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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Yuli Wang Li Tao Craig S. Levin Jianfeng Xu Electrical and computer Engineering University of California Santa Cruz Santa Cruz USA Department of Electrical Engineering Stanford University Stanford CA USA Departments of Radiology Physics Electrical Engineering and Bioengineering Stanford University Stanford CA USA State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong Univ. of Sci. and Tech. Wuhan China

ISBN: (数字)9781728141640

ISBN: (纸本)9781728141657

In this paper, a novel optical setup based on two-crossed-polarizers is introduced to achieve ionizing radiation detection, which is an easy-build-up setup with equivalent ionizing radiation detection ability as previous work [1], [2], [3]. The performance of our proposed setup with Lithium Niobate (LiNbO 3 ) and Cadmium Telluride (CdTe) detector crystals was evaluated. The 511keV photons induced modulation signal could be detected using two-crossed-polarizer based method with LiNbO 3 and CdTe as detector. Moreover, the strength of modulation signal is linear proportion with bias voltage before being saturated. Due to LiNbO 3 's high resistivity (which could reduce the dark current), its modulation signal strength keeps increased trend after 2000V, while that signal of CdTe tended to be saturated at voltage higher than 1200V since CdTe with lower resistivity. Therefore, to improve the detection sensitivity for 511keV, we could further increase the bias voltage for detector crystals (especially for detector with high resistivity).

关键词： II-VI semiconductor materials Cadmium compounds Lithium niobate Detectors Optical modulation Ultrafast optics

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Low-cost,μm-thick,tape-free electronic tattoo sensors with minimized motion and sweat artifacts

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npj Flexible Electronics 2018年第1期2卷 35-41页

作者： Youhua Wang Yitao Qiu Shideh Kabiri Ameri Hongwoo Jang Zhaohe Dai YongAn Huang Nanshu Lu Center for Mechanics of Solids Structures and MaterialsDepartment of Aerospace Engineering and Engineering MechanicsThe University of Texas at AustinAustinTX 78712USA State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhanChina Flexible Electronics Research Center Huazhong University of Science and TechnologyWuhanChina Deparment of Electrical and Computer Engineering The University of Texas at AustinAustinTXUSA Texas Materials Institute The University of Texas at AustinAustinTXUSA Department of Biomedical Engineering The University of Texas at AustinAustinTXUSA Present address:Department of Civil&Environmental Engineering Stanford UniversityStanfordCA 94305USA

Electronic tattoos(e-tattoos),also known as epidermal electronics,are ultra-thin and ultra-soft noninvasive but skin-conformable devices with capabilities including physiological sensing and transdermal stimulation and *** fabrication of e-tattoos out of conventional inorganic electronic materials used to be tedious and *** developed cut-and-paste method has significantly simplified the process and lowered the ***,existing cut-and-paste method entails a medical tape on which the electronic tattoo sensors should be pasted,which increases tattoo thickness and degrades its *** address this problem,here we report a slightly modified cut-and-paste method to fabricate low-cost,open-mesh e-tattoos with a total thickness of just 1.5μm.E-tattoos of such thinness can be directly pasted on human skin and conforms to natural skin *** demonstrate that this ultra-thin,tape-free e-tattoo can confidently measure electrocardiogram(ECG),skin temperature,and skin *** rate and even respiratory rate can be extracted from the ECG signals.A special advantage of such ultra-thin e-tattoo is that it is capable of high-fidelity sensing with minimized motion artifacts under various body *** of perspiration are found to be insignificant due to the breathability of such e-tattoos.

关键词： paste cost electronic

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Bayesian data assimilation for estimating epidemic evolution: A COVID-19 study

arXiv

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arXiv 2020年

作者： Yang, Xian Wang, Shuo Xing, Yuting Li, Ling Xu, Richard Yi Da Friston, Karl J. Guo, Yike Department of Computer Science Hong Kong Baptist University Hong Kong Special Administrative Region Hong Kong Data Science Institute Imperial College London United Kingdom Digital Medical Research Center School of Basic Medical Sciences Fudan University China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention China School of Computing University of Kent United Kingdom Faculty of Engineering and Information Technology University of Technology Sydney Australia Institute of Neurology University College London United Kingdom

The evolution of epidemiological parameters, such as instantaneous reproduction number Rt, is important for understanding the transmission dynamics of infectious diseases. Current estimates of time-varying epidemiological parameters often face problems such as lagging observations, averaging inference, and improper quantification of uncertainties. To address these problems, we propose a Bayesian data assimilation framework for time-varying parameter estimation. Specifically, this framework is applied to Rt estimation, resulting in the state-of-the-art 'DARt' system. With DARt, time misalignment caused by lagging observations is tackled by incorporating observation delays into the joint inference of infections and Rt;the drawback of averaging is overcome by instantaneously updating upon new observations and developing a model selection mechanism that captures abrupt changes;the uncertainty is quantified and reduced by employing Bayesian smoothing. We validate the performance of DARt and demonstrate its power in revealing the transmission dynamics of COVID-19. The proposed approach provides a promising solution for accurate and timely estimating transmission dynamics from reported data. Copyright © 2020, The Authors. All rights reserved.

关键词： Cell proliferation

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Data analytics for fog computing by distributed online learning with asynchronous update

arXiv

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arXiv 2019年

作者： Li, Guangxia Zhao, Peilin Lu, Xiao Liu, Jia Shen, Yulong Shaanxi Key Laboratory of Network and System Security Xidian University China State Key Laboratory of Integrated Service Networks Xidian University China School of Computer Science and Technology Xidian University China Tencent AI Lab Tencent Inc. China Department of Electrical and Computer Engineering University of Alberta Canada

—Fog computing extends the cloud computing paradigm by allocating substantial portions of computations and services towards the edge of a network, and is, therefore, particularly suitable for large-scale, geo-distributed, and data-intensive applications. As the popularity of fog applications increases, there is a demand for the development of smart data analytic tools, which can process massive data streams in an efficient manner. To satisfy such requirements, we propose a system in which data streams generated from distributed sources are digested almost locally, whereas a relatively small amount of distilled information is converged to a center. The center extracts knowledge from the collected information, and shares it across all subordinates to boost their performances. Upon the proposed system, we devise a distributed machine learning algorithm using the online learning approach, which is well known for its high efficiency and innate ability to cope with streaming data. An asynchronous update strategy with rigorous theoretical support is applied to enhance the system robustness. Experimental results demonstrate that the proposed method is comparable with a model trained over a centralized platform in terms of the classification accuracy, whereas the efficiency and scalability of the overall system are improved. Copyright © 2019, The Authors. All rights reserved.

关键词： Fog computing

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Accumulative time-based ranking method to reputation evaluation in information networks

arXiv

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arXiv 2019年

作者： Liao, Hao Liu, Qi-Xin Huang, Ze-Cheng Yeung, Chi Ho Zhang, Yi-Cheng National Engineering Laboratory on Big Data System Computing Technology Guangdong Province Engineering Center of China-made High Performance Data Computing System College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Institute of Big Data Intelligent Management and Decision Shenzhen University Shenzhen518060 China Department of Science and Environmental Studies The Education University of Hong Kong Hong Kong Hong Kong Department of Physics University of Fribourg Fribourg Switzerland

With the rapid development of modern technology, the Web has become an important platform for users to make friends and acquire information. However, since information on the Web is over-abundant, information filtering becomes a key task for online users to obtain relevant suggestions. As most Websites can be ranked according to users’ rating and preferences, relevance to queries, and recency, how to extract the most relevant item from the over-abundant information is always a key topic for researchers in various fields. In this paper, we adopt tools used to analyze complex networks to evaluate user reputation and item quality. In our proposed accumulative time-based ranking (ATR) algorithm, we incorporate two behavioral weighting factors which are updated when users select or rate items, to reflect the evolution of user reputation and item quality over time. We showed that our algorithm outperforms state-of-the-art ranking algorithms in terms of precision and robustness on empirical datasets from various online retailers and the citation datasets among research publications. Copyright © 2019, The Authors. All rights reserved.

关键词： Information filtering

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On Theoretical Optimization of the Sensing Matrix for Sparse-Dictionary Signal Recovery

On Theoretical Optimization of the Sensing Matrix for Sparse...

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IEEE Global Conference on Signal and Information Processing (GlobalSIP)

作者： Jianchen Zhu Shengjie Zhao Xu Ma Gonzalo R. Arce Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai CHN School of Optics and Photonics Beijing Institute of Technology Beijing CHN Department of Electrical and Computer Engineering University of Delaware Newark Delaware USA

Compressive Sensing (CS) is a new paradigm for the efficient acquisition of signals that have sparse representation in a certain domain. Traditionally, CS has provided numerous methods for signal recovery over an orthonormal basis. However, modern applications have sparked the emergence of related methods for signals not sparse in an orthonormal basis but in some arbitrary, perhaps highly overcomplete, dictionary, particularly due to their potential to generate different kinds of sparse representation of signals. Here, we first propose the Signal space Subspace Pursuit (SSSP) algorithm, and then we derive a low bound on the number of measurements required. The algorithm has low computational complexity and provides high recovery accuracy.

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DPHL:A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery

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Genomics, Proteomics & Bioinformatics 2020年第2期18卷 104-119页

作者： Tiansheng Zhu Yi Zhu Yue Xuan Huanhuan Gao Xue Cai Sander R.Piersma Thang V.Pham Tim Schelfhorst Richard R.G.D.Haas Irene V.Bijnsdorp Rui Sun Liang Yue Guan Ruan Qiushi Zhang Mo Hu Yue Zhou Winan J.Van Houdt Tessa Y.S.Le Large Jacqueline Cloos Anna Wojtuszkiewicz Danijela Koppers-Lalic Franziska Bottger Chantal Scheepbouwer Ruud H.Brakenhoff Geert J.L.H.van Leenders Jan N.M.Ijzermans John W.M.Martens Renske D.M.Steenbergen Nicole C.Grieken Sathiyamoorthy Selvarajan Sangeeta Mantoo Sze S.Lee Serene J.Y.Yeow Syed M.F.Alkaff Nan Xiang Yaoting Sun Xiao Yi Shaozheng Dai Wei Liu Tian Lu Zhicheng Wu Xiao Liang Man Wang Yingkuan Shao Xi Zheng Kailun Xu Qin Yang Yifan Meng Cong Lu Jiang Zhu Jin'e Zheng Bo Wang Sai Lou Yibei Dai Chao Xu Chenhuan Yu Huazhong Ying Tony K.Lim Jianmin Wu Xiaofei Gao Zhongzhi Luan Xiaodong Teng Peng Wu Shi'ang Huang Zhihua Tao Narayanan G.Iyer Shuigeng Zhou Wenguang Shao Henry Lam Ding Ma Jiafu Ji Oi L.Kon Shu Zheng Ruedi Aebersold Connie R.Jimenez Tiannan Guo Zhejiang Provincial Laboratory of Life Sciences and Biomedicine Westlake UniversityHangzhou 310024China Key Laboratory of Structural Biology of Zhejiang Province School of Life SciencesWestlake UniversityHangzhou 310024China Institute of Basic Medical Sciences Westlake Institute for Advanced StudyHangzhou 310024China School of Computer Science Shanghai Key Laboratory of Intelligent Information ProcessingFudan UniversityShanghai 200433China Thermo Fisher Scientific(BREMEN)GmbH Bremen 28195Germany OncoProteomics Laboratory Department of Medical OncologyVU University Medical CenterVU UniversityAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamUrologyCancer Center AmsterdamAmsterdam 1011The Netherlands Thermo Fisher Scientific Shanghai 201206China The Netherlands Cancer Institute Surgical OncologyAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamSurgeryCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamPediatric Oncology/HematologyCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamHematologyCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamMedical OncologyCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamNeurosurgeryCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamPathologyCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamOtolaryngology/Head and Neck SurgeryCancer Center AmsterdamAmsterdam 1011The Netherlands Erasmus MC University Medical Center PathologyRotterdam 1016LVThe Netherlands Erasmus MC University Medical Center SurgeryRotterdam 1016LVThe Netherlands Erasmus MC University Medical Center Medical OncologyRotterdam 1016LVThe Netherlands Department of Anatomical Pathology Singapore General HospitalSingapore 169608Singapore Division of Medical Scie

To address the increasing need for detecting and validating protein biomarkers in clinical specimens,mass spectrometry(MS)-based targeted proteomic techniques,including the selected reaction monitoring(SRM),parallel reaction monitoring(PRM),and massively parallel dataindependent acquisition(DIA),have been *** optimal performance,they require the fragment ion spectra of targeted peptides as prior *** this report,we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue *** build the spectral resource,we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on *** then applied the workflow to generate DPHL,a comprehensive DIA pan-human library,from 1096 data-dependent acquisition(DDA)MS raw files for 16 types of cancer *** extensive spectral resource was then applied to a proteomic study of 17 prostate cancer(PCa)***,PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was *** a second application,the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma(DLBCL)patients and 18 healthy control *** expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by *** data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker *** is freely accessible at https://***/page/***?id=IPX0001400000.

关键词： Data-independent acquisition Parallel reaction monitoring Spectral library Prostate cancer Diffuse large B cell lymphoma

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Direct detection optical transmission systems employing Stokes vector Kramers Kronig transceivers

Direct detection optical transmission systems employing Stok...

引用

Signal Processing in Photonic Communications, SPPCom 2018

作者： Hoang, Thang Zhuge, Q. Xing, Z. Sowailem, M. Morsy-Osman, M. Xiang, M. El-Fiky, E. Fan, S. Plant, D.V. Electrical and Computer Engineering Department McGill University 3480 University Street MontrealQCH3A 0E9 Canada State Key Laboratory of Advanced Optical Communication System and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China Eletrical Engineering Department Alexandria University 21544 Egypt

We use a Stokes vector receiver to demonstrate polarization multiplexing Kramers Kronig detection signals. The impact of several parameters is discussed. 480-Gb/s capacity is achieved for 80 km of standard single mode... 详细信息

ISBN: (纸本)9781943580439

关键词： Light transmission

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CEPC Technical Design Report

引用

Radiation Detection Technology and Methods 2024年第1期8卷 I0003-I0016,1-1091页

作者： Waleed Abdallah Tiago Carlos Adorno de Freitas Konstantin Afanaciev Shakeel Ahmad Ijaz Ahmed Xiaocong Ai Abid Aleem Wolfgang Altmannshofer Fabio Alves Weiming An Rui An Daniele Paolo Anderle Stefan Antusch Yasuo Arai Andrej Arbuzov Abdesslam Arhrib Mustafa Ashry Sha Bai Yu Bai Yang Bai Vipul Bairathi Csaba Balazs Philip Bambade Yong Ban Tripamo Bandyopadhyay Shou-Shan Bao Desmond P.Barber Ayse Bat Varvara Batozskaya Subash Chandra Behera Alexander Belyaev Michele Bertucci Xiao-Jun Bi Yuanjie Bi Tianjian Bian Fabrizio Bianchi Thomas Biekotter Michela Biglietti Shalva Bilanishvili Deng Binglin Denis Bodrov Anton Bogomyagkov Serge Bondarenko Stewart Boogert Maarten Boonekamp Marcello Borri Angelo Bosotti Vincent Boudry Mohammed Boukidi Igor Boyko Ivanka Bozovic Giuseppe Bozzi Jean-Claude Brient Anastasiia Budzinskaya Masroor Bukhari Vladimir Bytev Giacomo Cacciapaglia Hua Cai Wenyong Cai Wujun Cai Yijian Cai Yizhou Cai Yuchen Cai Haiying Cai Huacheng Cai Lorenzo Calibbi Junsong Cang Guofu Cao Jianshe Cao Antoine Chance Xuejun Chang Yue Chang Zhe Chang Xinyuan Chang Wei Chao Auttakit Chatrabhuti Yimin Che Yuzhi Che Bin Chen Danping Chen Fuqing Chen Fusan Chen Gang Chen Guoming Chen Hua-Xing Chen Huirun Chen Jinhui Chen Ji-Yuan Chen Kai Chen Mali Chen Mingjun Chen Mingshui Chen Ning Chen Shanhong Chen Shanzhen Chen Shao-Long Chen Shaomin Chen Shiqiang Chen Tianlu Chen Wei Chen Xiang Chen Xiaoyu Chen Xin Chen Xun Chen Xurong Chen Ye Chen Ying Chen Yukai Chen Zelin Chen Zilin Chen Gang Chen Boping Chen Chunhui Chen Hok Chuen Cheng Huajie Cheng Shan Cheng Tongguang Cheng Yunlong Chi Pietro Chimenti Wen Han Chiu Guk Cho Ming-Chung Chu Xiaotong Chu Ziliang Chu Guglielmo Coloretti Andreas Crivellin Hanhua Cui Xiaohao Cui Zhaoyuan Cui Brunella D'Anzi Ling-Yun Dai Xinchen Dai Xuwen Dai Antonio De Maria Nicola De Filippis Christophe De La Taille Francesca De Mori Chiara De Sio Elisa Del Core Shuangxue Deng Wei-Tian Deng Zhi Deng Ziyan Deng Bhupal Dev Tang Dewen Biagio Di Micco Ran Ding Siqin Dingl Yadong Ding Haiyi Dong Jianin AGH University of Science and Technology Faculty of Physics and Applied Computer ScienceKrakow Anhui University HefeiAnhui Applied Physics Department Federal Urdu University of ArtsScience and TechnologyIslamabad Banaras Hindu University Institute of ScienceVaranasi Bandirma Onyedi Eylul University Bandirma Beihang University Beijing Beijing Computational Science Research Center Beijing Beijing Conveyi LTD Beijing Beijing Glass Research Institute Co. LtdBeijing Beijing Institute of Technology Beijing Beijing Normal University Beijing Brown University ProvidenceRI Budker Institute of Nuclear Physics Novosibirsk Cadi Ayyad University Laboratory of Fundamental and Applied PhysicsPolydisciplinary FacultyMarrakech Cairo University Giza Center for Theory and Computation National Tsing Hua UniversityHsinchu Central China Normal University WuhanHubei Central South University ChangshaHunan Centro de Fisica Teorica de Particulas Universidade Tecnica de LisboaLisboa Chengdu KaitengSifang Digital Radio&TV Equipment Co. LtdChengduSichuan China academy of engineering physics MianyangSichuan China building materials academy Beijing China Center of Advanced Science and Technology Beijing China Institute of Atomic Energy Beijing China Jiliang University HangzhouZhejiang China Nuclear Instrument CO. LTDBeijing China University of Geosciences Beijing China University of Geosciences WuhanHubei China University of Mining and Technology XuzhouJiangsu China West Normal University NanchongSichuan Chongqing University Department of PhysicsChongqing Chulalongkorn University Bangkok City University of Hong Kong Department of PhysicsHong Kong Cockcroft Institute Daresbury Cornell University IthacaNY CPPM(AMU/IPhU&CNRS/INP) Marseille Dalian Minzu University DalianLiaoning Dalian University of Technology Department of PhysicsDalian Deutsches Elektronen-Synchrotron DESY Hamburg Dzhelepov Laboratory of Nuclear Problems of Joint Institute for Nuclear Research(DLNP JINR) Dubna East China University Of Science And Technol

The Circular Electron Positron Collider(CEPC)is a large scientific project initiated and hosted by China,fostered through extensive collaboration with international *** complex comprises four accelerators:a 30 GeV Linac,a 1.1 GeV Damping Ring,a Booster capable of achieving energies up to 180 GeV,and a Collider operating at varying energy modes(Z,W,H,and tt).The Linac and Damping Ring are situated on the surface,while the subterranean Booster and Collider are housed in a 100 km circumference underground tunnel,strategically accommodating future expansion with provisions for a potential Super Proton Proton Collider(SPPC).The CEPC primarily serves as a Higgs *** its baseline design with synchrotron radiation(SR)power of 30 MW per beam,it can achieve a luminosity of 5×10^(34)cm^(-2)s^(-1)per interaction point(IP),resulting in an integrated luminosity of 13 ab^(-1)for two IPs over a decade,producing 2.6 million Higgs *** the SR power to 50 MW per beam expands the CEPC's capability to generate 4.3 million Higgs bosons,facilitating precise measurements of Higgs coupling at sub-percent levels,exceeding the precision expected from the HL-LHC by an order of *** Technical Design Report(TDR)follows the Preliminary Conceptual Design Report(Pre-CDR,2015)and the Conceptual Design Report(CDR,2018),comprehensively detailing the machine's layout,performance metrics,physical design and analysis,technical systems design,R&D and prototyping efforts,and associated civil engineering ***,it includes a cost estimate and a preliminary construction timeline,establishing a framework for forthcoming engineering design phase and site selection *** is anticipated to begin around 2027-2028,pending government approval,with an estimated duration of 8 *** commencement of experiments and data collection could potentially be initiated in the mid-2030s.

关键词： initiated exceeding precise

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A Two-Stage Algorithm to Harvest Maximum Power from Photovoltaic system 2

A Two-Stage Algorithm to Harvest Maximum Power from Photovol...

引用

2nd IEEE Conference on Energy Internet and Energy system Integration, EI2 2018

作者： Hanan, Muhammad Ai, Xin Javed, Muhammad Yaqoob Majid Gulzar, Muhammad Ahmad, Saqib State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing China Department of Electrical and Computer Engineering COMSATS University Islamabad Lahore Punjab Pakistan Department of Electrical Engineering University of Central Punjab Lahore Punjab Pakistan

ISBN: (纸本)9781538685495

Photovoltaic (PV) systems are gradually becoming the key renewable source of electrical energy. But the nonlinear characteristics of the PV module require special techniques to harvest maximum power. The techniques used to track the Maximum Power Point (MPP) from the nonlinear I-V characteristics through power electronic circuits are known as Maximum Power Point Tracking (MPPT) techniques. Although enormous MPPT techniques have been anticipated in literature, each endures its own advantages and disadvantages. This paper proposes a novel hybrid technique to enhance the performance of Incremental conductance (InC) technique. Our proposed technique removes the limitations of InC under rapid changing environmental condition. It improves the efficiency and reduces the oscillation power loss under steady state. A hybrid combination of variable-step sized Incremental Conductance with Fractional Short Circuit Current (FSCC) technique is proposed in this research work. Initially, the FSCC forces the PV system to work near MPP and then InC technique track the exact peak. Matlab/Simulink software is used to implement the proposed hybrid technique. Finally, the results verify its superior performance under rapidly changing environmental conditions. © 2018 IEEE.

关键词： Timing circuits

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