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2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Wang, Xiaowei Han, Jungang Li, Ben Pan, Xiaoying Xu, Hui Xi'An University of Posts and Telecommunications School of Computer Science Xi'an China Shaanxi Key Laboratory of Network Data Analysis and Intelligence Processing Xi'an China Technology Co. LTD Beijing China

ISBN: (纸本)9781665401265

Classifying diseases in electronic medical records into corresponding ICD codes requires not only a large amount of medical knowledge but also a large number of coders, which is time-consuming and labor-consuming. Therefore, automatic coding is of great significance. This paper aims to build a deep learning model for automatic ICD-10 coding from a batch of Chinese electronic medical records. The data enhancement, convolutional neural network, attention mechanism, and the gating residual network proposed by the author were used to code ICD code corresponding to the distribution of medical record information by supervised learning. The benchmark model and ablation model were tested on a data set of Chinese electronic medical records. The effectiveness of the proposed modules, such as feature aggregation, multi-head attention mechanism, dilated convolution, and gating residuals, was verified. In the automatic ICD coding task for 104 diseases, the accuracy of the proposed method is 91.71%, and the F1-Score is 92.11%.1 © 2021 IEEE.

关键词： Convolution

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Spherical paragraph model

arXiv

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arXiv 2017年

作者： Zhang, Ruqing Guo, Jiafeng Lan, Yanyan Xu, Jun Cheng, Xueqi CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China

Representing texts as fixed-length vectors is central to many language processing tasks. Most traditional methods build text representations based on the simple Bag-of-Words (BoW) representation, which loses the rich semantic relations between words. Recent advances in natural language processing have shown that semantically meaningful representations of words can be efficiently acquired by distributed models, making it possible to build text representations based on a better foundation called the Bag-of-Word-Embedding (BoWE) representation. However, existing text representation methods using BoWE often lack sound probabilistic foundations or cannot well capture the semantic relatedness encoded in word vectors. To address these problems, we introduce the Spherical Paragraph Model (SPM), a probabilistic generative model based on BoWE, for text representation. SPM has good probabilistic interpretability and can fully leverage the rich semantics of words, the word co-occurrence information as well as the corpus-wide information to help the representation learning of texts. Experimental results on topical classification and sentiment analysis demonstrate that SPM can achieve new state-of-the-art performances on several benchmark datasets. Copyright © 2017, The Authors. All rights reserved.

关键词： Sentiment analysis

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Leaky Autofill: An Empirical Study on the Privacy Threat of Password Managers’ Autofill Functionality 40

Leaky Autofill: An Empirical Study on the Privacy Threat of ...

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40th Annual Computer Security Applications Conference, ACSAC 2024

作者： Fu, Yanduo Wang, Ding College of Cyber Science Nankai University Tianjin300350 China Ministry of Education Tianjin300350 China Tianjin Key Laboratory of Network and Data Security Technology Nankai University Tianjin300350 China

ISBN: (纸本)9798331520885

Password managers (PMs) provide users with convenient and robust functionalities to manage their credentials, highly recommended by security experts and major standard bodies. One of the most popular features is the autofill functionality, with which users need a single click or a few clicks to fill in every field in web forms, facilitating the process of completing web forms. However, such indiscriminate autofill brings severe privacy threats. PMs may inadvertently fill data into wrong fields in web forms, even hidden fields, potentially leading to privacy leaks and credential theft. In this paper, we conduct an empirical study evaluating the effectiveness of 30 popular PMs in identifying and handling hidden fields. We focus on the privacy threats posed by the autofill functionality, which fills data into hidden fields. We develop a semi-automated autofill testing tool and explore whether PMs autofill sensitive data into hidden fields across 15 concealment techniques and three web forms, including personal information, credit card, and login forms. Experimental results reveal that every PM autofills data into hidden fields in at least one web form, with an overall filled probability of 58.7% in 1032 scenarios. Further analysis reveals that login forms are the most vulnerable, with a 65.7% probability of hidden fields autofill. Hidden fields concealed by clip-path and content-visibility are filled with passwords by all PMs. Besides, built-in-browser PMs exhibit a 4.07 times higher likelihood of filling data into hidden fields than separately-installed PMs. Even more concerning, built-in-browser PMs, except Safari, autofill passwords into hidden fields under any concealment technique. 37.7% of autofill scenarios with insufficient user interaction pose heightened privacy threats, as users are unaware of autofill content. These privacy threats have been confirmed by popular PMs like LastPass. To mitigate the threats brought by the autofill functionality, we present two

关键词： Visual languages

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MatchZoo: A toolkit for deep text matching

arXiv

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arXiv 2017年

作者： Fan, Yixing Pang, Liang Hou, JianPeng Guo, Jiafeng Lan, Yanyan Cheng, Xueqi Cas Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China

In recent years, deep neural models have been widely adopted for text matching tasks, such as question answering and information retrieval, showing improved performance as compared with previous methods. In this paper, we introduce the MatchZoo toolkit that aims to facilitate the designing, comparing and sharing of deep text matching models. Specifically, the toolkit provides a unified data preparation module for different text matching problems, a flexible layer-based model construction process, and a variety of training objectives and evaluation metrics. In addition, the toolkit has implemented two schools of representative deep text matching models, namely representation-focused models and interaction-focused models. Finally, users can easily modify existing models, create and share their own models for text matching in MatchZoo. Copyright © 2017, The Authors. All rights reserved.

关键词： Deep learning

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Improving preparation and luminescence properties of Eu and dy doped Sr2MgSi2O7 phosphors by adding excess silica

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Scientific reports 2025年第1期15卷 18367页

作者： Chi Zhang Liuming Wei Qin Liu Ruirui Cui Chaoyong Deng Jingyu Li College of Electrical Engineering Henan University of Technology Zhengzhou 450001 China. chizhang@***. Department of Network Security Henan Police College Zhengzhou 450046 China. Anqiu Qingyun Bilingual School Weifang China. Key Laboratory of Functional Composite Materials of Guizhou Province College of Big Data and Information Engineering Guizhou University Guiyang 550025 China. Key Laboratory of Functional Composite Materials of Guizhou Province College of Big Data and Information Engineering Guizhou University Guiyang 550025 China. cydeng@***. Spallation Neutron Source Science Center Dongguan 523803 China. ***@***.

Solid state reaction method is most commonly used to synthesize SrMgSiO: Eu, Dy phosphors. In order to avoid the energy waste caused by high sintering temperature, we systematically studied and optimized the preparation process of SrMgSiO: Eu, Dy long afterglow phosphors by increasing the Si/Sr ratio in the raw materials. The appropriate addition of silica not only facilitates the preparation of single phase SrMgSiO: Eu, Dy phosphor but also enhances the rate of solid state reaction, so as to achieve the purpose of reducing the sintering temperature. The photoluminescence performance of the sample with a Si/Sr ratio of 1.1 sintered at 1350 °C is the highest, followed by that of the sample sintered at 1400 °C with a Si/Sr ratio of 1.0. Notably, the photoluminescence properties of the Si/Sr ratio of 1.3 sample sintered at 1300 °C are comparable to those of the Si/Sr ratio of 1.0 sample sintered at 1400 °C. However, in terms of afterglow properties, the former exhibits an enhancement by a factor of 3.5 compared to the latter. This finding suggests that strategically increasing the Si/Sr ratio can reduce the sintering temperature by 100 °C while maintaining or even enhancing the luminescence and afterglow properties of the samples. Additionally, the electronic structures of the SrMgSiO host, the doped luminescence center Eu, the oxygen vacancies and the co-doped activator Dy have been methodically investigated through first-principles calculations. By integrating the findings on the distribution of the dopants and defects levels, we predict and propose the photoluminescence and afterglow mechanisms of SrMgSiO: Eu, Dy. These studies suggest an efficient, cheap and energy-saving strategy for the preparation of SrMgSiO: Eu, Dy long afterglow phosphor, and reveal the roles of oxygen vacancies and co-doped Dy in the afterglow luminescence.

关键词： Electron traps First-principles calculation Optimizing synthesis Persistent luminescence Sr2MgSi2O7

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Contrastive Meta-Learning for Drug-Target Binding Affinity Prediction

Contrastive Meta-Learning for Drug-Target Binding Affinity P...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Li, Mei Xu, Sihan Cai, Xiangrui Zhang, Zhong Ji, Hua Tianjin Key Laboratory of Network and Data Security Technology China College of Computer Science Nankai University Tianjin China College of Cyber Science Nankai University Tianjin China Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission China Tianjin Normal University Tianjin China

ISBN: (纸本)9781665468190

Effective drug-target binding affinity (DTA) prediction is essential for drug discovery and development. The development of machine learning techniques considerably advances it. However, the cold-start problems in DTA prediction are still under-explored, which significantly degrades prediction performances on novel drugs and novel targets. In this paper, we propose a contrastive meta-learning (CML) framework to address these issues. We define drug-anchored tasks and target-anchored tasks, which enables the employment of meta-learning to accumulate common knowledge from various tasks so as to adapt to new tasks faster and better. Besides, we utilize a task inequality loss to measure task disparities and enhance model sensitivities to new tasks. We also propose a contrastive learning block (CLB) to explore correlations among drug-target pairs across tasks, which facilitates DTA prediction performance improvements. We compare CML with various baselines on two benchmarks and comparison results show that CML outperforms or achieves competitive results to its competitors. © 2022 IEEE.

关键词： Forecasting

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Junctional and somatic hypermutation-induced CX4C motif is critical for the recognition of a highly conserved epitope on HCV E2 by a human broadly neutralizing antibody

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Cellular & Molecular Immunology 2021年第3期18卷 675-685页

作者： Chunyan Yi Jing Xia Lan He Zhiyang Ling Xuesong Wang Yu Yan Jiangjun Wang Xinhao Zhao Weiguo Fan Xiaoyu Sun Ronghua Zhang Sheng Ye Rongguang Zhang Yongfen Xu Liyan Ma Yaguang Zhang Honglin Zhou Zhong Huang Junqi Niu Gang Long Junxia Lu Jin Zhong Bing Sun State Key Laboratory of Cell Biology CAS Center for Excellence in Molecular Cell ScienceShanghai Institute of Biochemistry and Cell BiologyChinese Academy of Sciences/University of Chinese Academy of SciencesShanghaiChina CAS Key Laboratory of Molecular Virology and Immunology Institut Pasteur of ShanghaiChinese Academy of Sciences/University of Chinese Academy of SciencesShanghaiChina School of Life Science and Technology ShanghaiTech UniversityShanghaiChina CAS Key Laboratory of Synthetic Chemistry of Natural Substances Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghaiChina College of Biology Hunan Provincial Key Laboratory of Medical VirologyHunan UniversityChangshaChina National Laboratory of Biophysics Institute of BiophysicsChinese Academy of Sciences/University of Chinese Academy of Sciences BdjingBeijingChina Interdisciplinary Innovation Institute of Medicine&Engineering Beijing Advanced Innovation Center for Big Data-Based Precision MedicineSchool of Biological Science and Medical EngineeringBeihang UniversityBeijingChina Nanjing Galaxy Biopharma Co. LtdNanjingChina Hepatology Section First HospitalUniversity of JilinChangchunChina

Induction of broadly neutralizing monoclonal antibodies(bNAbs)that bind to the viral envelope glycoproteins is a major goal of hepatitis C virus(HCV)vaccine *** study of bNAbs arising in natural infection is essential in this *** generated a human antibody,8D6,recognizing the E2 protein of HCV isolated from a chronic hepatitis C *** antibody shows broadly neutralizing activity,which covers a pan-genotypic panel of cell culture-derived HCV virions(HCVcc).Functional and epitope analyses demonstrated that 8D6 can block the interaction between E2 and CD81 by targeting a highly conserved epitope on *** describe how the 8D6 lineage evolved via somatic hypermutation to achieve broad *** found that the V(D)J recombination-generated junctional and somatic hypermutation-induced disulfide bridge(C-C)motif in the CDRH3 is critical for the broad neutralization and binding activity of *** motif is conserved among a series of broadly neutralizing HCV antibodies,indicating a common binding ***,the 8D6 inferred germline(iGL)was reconstructed and tested for its binding affinity and neutralization ***,8D6 iGL-mediated relatively strong inhibition of the 1b genotype PR79L9 strain,suggesting that PR79L9 may serve as a potential natural viral strain that provides E2 sequences that induce ***,our detailed epitope mapping and genetic studies of the HCV E2-specific mAb 8D6 have allowed for further refinement of antigenic sites on E2 and reveal a new mechanism to generate a functional CDRH3,while its iGL can serve as a probe to identify potential HCV vaccine strains.

关键词： Hepatitis C virus neutralizing antibody inferred germline CDRH3 disulfide bridge motif

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Rank internet service quality using multiple features: A machine learning approach

Rank internet service quality using multiple features: A mac...

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6th International Conference on Semantics, Knowledge and Grid, SKG 2010

作者： Tu, Dandan Shu, Chengchun Shi, Jingwei Zhu, Tao Wang, Shuang Yu, Haiyan Key Laboratory of Network Science and Technology ICT Institute of Computing Technology CAS P.O.Box 2704 100190 Beijing China NEC Labs China 11F Bldg Innovation Plaza Tsinghua Science Park Beijing 100084 China

ISBN: (纸本)9780769541891

This paper addresses the problem of Ranking Internet service quality by taking a machine learning approach using multiple service features. Ranking helps find good services for applications that use services as building blocks. Unlike other ranking problems, the goodness of Internet service qualities is dependent upon multiple key features. The key features vary across different service categories and have unequally discriminative natures. This paper divides the ranking problem into four subtasks including categorizing services according to the service functionalities, identifying key features that determine the quality, denoising for feature measurement values and computing global ranking scores with multiple key features, which are cast into machine learning problems and solved using techniques classification, feature selection, clustering, and regression respectively. In particular, we propose in this paper an efficient dense-block based denoising method for subjective features, and a Supported Vector Regression based method for computing global ranking scores. Experimental results on both synthetic and real data show that the proposed approach can quantitatively identify the key features across service categories, discard noisy measurement values in 10 times faster, and compute the global ranking scores using multiple features with low mean squared errors for both linear and nonlinear ranking functions. © 2010 IEEE.

关键词： Mean square error

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Initial years'neutron-induced cross-section measurements at the CSNS Back-n white neutron source

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Chinese Physics C 2021年第6期45卷 1-14页

作者： Jingyu Tang Rong Liu Guohui Zhang Xichao Ruan Xiaoguang Wu Qi An Jiangbo Bai Jie Bao Yu Bao Ping Cao Haolei Chen Qiping Chen Yonghao Chen Zhen Chen Zengqi Cui Ruirui Fan Changqing Feng Lin Gan Keqing Gao Xiaolong Gao Minhao Gu Changcai Han Zijie Han Guozhu He Yongcheng He Yang Hong Yiwei Hu Hanxiong Huang Xiru Huang Haoyu Jiang Wei Jiang Zhijie Jiang Hantao Jing Ling Kang Bo Li Chao Li Jiawen Li Qiang Li Xiao Li Yang Li Jie Liu Minliang Liu Shubin Liu Xingyan Liu Ze Long Guangyuan Luan Changjun Ning Mengchen Niu Binbin Qi Jie Ren Zhizhou Ren Zhaohui Song Kang Sun Zhijia Sun Zhixin Tan Xinyi Tang Binbin Tian Lijiao Wang Pengcheng Wang Zhaohui Wang Jie Wen Zhongwei Wen Xuan Wu Likun Xie Xiaoyun Yang Yiwei Yang Han Yi Li Yu Tao Yu Yongji Yu Linhao Zhang Qiwei Zhang Xianpeng Zhang Yuliang Zhang Zhiyong Zhang Luping Zhou Zhihao Zhou Kejun Zhu State Key Laboratory of Particle Detection and Electronics Institute of High Energy Physics Chinese Academy of Sciences(CAS)Beijing 100049China Spallation Neutron Source Science Center Dongguan 523803China University of Chinese Academy of Sciences Beijing 100049China Institute of Nuclear Physics and Chemistry China Academy of Engineering PhysicsMianyang 621900China State Key Laboratory of Nuclear Physics and Technology School of PhysicsPeking UniversityBeijing 100871China Key Laboratory of Nuclear Data China Institute of Atomic EnergyBeijing 102413China Department of Modern Physics University of Science and Technology of ChinaHefei 230026China College of Physics and Optoelectronic Engineering Shenzhen UniversityShenzhen 518060China Northwest Institute of Nuclear Technology Xi'an 710024China Institute of Modern Physics Chinese Academy of Sciences(CAS)Lanzhou 730000China

The Back-n white neutron source(known as Back-n)is based on back-streaming neutrons from the spallation target at the China Spallation Neutron Source(CSNS).With its excellent beam properties,e.g.,a neutron flux of approximately 1.8×107 n/cm2/s at 55 m from the spallation target,energy range spanning from 0.5 eV to 200 MeV,and time-of-flight resolution of a few per thousand,along with the equipped physical spectrometers,Back-n is considered to be among the best facilities in the world for carrying out nuclear data *** its completion and commencement of operation in May 2018,five types of cross-section measurements concerning neutron capture cross-sections,fission cross-sections,total cross-sections,light charged particle emissions,in-beam gamma spectra,and more than forty nuclides have been *** article presents an overview of the experimental setup and result analysis on the neutron-induced cross-section measurements and gamma spectroscopy at Back-n in the initial years.

关键词： white neutron beam experimental spectrometers nuclear data measurements nuclides data analysis

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10B-doped MCP detector developed for neutron resonance imaging at Back-n white neutron source

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Nuclear science and Techniques 2024年第8期35卷 58-68页

作者： Qiang Li Li‑Jiao Wang Jing‑Yu Tang Xiang‑Biao Qiu Zhen Chen Mao‑Yuan Zhao Chang‑Jun Ning Kai Pan Wei Xu Tao Li Su‑Peng Lu Han Yi Rui‑Rui Fan Chang‑Qing Feng Rong Zhang Xiao‑Yang Sun Qi An Hao‑Fan Bai Jiang‑Bo Bai Jie Bao Ping Cao Qi‑Ping Chen Yong‑Hao Chen Zeng‑Qi Cui An‑Chuan Fan Fan‑Zhen Feng Min‑Hao Gu Chang‑Cai Han Zi‑Jie Han Guo‑Zhu He Yong‑Cheng He Yang Hong Yi‑Wei Hu Han‑Xiong Huang Wei Jiang Zhi‑Jie Jiang Zheng‑Yao Jin Ling Kang Bo Li Gong Li Xiao Li Yang Li Jie Liu Rong Liu Shu‑Bin Liu Yi‑Na Liu Guang‑Yuan Luan Jie Ren Zhi‑Zhou Ren Xi‑Chao Ruan Zhao‑Hui Song Kang Sun Zhi‑Xin Tan Sheng‑Da Tang Jin‑Cheng Wang Peng‑Cheng Wang Zhao‑Hui Wang Zhong‑Wei Wen Xiao‑Guang Wu Xuan Wu Cong Xia Yong‑Ji Yu Guo‑Hui Zhang Hang‑Chang Zhang Lin‑Hao Zhang Qi‑Wei Zhang Xian‑Peng Zhang Yu‑Liang Zhang Yue Zhang Zhi‑Yong Zhang Zhi‑Hao Zhou Ke‑Jun Zhu Chong Zou Institute of High Energy Physics Chinese Academy of Sciences(CAS)Beijing 100049China Spallation Neutron Source Science Center Dongguan 523803China State Key Laboratory of Particle Detection and Electronics Institute of High Energy Physics Chinese Academy of SciencesBeijing 100049China Dongguan Songshan Lake Future School Dongguan 523808China School of Nuclear Science and Technology University of Science and Technology of ChinaHefei 230027China State Key Laboratory of Particle Detection and Electronics University of Science and Technology of ChinaHefei 230026China North Night Vision Science and Technology(Nanjing)Research Institute Co.Ltd Nanjing 211106China Department of Modern Physics University of Science and Technology of ChinaHefei 230026China State Key Laboratory of Nuclear Physics and Technology School of PhysicsPeking UniversityBeijing 100871China Institute of Modern Physics Fudan UniversityShanghai 200433China Key Laboratory of Nuclear Data China Institute of Atomic EnergyBeijing 102413China China Academy of Engineering Physics Institute of Nuclear Physics and ChemistryMianyang 621900China USTC archaeometry lab University of Science and Technology of ChinaHefei 230026China Northwest Institute of Nuclear Technology Xi’an 710024China University of Chinese Academy of Sciences Beijing 100049China China Shipbuilding Trading Co. LtdBeijing 100044China

Neutron resonance imaging(NRI)has recently emerged as an appealing technique for neutron *** complexity surpasses that of conventional transmission imaging,as it requires a high demand for both a neutron source and ***,the progression of NRI technology has been sluggish since its inception in the 1980s,particularly considering the limited studies analyzing the neutron energy range above *** white neutron source(Back-n)at the China Spallation Neutron Source(CSNS)provides favorable beam conditions for the development of the NRI technique over a wide neutron energy range from eV to ***-sensitive microchannel plates(MCP)have emerged as a cutting-edge tool in the field of neutron detection owing to their high temporal and spatial resolutions,high detection efficiency,and low *** this study,we report the development of a 10B-doped MCP detector,along with its associated electronics,data processing system,and NRI experiments at the *** heavy elements such as gold,silver,tungsten,and indium can be easily identified in the transmission images by their characteristic resonance peaks in the 1–100 eV energy range;the more difficult medium-weight elements such as iron,copper,and aluminum with resonance peaks in the 1–100 keV energy range can also be *** particular,results in the neutron energy range of dozens of keV(Aluminum)are reported here for the first time.

关键词： Neutron resonance imaging 10B doped MCP detector White neutron source Sample nuclide identification

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