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

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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Archimedean Spiral Multi-resonator for Chipless RFID Tag Using Frequency-Coded Decimal Method

Archimedean Spiral Multi-resonator for Chipless RFID Tag Usi...

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SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference

作者： Hillner de P. A. Ferreira Alexandre J. R. Serres Georgina Karla de F. Serres Francisco M. de Assis Alfredo Gomes Neto Post-Graduate Program in Electrical Engineering Federal University of Campina Grande Group of Telecom. and Applied Electromagnetism Federal Inst. of Educ. Science and Technology of Paraiba

ISBN: (纸本)9781467394932

A compact electromagnetic multi-resonator is presented in this paper using a new technique for chipless RFID tag data encoding. Employing Archimedean spirals, the information is applied into the spectral signature shifting resonant frequencies in several positions. The multi-resonator tag proposed operates in microwave band (between 3.0-7.0GHz) and has a coding data capacity of up to 100 decimal numbers for two resonant frequencies. The simulated and measured results show a good concordance and a great perspective to use in low-cost RFID chipless tag applications.

关键词： RFID chipless Frequency-Coded Decimal Archimedean spiral Multi-resonator

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Abstracts from the 20th International Symposium on Signal Transduction at the Blood-Brain Barriers Abstracts

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FLUIDS AND BARRIERS OF THE CNS 2017年第SUPPL 2期14卷 27-27页

作者： [Anonymous] The Jerzy Kukuczka Academy of Physical Education Katowice Poland The Institute of Animal Physiology and Food Research Polish Academy of Sciences Olsztyn Poland University of Miami Miami FL USA Institute of Pharmaceutical Science King’s College London London United Kingdom Department of Ophthalmology and Molecular and Integrative Physiology The University of Michigan Ann Arbor MI USA Department of Internal Medicine and Cardiology The University of Michigan Ann Arbor MI USA School of Medicine Department of Cellular and Molecular Medicine Koc University Istanbul Turkey Department of Cellular and Molecular Medicine Medical Faculty Koc University Istanbul Turkey Department of Neuroscience School of Medicine Koc University Istanbul Turkey Department of Neuroscience Medical Faculty Koc University Istanbul Turkey Department of Laboratory Animals Science Aziz Sancar Experimental Medicine Research Institute Istanbul University Istanbul Turkey Department of Neuroscience Aziz Sancar Experimental Medicine Research Institute Istanbul University Istanbul Turkey School of Medicine Koc University Istanbul Turkey Department of Forensic Science Istanbul Faculty of Medicine Istanbul University Istanbul Turkey Department of Histology and Embryology School of Medicine Koc University Istanbul Turkey Department of Histology and Embryology Istanbul Faculty of Medicine Istanbul University Istanbul Turkey Department of Physiology School of Medicine Koc University Istanbul Turkey Theodor Kocher Institute University of Bern Bern Switzerland Institute of Veterinary Physiology Vetsuisse Faculty University of Zurich Zurich Switzerland Zurich Center for Integrative Human Physiology University of Zurich Zurich Switzerland Zurich Center of Integrative Human Physiology University of Zurich Zurich Switzerland Institute for Veterinary Physiology and Zurich Center for Integrative Human Physiology University of Zurich Zurich Switzerland Institute of Veterinary Physiology Univer

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Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis (vol 50, pg 1368, 2020)

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PSYCHOLOGICAL MEDICINE 2020年第16期50卷 2816-2816页

作者： Wu, Yin Levis, Brooke Riehm, Kira E. Saadat, Nazanin Levis, Alexander W. Azar, Marleine Rice, Danielle B. Boruff, Jill Cuijpers, Pim Gilbody, Simon Ioannidis, John P. A. Kloda, Lorie A. McMillan, Dean Patten, Scott B. Shrier, Ian Ziegelstein, Roy C. Akena, Dickens H. Arroll, Bruce Ayalon, Liat Baradaran, Hamid R. Baron, Murray Bombardier, Charles H. Butterworth, Peter Carter, Gregory Chagas, Marcos H. Chan, Juliana C. N. Cholera, Rushina Conwell, Yeates de Manvan Ginkel, Janneke M. Fann, Jesse R. Fischer, Felix H. Fung, Daniel Gelaye, Bizu Goodyear-Smith, Felicity Greeno, Catherine G. Hall, Brian J. Harrison, Patricia A. Harter, Martin Hegerl, Ulrich Hides, Leanne Hobfoll, Stevan E. Hudson, Marie Hyphantis, Thomas Inagaki, Masatoshi Jette, Nathalie Khamseh, Mohammad E. Kiely, Kim M. Kwan, Yunxin Lamers, Femke Liu, Shen-Ing Lotrakul, Manote Loureiro, Sonia R. Lowe, Bernd McGuire, Anthony Mohd-Sidik, Sherina Munhoz, Tiago N. Muramatsu, Kumiko Osorio, Flavia L. Patel, Vikram Pence, Brian W. Persoons, Philippe Picardi, Angelo Reuter, Katrin Rooney, Alasdair G. Santos, Ina S. Shaaban, Juwita Sidebottom, Abbey Simning, Adam Stafford, Lesley Sung, Sharon Tan, Pei Lin Lynnette Turner, Alyna van Weert, Henk C. White, Jennifer Whooley, Mary A. Winkley, Kirsty Yamada, Mitsuhiko Benedetti, Andrea Thombs, Brett D. [a1]Lady Davis Institute for Medical Research Jewish General Hospital Montréal Québec Canada [a2]Department of Psychiatry McGill University Montréal Québec Canada [a3]Department of Epidemiology Biostatistics and Occupational Health McGill University Montréal Québec Canada [a4]Department of Psychology McGill University Montréal Québec Canada [a5]Schulich Library of Physical Sciences Life Sciences and Engineering McGill University Montreal Quebec Canada [a6]Department of Clinical Neuro and Developmental Psychology Amsterdam Public Health Research Institute Vrije Universiteit Amsterdam the Netherlands [a7]Hull York Medical School and the Department of Health Sciences University of York Heslington York UK [a8]Department of Medicine Department of Health Research and Policy Department of Biomedical Data Science Department of Statistics Stanford University Stanford California USA [a9]Library Concordia University Montréal Québec Canada [a10]Department of Community Health Sciences University of Calgary Calgary Alberta Canada [a11]Hotchkiss Brain Institute and O’Brien Institute for Public Health University of Calgary Calgary Alberta Canada [a12]Department of Medicine Johns Hopkins University School of Medicine Baltimore Maryland USA [a13]Department of Psychiatry Makerere University College of Health Sciences Kampala Uganda [a14]Department of General Practice and Primary Health Care University of Auckland Auckland New Zealand [a15]Louis and Gabi Weisfeld School of Social Work Bar Ilan University Ramat Gan Israel [a16]Endocrine Research Center Institute of Endocrinology and Metabolism Iran University of Medical Sciences Tehran Iran [a17]Ageing Clinical & Experimental Research Team Institute of Applied Health Sciences School of Medicine Medical Sciences and Nutrition University of Aberdeen Aberdeen Scotland UK [a18]Department of Medicine McGill University Montréal Québec Canada [a19]Department of Rehabilitation Medicine University of Washington S

BackgroundItem 9 of the Patient Health Questionnaire-9 (PHQ-9) queries about thoughts of death and self-harm, but not suicidality. Although it is sometimes used to assess suicide risk, most positive responses are not associated with suicidality. The PHQ-8, which omits Item 9, is thus increasingly used in research. We assessed equivalency of total score correlations and the diagnostic accuracy to detect major depression of the PHQ-8 and *** conducted an individual patient data meta-analysis. We fit bivariate random-effects models to assess diagnostic ***16 742 participants (2097 major depression cases) from 54 studies were included. The correlation between PHQ-8 and PHQ-9 scores was 0.996 (95% confidence interval 0.996 to 0.996). The standard cutoff score of 10 for the PHQ-9 maximized sensitivity + specificity for the PHQ-8 among studies that used a semi-structured diagnostic interview reference standard (N = 27). At cutoff 10, the PHQ-8 was less sensitive by 0.02 (−0.06 to 0.00) and more specific by 0.01 (0.00 to 0.01) among those studies (N = 27), with similar results for studies that used other types of interviews (N = 27). For all 54 primary studies combined, across all cutoffs, the PHQ-8 was less sensitive than the PHQ-9 by 0.00 to 0.05 (0.03 at cutoff 10), and specificity was within 0.01 for all cutoffs (0.00 to 0.01).ConclusionsPHQ-8 and PHQ-9 total scores were similar. Sensitivity may be minimally reduced with the PHQ-8, but specificity is similar.

关键词： Depression diagnostic accuracy individual participant data meta-analysis meta-analysis PHQ-8 PHQ-9 screening systematic review

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Analysis of the resonant behavior of FSS using matryoshka geometry

Analysis of the resonant behavior of FSS using matryoshka ge...

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SBMO/IEEE MTT-S International Conference on Microwave and Optoelectronics (IMOC)

作者： Alfrêdo Gomes Neto Jefferson C. e Silva Joabson Nogueira de Carvalho Josiel Do Nascimento Cruz Hillner De Paiva Almeida Ferreira Group of Telecom. and Applied Electromagnetism Federal Inst. of Educ. Science and Technology of Paraiba Joao Pessoa PB Brazil Post-Graduate Program in Electrical Engineering Federal University of Campina Grande Brazi Brazil Group of Telecom. and Applied Electromagnetism Federal Inst. of Educ. Science and Technology of Paraíba Brazil Post-Graduate Program in Electrical Engineering Universidade Federal de Campina Grande Campina Grande PB BR

ISBN: (纸本)9781467394932

In this paper the resonant behavior of frequency selective surfaces, FSS, using matryoshka geometry is analyzed considering polarizations x and y. The basics of the FSS using matryoshka geometry are described for usual and open cases, including an expression to estimate the first resonant frequency. Initially, the FSS with two concentric square rings is considered and its resonant behavior analyzed. Then, the resonant behavior of FSS with two rings matryoshka geometry is examined. The analysis is based on the electric current distribution obtained using the commercial software ANSYS-Designer. With a better understanding of the resonance nature in matryoshka geometry the design parameters can be better adjusted and desired frequency responses properly achieved.

关键词： Frequency selective surfaces Geometry Resonant frequency Current Frequency response Europe

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Solid electrolyte for solid-state batteries: Have lithium-ion batteries reached their technical limit?

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AIP Conference Proceedings 2016年第1期1710卷

作者： Evvy Kartini Maykel Manawan 1Center for Science and Technology of Advanced Materials – National Nuclear Energy Agency Kawasan Puspiptek Serpong Tangerang Selatan15314 Banten Indonesia 2Post Graduate Program of Materials Science University of Indonesia Jl.Salemba Raya No.4 Jakarta 10430 Indonesia

With increasing demand for electrical power on a distribution grid lacking storage capabilities, utilities and project developers must stabilize what is currently still intermittent energy production. In fact, over half of utility executives say “the most important emerging energy technology” is energy storage. Advanced, low-cost battery designs are providing promising stationary storage solutions that can ensure reliable, high-quality power for customers, but research challenges and questions lefts. Have lithium-ion batteries (LIBs) reached their technical limit? The industry demands are including high costs, inadequate energy densities, long recharge times, short cycle-life times and safety must be continually addressed. Safety is still the main problem on developing the lithium ion *** safety issue must be considered from several aspects, since it would become serious problems, such as an explosion in a Japan Airlines 787 Dreamliner’s cargo hold, due to the battery problem. The combustion is mainly due to the leakage or shortcut of the electrodes, caused by the liquid electrolyte and polymer separator. For this reason, the research on solid electrolyte for replacing the existing liquid electrolyte is very important. The materials used in existing lithium ion battery, such as a separator and liquid electrolyte must be replaced to new solid electrolytes, solid materials that exhibits high ionic conductivity. Due to these reasons, research on solid state ionics materials have been vastly growing worldwide, with the main aim not only to search new solid electrolyte to replace the liquid one, but also looking for low cost materials and environmentally friendly. A revolutionary paradigm is also required to design new stable anode and cathode materials that provide electrochemical cells with high energy, high power, long lifetime and adequate safety at competitive manufacturing costs. Lithium superionic conductors, which can be used as solid electrolytes, promis

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Affinity Purification and Immobilization of Chitinase from Bacillus sp .R2

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Procedia technology 2015年 19卷 958-964页

作者： Ben Amar Cheba Taha Ibrahim Zaghloul Ahmad Rafik EL-Mahdy Mohammad Hisham EL-Massry Department of Biotechnology -Faculty of Nature and Life Sciences-University of Sciences and Technology-Oran Mohamed Boudiaf (USTOMB) BP 1505 Al Mnaouar Oran 31000 Algeria Department of Biotechnology Institute of Post Graduate Studies and Research University of Alexandria- Alexandria –Egypt Department of Food Science and Technology-Faculty of Agriculture-University of Alexandria- Alexandria -Egypt

Bacillus sp. R2 chitinase was purified to homogeneity using ammonium sulphate precipitation at 80% saturation, affinity chromatography on swollen crab shell chitin column, and followed by gel filtration chromatography on Sephadex G-100; the enzyme was purified to 14.89-fold and yield of 14.77%, respectively. Furthermore the purified chitinase was subjected to three immobilization techniques on ten various solid carriers;1-physical adsorption immobilization on activated charcoal and silica gel carriers; 2-covalent binding on crab shell chitin and chitosan; 3-Ionic binding on CM-Sepharose, Q-Sepharose, DEAE Cellulose, Amberlite IRC 50, Amberlite CG-120 (NA) and Amberlite CG -4B (OH)respectively. Immobilization results revealed that covalent and ionic binding were the best techniques whereas chitosan, Amberlite IRC50 and chitin gave the highest immobilization yields 72.9, 70.26 and 63.53% with the highest activity yields 63.36, 58.26 and 53.03% respectively. These findings improve the effectiveness of swollen crab shell chitin as matrix for chitinase affinity purification whereas chitin and chitosan as active natural biopolymers for chitinase continuous production through immobilization.

关键词： Bacillus sp .R2 chitin chitinase affinity purification immobilization activity yield

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Notes for genera:Ascomycota

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Fungal Diversity 2017年第5期86卷 1-594页

作者： Nalin N.Wijayawardene Kevin D.Hyde Kunhiraman C.Rajeshkumar David L.Hawksworth Hugo Madrid Paul M.Kirk Uwe Braun Rajshree V.Singh Pedro W.Crous Martin Kukwa Robert Lücking Cletus P.Kurtzman Andrey Yurkov Danny Haelewaters Andre´Aptroot H.Thorsten Lumbsch Einar Timdal Damien Ertz Javier Etayo Alan J.L.Phillips Johannes Z.Groenewald Moslem Papizadeh Laura Selbmann Monika C.Dayarathne Gothamie Weerakoon E.B.Gareth Jones Satinee Suetrong Qing Tian Rafael F.Castanda-Ruiz Ali H.Bahkali Ka-Lai Pang Kazuaki Tanaka Dong Qin Dai Jariya Sakayaroj Martina Hujslová Lorenzo Lombard Belle D.Shenoy Ave Suija Sajeewa S.N.Maharachchikumbura Kasun M.Thambugala Dhanushka N.Wanasinghe Bharati O.Sharma Subhash Gaikwad Gargee Pandit Laura Zucconi Silvano Onofri Eleonora Egidi Huzefa A.Raja Rampai Kodsueb Marcela E.S.Caceres Sergio Perez-Ortega Patrícia O.Fiuza Josiane Santana Monteiro Larissa N.Vasilyeva Roger G.Shivas Maria Prieto Mats Wedin Ibai Olariaga Adebola Azeez Lateef Yamini Agrawal Seyed Abolhassan Shahzadeh Fazeli Mohammad Ali Amoozegar Guo Zhu Zhao Walter P.Pfliegler Gunjan Sharma Magdalena Oset Mohamed A.Abdel-Wahab Susumu Takamatsu Konstanze Bensch Nimali Indeewari de Silva AndréDe Kesel Anuruddha Karunarathna Saranyaphat Boonmee Donald H.Pfister Yong-Zhong Lu Zong-Long Luo Nattawut Boonyuen Dinushani A.Daranagama Indunil C.Senanayake Subashini C.Jayasiri Milan C.Samarakoon Xiang-Yu Zeng Mingkwan Doilom Luis Quijada Sillma Rampadarath Gabriela Heredia Asha J.Dissanayake Ruvishika S.Jayawardana Rekhani H.Perera Li Zhou Tang Chayanard Phukhamsakda Margarita Hernańdez-Restrepo Xiaoya Ma Saowaluck Tibpromma Luis F.P.Gusmao Darshani Weerahewa Samantha C.Karunarathna Key Laboratory for Plant Diversity and Biogeography of East Asia Kunming Institute of BotanyChinese Academy of ScienceKunming 650201YunnanPeople’s Republic of China Center of Excellence in Fungal Research Mae Fah Luang UniversityChiang Rai 57100Thailand World Agroforestry Centre East and Central AsiaKunming 650201YunnanPeople’s Republic of China Mushroom Research Foundation 128 M.3 Ban Pa Deng T.Pa PaeA.Mae TaengChiang Mai 50150Thailand National Fungal Culture Collection of India(NFCCI) Biodiversity and Palaeobiology(Fungi)GroupAgharkar Research InstitutePuneMaharashtra 411004India Royal Botanic Gardens KewRichmondSurrey TW93DSUK Department of Life Sciences The Natural History MuseumCromwell RoadLondon SW75BDUK Jilin Agricultural University Changchun 130118JilinPeople’s Republic of China Centro de Geno´mica y Bioinforma´tica Facultad de CienciasUniversidad Mayor de ChileCamino La Pira´mide 5750HuechurabaSantiagoChile Martin-Luther-Universita¨t Institut fu¨r BiologieBereich Geobotanik und Botanischer GartenHerbariumNeuwerk 2106099 Halle(Saale)Germany Westerdijk Fungal Biodiversity Institute Uppsalalaan 83584 CT UtrechtThe Netherlands Department of Plant Taxonomy and Nature Conservation Faculty of BiologyUniversity of Gdan´skWita Stwosza 5980-308 Gdan´skPoland Botanic Garden and Botanical Museum Königin-Luise-Str.6-814195 BerlinGermany Mycotoxin Prevention and Applied Microbiology Research Unit National Center for Agricultural Utilization ResearchAgricultural Research ServiceU.S.Department of AgriculturePeoriaIL 61604USA Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures Inhoffenstraße 7B38124 BrunswickGermany Farlow Reference Library and Herbarium of Cryptogamic Botany Harvard University22 Divinity AvenueCambridgeMA 02138USA Department of Organismic and Evolutionary Biology Harvard University22 Divinity AvenueCambridgeMA 02138USA ABL Herbarium G.v.d.Veenstraat 1073762 XK SoestThe Netherlands Science&Education The Field Museum1400

Knowledge of the relationships and thus the classification of fungi,has developed rapidly with increasingly widespread use of molecular techniques,over the past 10–15 years,and continues to *** genera have been found to be polyphyletic,and their generic concepts have subsequently been *** names have thus been introduced for species which are phylogenetically distinct from the type species of particular *** ending of the separate naming of morphs of the same species in 2011,has also caused changes in fungal generic *** order to facilitate access to all important changes,it was desirable to compile these in a single *** present article provides a list of generic names of Ascomycota(approximately 6500 accepted names published to the end of 2016),including those which are *** and summaries of the changes since the last edition of‘Ainsworth&Bisby’s Dictionary of the Fungi’in 2008 are *** notes include the number of accepted species,classification,type species(with location of the type material),culture availability,life-styles,distribution,and selected publications that have appeared since *** work is intended to provide the foundation for updating the ascomycete component of the"Without prejudice list of generic names of Fungi"published in 2013,which will be developed into a list of protected generic *** will be subjected to the XIXth International Botanical Congress in Shenzhen in July 2017 agreeing to a modification in the rules relating to protected lists,and scrutiny by procedures determined by the Nomenclature Committee for Fungi(NCF).The previously invalidly published generic names Barriopsis,Collophora(as Collophorina),Cryomyces,Dematiopleospora,Heterospora(as Heterosporicola),Lithophila,Palmomyces(as Palmaria)and Saxomyces are validated,as are two previously invalid family names,Bartaliniaceae and *** species of Lalaria,which were invalidly published are trans

关键词： Article 59 Classification One name Pleomorphic fungi Taxonomy

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Traditional TCP congestion control algorithms evaluation in wired-cum-wireless networks

Traditional TCP congestion control algorithms evaluation in ...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： M. C. Dias L. A. Caldeira A. Perkusich Post-graduate Program in Electrical Engineering - PpgEE - COPELE Federal University of Campina Grande - UFCG Campina Grande Brazil Electrical Engineering Coordination Federal Institute of Education Science and Technology of Paraíba - IFPB João Pessoa Brazil

Congestion control algorithms exist for decades to prevent package loss in intense traffic networks. Several solutions developed over the years tried to solve this problem, including the creation of new algorithms. However, hybrid wired and wireless networks, or wired-cum-wireless, common in modern days, bring new challenges to programmers and engineers who try to overcome the numerous new problems that this kind of network presents. This work carries out a performance comparison, in a wired-cum-wireless network, using TCP congestion control algorithms variants: New Reno and CUBIC. The comparison is to determine which of those algorithms performs better in several situations, like multiple disconnections caused by mobility, interference and congested links. The results showed that the CUBIC is a more stable and fair algorithm, but it has a significantly less data flow than New Reno.

关键词： Standards Interference Receivers Mobile handsets Transmitters Wireless communication Algorithm design and analysis

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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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