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Cross-cohort analysis identifies shared gut microbial signatures and validates microbial risk scores for colorectal cancer

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Journal of translational medicine 2025年第1期23卷 676页

作者： Yuhan Zhang Jiahui Luo Kuangyu Chen Na Li Chenyu Luo Shuang Di Junjie Qin Feng Zhang Hongda Chen Min Dai Center for Clinical and Epidemiologic Research Beijing Anzhen Hospital Capital Medical University Beijing Institute of Heart Lung and Blood Vessel Diseases Beijing 100029 China. Department of Cancer Epidemiology National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100021 China. Center for Prevention and Early Intervention National Infrastructures for Translational Medicine Institute of Clinical Medicine Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100730 China. Key Laboratory of Data Engineering and Knowledge Engineering (MOE) and School of Information Renmin University of China Beijing 100872 China. Centre for Data Science and Digital Health Hamilton Health Sciences Hamilton ON L8P 0A1 Canada. Dalla Lana School of Public Health University of Toronto Toronto ON M5T 3M7 Canada. School of Life Science and Technology School of Food Science and Engineering Nutrition and Health Research Institute Wuhan Polytechnic University Wuhan 430024 China. Center for Prevention and Early Intervention National Infrastructures for Translational Medicine Institute of Clinical Medicine Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100730 China. chenhongda@***. Department of Cancer Epidemiology National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100021 China. daimin2002@***.

BACKGROUND:Microbiome-wide association studies showed links between colorectal cancer (CRC) and gut microbiota. However, the clinical application of gut microbiota in CRC prevention has been hindered by the diversity of study populations and technical variations. We aimed to determine CRC-related gut microbial signatures based on cross-regional, cross-population, and cross-cohort metagenomic datasets, and elucidate its application value in CRC risk assessment. METHODS:We used the MMUPHin tool to perform a meta-analysis of our own cohort and seven publicly available metagenomics datasets to identify gut microbial species associated with CRC across different cohorts, comprising of 570 CRC cases and 557 controls. Based on differential species sets, we constructed the microbial risk score (MRS) using α-diversity of the sub-community (MRS), weighted/unweighted summation methods and machine learning algorithms. Cohort-to-cohort training and validation were performed to demonstrate the transferability. RESULTS:We found that MRS of core species was better validated and more interpretable than those constructed with summation methods or machine learning algorithms. Six species, including Parvimonas micra, Clostridium symbiosum, Peptostreptococcus stomatis, Bacteroides fragilis, Gemella morbillorum, and Fusobacterium nucleatum, were included in MRS constructed by half or more of the cohorts. The AUC of MRS, calculated based on the sub-community of six species, varied between 0.619 and 0.824 across the eight cohorts. CONCLUSION:We identified six CRC-related species across regions, populations, and cohorts. The constructed MRS could contribute to the risk prediction of CRC in different populations.

关键词： Colorectal cancer Cross-cohort Disease prediction Gut microbiota Microbial risk score

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Accumulated gradient normalization 9

Accumulated gradient normalization

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9th Asian Conference on Machine Learning, ACML 2017

作者： Hermans, Joeri R. Spanakis, Gerasimos Möckel, Rico Department of Electrical Engineering and Computer Science Liège University Belgium Department of Data Science and Knowledge Engineering Maastricht University Netherlands

This work addresses the instability in asynchronous data parallel optimization. It does so by introducing a novel distributed optimizer which is able to efficiently optimize a centralized model under communication constraints. The optimizer achieves this by pushing a normalized sequence of first-order gradients to a parameter server. This implies that the magnitude of a worker delta is smaller compared to an accumulated gradient, and provides a better direction towards a minimum compared to first-order gradients, which in turn also forces possible implicit momentum fluctuations to be more aligned since we make the assumption that all workers contribute towards a single minima. As a result, our approach mitigates the parameter staleness problem more effectively since staleness in asynchrony induces (implicit) momentum, and achieves a better convergence rate compared to other optimizers such as asynchronous easgd and dynsgd, which we show empirically. © 2017 J.R. Hermans, G. Spanakis & R. Möckel.

关键词： Optimization

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Adaptive structure-constrained robust latent low-rank coding for image recovery

arXiv

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arXiv 2019年

作者： Zhang, Zhao Wang, Lei Li, Sheng Wang, Yang Zhang, Zheng Zha, Zhengjun Wang, Meng School of Computer Science and Technology Soochow University Suzhou215006 China Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei University of Technology School of Computer Science and Information Engineering Hefei University of Technology Hefei China Department of Computer Science University of Georgia 549 Boyd GSRC AthensGA30602 Shenzhen China School of Information Science and Technology University of Science and Technology of China Hefei China

In this paper, we propose a robust representation learning model called Adaptive Structure-constrained Low-Rank Coding (AS-LRC) for the latent representation of data. To recover the underlying subspaces more accurately, AS-LRC seamlessly integrates an adaptive weighting based block-diagonal structure-constrained low-rank representation and the group sparse salient feature extraction into a unified framework. Specifically, AS-LRC performs the latent decomposition of given data into a low-rank reconstruction by a block-diagonal codes matrix, a group sparse locality-adaptive salient feature part and a sparse error part. To enforce the block-diagonal structures adaptive to different real datasets for the low-rank recovery, AS-LRC clearly computes an auto-weighting matrix based on the locality-adaptive features and multiplies by the low-rank coefficients for direct minimization at the same time. This encourages the codes to be block-diagonal and can avoid the tricky issue of choosing optimal neighborhood size or kernel width for the weight assignment, suffered in most local geometrical structures-preserving low-rank coding methods. In addition, our AS-LRC selects the L2,1-norm on the projection for extracting group sparse features rather than learning low-rank features by Nuclear-norm regularization, which can make learnt features robust to noise and outliers in samples, and can also make the feature coding process efficient. Extensive visualizations and numerical results demonstrate the effectiveness of our AS-LRC for image representation and recovery. Copyright © 2019, The Authors. All rights reserved.

关键词： Recovery

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Foundations of digital archæoludology

arXiv

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arXiv 2019年

作者： Browne, Cameron Soemers, Dennis J.N.J. Piette, Éric Stephenson, Matthew Conrad, Michael Crist, Walter Depaulis, Thierry Duggan, Eddie Horn, Fred Kelk, Steven Lucas, Simon M. Neto, João Pedro Parlett, David Saffidine, Abdallah Schädler, Ulrich Silva, Jorge Nuno de Voogt, Alex Winands, Mark H.M. Department of Data Science and Knowledge Engineering Maastricht University Netherlands Kunsthistorisches Institut Universität Zürich Switzerland Department of Anthropology American Museum of Natural History United States Department of Science Technology and Engineering University of Suffolk United Kingdom School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom University of Lisbon Portugal School of Computer Science and Engineering University of New South Wales Australia Swiss Museum of Games Switzerland Economics & Business Department Drew University United States

Digital Archæoludology (DAL) is a new field of study involving the analysis and reconstruction of ancient games from incomplete descriptions and archaeological evidence using modern computational techniques. The aim is to provide digital tools and methods to help game historians and other researchers better understand traditional games, their development throughout recorded human history, and their relationship to the development of human culture and mathematical knowledge. This work is being explored in the ERC-funded Digital Ludeme Project. The aim of this inaugural international research meeting on DAL is to gather together leading experts in relevant disciplines – computer science, artificial intelligence, machine learning, computational phylogenetics, mathematics, history, archaeology, anthropology, etc. – to discuss the key themes and establish the foundations for this new field of research, so that it may continue beyond the lifetime of its initiating project. Copyright © 2019, The Authors. All rights reserved.

关键词： History

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A filter of minhash for image similarity measures

arXiv

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arXiv 2018年

作者： Long, Jun Liu, Qunfeng Yuan, Xinpan Zhang, Chengyuan Liu, Junfeng School of Information Science and Engeering Central South University Big Data and Knowledge Engineering Institute Central South University School of Computer Hunan University of Technology

Image similarity measures play an important role in nearest neighbor search and duplicate detection for large-scale image datasets. Recently, Minwise Hashing (or Minhash) and its related hashing algorithms have achieved great performances in large-scale image retrieval systems. However, there are a large number of comparisons for image pairs in these applications, which may spend a lot of computation time and affect the performance. In order to quickly obtain the pairwise images that theirs similarities are higher than the specific threshold T (e.g., 0.5), we propose a dynamic threshold filter of Minwise Hashing for image similarity measures. It greatly reduces the calculation time by terminating the unnecessary comparisons in advance. We also find that the filter can be extended to other hashing algorithms, on when the estimator satisfies the binomial distribution, such as b-Bit Minwise Hashing, One Permutation Hashing, etc. In this pager, we use the Bag-of-Visual-Words (BoVW) model based on the Scale Invariant Feature Transform (SIFT) to represent the image features. We have proved that the filter is correct and effective through the experiment on real image datasets. Copyright © 2018, The Authors. All rights reserved.

关键词： Image analysis

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A Concept for Productivity Tracking based on Collaborative Interactive Learning Techniques 31

A Concept for Productivity Tracking based on Collaborative I...

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31st GI/ITG International Conference on Architecture of Computing Systems, ARCS 2018

作者： Calma, Adrian Kuhn, Jochen Leimeister, Jan Marco Lukowicz, Paul Oeste-Reiß, Sarah Schmidt, Albrecht Sick, Bernhard Stumme, Gerd Tomforde, Sven Zweig, Anna Katharina Intelligent Embedded Systems University of Kassel Germany Didactics of Physics University of Kaiserslautern Germany Algorithmic Accountability University of Kaiserslautern Germany Information Systems University of Kassel Germany Human-Centered Ubiquitous Media Ludwig-Maximilian-University Munich Germany Embedded Intelligence Dfki Kaiserslautern Germany Knowledge and Data Engineering University of Kassel Germany

ISBN: (纸本)9783800745593

The academic success of individual students differs widely and it depends on various factors, ranging from financial to social and to health aspects. In this article, we propose a concept for a novel productivity tracking system that provides the basis for a self-assessment of academic behaviour and that can be used by students to support their academic success. The development of such a system requires interdisciplinary efforts, most of them located in the field of collaborative interactive learning (CIL) that is grounded on a socio-technical system perspective. The system is interactive since it is based on bi-directional communication, collaborative in the sense that it uses students, other students, and external sources such as the Internet for generation of knowledge, and learning in the sense that it continuously and autonomously acquires knowledge. It is further self-organised as it decides about interaction partners and self-adaptive in terms of modifying its behaviour according to changing conditions. © ARCS 2018.

关键词： Students

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A study on the improvement and application of system dynamics model for demand forecasting of ships

A study on the improvement and application of system dynamic...

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RINA, Royal Institution of Naval Architects - International Conference on Computer Applications in Shipbuilding 2017, ICCAS 2017

作者： Wada, Y. Hamada, K. Hirata, N. Knowledge and Data System Department National Maritime Research Institute Japan Graduate School of Engineering Hiroshima University Japan

ISBN: (纸本)9781909024670

Shipbuilding is an industry in which the change in demand has been extremely drastic. Therefore, it is important to develop a method of demand forecasting for new ships in order to realize sustainable development of the shipbuilding industry. Recently, sufficient actual data on the shipbuilding market has become available, and it is expected to define an accurate demand-forecasting model by using these data. In this study, the system dynamics model of previous study is improved by using latest market data, and optimal measures planning system for shipbuilding industry is developed based on the proposed model. Thereby, some simulations using the proposed demand-forecasting model and system are conducted, and the effectiveness of proposed model and system are shown. © 2017: The Royal Institution of Naval Architects.

关键词： Shipbuilding

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NaCdSb: An Orthorhombic Zintl Phase with Exceptional Intrinsic Thermoelectric Performance

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Angewandte Chemie 2022年第3期135卷

作者： Kai Guo Yuting Zhang Song Yuan Qinghang Tang Chen Lin Pengfei Luo Jiong Yang Shusheng Pan Li-Dong Zhao Guofeng Cheng Jiye Zhang Jun Luo School of Physics and Materials Science Guangzhou University Guangzhou 510006 China Research Center for Advanced Information Materials (CAIM) Huangpu Research & Graduate School of Guangzhou University Sino-Singapore Guangzhou Knowledge City Huangpu District Guangzhou 510555 China Contribution: Conceptualization (lead) Formal analysis (equal) Writing - original draft (lead) School of Materials Science and Engineering Shanghai University 99 Shangda Road Shanghai 200444 China Contribution: Data curation (equal) Investigation (equal) Validation (lead) Contribution: Data curation (lead) Formal analysis (equal) Materials Genome Institute Shanghai University 99 Shangda Road Shanghai 200444 China Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology Wuhan University Wuhan 430072 China Contribution: Investigation (equal) Contribution: Investigation (equal) Methodology (supporting) Contribution: Investigation (equal) Writing - review & editing (supporting) School of Materials Science and Engineering Beihang University Beijing 100191 China Contribution: Methodology (equal) Writing - review & editing (equal) Analysis & Testing Center for Inorganic Materials Shanghai Institute of Ceramics Chinese Academy of Sciences Shanghai 200050 China Contribution: Formal analysis (equal) Investigation (supporting) Contribution: Data curation (equal) Writing - review & editing (supporting) Contribution: Supervision (lead) Writing - review & editing (equal)

Many Zintl phases are promising thermoelectric materials owning to their features like narrow band gaps, multiband behaviors, ideal charge transport tunnels, and loosely bound cations. Herein we show a new Zintl phase NaCdSb with exceptional intrinsic thermoelectric performance. Pristine NaCdSb exhibits semiconductor behaviors with an experimental hole concentration of 2.9×10 18 cm −3 and a calculated band gap of 0.5 eV. As the temperature increases, the hole concentration rises gradually and approaches its optimal one, leading to a high power factor of 11.56 μW cm −1 K −2 at 673 K. The ultralow thermal conductivity is derived from the small phonon group velocity and short phonon lifetime, ascribed to the structural anharmonicity of Cd−Sb bonds. As a consequence, a maximum zT of 1.3 at 673 K has been achieved without any doping optimization or structural modification, demonstrating that NaCdSb is a remarkable thermoelectric compound with great potential for performance improvement.

关键词： Electron-Crystal NaCdSb Phonon-Glass Thermoelectric Properties Zintl Phase

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On the relationship between classical and computable topology 14

On the relationship between classical and computable topolog...

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14th International Conference on Computability and Complexity in Analysis, CCA 2017

作者： Collins, Pieter Department of Data Science and Knowledge Engineering Maastricht University Bouillonstraat 8-10 Postbus 616 6200MD Netherlands

In this talk, we will look at some important concepts in classical topology, and discuss their computable counterparts. The main goals are to combine many important results which are scattered throughout the literature, and to -nd the most natural de-nitions for computable versions of classical properties. It turns out that many notions in computable topology coincide more closely with the corresponding notion in limit/sequential spaces than the classical topological notion. Further, for the class of spaces admitting an admissible representation, in many cases the de-nitions coincide;an important case are the various topologies on the open sets, including the Scott topology. © 2017 14th International Conference on Computability and Complexity in Analysis, CCA 2017 - Proceedings. All rights reserved.

关键词： Topology

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Personalized Concept-Based Search on the Linked Open data

SSRN

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SSRN 2018年

作者： Sah, Melike Wade, Vincent Department of Computer Engineering Near East University via Mersin 10 Nicosia North Cyprus Turkey Centre for Global Intelligent Content Knowledge and Data Engineering Group Trinity College Dublin Dublin Ireland

In this paper, we present a novel personalized concept-based search mechanism for the Web of data based on results *** innovation of the paper comes from combining novel categorization and personalization techniques, and using categorization for providing personalization. In our approach, search results (Linked Open data resources) are dynamically categorized into Upper Mapping and Binding Exchange Layer (UMBEL) concepts using a novelfuzzy retrieval model. Then, results with the same concepts are grouped together to form categories, which we call conceptlenses. Such categorization enables concept-based browsing of the retrieved results aligned to users’ intent or interests. When the user selects a concept lens for exploration, results are immediately personalized. In particular, all concept lenses are personally re-organized according to their similarity to the selected lens. Within the selected concept lens;more relevant results are included using results re-ranking and query expansion, as well as relevant concept lenses are suggested to support results exploration. This allows dynamic adaptation of results to the user's local choices. We also support interactive personalization;when the user clicks on a result, within the interacted lens, relevant lenses and results are included using results re-ranking and query expansion. Extensive evaluations were performed to assess our approach: (i) Performance of our fuzzy-based categorization approach was evaluated on a particular benchmark (~10,000 mappings). The evaluations showed that we can achieve highly acceptable categorization accuracy and perform better than the vector space model. (ii) Personalized search efficacy was assessed using a user study with 32 participants in a tourist domain. The results revealed that our approach performed significantly better than a non-adaptive baseline search.(iii) Dynamic personalization performance was evaluated, which illustrated that our personalization approach i

关键词： Mapping

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