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The Society of Instrument and Control Engineers Annual Conference 2015

作者： Navapadol Kittiamornkul Kamon Jirasereeamornkul Supaporn Kiattisin Kosin Chamnongthai Kohji Higuchi Department of Electronic and Telecommunication Engineering King Mongkut’s University of Technology Thonburi Technology of Information System Management Program Faculty of Engineering Mahidol University Department of Electrical Engineering The University of Electro-Communications

This paper represents a prototype of the designed hybrid rectangular and circular waveguide resonator. This proposed resonator is designed for granular moisture measurement. It also can resonate 2.45 GHz which relates with moisture content of material. This paper contain part of the simulation which is denoted by contour of 3D projection of electric field distribution. The result of simulation is showed by plot of probability density function(PDF) and cumulative distribution functions(CDF) shall be used to determine the probability of electric field distributions of proposed *** prototype construction, the anodizing aluminum which has 3.82×107S/m of conductivity is used as the material. The connector of the proposed prototype is copper SMA connector which has 5.96×107S/m conductivity to transfer microwave signal from microwave meter to the proposed resonator. The experiment contains the moisture measurement of 10 paddy samples. To evaluate the accuracy of the proposed prototype, the moisture result is compare with the basic moisture measurement which is dry-weight method. The result shows 82.69% comparing with dry-weight method, but the processing time is extremely reduced, and it is the non-destructive method that the sample is not be destroyed in the measurement.

关键词： moisture measurement,microwave,resonator,granular material

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Correction to: 2021 Taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales

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Archives of virology 2021年第12期166卷 3567-3579页

作者： Jens H Kuhn Scott Adkins Bernard R Agwanda Rim Al Kubrusli Sergey V Alkhovsky Gaya K Amarasinghe Tatjana Avšič-Županc María A Ayllón Justin Bahl Anne Balkema-Buschmann Matthew J Ballinger Christopher F Basler Sina Bavari Martin Beer Nicolas Bejerman Andrew J Bennett Dennis A Bente Éric Bergeron Brian H Bird Carol D Blair Kim R Blasdell Dag-Ragnar Blystad Jamie Bojko Wayne B Borth Steven Bradfute Rachel Breyta Thomas Briese Paul A Brown Judith K Brown Ursula J Buchholz Michael J Buchmeier Alexander Bukreyev Felicity Burt Carmen Büttner Charles H Calisher Mengji Cao Inmaculada Casas Kartik Chandran Rémi N Charrel Qi Cheng Yuya Chiaki Marco Chiapello Il-Ryong Choi Marina Ciuffo J Christopher S Clegg Ian Crozier Elena Dal Bó Juan Carlos de la Torre Xavier de Lamballerie Rik L de Swart Humberto Debat Nolwenn M Dheilly Emiliano Di Cicco Nicholas Di Paola Francesco Di Serio Ralf G Dietzgen Michele Digiaro Olga Dolnik Michael A Drebot J Felix Drexler William G Dundon W Paul Duprex Ralf Dürrwald John M Dye Andrew J Easton Hideki Ebihara Toufic Elbeaino Koray Ergünay Hugh W Ferguson Anthony R Fooks Marco Forgia Pierre B H Formenty Jana Fránová Juliana Freitas-Astúa Jingjing Fu Stephanie Fürl Selma Gago-Zachert George Fú Gāo María Laura García Adolfo García-Sastre Aura R Garrison Thomas Gaskin Jean-Paul J Gonzalez Anthony Griffiths Tony L Goldberg Martin H Groschup Stephan Günther Roy A Hall John Hammond Tong Han Jussi Hepojoki Roger Hewson Jiang Hong Ni Hong Seiji Hongo Masayuki Horie John S Hu Tao Hu Holly R Hughes Florian Hüttner Timothy H Hyndman M Ilyas Risto Jalkanen Dàohóng Jiāng Gilda B Jonson Sandra Junglen Fujio Kadono Karia H Kaukinen Michael Kawate Boris Klempa Jonas Klingström Gary Kobinger Igor Koloniuk Hideki Kondō Eugene V Koonin Mart Krupovic Kenji Kubota Gael Kurath Lies Laenen Amy J Lambert Stanley L Langevin Benhur Lee Elliot J Lefkowitz Eric M Leroy Shaorong Li Longhui Li Jiànróng Lǐ Huazhen Liu Igor S Lukashevich Piet Maes William Marciel de Souza Marco Marklewitz Sergio H Marshall Shin-Yi L Marzano Se Integrated Research Facility at Fort Detrick National Institute of Allergy and Infectious Diseases National Institutes of Health Frederick MD USA. kuhnjens@mail.nih.gov. United States Department of Agriculture Agricultural Research Service US Horticultural Research Laboratory Fort Pierce FL USA. Zoology Department National Museums of Kenya Nairobi Kenya. Jomo Kenyatta University of Agriculture & Technology Nairobi Kenya. Division Phytomedicine Faculty of Life Sciences Humboldt-Universität zu Berlin Berlin Germany. D.I. Ivanovsky Institute of Virology of N.F. Gamaleya National Center on Epidemiology and Microbiology of Ministry of Health of Russian Federation Moscow Russia. Department of Pathology and Immunology Washington University School of Medicine St. Louis MO USA. Faculty of Medicine University of Ljubljana Ljubljana Slovenia. Centro de Biotecnología y Genómica de Plantas Universidad Politécnica de Madrid-Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria Campus de Montegancedo Pozuelo de Alarcón Madrid Spain. Departamento de Biotecnología-Biología Vegetal Escuela Técnica Superior de Ingeniería Agronómica Alimentaria y de Biosistemas Universidad Politécnica de Madrid Madrid Spain. Center for Ecology of Infectious Diseases Department of Infectious Diseases Department of Epidemiology and Biostatistics Insitute of Bioinformatics University of Georgia Athens GA USA. Institute of Novel and Emerging Infectious Diseases Friedrich-Loeffler-Institut Federal Research Institute for Animal Health Greifswald-Insel Riems Germany. Department of Biological Sciences Mississippi State University Mississippi State MS USA. Center for Microbial Pathogenesis Institute for Biomedical Sciences Georgia State University Atlanta GA USA. Edge BioInnovation Consulting and Mgt Frederick MD USA. Institute of Diagnostic Virology Friedrich-Loeffler-Institut Greifswald-Insel Riems Germany. UFyMA INTA-CONICET Cordoba Argentina. Genomics and Bioinformatics D

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Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

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Scientific data 2021年第1期8卷 72页

作者： Gilberto Pastorello Carlo Trotta Eleonora Canfora Housen Chu Danielle Christianson You-Wei Cheah Cristina Poindexter Jiquan Chen Abdelrahman Elbashandy Marty Humphrey Peter Isaac Diego Polidori Markus Reichstein Alessio Ribeca Catharine van Ingen Nicolas Vuichard Leiming Zhang Brian Amiro Christof Ammann M Altaf Arain Jonas Ardö Timothy Arkebauer Stefan K Arndt Nicola Arriga Marc Aubinet Mika Aurela Dennis Baldocchi Alan Barr Eric Beamesderfer Luca Belelli Marchesini Onil Bergeron Jason Beringer Christian Bernhofer Daniel Berveiller Dave Billesbach Thomas Andrew Black Peter D Blanken Gil Bohrer Julia Boike Paul V Bolstad Damien Bonal Jean-Marc Bonnefond David R Bowling Rosvel Bracho Jason Brodeur Christian Brümmer Nina Buchmann Benoit Burban Sean P Burns Pauline Buysse Peter Cale Mauro Cavagna Pierre Cellier Shiping Chen Isaac Chini Torben R Christensen James Cleverly Alessio Collalti Claudia Consalvo Bruce D Cook David Cook Carole Coursolle Edoardo Cremonese Peter S Curtis Ettore D'Andrea Humberto da Rocha Xiaoqin Dai Kenneth J Davis Bruno De Cinti Agnes de Grandcourt Anne De Ligne Raimundo C De Oliveira Nicolas Delpierre Ankur R Desai Carlos Marcelo Di Bella Paul di Tommasi Han Dolman Francisco Domingo Gang Dong Sabina Dore Pierpaolo Duce Eric Dufrêne Allison Dunn Jiří Dušek Derek Eamus Uwe Eichelmann Hatim Abdalla M ElKhidir Werner Eugster Cacilia M Ewenz Brent Ewers Daniela Famulari Silvano Fares Iris Feigenwinter Andrew Feitz Rasmus Fensholt Gianluca Filippa Marc Fischer John Frank Marta Galvagno Mana Gharun Damiano Gianelle Bert Gielen Beniamino Gioli Anatoly Gitelson Ignacio Goded Mathias Goeckede Allen H Goldstein Christopher M Gough Michael L Goulden Alexander Graf Anne Griebel Carsten Gruening Thomas Grünwald Albin Hammerle Shijie Han Xingguo Han Birger Ulf Hansen Chad Hanson Juha Hatakka Yongtao He Markus Hehn Bernard Heinesch Nina Hinko-Najera Lukas Hörtnagl Lindsay Hutley Andreas Ibrom Hiroki Ikawa Marcin Jackowicz-Korczynski Dalibor Janouš Wilma Jans Rachhpal Jassal Shicheng Jiang Tomomichi Kato Myr Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. gzpastorello@lbl.gov. DIBAF University of Tuscia Viterbo 01100 Italy. Euro-Mediterranean Centre on Climate Change Foundation (CMCC) Lecce 73100 Italy. Climate & Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. Department of Civil Engineering California State University Sacramento CA 95819 USA. Department of Geography Environment and Spatial Sciences Michigan State University East Lansing MI 48823 USA. Department of Computer Science University of Virginia Charlottesville VA 22904 USA. TERN Ecosystem Processes Menzies Creek VIC3159 Australia. Max Planck Institute for Biogeochemistry Jena 07701 Germany. Laboratoire des Sciences du Climat et de l'Environnement (LSCE) CEA CNRS UVSQ UPSACLAY Gif sur Yvette 91190 France. Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China. Department of Soil Science University of Manitoba Winnipeg MB R3T2N2 Canada. Department of Agroecology and Environment Agroscope Research Institute Zürich 8046 Switzerland. School of Geography and Earth Sciences McMaster University L8S4K1 Hamilton ON Canada. Department of Physical Geography and Ecosystem Science Lund University Lund 22362 Sweden. Department of Agronomy and Horticulture University of Nebraska-Lincoln Lincoln NE 68583 USA. School of Ecosystem and Forest Sciences The University of Melbourne Richmond VIC3121 Australia. Department of Biology Research Group PLECO University of Antwerp Antwerp 2610 Belgium. Joint Research Centre European Commission Ispra 21027 Italy. TERRA Teaching and Research Center University of Liege Gembloux B-5030 Belgium. Finnish Meteorological Institute Helsinki 00560 Finland. ES

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The electric field distribution of a hybrid rectangular and circular waveguide resonator for use in granular material dielectric measurements

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IEEJ Transactions on Fundamentals and Materials 2015年第8期135卷 439-449页

作者： Kittiamornkul, Navapadol Jirasereeamornkul, Kamon Kiattisin, Supaporn Chamnongthai, Kosin Higuchi, Kohji Department of Electronic and Telecommunication Engineering King Mongkut's University of Technology Thonburi 126 Bangmod Tungkru Bangkok10140 Thailand Technology of Information System Management Program Faculty of Engineering Mahidol University 999 Salaya Nakhon Pathom73170 Thailand Department of Mechanical Engineering University of Electro-Communications 1-5-1 Chofugaoka Chofu182-8585 Japan

This paper represents a design for a hybrid rectangular and circular waveguide resonator. The resonator is designed specifically for the purpose of granular dielectric measurements, which resonates at 2.45 GHz. The electric field distributions of the proposed resonator will be compared against ordinary resonators, and illustrated using a 3D computer simulation of isosurfaces and their contours and 3D projections. In this simulation the properties of samples (paddies and soils) are loaded into each design, in order to observe the electrical field distributions of each sample. Next, the probability density functions (PDF) and cumulative distribution functions (CDF) shall be used to determine the probability of electric field distributions within each type of resonator. Each designed resonator was created in order to process real experiment circumstances. The experiments for each resonator were processed using 20 paddy samples and 20 soil samples, in order to replicate real circumstances in an efficient manner. The percentages of moisture content (%MC) from each design were compared against %MC obtained using dry weight methodology, used to find errors. From the results, mean square error (MSE) shows that the hybrid resonator can improve output greater than the ordinary resonators, which are the rectangular resonator and circular resonator, with 78.738% and 63.213% respectively for paddy sample, and 70.605% and 46.520% respectively for soil sample, respectively. This demonstrates that the proposed resonator creates better results than the ordinary resonators, although the sample is changed. © 2015 The Institute of Electrical Engineers of Japan.

关键词： Moisture

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Corrigendum: Dangling-bond charge qubit on a silicon surface (2010 New J. Phys. 12 083018)

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New Journal of Physics 2017年第11期19卷

作者： Lucian Livadaru Peng Xue Zahra Shaterzadeh-Yazdi Gino A DiLabio Josh Mutus Jason L Pitters Barry C Sanders Robert A Wolkow Quantum Silicon Inc. Edmonton Alberta T6G 2M9 Canada Department of Physics Southeast University Nanjing 211189 People's Republic of China Department of Engineering Science Faculty of Engineering University of Tehran Tehran Iran Department of Chemistry and Faculty of Management The University of British Columbia Kelowna British Columbia V1V 1V7 Canada Google Inc. Santa Barbara CA 93117 United States of America National Institute for Nanotechnology National Research Council of Canada Edmonton Alberta T6G 2M9 Canada Institute for Quantum Science and Technology University of Calgary Calgary Alberta Canada Hefei National Laboratory for Physical Sciences at Microscale University of Science and Technology of China Hefei Anhui 230026 People's Republic of China Shanghai Branch CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai 201315 People's Republic of China Program in Quantum Information Science Canadian Institute for Advanced Research Toronto Ontario M5G 1Z8 Canada Department of Physics University of Alberta Edmonton Alberta T6G 2J1 Canada

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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Research on a corrosion model of gathering pipelines of gas containing CO2 based on flow field

Research on a corrosion model of gathering pipelines of gas ...

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2014 International Conference on Pipelines and Trenchless technology, ICPTT 2014

作者： Luo, Zhengshan Wang, Fei Gu, Jianrong Management Faculty School of management Xi'an University of Architecture and Technology No.13 Yanta Road Xi'an710055 China Information Management and Information System Xi'an University of Architecture and Technology No.13 Yanta Road Xi'an710055 China Industry Engineering Xi'an University of Architecture and Technology No.13 Yanta Road Xi'an710055 China

ISBN: (纸本)9780784413821

During the process of transporting gas, mixed gas-liquid layer formed by condensed gas including CO2 etc, leads to corrosion of T-shaped pipe elbows etc, which influences service life of pipelines, triggers various leakage disasters and causes heavy casualties and property damages. Based on domestic and overseas researches, the paper puts forward the improved De Waard corrosion prediction model of gas pipelines by applying hydromechanics theory and considering the factors of gas flow rate, PH value, etc. The paper calculates the flow field inside T-shaped elbows by using fluid dynamics (FD) method, analyzes the influence of flow field parameters on pipelines corrosion rate combining with particle erosion model, and raises the corrosion model of wet gas containing CO2 pipeline based on hydromechanics theory. The field researches of applying this model shows that the major parameters influencing gas pipeline corrosion are the flow rate of media, turbulence kinetic energy and phase distribution. For T-shaped pipe elbows, the maximum corrosion position is the internal oblique confluence area. The results calculated by model coincide well with historical statistical data and field testing results, so it verifies the correctness of this corrosion model. It provides decision basis for maintaining and integrity management of gas gathering pipelines containing CO2 etc. © 2014 American Society of Civil Engineers.

关键词： Carbon dioxide

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Techniques for estimating blood pressure variation using video images

Techniques for estimating blood pressure variation using vid...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Norihiro Sugita Kazuma Obara Makoto Yoshizawa Makoto Abe Akira Tanaka Noriyasu Homma Department of Management Science and Technology Graduate School of Engineering Tohoku University Sendai 980-8579 Japan Department of Electrical and Communication Engineering Graduate School of Engineering Tohoku University Sendai 980-8579 Japan Information Synergy Center Tohoku University Sendai 980-8579 Japan Department of Human Support System Faculty of Symbiotic Systems Science Fukushima University Fukushima 960-1296 Japan Department of Health Science Graduate School of Medicine Tohoku University Sendai 980-8575 Japan

ISBN: (纸本)9781424492695

It is important to know about a sudden blood pressure change that occurs in everyday life and may pose a danger to human health. However, monitoring the blood pressure variation in daily life is difficult because a bulky and expensive sensor is needed to measure the blood pressure continuously. In this study, a new non-contact method is proposed to estimate the blood pressure variation using video images. In this method, the pulse propagation time difference or instantaneous phase difference is calculated between two pulse waves obtained from different parts of a subject's body captured by a video camera. The forehead, left cheek, and right hand are selected as regions to obtain pulse waves. Both the pulse propagation time difference and instantaneous phase difference were calculated from the video images of 20 healthy subjects performing the Valsalva maneuver. These indices are considered to have a negative correlation with the blood pressure variation because they approximate the pulse transit time obtained from a photoplethysmograph. However, the experimental results showed that the correlation coefficients between the blood pressure and the proposed indices were approximately 0.6 for the pulse wave obtained from the right hand. This result is considered to be due to the difference in the transmission depth into the skin between the green and infrared light used as light sources for the video image and conventional photoplethysmogram, respectively. In addition, the difference in the innervation of the face and hand may be related to the results.

关键词： Techniques forehead innervation

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