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152. Functional informed genome‐wide interaction analysis of body mass index, diabetes and colorectal cancer risk

Author

Xia, Zhiyu, Su, Yu‐Ru, Petersen, Paneen, Qi, Lihong, Kim, Andre E, Figueiredo, Jane C, Lin, Yi, Nan, Hongmei, Sakoda, Lori C, Albanes, Demetrius, Berndt, Sonja I, Bézieau, Stéphane, Bien, Stephanie, Buchanan, Daniel D, Casey, Graham, Chan, Andrew T, Conti, David V, Drew, David A, Gallinger, Steven J, Gauderman, W James, Giles, Graham G, Gruber, Stephen B, Gunter, Marc J, Hoffmeister, Michael, Jenkins, Mark A, Joshi, Amit D, Le Marchand, Loic, Lewinger, Juan P, Li, Li, Lindor, Noralane M, Moreno, Victor, Murphy, Neil, Nassir, Rami, Newcomb, Polly A, Ogino, Shuji, Rennert, Gad, Song, Mingyang, Wang, Xiaoliang, Wolk, Alicja, Woods, Michael O, Brenner, Hermann, White, Emily, Slattery, Martha L, Giovannucci, Edward L, Chang‐Claude, Jenny, Pharoah, Paul DP, Hsu, Li, Campbell, Peter T, and Peters, Ulrike

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Digestive Diseases, Human Genome, Genetics, Cancer, Diabetes, Prevention, Nutrition, Colo-Rectal Cancer, Metabolic and endocrine, ATPases Associated with Diverse Cellular Activities, Aged, Body Mass Index, Colorectal Neoplasms, Databases, Genetic, Diabetes Mellitus, Type 2, Female, Gene Expression, Genotype, Hepatocyte Nuclear Factor 3-alpha, Humans, Male, Microtubule-Associated Proteins, Middle Aged, Obesity, Phenotype, Proteasome Endopeptidase Complex, Protein Tyrosine Phosphatase, Non-Receptor Type 2, Sex Factors, Sialic Acid Binding Ig-like Lectin 3, Voltage-Gated Sodium Channel beta-1 Subunit, BMI, colorectal cancer, diabetes, gene expression, gene-environmental interaction, Biochemistry and Cell Biology, Oncology and carcinogenesis
Abstract

BackgroundBody mass index (BMI) and diabetes are established risk factors for colorectal cancer (CRC), likely through perturbations in metabolic traits (e.g. insulin resistance and glucose homeostasis). Identification of interactions between variation in genes and these metabolic risk factors may identify novel biologic insights into CRC etiology.MethodsTo improve statistical power and interpretation for gene-environment interaction (G × E) testing, we tested genetic variants that regulate expression of a gene together for interaction with BMI (kg/m2 ) and diabetes on CRC risk among 26 017 cases and 20 692 controls. Each variant was weighted based on PrediXcan analysis of gene expression data from colon tissue generated in the Genotype-Tissue Expression Project for all genes with heritability ≥1%. We used a mixed-effects model to jointly measure the G × E interaction in a gene by partitioning the interactions into the predicted gene expression levels (fixed effects), and residual G × E effects (random effects). G × BMI analyses were stratified by sex as BMI-CRC associations differ by sex. We used false discovery rates to account for multiple comparisons and reported all results with FDR

Published
2020

153. Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium

Author

Kapoor, Pooja Middha, Lindström, Sara, Behrens, Sabine, Wang, Xiaoliang, Michailidou, Kyriaki, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Dunning, Alison M, Pharoah, Paul DP, Schmidt, Marjanka K, Kraft, Peter, García-Closas, Montserrat, Easton, Douglas F, Milne, Roger L, Chang-Claude, Jenny, Ahearn, Thomas, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Augustinsson, Annelie, Freeman, Laura E Beane, Beckmann, Matthias W, Benitez, Javier, Bernstein, Leslie, Berrandou, Takiy, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brock, Ian W, Broeks, Annegien, Brooks-Wilson, Angela, Butterbach, Katja, Cai, Qiuyin, Campa, Daniele, Canzian, Federico, Carter, Brian D, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Cheng, Ting-Yuan David, Clarke, Christine L, Cordina-Duverger, Emilie, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dai, James Y, Dite, Gillian S, Earp, H Shelton, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Flyger, Henrik, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, Gapstur, Susan M, Gaudet, Mia M, Giles, Graham G, González-Neira, Anna, Grundy, Anne, Guénel, Pascal, Haeberle, Lothar, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan E, Harkness, Elaine F, Harstad, Tricia, He, Wei, Heyworth, Jane, Hoover, Robert N, Hopper, John L, Humphreys, Keith, Hunter, David J, Marrón, Pablo Isidro, John, Esther M, Jones, Michael E, Jung, Audrey, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Krüger, Ute, Lambrechts, Diether, Le Marchand, Loic, Lee, Eunjung, Lejbkowicz, Flavio, Linet, Martha, Lissowska, Jolanta, Llaneza, Ana, Lo, Wing-Yee, and Makalic, Enes

Subjects
Genetics, Estrogen, Clinical Research, Cancer, Breast Cancer, Prevention, 2.1 Biological and endogenous factors, Aetiology, Alleles, Breast Neoplasms, Case-Control Studies, Europe, Factor XIII, Female, Gene-Environment Interaction, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Polymorphism, Single Nucleotide, Receptors, Estrogen, Risk Factors, White People, Breast Cancer Association Consortium, Europeans, Gene-environment interaction, breast cancer, epidemiology, risk factors, single nucleotide polymorphism, Statistics, Public Health and Health Services, Epidemiology
Abstract

BackgroundPrevious gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions.MethodsAnalyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions.ResultsNoteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth.ConclusionsOverall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.

Published
2020

154. Minimizing Immune Costs in Social Networks Through Reinforcement Learning

Author

Nie, Haichao, Li, Pei, Zhou, Ying, Wang, Xiaoliang, Xiao, Chixin, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Sun, Xingming, editor, Zhang, Xiaorui, editor, Xia, Zhihua, editor, and Bertino, Elisa, editor

Published
2022
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155. A Scheme to Improve the Security of IoT Communication

Author

Fu, Junjie, Wang, Xiaoliang, Liu, Yuzhen, Yang, Qing, Jiang, Frank, 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, Sun, Xingming, editor, Zhang, Xiaorui, editor, and Xia, Zhihua, editor

Published
2022
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156. Adaptive Fault Diagnosis System for Railway Track Circuits

Author

Liu, Xigao, Wang, Xiaoliang, Han, Gaitang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, 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, Hirche, Sandra, 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, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Liang, Jianying, editor, Liu, Zhigang, editor, Diao, Lijun, editor, and An, Min, editor

Published
2022
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157. FastCache: A Client-Side Cache with Variable-Position Merging Schema in Network Storage System

Author

Qian, Lin, Ye, BaoLiu, Wang, XiaoLiang, Qu, Zhihao, Duan, Weiguo, Zhao, Ming, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Lai, Yongxuan, editor, Wang, Tian, editor, Jiang, Min, editor, Xu, Guangquan, editor, Liang, Wei, editor, and Castiglione, Aniello, editor

Published
2022
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158. A Train Positioning Method Based on Satellite Navigation System and Electronic Map

Author

Han, Gaitang, Wang, Xiaoliang, Lin, Ying, Liu, Xigao, Feng, Caixia, Yang, Peng, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, 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, Hirche, Sandra, 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, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Liang, Jianying, editor, Liu, Zhigang, editor, Diao, Lijun, editor, and An, Min, editor

Published
2022
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159. Adaptive Buffering Scheme for PCM/DRAM-Based Hybrid Memory Architecture

Author

Wang, Xiaoliang, Chen, Kaimeng, Jin, Peiquan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Cérin, Christophe, editor, Qian, Depei, editor, Gaudiot, Jean-Luc, editor, Tan, Guangming, editor, and Zuckerman, Stéphane, editor

Published
2022
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160. Adaptive Attitude Estimation and Control of Hypersonic Re-Entry Vehicle with Unknown Process Noise

Author

Wang, Xiaoliang, Wu, Shufan, Kang, Zeyu, Gong, Deren, Yu, Jianhui, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, 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, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Zhang, Junjie James, Series Editor, Yan, Liang, editor, and Yu, Xiang, editor

Published
2022
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161. The General Evaluation Method for Control Performance of Reentry Vehicle

Author

Kang, Zeyu, Wu, Shufan, Wang, Xiaoliang, Yu, Jianhui, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, 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, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Zhang, Junjie James, Series Editor, Yan, Liang, editor, and Yu, Xiang, editor

Published
2022
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182. Fast and Accurate, Convolutional Neural Network Based Approach for Object Detection from UAV

Author

Wang, Xiaoliang, Cheng, Peng, Liu, Xinchuan, and Uzochukwu, Benedict

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Unmanned Aerial Vehicles (UAVs), have intrigued different people from all walks of life, because of their pervasive computing capabilities. UAV equipped with vision techniques, could be leveraged to establish navigation autonomous control for UAV itself. Also, object detection from UAV could be used to broaden the utilization of drone to provide ubiquitous surveillance and monitoring services towards military operation, urban administration and agriculture management. As the data-driven technologies evolved, machine learning algorithm, especially the deep learning approach has been intensively utilized to solve different traditional computer vision research problems. Modern Convolutional Neural Networks based object detectors could be divided into two major categories: one-stage object detector and two-stage object detector. In this study, we utilize some representative CNN based object detectors to execute the computer vision task over Stanford Drone Dataset (SDD). State-of-the-art performance has been achieved in utilizing focal loss dense detector RetinaNet based approach for object detection from UAV in a fast and accurate manner., Comment: arXiv admin note: substantial text overlap with arXiv:1803.01114

Published
2018

183. Focal Loss Dense Detector for Vehicle Surveillance

Author

Wang, Xiaoliang, Cheng, Peng, Liu, Xinchuan, and Uzochukwu, Benedict

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Deep learning has been widely recognized as a promising approach in different computer vision applications. Specifically, one-stage object detector and two-stage object detector are regarded as the most important two groups of Convolutional Neural Network based object detection methods. One-stage object detector could usually outperform two-stage object detector in speed; However, it normally trails in detection accuracy, compared with two-stage object detectors. In this study, focal loss based RetinaNet, which works as one-stage object detector, is utilized to be able to well match the speed of regular one-stage detectors and also defeat two-stage detectors in accuracy, for vehicle detection. State-of-the-art performance result has been showed on the DETRAC vehicle dataset.

Published
2018

184. RDMAvisor: Toward Deploying Scalable and Simple RDMA as a Service in Datacenters

Author

Wang, Zhi, Wang, Xiaoliang, Qian, Zhuzhong, Ye, Baoliu, and Lu, Sanglu

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Networking and Internet Architecture, Computer Science - Performance
Abstract

RDMA is increasingly adopted by cloud computing platforms to provide low CPU overhead, low latency, high throughput network services. On the other hand, however, it is still challenging for developers to realize fast deployment of RDMA-aware applications in the datacenter, since the performance is highly related to many lowlevel details of RDMA operations. To address this problem, we present a simple and scalable RDMA as Service (RaaS) to mitigate the impact of RDMA operational details. RaaS provides careful message buffer management to improve CPU/memory utilization and improve the scalability of RDMA operations. These optimized designs lead to simple and flexible programming model for common and knowledgeable users. We have implemented a prototype of RaaS, named RDMAvisor, and evaluated its performance on a cluster with a large number of connections. Our experiment results demonstrate that RDMAvisor achieves high throughput for thousand of connections and maintains low CPU and memory overhead through adaptive RDMA transport selection., Comment: submitted to USENIX ATC 2017, No.9

Published
2018

185. Towards Reliable (and Efficient) Job Executions in a Practical Geo-distributed Data Analytics System

Author

Zhang, Xiaoda, Qian, Zhuzhong, Zhang, Sheng, Li, Yize, Li, Xiangbo, Wang, Xiaoliang, and Lu, Sanglu

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Geo-distributed data analytics are increasingly common to derive useful information in large organisations. Naive extension of existing cluster-scale data analytics systems to the scale of geo-distributed data centers faces unique challenges including WAN bandwidth limits, regulatory constraints, changeable/unreliable runtime environment, and monetary costs. Our goal in this work is to develop a practical geo-distribued data analytics system that (1) employs an intelligent mechanism for jobs to efficiently utilize (adjust to) the resources (changeable environment) across data centers; (2) guarantees the reliability of jobs due to the possible failures; and (3) is generic and flexible enough to run a wide range of data analytics jobs without requiring any changes. To this end, we present a new, general geo-distributed data analytics system, HOUTU, that is composed of multiple autonomous systems, each operating in a sovereign data center. HOUTU maintains a job manager (JM) for a geo-distributed job in each data center, so that these replicated JMs could individually and cooperatively manage resources and assign tasks. Our experiments on the prototype of HOUTU running across four Alibaba Cloud regions show that HOUTU provides nearly efficient job performance as in the existing centralized architecture, and guarantees reliable job executions when facing failures.

Published
2018

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