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Science China(Physics,Mechanics & Astronomy) 2019年第2期62卷 28-44页

作者： Anna L.Watts WenFei Yu Juri Poutanen Shu Zhang Sudip Bhattacharyya Slavko Bogdanov Long Ji Alessandro Patruno Thomas E.Riley Pavel Bakala Altan Baykal Federico Bernardini Ignazio Bombaci Edward Brown Yuri Cavecchi Deepto Chakrabarty Jér?me Chenevez Nathalie Degenaar Melania Del Santo Tiziana Di Salvo Victor Doroshenko Maurizio Falanga Robert D.Ferdman Marco Feroci Angelo F.Gambino MingYu Ge Svenja K.Greif Sebastien Guillot Can Gungor Dieter H.Hartmann Kai Hebeler Alexander Heger Jeroen Homan Rosario Iaria Jean in 't Zand Oleg Kargaltsev Aleksi KurkelaTheoretical Physics Department CERN XiaoYu Lai Ang Li XiangDong Li ZhaoSheng Li Manuel Linares FangJun Lu Simin Mahmoodifar Mariano Méndez M.Coleman Miller Sharon Morsink Joonas N?ttil? Andrea Possenti Chanda Prescod-Weinstein JinLu Qu Alessandro Riggio Tuomo Salmi Andrea Sanna Andrea Santangelo Hendrik Schatz Achim Schwenk LiMing Song Eva?rámková Benjamin Stappers Holger Stiele Tod Strohmayer Ingo Tews Laura Tolos Gabriel T?r?k David Tsang Martin Urbanec Andrea Vacchi RenXin Xu YuPeng Xu Silvia Zane GuoBao Zhang ShuangNan Zhang WenDa Zhang ShiJie Zheng Xia Zhou Anton Pannekoek Institute for Astronomy University of Amsterdam Shanghai Astronomical Observatory Tuorla Observatory Department of Physics and Astronomy University of Turku Nordita KTH Royal Institute of Technology and Stockholm University Institute of High Energy Physics Chinese Academy Sciences Tata Institute of Fundamental Research Columbia Astrophysics Laboratory Columbia University Institut für Astronomie und Astrophysik Tübingen Universit?t Tübingen Leiden Observatory Leiden University Research Center for Computational Physics and Data Processing Silesian University in Opava Physics Department Middle East Technical University INAF Osservatorio Astronomico di Roma New York University Abu Dhabi Dipartimento di Fisica Enrico Fermi University of Pisa INFN Italian National Institute for Nuclear Physics Department of Physics and Astronomy Michigan State University Department of Astrophysical Sciences Princeton University Mathematical Sciences and STAG Research Centre University of Southampton MIT Kavli Institute for Astrophysics and Space Research DTU Space Technical University of Denmark INAF/IASF Palermo via Ugo La Malfa 153 Universita degli Studi di Palermo Dipartimento di Fisica e Chimica International Space Science Institute (ISSI) Faculty of Science University of East Anglia INAF Istituto di Astrofisica e Planetologie Spaziali Institut für Kernphysik Technische Universit?t Darmstadt ExtreMe Matter Institute EMMI GSI Helmholtzzentrum für Schwerionenforschung GmbH Instituto de Astrof'?sica Pontificia Universidad Católica de Chile Department of Physics & Astronomy Kinard Lab of Physics Clemson University School of Physics and Astronomy Monash University SRON Netherlands Institute for Space Research Department of Physics The George Washington University Faculty of Science and Technology University of Stavanger School of Physics and Mechanical & Electrical Engineering Hubei University of Education Department of Astronomy Xiamen University (Haiyun Campus) School of Astronomy and Space

In this White Paper we present the potential of the Enhanced X-ray Timing and Polarimetry(eXTP) mission for determining the nature of dense matter; neutron star cores host an extreme density regime which cannot be replicated in a terrestrial laboratory. The tightest statistical constraints on the dense matter equation of state will come from pulse profile modelling of accretion-powered pulsars, burst oscillation sources, and rotation-powered pulsars. Additional constraints will derive from spin measurements, burst spectra, and properties of the accretion flows in the vicinity of the neutron star. Under development by an international Consortium led by the Institute of High Energy Physics of the Chinese Academy of Sciences, the eXTP mission is expected to be launched in the mid 2020 s.

关键词： neutron X-rays dense matter equation of state

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On the Orbits of Crossed Cubes

arXiv

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arXiv 2017年

作者： Shiau, Tzong-Huei Wang, Yue-Li Pai, Kung-Jui Computer & Communications Associates Incorporation Hinchu Taiwan Department of Industrial Engineering and Management Ming Chi University of Technology New Taipei City Taiwan Department of Information Management National Taiwan University of Science and Technology 43 Section 4 Kee-Lung Road Taipei10607 Taiwan

An orbit of G is a subset S of V (G) such that φ(u) = v for any two vertices u, v ∈ S, where φ is an isomorphism of G. The orbit number of a graph G, denoted by Orb(G), is the number of orbits of G. In [A Note on Path Embedding in Crossed Cubes with Faulty Vertices, Information Processing Letters 121 (2017) pp. 34–38], Chen et al. conjectured that Orb(CQn) = 2dn2 e−2 for n > 3, where CQn denotes an n-dimensional crossed cube. In this paper, we settle the *** Codes 68R10 Copyright © 2017, The Authors. All rights reserved.

关键词： Geometry

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Demo Abstract: Observability-driven sensor deployment in smart academic environments 14

Demo Abstract: Observability-driven sensor deployment in sma...

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14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016

作者： Agarwal, A. Jaiswal, K. Gudhaka, U. Munigala, V. Ramamritham, Krithi Karmakar, Gopinath Department of Computer Science Engineering Indian Institute of Technology Bombay United States Reactor Control System Design Section Bhabha Atomic Research Centre India

ISBN: (纸本)9781450342636

Saving energy without causing discomfort and without de-manding human intervention is the need of the day. It is important to develop sensor systems which not only satisfy user requirements, but also take energy consumption into consideration. In this demo, we present the sensing subsys-tems of a Smart Academic Environment, based upon the core concept of Observability' [1] which-while satisfying user needs-helps to reduce the number of sensors required. © 2016 Copyright held by the owner/author(s).

关键词： Observability

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Noise subtraction from KAGRA O3GK data using Independent Component Analysis

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Classical and Quantum Gravity 2023年第8期40卷 085015-085015页

作者： H Abe T Akutsu M Ando A Araya N Aritomi H Asada Y Aso S Bae Y Bae R Bajpai K Cannon Z Cao E Capocasa M Chan C Chen D Chen K Chen Y Chen C-Y Chiang Y-K Chu S Eguchi M Eisenmann Y Enomoto R Flaminio H K Fong Y Fujii Y Fujikawa Y Fujimoto I Fukunaga D Gao G-G Ge S Ha I P W Hadiputrawan S Haino W-B Han K Hasegawa K Hattori H Hayakawa K Hayama Y Himemoto N Hirata C Hirose T-C Ho B-H Hsieh H-F Hsieh C Hsiung H-Y Huang P Huang Y-C Huang Y-J Huang D C Y Hui S Ide K Inayoshi Y Inoue K Ito Y Itoh C Jeon H-B Jin K Jung P Jung K Kaihotsu T Kajita M Kakizaki M Kamiizumi N Kanda T Kato K Kawaguchi C Kim J Kim J C Kim Y-M Kim N Kimura T Kiyota Y Kobayashi K Kohri K Kokeyama A K H Kong N Koyama C Kozakai J Kume Y Kuromiya S Kuroyanagi K Kwak E Lee H W Lee R Lee M Leonardi K L Li P Li L C -C Lin C-Y Lin E T Lin F-K Lin F-L Lin H L Lin G C Liu L-W Luo M Ma’arif E Majorana Y Michimura N Mio O Miyakawa K Miyo S Miyoki Y Mori S Morisaki N Morisue Y Moriwaki K Nagano K Nakamura H Nakano M Nakano Y Nakayama T Narikawa L Naticchioni L Nguyen Quynh W-T Ni T Nishimoto A Nishizawa S Nozaki Y Obayashi W Ogaki J J Oh K Oh M Ohashi T Ohashi M Ohkawa H Ohta Y Okutani K Oohara S Oshino S Otabe K-C Pan A Parisi J Park F E Pe na Arellano S Saha Y Saito K Sakai T Sawada Y Sekiguchi L Shao Y Shikano H Shimizu K Shimode H Shinkai T Shishido A Shoda K Somiya I Song R Sugimoto J Suresh T Suzuki H Tagoshi H Takahashi R Takahashi S Takano H Takeda M Takeda K Tanaka T Tanaka S Tanioka A Taruya T Tomaru T Tomura L Trozzo T Tsang J-S Tsao S Tsuchida T Tsutsui D Tuyenbayev N Uchikata T Uchiyama A Ueda T Uehara K Ueno G Ueshima T Ushiba M H P M van Putten J Wang T Washimi C Wu H Wu T Yamada K Yamamoto T Yamamoto K Yamashita R Yamazaki Y Yang S Yeh J Yokoyama T Yokozawa T Yoshioka H Yuzurihara S Zeidler M Zhan H Zhang Y Zhao Z-H Zhu The KAGRA Collaboration Graduate School of Science Tokyo Institute of Technology Meguro-ku Tokyo 152-8551 Japan Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe (RESCEU) The University of Tokyo Bunkyo-ku Tokyo 113-0033 Japan Earthquake Research Institute The University of Tokyo Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Gravitational Wave Science Project Hirosaki University Hirosaki City Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan (NAOJ) Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information (KISTI) Yuseong-gu Daejeon 34141 Republic of Korea National Institute for Mathematical Sciences Yuseong-gu Daejeon 34047 Republic of Korea School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University Beijing 100875 People’s Republic of China Department of Applied Physics Fukuoka University Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University Danshui Dist. New Taipei City 25137 Taiwan Department of Physics and Institute of Astronomy National Tsing Hua University Hsinchu 30013 Taiwan Department of Physics Center for High Energy and High Field Physics National Central University Zhongli District Taoyuan City 32001 Taiwan Department of Physics National Tsing Hua University Hsinchu 30013 Taiwan Institute of Physics Academia Sinica Nankang Taipei 11529 Taiwan Univ. Grenoble Alpes Laboratoire d’Annecy de Physique des Particules (LAPP) Université Savoie M

During April 7–21 2020, KAGRA conducted its first scientific observation in conjunction with the GEO600 detector. The dominant noise sources during this run were found to be suspension control noise in the low-frequency range and acoustic noise in the mid-frequency range. In this study, we show that their contributions in the observational data can be reduced by a signal processing method called independent component analysis (ICA). The model of ICA is extended from that studied in the initial KAGRA data analysis to account for frequency dependence, while the linearity and stationarity of the coupling between the interferometer and the noise sources are still assumed. We identify optimal witness sensors in the application of ICA, leading to successful mitigation of these two dominant contributions. We also analyze the stability of the transfer functions for the entire two weeks of data to investigate the applicability of the proposed subtraction method in gravitational wave searches.

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Small P values may not yield robust findings:an example using REST-meta-PD

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Science Bulletin 2021年第21期66卷 2148-2152,M0003页

作者： Xi-Ze Jia Na Zhao Hao-Ming Dong Jia-Wei Sun Marek Barton Roxana Burciu Nicolas Carrière Antonio Cerasa Bo-Yu Chen Jun Chen Stephen Coombes Luc Defebvre Christine Delmaire Kathy Dujardin Fabrizio Esposito Guo-Guang Fan Federica Di Nardo Yi-Xuan Feng Brett W.Fling Saurabh Garg Moran Gilat Martin Gorges Shu-Leong Ho Fay BHorak Xiao Hu Xiao-Fei Hu Biao Huang Pei-Yu Huang Ze-Juan Jia Christina Jones Jan Kassubek Lenka Krajcovicova Ajay Kurani Jing Li Qing Li Ai-Ping Liu Bo Liu Hu Liu Wei-Guo Liu Renaud Lopes Yu-Ting Lou Wei Luo Tara Madhyastha Ni-Ni Mao Grainne McAlonan Martin J.McKeown Shirley Pang Andrea Quattrone Irena Rektorova Alessia Sarica Hui-Fang Shang James M.Shine Priyank Shukla Tomas Slavicek Xiao-Peng Song Gioacchino Tedeschi Alessandro Tessitore David Vaillancourt Jian Wang Jue Wang Z.Jane Wang Lu-Qing Wei Xia Wu Xiao-Jun Xu Lei Yan Jing Yang Wan-Qun Yang Nai-Lin Yao De-Long Zhang Jiu-Quan Zhang Min-Ming Zhang Yan-Ling Zhang Cai-Hong Zhou Chao-Gan Yan Xi-Nian Zuo Mark Hallett Tao Wu Yu-Feng Zang Center for Cognition and Brain Disorders the Affiliated HospitalHangzhou Normal UniversityHangzhou 310015China Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments Hangzhou 311121China National Basic Science Data Center Beijing 100190China State Key Laboratory of Cognitive Neuroscience and Learning&McGovern Institute for Brain Research Beijing Normal UniversityBeijing 100875China School of Information and Electronics Technology Jiamusi UniversityJiamusi 154007China Neuroscience Program Central European Institute of TechnologyCEITECMasaryk UniversityBrno 62500Czech Republic Department of Applied Physiology and Kinesiology University of FloridaGainesville FL 32611USA Univ.Lille InsermCHU LilleU1172-LilNCog-Lille Neuroscience&CognitionLille F-59000France The Institute for Biomedical Research and Innovation National Research CouncilMangone CS 87050Italy Department of Radiology The First Affiliated Hospital of China Medical UniversityShenyang 110001China Department of Radiology Guangdong Provincial Hospital of Chinese MedicineGuangzhou 510120China Department of Medicine Surgery and DentistryScuola Medica SalernitanaUniversity of SalernoFiscianoSA 132-84084Italy Department of Advanced Medical and Surgery Sciences University of Campania“Luigi Vanvitelli”Caserta 81100Italy Eye Center of the 2nd Affiliated Hospital Medical College of Zhejiang UniversityHangzhou 310020China Zhejiang Provincial Key Lab of Ophthalmology Hangzhou 310020China Department of Health and Exercise Science Colorado State UniversityFort Collins CO 80523USA Pacific Parkinson’s Research Centre University of British ColumbiaVancouver BC V6E 2M6Canada Department of Medicine(Neurology)University of British Columbia Vancouver BC V6T 1B7Canada Brain and Mind Center The University of SydneySydney NSW 2006Australia Department of Neurology Ulm UniversityUlm 89081Germany Division of Neurology Department of MedicineQueen Mary HospitalUniversity of Hong KongHong Kong 999077China Department of

Thousands of resting state functional magnetic resonance imaging(RS-f MRI)articles have been published on brain *** precise localization of abnormal brain activity,a voxel-level comparison is *** of the large number of voxels in the brain,multiple comparison correction(MCC)must be performed to reduce false positive rates,and a smaller P value(usually including either liberal or stringent MCC)is widely recommended[1].

关键词：帕金森病 precise correction

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Hearing loss prevalence and years lived with disability, 1990-2019: Findings from the Global Burden of Disease Study 2019

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The Lancet 2021年第10278期397卷 996-1009页

作者： Haile, Lydia M. Kamenov, Kaloyan Briant, Paul Svitil Orji, Aislyn U. Steinmetz, Jaimie D. Abdoli, Amir Abdollahi, Mohammad Abu-Gharbieh, Eman Afshin, Ashkan Ahmed, Haroon Rashid, Tarik Ahmed Akalu, Yonas Alahdab, Fares Alanezi, Fahad Mashhour Alanzi, Turki M. Al Hamad, Hanadi Ali, Liaqat Alipour, Vahid Al-Raddadi, Rajaa M. Amu, Hubert Arabloo, Jalal Arab-Zozani, Morteza Arulappan, Judie Ashbaugh, Charlie Atnafu, Desta Debalkie Babar, Zaheer-Ud-Din Baig, Atif Amin Banik, Palash Chandra Bärnighausen, Till Winfried Barrow, Amadou Bender, Rose G. Bhagavathula, Akshaya Srikanth Bhardwaj, Nikha Bhardwaj, Pankaj Bibi, Sadia Bijani, Ali Burkart, Katrin Cederroth, Christopher R. Charan, Jaykaran Choudhari, Sonali Gajanan Chu, Dinh-Toi Couto, Rosa A.S. Dagnew, Amare Belachew Dagnew, Baye Dahlawi, Saad M.A. Dai, Xiaochen Dandona, Lalit Dandona, Rakhi Desalew, Assefa Dhamnetiya, Deepak Dhimal, Mandira Lamichhane Dhimal, Meghnath Doyle, Kerrie E. Duncan, Bruce B. Ekholuenetale, Michael Filip, Irina Fischer, Florian Franklin, Richard Charles Gaidhane, Abhay Motiramji Gaidhane, Shilpa Gallus, Silvano Ghamari, Farhad Ghashghaee, Ahmad Ghozali, Ghozali Gilani, Syed Amir Glǎvan, Ionela-Roxana Golechha, Mahaveer Goulart, Barbara Niegia Garcia Gupta, Veer Bala Gupta, Vivek Kumar Hamidi, Samer Hammond, Billy Randall Hay, Simon I. Hayat, Khezar Heidari, Golnaz Hoffman, Howard J. Hopf, Kathleen Pillsbury Hosseinzadeh, Mehdi Househ, Mowafa Hussain, Rabia Hwang, Bing-Fang Iavicoli, Ivo Ibitoye, Segun Emmanuel Ilesanmi, Olayinka Stephen Irvani, Seyed Sina Naghibi Islam, Sheikh Mohammed Shariful Iwagami, Masao Jacob, Louis Jayapal, Sathish Kumar Jha, Ravi Prakash Jonas, Jost B. Kalhor, Rohollah Al-Salihi, Nawzad Kameran Kandel, Himal Kasa, Ayele Semachew Kayode, Gbenga A. Khalilov, Rovshan Khan, Ejaz Ahmad Khatib, Mahalaqua Nazli Kosen, Soewarta Koyanagi, Ai Kumar, G. Anil Landires, Ivan Lasrado, Savita Lim, Stephen S. Liu, Xuefeng Lobo, Stany W. Lugo, Alessandra Makki, Alaa Mendoza, Walter Mersha, Amanual Getnet Mihretie, Kebadnew Mulatu Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Noncommunicable Diseases World Health Organization (WHO) Geneva Switzerland Department of Parasitology and Mycology Jahrom University of Medical Sciences Jahrom Iran The Institute of Pharmaceutical Sciences (TIPS) Tehran University of Medical Sciences Tehran Iran School of Pharmacy Tehran University of Medical Sciences Tehran Iran Clinical Sciences Department University of Sharjah Sharjah United Arab Emirates Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Department of Biosciences COMSATS Institute of Information Technology Islamabad Pakistan Department of Computer Science and Engineering University of Kurdistan Hewler Erbil Iraq Department of Medical Physiology University of Gondar Gondar Ethiopia Mayo Evidence-based Practice Center Mayo Clinic Foundation for Medical Education and Research Rochester MN United States Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia Health Information Management and Technology Department Dammam Saudi Arabia Geriatric and Long Term Care Department Hamad Medical Corporation Doha Qatar Rumailah Hospital Hamad Medical Corporation Doha Qatar Department of Biological Sciences National University of Medical Sciences (NUMS) Rawalpindi Pakistan Health Management and Economics Research Center Tehran Iran Department of Community Medicine King Abdulaziz University Jeddah Saudi Arabia Department of Population and Behavioural Sciences University of Health and Allied Sciences Ho Ghana Social Determinants of Health Research Center Birjand University of Medical Sciences Birjand Iran Department of Maternal and Child Health Sultan Qaboos University Muscat Oman Department of Health System and Health Economics Bahir Dar University Bahir Dar Ethiopia Department of Pharmacy University of Huddersfield Huddersfield United Kingdom Unit of Biochemistry Universiti

Background: Hearing loss affects access to spoken language, which can affect cognition and development, and can negatively affect social wellbeing. We present updated estimates from the Global Burden of Disease (GBD) study on the prevalence of hearing loss in 2019, as well as the condition's associated disability. Methods: We did systematic reviews of population-representative surveys on hearing loss prevalence from 1990 to 2019. We fitted nested meta-regression models for severity-specific prevalence, accounting for hearing aid coverage, cause, and the presence of tinnitus. We also forecasted the prevalence of hearing loss until 2050. Findings: An estimated 1·57 billion (95% uncertainty interval 1·51–1·64) people globally had hearing loss in 2019, accounting for one in five people (20·3% [19·5–21·1]). Of these, 403·3 million (357·3–449·5) people had hearing loss that was moderate or higher in severity after adjusting for hearing aid use, and 430·4 million (381·7–479·6) without adjustment. The largest number of people with moderate-to-complete hearing loss resided in the Western Pacific region (127·1 million people [112·3–142·6]). Of all people with a hearing impairment, 62·1% (60·2–63·9) were older than 50 years. The Healthcare Access and Quality (HAQ) Index explained 65·8% of the variation in national age-standardised rates of years lived with disability, because countries with a low HAQ Index had higher rates of years lived with disability. By 2050, a projected 2·45 billion (2·35–2·56) people will have hearing loss, a 56·1% (47·3–65·2) increase from 2019, despite stable age-standardised prevalence. Interpretation: As populations age, the number of people with hearing loss will increase. Interventions such as childhood screening, hearing aids, effective management of otitis media and meningitis, and cochlear implants have the potential to ameliorate this burden. Because the burden of moderate-to-complete hearing loss is concentrated in countries with low health-ca

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Obstacle-avoiding wind turbine placement for power loss and wake effect optimization

Obstacle-avoiding wind turbine placement for power loss and ...

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作者： Wu, Yu-Wei Shi, Yiyu Roy, Sudip Ho, Tsung-Yi Department of Computer Science and Information Engineering National Cheng Kung University No. 1 University Road Tainan City701 Taiwan Departments of Computer Science and Engineering and Electrical Engineering University of Notre Dame Notre DameIN46556 United States Department of Computer Science and Engineering Indian Institute of Technology Roorkee RoorkeeUttarakhand247667 India Department of Computer Science National Tsing Hua University No. 101 Section 2 Kuang-Fu Road Hsinchu Taiwan

As finite energy resources are being consumed at faster rate than they can be replaced, renewable energy resources have drawn extensive attention. Wind power development is one such example growing significantly throughout the world. The main difficulty in wind power development is that wind turbines interfere with each other. The produced turbulence - wake effect - directly reduces the power generation. In addition, wirelength of the collection network among wind turbines is not merely an economic factor;it also decides power loss on the wind farm. Moreover, in reality, obstacles (buildings, lakes, etc.) exist on the wind farm, which are unavoidable. Nevertheless, to the best of our knowledge, none of the existing works consider wake effect, wirelength, and avoidance of obstacles all together in the wind turbine placement problem. In this article, we propose an analytical method to obtain the obstacle-avoiding placement of wind turbines, thus minimizing both power loss and wake effect. We also propose a postprocessing method to fine-tune the solution obtained from the analytical method to find a better solution. Simulation results show that our tool is 12x faster than the state-of-the-art industrial tool AWS OpenWind and 203x faster than the state-of-the-art academic tool TDA with almost the same produced power. © 2016 ACM.

关键词： Wind turbines

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Hypoglycemia Detection and Carbohydrate Suggestion in an Artificial Pancreas

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Journal of Diabetes Science and technology 2016年第6期10卷 1236-1244页

作者： Turksoy, Kamuran Kilkus, Jennifer Hajizadeh, Iman Samadi, Sediqeh Feng, Jianyuan Sevil, Mert Lazaro, Caterina Frantz, Nicole Littlejohn, Elizabeth Cinar, Ali Department of Biomedical Engineering Illinois Institute of Technology Chicago IL United States Department of Pediatrics and Medicine Section of Endocrinology Kovler Diabetes Center University of Chicago Chicago IL United States Department of Chemical and Biological Engineering Illinois Institute of Technology 10 W 33rd St Chicago 60616 IL United States Department of Electrical and Computer Engineering Illinois Institute of Technology Chicago IL United States

Fear of hypoglycemia is a major concern for many patients with type 1 diabetes and affects patient decisions for use of an artificial pancreas system. We propose an alternative way for prevention of hypoglycemia by issuing predictive hypoglycemia alarms and encouraging patients to consume carbohydrates in a timely manner. The algorithm has been tested on 6 subjects (3 males and 3 females, age 24.2 ± 4.5 years, weight 79.2 ± 16.2 kg, height 172.7 ± 9.4 cm, HbA1C 7.3 ± 0.48%, duration of diabetes 209.2 ± 87.9 months) over 3-day closed-loop clinical experiments as part of a multivariable artificial pancreas control system. Over 6 three-day clinical experiments, there were only 5 real hypoglycemia episodes, of which only 1 hypoglycemia episode occurred due to being missed by the proposed algorithm. The average hypoglycemia alarms per day and per subject was 3. Average glucose value when the first alarms were triggered was recorded to be 117 ± 30.6 mg/dl. Average carbohydrate consumption per alarm was 14 ± 7.8 grams. Our results have shown that most low glucose concentrations can be predicted in advance and the glucose levels can be raised back to the desired levels by consuming an appropriate amount of carbohydrate. The proposed algorithm is able to prevent most hypoglycemic events by suggesting appropriate levels of carbohydrate consumption before the actual occurrence of hypoglycemia. © Diabetes technology Society.

关键词： artificial pancreas carbohydrate suggestion hypoglycemia type 1 diabetes

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Information entropy of coding metasurface

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Light(Science & Applications) 2016年第1期5卷 403-414页

作者： Tie-Jun Cui Shuo Liu Lian-Lin Li Department of Radio Engineering State Key Laboratory of Millimeter WavesSoutheast University2 Si-Pai-LouNanjing 210096China Innovation Centre of Terahertz Science No.4Section 2North Jianshe RoadChengdu 610054China Synergetic Innovation Center of Wireless Communication Technology Southeast UniversityNanjing 210096China School of Electronics Engineering and Computer Sciences Peking UniversityBeijing 100871China

Because of their exceptional capability to tailor the effective medium parameters,metamaterials have been widely used to control electromagnetic waves,which has led to the observation of many interesting phenomena,for example,negative refraction,invisibility cloaking,and anomalous reflections and ***,the studies of metamaterials or metasurfaces are mainly limited to their physical features;currently,there is a lack of viewpoints on metamaterials and metasurfaces from the information *** we propose to measure the information of a coding metasurface using Shannon *** establish an analytical connection between the coding pattern of an arbitrary coding metasurface and its far-field *** introduce geometrical entropy to describe the information of the coding pattern(or coding sequence)and physical entropy to describe the information of the far-field pattern of the *** coding metasurface is demonstrated to enhance the information in transmitting messages,and the amount of enhanced information can be manipulated by designing the coding pattern with different information *** proposed concepts and entropy control method will be helpful in new information systems(for example,communication,radar and imaging)that are based on the coding metasurfaces.

关键词： coding entropy information metasurface

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Towards a consensus atlas of human and mouse adipose tissue at single-cell resolution

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Nature metabolism 2025年第5期7卷 2025 May 13页

作者： Anne Loft Margo P Emont Ada Weinstock Adeline Divoux Adhideb Ghosh Allon Wagner Ann V Hertzel Babukrishna Maniyadath Bart Deplancke Boxiang Liu Camilla Scheele Carey Lumeng Changhai Ding Chenkai Ma Christian Wolfrum Clarissa Strieder-Barboza Congru Li Danh D Truong David A Bernlohr Elisabet Stener-Victorin Erin E Kershaw Esti Yeger-Lotem Farnaz Shamsi Hannah X Hui Henrique Camara Jiawei Zhong Joanna Kalucka Joseph A Ludwig Julie A Semon Jutta Jalkanen Katie L Whytock Kyle D Dumont Lauren M Sparks Lindsey A Muir Lingzhao Fang Lucas Massier Luis R Saraiva Marc D Beyer Marc G Jeschke Marcelo A Mori Mariana Boroni Martin J Walsh Mary-Elizabeth Patti Matthew D Lynes Matthias Blüher Mikael Rydén Natnael Hamda Nicole L Solimini Niklas Mejhert Peng Gao Rana K Gupta Rinki Murphy Saeed Pirouzpanah Silvia Corvera Su'an Tang Swapan K Das Søren F Schmidt Tao Zhang Theodore M Nelson Timothy E O'Sullivan Vissarion Efthymiou Wenjing Wang Yihan Tong Yu-Hua Tseng Susanne Mandrup Evan D Rosen Center for Functional Genomics and Tissue Plasticity (ATLAS) Department of Biochemistry and Molecular Biology University of Southern Denmark (SDU) Odense Denmark. anlo@bmb.sdu.dk. Section of Endocrinology Diabetes and Metabolism University of Chicago Chicago IL USA. margo@uchicago.edu. Department of Medicine Section of Genetic Medicine University of Chicago Chicago IL USA. Translational Research Institute AdventHealth Orlando FL USA. Department of Health Sciences and Technology Institute of Food Nutrition and Health ETH Zurich Schwerzenbach Switzerland. Department of Electrical Engineering and Computer Sciences University of California Berkeley Berkeley CA USA. Department of Molecular and Cell Biology University of California Berkeley Berkeley CA USA. Center for Computational Biology University of California Berkeley Berkeley CA USA. Department of Biochemistry Molecular Biology and Biophysics Institute on the Biology of Aging and Metabolism The University of Minnesota-Twin Cities Minneapolis MN USA. Center for Functional Genomics and Tissue Plasticity (ATLAS) Department of Biochemistry and Molecular Biology University of Southern Denmark (SDU) Odense Denmark. Laboratory of Systems Biology and Genetics Institute of Bioengineering School of Life Sciences École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland. Department of Pharmacy and Pharmaceutical Sciences Faculty of Science National University of Singapore Singapore Singapore. Department of Biomedical Informatics Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore. Genome Institute of Singapore (GIS) Agency for Science Technology and Research (A*STAR) Singapore Singapore. Precision Medicine Translational Research Programme Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore. Cardiovascular-Metabolic Disease Translational Research Programme Yong Loo Lin School of Medicine National University of Singapore Singapor

Adipose tissue (AT) is a complex connective tissue with a high relative proportion of adipocytes, which are specialized cells with the ability to store lipids in large droplets. AT is found in multiple discrete depots throughout the body, where it serves as the primary repository for excess calories. In addition, AT has an important role in functions as diverse as insulation, immunity and regulation of metabolic homeostasis. The Human Cell Atlas Adipose Bionetwork was established to support the generation of single-cell atlases of human AT as well as the development of unified approaches and consensus for cell annotation. Here, we provide a first roadmap from this bionetwork, including our suggested cell annotations for humans and mice, with the aim of describing the state of the field and providing guidelines for the production, analysis, interpretation and presentation of AT single-cell data.

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