhang, Yinfei, Liu, Chao, Wang, Youmin, Wu, Shengli, Yang, Tao, Deng, Huacong, Zhao, Jiajun, Mu, Yiming, Xu, Guowang, Lai, Shenghan, Li, Donghui, Ning, Guang, Wang, Weiqing, Bi, Yufang, and Lu, Jieli

Published
2024
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