Forward 5 Contributors 6 I. BASIC SCIENCES 8

合集下载

Pearson Edexcel International Advanced Level 计算机信

 Pearson Edexcel International Advanced Level 计算机信

Mark Scheme (Results)Summer 2019Pearson Edexcel International Advanced Level In Information Technology (IT)(WIT11) Paper 01Edexcel and BTEC QualificationsEdexcel and BTEC qualifications are awarded by Pearson, the UK’s largest awarding body. We provide a wide range of qualifications including academic, vocational, occupational and specific programmes for employers. For further information visit our qualifications websites at or . Alternatively, you can get in touch with us using the details on our contact us page at /contactus.Pearson: helping people progress, everywherePearson aspires to be the world’s leading learning company. Our aim is to help everyone progress in their lives through education. We believe in every kind of learning, for all kinds of people, wherever they are in the world. We’ve been involved in educati on for over 150 years, and by working across 70 countries, in 100 languages, we have built an international reputation for our commitment to high standards and raising achievement through innovation in education. Find out more about how we can help you and your students at:/ukSummer 2019Publications Code WIT11_01_1906_MSAll the material in this publication is copyright© Pearson Education Ltd 2019General Marking Guidance•All candidates must receive the same treatment. Examiners must mark the first candidate in exactly the same way as they mark the last.•Mark schemes should be applied positively. Candidates must be rewarded for what they have shown they can do rather than penalised for omissions.•Examiners should mark according to the mark scheme not according to their perception of where the grade boundaries may lie.•There is no ceiling on achievement. All marks on the mark scheme should be used appropriately.•All the marks on the mark scheme are designed to be awarded. Examiners should always award full marks if deserved, i.e. if the answer matches the mark scheme. Examiners should also be prepared to award zero marks if the candidate’s response is not worthy of creditaccording to the mark scheme.•Where some judgement is required, mark schemes will provide the principles by which marks will be awarded and exemplification may be limited.•When examiners are in doubt regarding the application of the mark scheme to a candidat e’s response, the team leader must be consulted.•Crossed out work should be marked UNLESS the candidate has replaced it with an alternative response.GuidanceThe diagram shows the functionality – the location of particular devices may vary. Allow radio signals for connecting devices as long as a receiver is included.Award one mark for each item to a maximum of ten marks:a)microprocessor / processor / embedded computer in control box / server / computerb)modem / router in control box /attached or wired to the boxc)timer / clock in box or from internetd)microprocessor (or device credited in (a)) connects to Internet via router/modeme)red light / traffic camera on main/side roadf)red light sensor identified, motion (radar, camera)g)speed sensor on main/side road (radar, camera) (must be at entrance to the village)h)appropriate vehicle sensor on side road, proximity (pressure, radar, induction loop, camera)i)radio receiverj)wireless signal to radio receiver (vehicle is not needed for the mark)k)all sensors, lights, cameras and radio receiver connect to switch Allow software based clock / timer for (c)Pearson Education Limited. Registered company number 872828with its registered office at 80 Strand, London, WC2R 0RL, United Kingdom。

生物信息学网站网址(全)

生物信息学网站网址(全)

生物信息学网站分子生物学数据库综合目录1. SRS序列查询系统(分子生物学数据库网络浏览器) http://www.embl-heidelberg.ed/srs5/2. 分子生物学数据库及服务器概览/people/pkarp/mimbd/rsmith.html3. BioMedNet图书馆4. DBGET数据库链接http://www.genome.ad.jp/dbget/dbget.links.html5. 哈佛基因组研究数据库与精选服务器6. 约翰. 霍普金斯大学(Johns Hopkins University) OWL网络服器/Dan/proteins/owl.html7. 生物网络服务器索引,USCS /network/science/biology/index.html8. 分子生物学数据库列表(LiMB) gopher:///11/molbio/other9. 病毒学的WWW服务器,UW-Madison /Welcome.html10. UK MRC 人类基组图谱计划研究中心/11. 生物学家和生物化学家的WWW资源http://www.yk.rim.pr.jp/~aisoai/index.html12. 其他生物网络服务器的链接/biolinks.html13. 分子模型服务器与数据库/lap/rsccom/dab/ind006links.html14. EMBO实际结构数据库http://xray.bmc.uu.se/embo/structdb/links.html15. 蛋白质科学家的网络资源/protein/ProSciDocs/WWWResources.html16. ExPASy分子生物学服务器http://expasy.hcuge.ch/cgi-bin/listdoc17. 抗体研究网页18. 生物信息网址http://biochem.kaist.ac.kr/bioinformatics.html19. 乔治.梅森大学(George Mason University)的生物信息学与计算分子生物学专业/~michaels/Bioinformatics/20. INFOBIOGEN数据库目录biogen.fr/services/dbcat/21. 国家生物技术信息研究室/data/data.html22. 人类基因组计划情报/TechResources/Human_Genome23. 生物学软件及数据库档案/Dan/software/biol-links.html24. 蛋白质组研究:功能基因组学的新前沿(著作目录) http://expasy.hcuge.ch/ch2d/LivreTOC.html序列与结构数据库一.主要的公共序列数据库1. EMBL WWW服务器http://www.EMBL-heidelberg.ed/Services/index.html2. Genbank 数据库查询形式(得到Genbank的一个记录) /genbank/query_form.html3. 蛋白质结构数据库WWW服务器(得到一PDB结构) 4. 欧洲生物信息学研究中心(EBI) /5. EBI产业支持/6. SWISS-PROT(蛋白质序列库) http://www.expasy.ch/sprot/sprot-top.html7. 大分子结构数据库/cgi-bin/membersl/shwtoc.pl?J:mms8. Molecules R Us(搜索及观察一蛋白质分子) /modeling/net_services.html9. PIR国际蛋白质序列数据库/Dan/proteins/pir.html10. SCOP(蛋白质的结构分类),MRC /scop/data/scop.l.html11. 洛斯阿拉莫斯的HIV分子免疫数据库/immuno/index.html12. TIGR数据库/tdb/tdb.html13. NCBI WWW Entrez浏览器/Entrez/index.html14. 剑桥结构数据库(小分子有机的及有机金属的结晶结构) 15. 基因本体论坛/GO/二. 专业数据库1. ANU生物信息学超媒体服务(病毒数据库、分类及病毒的命名法) .au/2. O-GL YCBASE(O联糖基化蛋白质的修订数据库) http://www.cbs.dtu.dk/OGLYCBASE/cbsoglycbase.html3. 基因组序列数据序(GSDB)(已注释的DNA序列的关系数据序) 4. EBI蛋白质拓扑图/tops/Serverintermed.html5. 酶及新陈代谢途径数据库(EMP) /6. 大肠杆菌数据库收集(ECDC)(大肠杆菌K12的DNA序列汇编) http://susi.bio.uni-giessen.de/ecdc.html7. EcoCyc(大肠杆菌基因及其新陈代谢的百科全书) /ecocyc/ecocyc.html8. Eddy实验室的snoRNA数据库/snoRNAdb/9. GenproEc(大肠杆菌基因及蛋白质) /html/ecoli.html10. NRSub(枯草芽胞杆菌的非冗余数据库) http://pbil.univ-lyonl.fr/nrsub/nrsub.html11. YPD(酿酒酵母蛋白质) /YPDhome.html12. 酵母基因组数据库/Saccharomyces/13. LISTA、LISTA-HOP及LISTA-HON(酵母同源数据库汇编) /14. MPDB(分子探针数据库) http://www.biotech.est.unige.it/interlab/mpdb.html15. tRNA序列及tRNA基因序列汇编http://www.uni-bayreuth.de/departments/biochemie/trna/index/html16. 贝勒医学院(Baylor College of Medicine)的小RNA数据库/dbs/SRPDB/SRPDB.html17. SRPDB(信号识别粒子数据库) /dbs/SRPDB/SRPDB.html18. RDP(核糖体数据库计划) /19. 小核糖体亚蛋白RNA结构http://rrna.uia.ac.be/ssu/index.html20. 大核糖体亚蛋白RNA结构http://rrna.uia.ac.be/lsu/index.html21. RNA修饰数据库/RNAmods/22. 16SMDB及23SMDB(16S和23S核糖体RNA突变数据库)/Departments/Biology/Databases/RNA.html23. SWISS-2DPAGE(二维凝胶电泳数据库) http://expasy.hcuge.ch/ch2d/ch2d-top.html24. PRINTS /bsm/dbbrowser/PRINTS/PRINTS.html25. KabatMan(抗体结构及序列信息数据库) /abs26. ALIGN(蛋白质序列比对一览) /bsm/dbbrowser/ALIGN/ALIGN.html27. CATH(蛋白质结构分类系统) /bsm/cath28. ProDom(蛋白质域数据库) http://protein.toulouse.inra.fr/29. Blocks数据库(蛋白质分类系统) /30. HSSP(按同源性导出的蛋白质二级结构数据库) http://www.sander.embl-heidelberg.de/hssp/31. FSSP(基于结构比对的蛋白质折叠分类) /dali/fssp/fssp.html32. SBASE蛋白质域(已注释的蛋白质序列片断) http://www.icgeb.trieste.it/~sbasessrv/33. TransTerm(翻译控制信号数据库) /Transterm.html34. GRBase(参与基因调控的蛋白质的相关信息数据库) /~regulate/trevgrb.html35. REBASE(限制性内切酶和甲基化酶数据库) /rebase/36. RNaseP数据库/RNaseP/home.html37. REGULONDB(大肠杆菌转录调控数据库) http://www.cifn.unam.mx/Computational_Biology/regulondb/38. TRANSFAC(转录因子及其DNA结合位点数据库) http://transfac.gbf.de/39. MHCPEP(MHC结合肽数据库) .au/mhcpep/40. ATCC(美国菌种保藏中心) /41. 高度保守的核蛋白序列的组蛋白序列数据库/Baxevani/HISTONES42. 3Dee(蛋白质结构域定义数据库) /servers/3Dee.html43. InterPro(蛋白质域以及功能位点的完整资源) /interpro/序列相似性搜索1. EBI序列相似性研究网页/searches/searches.html2. NCBI: BLAST注释/BLAST3. EMBL的BLITZ ULTRA快速搜索/searches/blitz_input.html4. EMBL WWW服务器http://www.embl-heidelberg.de/Services/index.html#55. 蛋白质或核苷酸的模式浏览/compbio/PatScan/HTML/patscan.html6. MEME(蛋白质超二级结构模体发现与研究) /meme/website7. CoreSearch(DNA序列保守元件的识别) http://www.gsf.de/biodv/coresearch.html8. PRINTS/PROSIT浏览(搜索motif数据库) /cgi-bin/attwood/SearchprintsForm.pl9. 苏黎世ETH服务器的DARWIN系统http://cbrg.inf.ethz.ch/10. 利用动态规划找出序列相似性的Pima IIhttp://bmerc-www.bu.ede/protein-seq/pimaII-new.html11. 利用与模式库进行哈希码(hashcode)比较找到序列相似性的DashPat /protein-seq/dashPat-new.html12. PROPSEARCH(基于氨基酸组成的搜索) http://www.embl-heidelberg.de/aaa.html13. 序列搜索协议(集成模式搜索) /bsm/dbbrowser/protocol.html14. ProtoMap(SEISS-PROT中所有蛋白质的自动层次分类) http://www.protomap.cs.huji.ac.il/15. GenQuest(利用Fasta、Blast、Smith-Waterman方法在任意数据库中搜索) http://www.gdb.rog/Dan/gq/gq.form.html16. SSearch(对特定数据库的搜索) http://watson.genes.nig.ac.jp/homology/ssearch-e_help.html17. Peer Bork搜索列表(motif/模式序列谱搜索) http://www.embl-heidelberg.de/~bork/pattern.html18. PROSITE数据库搜索(搜索序列的功能位点) /searches/prosite.html19. PROWL(Skirball研究中心的蛋白质信息检索) /index.html序列和结构的两两比对1. 蛋白质两两比对(SIM) http://expasy.hcuge.ch/sprot/sim-prot.html2. LALNVIEW比对可视化观察程序ftp://expasy.hcuge.ch/pub/lalnview3. BCM搜索装置(两两序列比对) /seq-search/alignment.html4. DALI蛋白质三维结构比较/dali/5. DIALIGN(无间隙罚分的比对程序) http://www.gsf.de/biodv/dialign/html多重序列比对及系统进行树1. ClustalW(BCM的多重序列比对) /multi-align/multi-align.html2. PHYLIP(推测系统进行树的程序) /phylip.html3. 其它系统进行树程序,PHYLIP文档的汇编http://expasy.hcuge.ch/info/phylogeny.html4. 系统进行树分析程序(生命树列表) /tree/programs/programs.html5. 遗传分类学软件(Willi hennig协会提供的列表) /education.html6. 用于多重序列比对的BCM搜索装置/multi-align/multi-align.html7. AMAS(分析多重序列比对中的序列) /servers/amas_server.html8. 维也纳RNA二级结构软件包http://www.tbi.univie.ac.at/~ivo/RNA/四. 有代表性的预测服务器1. PHD蛋白质预测服务器,用于二级结构、水溶性以及跨膜片断的预测http://www.embl-heidelberg.de/predictprotein/predictprotein.html2. PhdThreader(利用逆折叠方法预测、识别折叠类) http://www.embl-heidelberg.de/predictprotein/phd_help.html3. PSIpred(蛋白质结构预测服务器) /psipred4. THREADER(戴维. 琼斯) /~jones/threader.html5. TMHMM(跨膜螺旋蛋白的预测) http://www.cbs.dtu.dk/services/TMHMM/6. 蛋白质结构分析,BMERC /protein-seq/protein-struct.html7. 蛋白质域和折叠预测的提交表http://genome.dkfz-heidelberg.de/nnga/def-query.html8. NNSSP(利用最近相邻法预测蛋白质的二级结构) /pss/pss.html9. Swiss-Model(基于知识的蛋白质自动同源建模服务器) http://www.expasy.ch/swissmod/SWISS-MODEL.html10. SSPRED(用多重序列比对进行二级结构预测) /jong/predict/sspred.html11. 法国IBCP的SOPM(自寻优化预测方法、二级结构) http://pbil.ibcp.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_sopm.html12. TMAP(蛋白质跨膜片断的预测服务) http://www.embl-heidelberg.de/tmap/tmap_info.html13. TMpred(跨膜区域和方向的预测) /software/TMPRED_form.html14. MultPredict(多重序列比对的序列的二级结构) /zpred.html15. BCM搜索装置(蛋白质二级结构预测) /seq-search/struc-predict.html16. COILS(蛋白质的卷曲螺旋区域预测) /software/coils/COILS_doc.html17. Coiled Coils(卷曲螺旋) /depts/biol/units/coils/coilcoil.html18. Paircoil(氨基酸序列中的卷曲螺旋定位) /bab/webcoil.html19. PREDATOR(由单序列预测蛋白质二级结构) http://www.embl-heidelberg.de/argos/predator/predator_info.html20. EV A(蛋白质结构预测服务器的自动评估) /eva/五. 其他预测服务器1. SignalP (革兰氏阳性菌、革兰氏阴性菌和真核生物蛋白质的信号肽及剪切位点) http://www.cbs.dtu.dk/services/SignalP/2. PEDANT(蛋白质提取、描述及分析工具) http://pedant.mips.biochem.mpg.de/六. 分子生物学软件链接1. 生物信息学可视化工具/alan/VisSupp/2. EBI分子生物学软件档案/software/software.html3. BioCatalog /biocat/e-mail_Server_ANAL YSIS.html4. 生物学软件和数据库档案/Dan/softsearch/biol-links.html5. UC Santa Cruz的序列保守性HMM的SAM软件/research/compbio/sam.html七. 网上博士课程1. 生物计算课程资源列表:课程大纲http://www.techfak.uni-bielefeld.de/bcd/Curric/syllabi.html2. 生物序列分析和蛋白质建模的Ph.D课程http://www.cbs.dtu.dk/phdcourse/programme.html3. 分子科学虚拟学校/vsms/sbdd/4. EMBnet 生物计算指南http://biobase.dk/Embnetut/Universl/embnettu.html5. 蛋白质结构的合作课程/PPS/index.html6. 自然科学GNA虚拟学校http://www.techfak.uni-bielefeld.de/bcd/Vsns/index.html7. 分子生物学算法/education/courses/590bi。

Easy5 2020 Reference Manual

Easy5 2020 Reference Manual

For Windows® and Linux®Worldwide WebSupport/Contents/Services/Technical-Support/Contact-Technical-Support.aspxDisclaimerThis documentation, as well as the software described in it, is furnished under license and may be used only in accordance with the terms of such license.MSC Software Corporation reserves the right to make changes in specifications and other information contained in this document without prior notice.The concepts, methods, and examples presented in this text are for illustrative and educational purposes only, and are not intended to be exhaustive or to apply to any particular engineering problem or design. MSC Software Corporation assumes no liability or responsibility to any person or company for direct or indirect damages resulting from the use of any information contained er Documentation: Copyright © 2020 MSC Software Corporation. Printed in U.S.A. All Rights Reserved.This notice shall be marked on any reproduction of this documentation, in whole or in part. Any reproduction or distribution of this document, in whole or in part, without the prior written consent of MSC Software Corporation is prohibited.This software may contain certain third-party software that is protected by copyright and licensed from MSC Software suppliers. Additional terms and conditions and/or notices may apply for certain third party software. Such additional third party software terms and conditions and/or notices may be set forth in documentation and/or at /thirdpartysoftware (or successor website designated by MSC from time to time). Portions of this software are owned by Siemens Product Lifecycle Management, Inc. © Copyright 2020The MSC Software logo, MSC, MSC Adams, MD Adams, Adams and Easy5 are trademarks or registered trademarks of MSC Software Corporation and/or its subsidiaries in the United States and other countries. Hexagon and the Hexagon logo are trademarks or registered trademarks of Hexagon AB and/or its subsidiaries. NASTRAN is a registered trademark of NASA. FLEXlm and FlexNet Publisher are trademarks or registered trademarks of Flexera Software. Parasolid is a registered trademark of Siemens Product Lifecycle Management, Inc. All other trademarks are the property of their respective owners.Use, duplicate, or disclosure by the U.S. Government is subjected to restrictions as set forth in FAR 12.212 (Commercial Computer Software) and DFARS 227.7202 (Commercial Computer Software and Commercial Computer Software Documentation), as applicable.February 12, 2020Corporate Europe, Middle East, AfricaMSC Software Corporation MSC Software GmbH 4675 MacArthur Court, Suite 900Am Moosfeld 13Newport Beach, CA 9266081829 Munich, Germany Telephone: (714) 540-8900Telephone: (49) 89 431 98 70TollFreeNumber:185****7638Email :**********************Email :********************************Japan Asia-PacificMSC Software Japan Ltd.MSC Software (S) Pte. Ltd.Shinjuku First West 8F 100 Beach Road 23-7 Nishi Shinjuku #16-05 Shaw Tower 1-Chome, Shinjuku-Ku Singapore 189702Tokyo 160-0023, JAPAN Telephone: 65-6272-0082Telephone: (81) (3)-6911-1200Email :****************************Email :***************************Documentation FeedbackAt MSC Software, we strive to produce the highest quality documentation and welcome your feedback. If you have comments or suggestions about our documentation, write to us at: documentation-************************.Please include the following information with your feedback:⏹Document name⏹Release/Version number⏹Chapter/Section name⏹Topic title (for Online Help)⏹Brief description of the content (for example, incomplete/incorrect information, grammaticalerrors, information that requires clarification or more details and so on).⏹Your suggestions for correcting/improving documentationYou may also provide your feedback about MSC Software documentation by taking a short 5-minute survey at:.The above mentioned e-mail address is only for providing documentation specificfeedback. If you have any technical problems, issues, or queries, please contact TechnicalSupport.C o n t e n t sReference ManualPrefaceConventions Used in This Guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xviii1 Reference Manual TopicsOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Accelerator Keys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Adding Components. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Add Components Window. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6Adding Components to the Schematic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9Add Components by Name Reference. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Analyses. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Nonlinear Analyses. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11Linear Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Analysis Data Form. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Analysis Data Form Header. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13Analysis Data Form. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Auxiliary Input File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Analysis Title . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15Time of the Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16Initial Operating Point. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16Model Explorer “Pickable” Fields . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17Auxiliary Input File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18Creating an Auxiliary Input File. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18Using an “auxfile” To Enter Blocks of Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19Specifying a Label in an Auxiliary Input File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Auxiliary Input File Data Format . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 PARAMETER VALUES Command. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22Scalar Parameter Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22Array Parameter Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23Tabular Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25“Analysis Only” Mode. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Operations Allowed. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29viReference ManualDisabled Functionality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29Creating a “Locked Configuration” Model for Distribution Purposes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30Using a Locked Configuration Easy5 Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Background Processes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31C Component. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33Adding C Code. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34Example C Code Component . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35Adding C Declarations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37C Code Files and Structure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37Code Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38Command Line Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Option Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Compiling External Code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Default Compiler Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43Obtaining Current Compiler Options. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43Setting Debug Compiler Options. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44User Specified Compiler Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44Examples of Compiling External Code. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44Compiling and Linking Mixed Code. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Components. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 Component Basics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50Blocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53Standard Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53Code Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54User-defined Library Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55Extension Components. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56Dimensioned Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Component Data Table. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Documentation/Configuration Tab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59States Tab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64Variables Tab. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65Version Tab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66User-Comments Tab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Connecting Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Rules for Connecting Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67Default Connections. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67Port Connections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69Default Port Connection Points. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70Custom Connections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71Making a Branch Connection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73Connecting Incompatibly Vectorized Components. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 Connection Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Moving Connection Line Endpoints. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75viiContentsMoving Connection Line Segments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 Changing an Anchored Connection Back to an Autoroute Connection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Customized Line Routing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Defining Connection Line Labels and Attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 Connection Line Navigation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Submodel Connection Labels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Connection Label Options. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Moving Submodel Connection Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 Connection Line Color Dots. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Copying Components and Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 Copying Components within a Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 Copying Components From or To Another Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Copying Components With User-defined Names. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..87 Data Display. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Data Types. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 States. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Parameters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Debugging the Model and Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Example of Using the Symbolic Debugger on Windows. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Example of Using the Symbolic Debugger on a Linux Platform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 Deleting Components and Connections. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 Deleting Components. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 Deleting Connections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 Discrete (Digital) System Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Operating Point Considerations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Linear Analysis Considerations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Integration Method Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 Discrete (Digital) System Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 Digital Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 Hybrid Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Discrete System Modeling Using Fortran, C and LIbrary Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 Matching TAU Method (obsolete). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Documenting and Printing the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 Generating a Model Document File. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 Exporting an Easy5 Model as a MAT EMX Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 MAT function “ezmodel”. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 Easy5 Window . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 Description Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Model Info . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112viiiReference ManualMenu Bar. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112Tool Bar. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112Dockable Add Component WIndow. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112Scroll Bars. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112Message Line. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113Schematic Window . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113Working with Easy5 Windows. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Eigenvalue Sensitivity Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Setting up an Eigenvalue Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Eigenvalue Sensitivity Analysis Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116Executable Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Create Executable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118Link External Object. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119Solve Implicit Loops. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119Force Explicit Typing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119Check for Duplicate Names . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119Debug Mode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119Stop Create Executable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 Executable Output Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 Create Executable Process. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120Model Generation Listing File. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121Executable Source File. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121Executable Error File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 External (Environment) Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123Fortran Component . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 Forced Explicit Typing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128Using Integer or Logical Variables in Fortran Code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129Adding Nonexecutable Fortran Statements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130Reserved Fortran Unit Numbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131Adding Comments to Fortran Code. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131Easy5 Reserved Words. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131Calculating Initial Condition Values in a User-Code Component. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133Easy5 Matrix Operations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133Sorting Fortran Component Code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 Function Scan Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 Setting up a Function Scan Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135Function Scan with Two Independent Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 Function Scan Analysis Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138Graphic Files, EMFs, and PostScript. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 Generating the Schematic Block Diagram EMF Graphics File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138Generating Plotter EMF Graphics File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140Using EMF Graphics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140Overriding Hard copy and EMF Plot Curve and Grid Widths. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141ixContentsExporting Plot Files. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Importing a PostScript File Into a Document . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Icon Editor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Implicit Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 Definition of an Implicit Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Example of an Implicit Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 How to Break Implicit Loops. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 Initial Condition Calculation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 Initialization Statement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Integration Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 The Integration Method. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 Integration Methods Available. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 Definition of Terms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 The BCS Gear Method. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 The Runge-Kutta Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 The Huen Method. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 The Euler Method. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 The Adams Method. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 The User-defined Method. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Integration Method Selection Guidelines. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Guidelines for Setting Error Controls. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 Interactive Simulation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 Linear Model Generation Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 Types of Linear Model Generation Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 Setting up a Linear Model Generation Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 Controlling the Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 Saving the Linear Model System Matrices. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 Linear Model Generation Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 Continuous Systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 Stability Analysis for Sampled-Data Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 Linking External Code. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 Linking Routines Using the Build Menu. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 Linking Routines Using the EASY5_OBJECT Variable. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176 Linking Routines Using an Object Library . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 Linking Library Component Routines. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178 Library Component Code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Using Variable Dimensions in Library Component Code. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Using Integer or Logical Variables in Library Component Code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180 Configurations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 Component Libraries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 Matrix Operations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182。

25845322_《国际中文教育中文水平等级标准》专家解读

25845322_《国际中文教育中文水平等级标准》专家解读

《国际中文教育中文水平等级标准》(GF0025-2021)(以下简称《标准》)经国家语委语言文字规范标准审定委员会审定,2021年3月由教育部、国家语言文字工作委员会发布,作为国家语委语言文字规范自2021年7月1日起正式实施。

以下是《标准》研发组专家对《标准》内容及研发情况做出的部分解读。

Chinese Proficiency Standards for International Chinese Language Education (GF0025-2021) (hereinafter referred to as The Standards) was validated by the Standard Validation Committee of the State Language Commission for Language Specifications and released by the Ministry of Education and the State Language Commission in March 2021. It has been officially implemented as the national language standards since July 1, 2021. The following is an interpretation of The Standards by the experts who participated in its making.H ow long did the preparation of The Standards take? Howmany experts were involved? What was the starting pointand basis for it?At present, 75 countries around the world have included Chinesein their national education systems, more than 4,000 foreignuniversities have offered Chinese language courses, 25 million people have been studying Chinese, and 40 million Chinese language tests have been taken. The international Chinese language education has undergone significant changes in terms of many aspects including its scale and form. In order to further improve international Chinese language education and meet diversified needs of learning, there is an urgent need to introduce a new set of standards that is scientific, inclusive and easy to implement to guide the learning, teaching, testing and assessment of Chinese language, and to provide reference and services for countries around the world to carry out Chinese language education. Since May 2017, commissioned by Center for Language Education and Cooperation, Chinese Testing International has formed a task force of more than 20 experts in related fields from Peking University, Beijing Language and Culture University, Beijing Normal University, Renmin University of China, Capital Normal University, Chinese Academy of Social Sciences, East China Normal University, Shanghai University and other institutions to develop The Standards . The group has consulted more than 80 Chinese and foreign experts and scholars from more than 30 institutions in countries including the United States, the United Kingdom, France, Germany, Japan, Korea, and conducted more than 50 interviews and focused discussions. After three and a half years of discussion and revision, The Standards eventually came into being in early 2021.《标准》从筹备到正式出台,经历了多长时间?有多少专家参与?修改的动机和依据是什么?目前全球已有75个国家将中文纳入国民教育体系,4,000多所国外大学开设了中文课程,2,500多万人学习中文,4,000多万人次参加各类中文考试,国际中文教育的规模、形式等都发生了重大变化。

Quantum Computing for Computer Scientists

Quantum Computing for Computer Scientists

More informationQuantum Computing for Computer ScientistsThe multidisciplinaryfield of quantum computing strives to exploit someof the uncanny aspects of quantum mechanics to expand our computa-tional horizons.Quantum Computing for Computer Scientists takes read-ers on a tour of this fascinating area of cutting-edge research.Writtenin an accessible yet rigorous fashion,this book employs ideas and tech-niques familiar to every student of computer science.The reader is notexpected to have any advanced mathematics or physics background.Af-ter presenting the necessary prerequisites,the material is organized tolook at different aspects of quantum computing from the specific stand-point of computer science.There are chapters on computer architecture,algorithms,programming languages,theoretical computer science,cryp-tography,information theory,and hardware.The text has step-by-stepexamples,more than two hundred exercises with solutions,and program-ming drills that bring the ideas of quantum computing alive for today’scomputer science students and researchers.Noson S.Yanofsky,PhD,is an Associate Professor in the Departmentof Computer and Information Science at Brooklyn College,City Univer-sity of New York and at the PhD Program in Computer Science at TheGraduate Center of CUNY.Mirco A.Mannucci,PhD,is the founder and CEO of HoloMathics,LLC,a research and development company with a focus on innovative mathe-matical modeling.He also serves as Adjunct Professor of Computer Sci-ence at George Mason University and the University of Maryland.QUANTUM COMPUTING FORCOMPUTER SCIENTISTSNoson S.YanofskyBrooklyn College,City University of New YorkandMirco A.MannucciHoloMathics,LLCMore informationMore informationcambridge university pressCambridge,New York,Melbourne,Madrid,Cape Town,Singapore,S˜ao Paulo,DelhiCambridge University Press32Avenue of the Americas,New York,NY10013-2473,USAInformation on this title:/9780521879965C Noson S.Yanofsky and Mirco A.Mannucci2008This publication is in copyright.Subject to statutory exceptionand to the provisions of relevant collective licensing agreements,no reproduction of any part may take place withoutthe written permission of Cambridge University Press.First published2008Printed in the United States of AmericaA catalog record for this publication is available from the British Library.Library of Congress Cataloging in Publication dataYanofsky,Noson S.,1967–Quantum computing for computer scientists/Noson S.Yanofsky andMirco A.Mannucci.p.cm.Includes bibliographical references and index.ISBN978-0-521-87996-5(hardback)1.Quantum computers.I.Mannucci,Mirco A.,1960–II.Title.QA76.889.Y352008004.1–dc222008020507ISBN978-0-521-879965hardbackCambridge University Press has no responsibility forthe persistence or accuracy of URLs for external orthird-party Internet Web sites referred to in this publicationand does not guarantee that any content on suchWeb sites is,or will remain,accurate or appropriate.More informationDedicated toMoishe and Sharon Yanofskyandto the memory ofLuigi and Antonietta MannucciWisdom is one thing:to know the tho u ght by which all things are directed thro u gh allthings.˜Heraclitu s of Ephe s u s(535–475B C E)a s quoted in Dio g ene s Laertiu s’sLives and Opinions of Eminent PhilosophersBook IX,1. More informationMore informationContentsPreface xi1Complex Numbers71.1Basic Definitions81.2The Algebra of Complex Numbers101.3The Geometry of Complex Numbers152Complex Vector Spaces292.1C n as the Primary Example302.2Definitions,Properties,and Examples342.3Basis and Dimension452.4Inner Products and Hilbert Spaces532.5Eigenvalues and Eigenvectors602.6Hermitian and Unitary Matrices622.7Tensor Product of Vector Spaces663The Leap from Classical to Quantum743.1Classical Deterministic Systems743.2Probabilistic Systems793.3Quantum Systems883.4Assembling Systems974Basic Quantum Theory1034.1Quantum States1034.2Observables1154.3Measuring1264.4Dynamics1294.5Assembling Quantum Systems1325Architecture1385.1Bits and Qubits138viiMore informationviii Contents5.2Classical Gates1445.3Reversible Gates1515.4Quantum Gates1586Algorithms1706.1Deutsch’s Algorithm1716.2The Deutsch–Jozsa Algorithm1796.3Simon’s Periodicity Algorithm1876.4Grover’s Search Algorithm1956.5Shor’s Factoring Algorithm2047Programming Languages2207.1Programming in a Quantum World2207.2Quantum Assembly Programming2217.3Toward Higher-Level Quantum Programming2307.4Quantum Computation Before Quantum Computers2378Theoretical Computer Science2398.1Deterministic and Nondeterministic Computations2398.2Probabilistic Computations2468.3Quantum Computations2519Cryptography2629.1Classical Cryptography2629.2Quantum Key Exchange I:The BB84Protocol2689.3Quantum Key Exchange II:The B92Protocol2739.4Quantum Key Exchange III:The EPR Protocol2759.5Quantum Teleportation27710Information Theory28410.1Classical Information and Shannon Entropy28410.2Quantum Information and von Neumann Entropy28810.3Classical and Quantum Data Compression29510.4Error-Correcting Codes30211Hardware30511.1Quantum Hardware:Goals and Challenges30611.2Implementing a Quantum Computer I:Ion Traps31111.3Implementing a Quantum Computer II:Linear Optics31311.4Implementing a Quantum Computer III:NMRand Superconductors31511.5Future of Quantum Ware316Appendix A Historical Bibliography of Quantum Computing319 by Jill CirasellaA.1Reading Scientific Articles319A.2Models of Computation320More informationContents ixA.3Quantum Gates321A.4Quantum Algorithms and Implementations321A.5Quantum Cryptography323A.6Quantum Information323A.7More Milestones?324Appendix B Answers to Selected Exercises325Appendix C Quantum Computing Experiments with MATLAB351C.1Playing with Matlab351C.2Complex Numbers and Matrices351C.3Quantum Computations354Appendix D Keeping Abreast of Quantum News:QuantumComputing on the Web and in the Literature357by Jill CirasellaD.1Keeping Abreast of Popular News357D.2Keeping Abreast of Scientific Literature358D.3The Best Way to Stay Abreast?359Appendix E Selected Topics for Student Presentations360E.1Complex Numbers361E.2Complex Vector Spaces362E.3The Leap from Classical to Quantum363E.4Basic Quantum Theory364E.5Architecture365E.6Algorithms366E.7Programming Languages368E.8Theoretical Computer Science369E.9Cryptography370E.10Information Theory370E.11Hardware371Bibliography373Index381More informationPrefaceQuantum computing is a fascinating newfield at the intersection of computer sci-ence,mathematics,and physics,which strives to harness some of the uncanny as-pects of quantum mechanics to broaden our computational horizons.This bookpresents some of the most exciting and interesting topics in quantum computing.Along the way,there will be some amazing facts about the universe in which we liveand about the very notions of information and computation.The text you hold in your hands has a distinctflavor from most of the other cur-rently available books on quantum computing.First and foremost,we do not assumethat our reader has much of a mathematics or physics background.This book shouldbe readable by anyone who is in or beyond their second year in a computer scienceprogram.We have written this book specifically with computer scientists in mind,and tailored it accordingly:we assume a bare minimum of mathematical sophistica-tion,afirst course in discrete structures,and a healthy level of curiosity.Because thistext was written specifically for computer people,in addition to the many exercisesthroughout the text,we added many programming drills.These are a hands-on,funway of learning the material presented and getting a real feel for the subject.The calculus-phobic reader will be happy to learn that derivatives and integrals are virtually absent from our text.Quite simply,we avoid differentiation,integra-tion,and all higher mathematics by carefully selecting only those topics that arecritical to a basic introduction to quantum computing.Because we are focusing onthe fundamentals of quantum computing,we can restrict ourselves to thefinite-dimensional mathematics that is required.This turns out to be not much more thanmanipulating vectors and matrices with complex entries.Surprisingly enough,thelion’s share of quantum computing can be done without the intricacies of advancedmathematics.Nevertheless,we hasten to stress that this is a technical textbook.We are not writing a popular science book,nor do we substitute hand waving for rigor or math-ematical precision.Most other texts in thefield present a primer on quantum mechanics in all its glory.Many assume some knowledge of classical mechanics.We do not make theseassumptions.We only discuss what is needed for a basic understanding of quantumxiMore informationxii Prefacecomputing as afield of research in its own right,although we cite sources for learningmore about advanced topics.There are some who consider quantum computing to be solely within the do-main of physics.Others think of the subject as purely mathematical.We stress thecomputer science aspect of quantum computing.It is not our intention for this book to be the definitive treatment of quantum computing.There are a few topics that we do not even touch,and there are severalothers that we approach briefly,not exhaustively.As of this writing,the bible ofquantum computing is Nielsen and Chuang’s magnificent Quantum Computing andQuantum Information(2000).Their book contains almost everything known aboutquantum computing at the time of its publication.We would like to think of ourbook as a usefulfirst step that can prepare the reader for that text.FEATURESThis book is almost entirely self-contained.We do not demand that the reader comearmed with a large toolbox of skills.Even the subject of complex numbers,which istaught in high school,is given a fairly comprehensive review.The book contains many solved problems and easy-to-understand descriptions.We do not merely present the theory;rather,we explain it and go through severalexamples.The book also contains many exercises,which we strongly recommendthe serious reader should attempt to solve.There is no substitute for rolling up one’ssleeves and doing some work!We have also incorporated plenty of programming drills throughout our text.These are hands-on exercises that can be carried out on your laptop to gain a betterunderstanding of the concepts presented here(they are also a great way of hav-ing fun).We hasten to point out that we are entirely language-agnostic.The stu-dent should write the programs in the language that feels most comfortable.Weare also paradigm-agnostic.If declarative programming is your favorite method,gofor it.If object-oriented programming is your game,use that.The programmingdrills build on one another.Functions created in one programming drill will be usedand modified in later drills.Furthermore,in Appendix C,we show how to makelittle quantum computing emulators with MATLAB or how to use a ready-madeone.(Our choice of MATLAB was dictated by the fact that it makes very easy-to-build,quick-and-dirty prototypes,thanks to its vast amount of built-in mathematicaltools.)This text appears to be thefirst to handle quantum programming languages in a significant way.Until now,there have been only research papers and a few surveyson the topic.Chapter7describes the basics of this expandingfield:perhaps some ofour readers will be inspired to contribute to quantum programming!This book also contains several appendices that are important for further study:Appendix A takes readers on a tour of major papers in quantum computing.This bibliographical essay was written by Jill Cirasella,Computational SciencesSpecialist at the Brooklyn College Library.In addition to having a master’s de-gree in library and information science,Jill has a master’s degree in logic,forwhich she wrote a thesis on classical and quantum graph algorithms.This dualbackground uniquely qualifies her to suggest and describe further readings.More informationPreface xiii Appendix B contains the answers to some of the exercises in the text.Othersolutions will also be found on the book’s Web page.We strongly urge studentsto do the exercises on their own and then check their answers against ours.Appendix C uses MATLAB,the popular mathematical environment and an es-tablished industry standard,to show how to carry out most of the mathematicaloperations described in this book.MATLAB has scores of routines for manip-ulating complex matrices:we briefly review the most useful ones and show howthe reader can quickly perform a few quantum computing experiments with al-most no effort,using the freely available MATLAB quantum emulator Quack.Appendix D,also by Jill Cirasella,describes how to use online resources to keepup with developments in quantum computing.Quantum computing is a fast-movingfield,and this appendix offers guidelines and tips forfinding relevantarticles and announcements.Appendix E is a list of possible topics for student presentations.We give briefdescriptions of different topics that a student might present before a class of hispeers.We also provide some hints about where to start looking for materials topresent.ORGANIZATIONThe book begins with two chapters of mathematical preliminaries.Chapter1con-tains the basics of complex numbers,and Chapter2deals with complex vectorspaces.Although much of Chapter1is currently taught in high school,we feel thata review is in order.Much of Chapter2will be known by students who have had acourse in linear algebra.We deliberately did not relegate these chapters to an ap-pendix at the end of the book because the mathematics is necessary to understandwhat is really going on.A reader who knows the material can safely skip thefirsttwo chapters.She might want to skim over these chapters and then return to themas a reference,using the index and the table of contents tofind specific topics.Chapter3is a gentle introduction to some of the ideas that will be encountered throughout the rest of the ing simple models and simple matrix multipli-cation,we demonstrate some of the fundamental concepts of quantum mechanics,which are then formally developed in Chapter4.From there,Chapter5presentssome of the basic architecture of quantum computing.Here one willfind the notionsof a qubit(a quantum generalization of a bit)and the quantum analog of logic gates.Once Chapter5is understood,readers can safely proceed to their choice of Chapters6through11.Each chapter takes its title from a typical course offered in acomputer science department.The chapters look at that subfield of quantum com-puting from the perspective of the given course.These chapters are almost totallyindependent of one another.We urge the readers to study the particular chapterthat corresponds to their favorite course.Learn topics that you likefirst.From thereproceed to other chapters.Figure0.1summarizes the dependencies of the chapters.One of the hardest topics tackled in this text is that of considering two quan-tum systems and combining them,or“entangled”quantum systems.This is donemathematically in Section2.7.It is further motivated in Section3.4and formallypresented in Section4.5.The reader might want to look at these sections together.xivPrefaceFigure 0.1.Chapter dependencies.There are many ways this book can be used as a text for a course.We urge instructors to find their own way.May we humbly suggest the following three plans of action:(1)A class that provides some depth might involve the following:Go through Chapters 1,2,3,4,and 5.Armed with that background,study the entirety of Chapter 6(“Algorithms”)in depth.One can spend at least a third of a semester on that chapter.After wrestling a bit with quantum algorithms,the student will get a good feel for the entire enterprise.(2)If breadth is preferred,pick and choose one or two sections from each of the advanced chapters.Such a course might look like this:(1),2,3,4.1,4.4,5,6.1,7.1,9.1,10.1,10.2,and 11.This will permit the student to see the broad outline of quantum computing and then pursue his or her own path.(3)For a more advanced class (a class in which linear algebra and some mathe-matical sophistication is assumed),we recommend that students be told to read Chapters 1,2,and 3on their own.A nice course can then commence with Chapter 4and plow through most of the remainder of the book.If this is being used as a text in a classroom setting,we strongly recommend that the students make presentations.There are selected topics mentioned in Appendix E.There is no substitute for student participation!Although we have tried to include many topics in this text,inevitably some oth-ers had to be left out.Here are a few that we omitted because of space considera-tions:many of the more complicated proofs in Chapter 8,results about oracle computation,the details of the (quantum)Fourier transforms,and the latest hardware implementations.We give references for further study on these,as well as other subjects,throughout the text.More informationMore informationPreface xvANCILLARIESWe are going to maintain a Web page for the text at/∼noson/qctext.html/The Web page will containperiodic updates to the book,links to interesting books and articles on quantum computing,some answers to certain exercises not solved in Appendix B,anderrata.The reader is encouraged to send any and all corrections tonoson@Help us make this textbook better!ACKNOLWEDGMENTSBoth of us had the great privilege of writing our doctoral theses under the gentleguidance of the recently deceased Alex Heller.Professor Heller wrote the follow-ing1about his teacher Samuel“Sammy”Eilenberg and Sammy’s mathematics:As I perceived it,then,Sammy considered that the highest value in mathematicswas to be found,not in specious depth nor in the overcoming of overwhelmingdifficulty,but rather in providing the definitive clarity that would illuminate itsunderlying order.This never-ending struggle to bring out the underlying order of mathematical structures was always Professor Heller’s everlasting goal,and he did his best to passit on to his students.We have gained greatly from his clarity of vision and his viewof mathematics,but we also saw,embodied in a man,the classical and sober ideal ofcontemplative life at its very best.We both remain eternally grateful to him.While at the City University of New York,we also had the privilege of inter-acting with one of the world’s foremost logicians,Professor Rohit Parikh,a manwhose seminal contributions to thefield are only matched by his enduring com-mitment to promote younger researchers’work.Besides opening fascinating vis-tas to us,Professor Parikh encouraged us more than once to follow new directionsof thought.His continued professional and personal guidance are greatly appre-ciated.We both received our Ph.D.’s from the Department of Mathematics in The Graduate Center of the City University of New York.We thank them for providingus with a warm and friendly environment in which to study and learn real mathemat-ics.Thefirst author also thanks the entire Brooklyn College family and,in partic-ular,the Computer and Information Science Department for being supportive andvery helpful in this endeavor.1See page1349of Bass et al.(1998).More informationxvi PrefaceSeveral faculty members of Brooklyn College and The Graduate Center were kind enough to read and comment on parts of this book:Michael Anshel,DavidArnow,Jill Cirasella,Dayton Clark,Eva Cogan,Jim Cox,Scott Dexter,EdgarFeldman,Fred Gardiner,Murray Gross,Chaya Gurwitz,Keith Harrow,JunHu,Yedidyah Langsam,Peter Lesser,Philipp Rothmaler,Chris Steinsvold,AlexSverdlov,Aaron Tenenbaum,Micha Tomkiewicz,Al Vasquez,Gerald Weiss,andPaula Whitlock.Their comments have made this a better text.Thank you all!We were fortunate to have had many students of Brooklyn College and The Graduate Center read and comment on earlier drafts:Shira Abraham,RachelAdler,Ali Assarpour,Aleksander Barkan,Sayeef Bazli,Cheuk Man Chan,WeiChen,Evgenia Dandurova,Phillip Dreizen,C.S.Fahie,Miriam Gutherc,RaveHarpaz,David Herzog,Alex Hoffnung,Matthew P.Johnson,Joel Kammet,SerdarKara,Karen Kletter,Janusz Kusyk,Tiziana Ligorio,Matt Meyer,James Ng,SeverinNgnosse,Eric Pacuit,Jason Schanker,Roman Shenderovsky,Aleksandr Shnayder-man,Rose B.Sigler,Shai Silver,Justin Stallard,Justin Tojeira,John Ma Sang Tsang,Sadia Zahoor,Mark Zelcer,and Xiaowen Zhang.We are indebted to them.Many other people looked over parts or all of the text:Scott Aaronson,Ste-fano Bettelli,Adam Brandenburger,Juan B.Climent,Anita Colvard,Leon Ehren-preis,Michael Greenebaum,Miriam Klein,Eli Kravits,Raphael Magarik,JohnMaiorana,Domenico Napoletani,Vaughan Pratt,Suri Raber,Peter Selinger,EvanSiegel,Thomas Tradler,and Jennifer Whitehead.Their criticism and helpful ideasare deeply appreciated.Thanks to Peter Rohde for creating and making available to everyone his MAT-LAB q-emulator Quack and also for letting us use it in our appendix.We had a gooddeal of fun playing with it,and we hope our readers will too.Besides writing two wonderful appendices,our friendly neighborhood librar-ian,Jill Cirasella,was always just an e-mail away with helpful advice and support.Thanks,Jill!A very special thanks goes to our editor at Cambridge University Press,HeatherBergman,for believing in our project right from the start,for guiding us through thisbook,and for providing endless support in all matters.This book would not existwithout her.Thanks,Heather!We had the good fortune to have a truly stellar editor check much of the text many times.Karen Kletter is a great friend and did a magnificent job.We also ap-preciate that she refrained from killing us every time we handed her altered draftsthat she had previously edited.But,of course,all errors are our own!This book could not have been written without the help of my daughter,Hadas-sah.She added meaning,purpose,and joy.N.S.Y.My dear wife,Rose,and our two wondrous and tireless cats,Ursula and Buster, contributed in no small measure to melting my stress away during the long andpainful hours of writing and editing:to them my gratitude and love.(Ursula is ascientist cat and will read this book.Buster will just shred it with his powerful claws.)M.A.M.。

at89s51

at89s51

AT89S51IntroductionAT89S51 is a popular 8-bit microcontroller from the Atmel family. It belongs to the AT89xx series of microcontrollers and is known for its versatility and wide range of applications. In this documentation, we will explore the various features, specifications, and programming aspects of the AT89S51 microcontroller.FeaturesThe AT89S51 microcontroller boasts of several notable features that make it suitable for a wide range of embedded system applications. Some of the key features of the AT89S51 are:1.8-bit CPU: The AT89S51 is based on an 8-bit CentralProcessing Unit (CPU) architecture, making it capable ofexecuting small to medium-sized programs.2.Flash Memory: The microcontroller comes with aFlash memory of 4KB, which can be reprogrammed formultiple applications. This feature allows for easy andquick updates to the firmware.3.Input/Output Ports: The AT89S51 offers four 8-bitInput/Output (I/O) ports, namely P0, P1, P2, and P3. These ports provide different configurations for interfacing with peripheral devices.4.Timer/Counters: The microcontroller includes two16-bit Timer/Counters, namely Timer/Counter 0 andTimer/Counter 1. These timers can be used for variousapplications like generating precise time delays, eventcounting, or as baud rate generators for serialcommunication.5.Serial Communication: AT89S51 supports full-duplex serial communication through its UART (Universal Asynchronous Receiver/Transmitter) interface. Thisfeature enables communication with other devices usingprotocols like RS232.6.Interrupt System: The AT89S51 comes with aflexible interrupt system that supports both external andinternal interrupts. It allows for efficient handling of time-critical tasks and improves the overall system performance.7.Power Management: The microcontroller hasmultiple power-saving modes, including Idle mode andPower-down mode. These modes help in reducing power consumption, making it ideal for battery-poweredapplications.SpecificationsThe AT89S51 microcontroller has the following specifications:•Operating Voltage: The microcontroller operates at a supply voltage range of 2.7V to 6V.•Clock Frequency: The maximum clock frequency that the AT89S51 can operate at is 33 MHz.•Instruction Set: It supports a wide range of instructions, including arithmetic, logical, and bitwiseoperations, making it suitable for various computational tasks.•Memory: The AT89S51 has a total of 4KB Flash memory for storing program code. Additionally, it has 128 bytes of on-chip RAM for data storage.•I/O Pins: The microcontroller provides a total of 32 I/O pins, which can be configured as input or outputaccording to the application requirements.•Package Options: The AT89S51 microcontroller is available in various package options, including PDIP, PLCC, and TQFP.Programming AT89S51Programming the AT89S51 microcontroller can be done using various programming languages and tools. Some commonly used programming languages for AT89S51 include Assembly language and C. The programming tools include an Integrated Development Environment (IDE), such as KeilµVision, which provides a user-friendly interface for writing, compiling, and debugging the code.The following steps outline the programming process for AT89S51:1.Create a new project in the IDE and select theAT89S51 microcontroller as the target device.2.Write the program code in the selectedprogramming language. The code can include initialization routines, application logic, and interrupt service routines if needed.pile the code using the IDE. The compiler willgenerate the corresponding machine code for themicrocontroller.4.Connect the AT89S51 microcontroller to theprogramming tool (such as a USB programmer) using the appropriate interface.5.Flash the compiled code onto the microcontroller’sFlash memory using the programming tool. This processtransfers the machine code from the computer to themicrocontroller.6.Once the code is successfully flashed onto themicrocontroller, it can be powered on, and the program will start executing.ConclusionIn conclusion, the AT89S51 microcontroller is a versatile and powerful 8-bit microcontroller from the Atmel family. It offers a wide range of features and specifications that make it suitable for various embedded system applications. With its flash memory, extensive I/O capabilities, timer/counters, and interrupt system, the AT89S51 provides a flexible and efficientplatform for developing embedded systems. By following the appropriate programming steps using languages like Assembly or C and a suitable IDE, developers can easily write and flash code onto the AT89S51 microcontroller, enabling them to create innovative and functional electronic projects.。

Design and characterization of bubble-splitting distributor for scaled-out multiphase microreactors

Design and characterization of bubble-splitting distributor for scaled-out multiphase microreactors

Design and characterization of bubble-splitting distributor for scaled-out multiphasemicroreactorsDuong A.Hoang,Cees Haringa,Luis M.Portela,Michiel T.Kreutzer,Chris R.Kleijn,Volkert van Steijn ⇑JM Burgers Centre for TU Delft Process Technology Guidelines on how to operate a bubble-splitting distributor.a r t i c l e i n f o Article history:Received 17June 2013Received in revised form 5August 2013Accepted 14August 2013Available online 2September 2013Keywords:Microbubble Bubble breakup Confinement Numbering upAsymmetric breakupa b s t r a c tThis paper reports an analysis of the parallelized production of bubbles in a microreactor based on the repeated break-up of bubbles at T-junctions linked in series.We address the question how to design and operate such a multi-junction device for the even distribution of bubbles over the exit channels.We study the influence of the three primary sources leading to the uneven distribution of bubbles:(1)nonuniformity in the size of bubbles fed to the distributor,(2)lack of bubble break-up,and (3)asymmetric bubble breakup caused by asymmetries in flow due to fabrication tolerances.Based on our theoretical and experimental analysis,we formulate two guidelines to operate the multi-junction bubble distributor.The device should be operated such that:(i)the capillary number exceeds a critical value at all junctions,Ca >Ca crit ,to ensure that all bubbles break,and (ii)the parameter (l s /w )ÁCa 1/3is sufficiently large,with l s /w the distance between the bubbles normalized by the channel width.More quantitatively,(l s /w )ÁCa 1/3>2for fabrication tolerances below 2%,which are typical for devices made by soft lithography.Furthermore,we address the question whether including a bypass channel around the T-junctions reduces flow asymmetries and corresponding nonuniformities in bubble size.While bubble nonuniformities in devices with and without bypass channels are comparable for fabrication tolerances of a few percent,we find that incorporating a bypass channels does have a beneficial effect for larger fabrication tolerances.The results presented in this paper facilitate the scale-out of bubble-based microreactors.Ó2013Elsevier B.V.All rights reserved.1.IntroductionMultiphase microreactors have emerged as an attractive class of reactors for the production of fine chemicals and pharmaceuticals [1,2],for the synthesis of micro-and nanoparticles [3–7],and for high-throughput screening applications [8–11].Besides excellent heat and mass transfer characteristics in microreactors,continuous flow chemistry basedon the confinement of reactions in picoliter1385-8947/$-see front matter Ó2013Elsevier B.V.All rights reserved./10.1016/j.cej.2013.08.066Corresponding author at:Department of Chemical Engineering,Delft University of Technology,Julianalaan 136,2628BL Delft,The Netherlands.Tel.:+31152787194.E-mail address:v.vansteijn@tudelft.nl (V.van Steijn).to nanoliter bubbles or droplets(a)enhances mixing,(b)reduces axial dispersion,and(c)prevents precipitation at walls and clog-ging of channels such that higher yields and selectivities are ob-tained[10,12].Despite the conceptually simple idea of numbering-up as a strategy to increase throughput,parallelization of segmentedflows remains a challenge in practice[13].One basic approach to in-crease throughput of segmentedflow microreactors is to produce droplets or bubbles in each individual channel[14–24].With a few notable exceptions[25–27],this approach requires that the supply of thefluids to all these channels is identical,as differences inflow lead to corresponding differences in the volume,frequency, and speed of the bubbles or droplets.Integrating resistive channels upstream of the segmentedflow channels minimizes cross-talk be-tween the channels and ensures a constant supply offluids,which is not affected by the dynamic pressurefluctuations in the seg-mentedflow channels[17,28].de Mas et al.[17]showed that the pressure drop over the resistive channels should be two orders of magnitude larger than the pressure drop over the segmentedflow channels.Fulfilling this requirement is particularly challenging for gas–liquidflows,because the low viscosity of gas requires resistive gas channels that are roughly two orders of magnitude smaller in width than the segmentedflow channels.These channels should be fabricated with high precision,as small difference in their hydrodynamic resistance lead to differences in the features of the segmentedflows running in parallel.An alternative approach that does not require on-chip integra-tion of resistive feed channels is to feed a segmentedflow to the chip,and split the bubbles or droplets at a series of successive junc-tions[29–33].To obtain segmentedflows with an identical bubble volume and bubble spacing in all channels downstream the bubble distributor,two key questions need to be addressed:(1)how to en-sure breakup at all junctions,(2)how to minimize asymmetries in flow.Thefirst question can be addressed based on the understand-ing of breakup of bubbles or droplets at single T-junctions. Whether a droplet breaks primarily depends on its length relative to the channel width,l/w,and on the capillary number,Ca[34–39]. Of secondary importance is the viscosity contrast between the two phases[40,41].The second question can be addressed by consider-ing the differences in hydrodynamic resistances of the channels due to fabrication inaccuracies.As well known for single T-junc-tions,a difference in velocity in the two exiting arms leads to the asymmetric breakup of bubbles[34,42–45].Consequently,the size of the bubbles and their distance apart is different in the two exit-ing arms.For a multi-junction device,Adamson et al.[29]identi-fied a second cause for unequalflow distribution:if bubbles enter downstream T-junctions at times that are not precisely coor-dinated,the backpressure generated when the bubbles split causes an imbalance in the pressure drops across the two exiting arms of the upstream T-junctions.This also leads to asymmetries in seg-mentedflows.They showed that this source of variation is reduced by designing the system such that the magnitude of the pressure pulses is negligible with respect to the total pressure drop over the branches.Another clever trick to reduce the influence of pres-sure pulses at downstream T-junctions is to reduce the coupling between the successive T-junctions by incorporating a pressure-equalizer at the T-junctions in the form of a bypass-like structure [32].Although this concept has been demonstrated,no quantative data is available on the influence on this bypass.Summarizing the work done on multi-junction bubble and droplet distributors,we conclude that–although there are some pointers on how to design and operate these devices–there is no systematic study how key operating conditions influence the performance,and to what extend polydispersity is reduced by incorporating a pressure equalizer.In this paper,we start with a discussion on the different design strategies and explain why a design thatfixes the relative length of the bubbles or droplets is favorable over other types of design.We then identify three primary sources leading to the uneven distribu-tion of bubbles and systematically study their influence on the uni-formity of the size of bubbles in the downstream channels of a multi-junction device.Additionally,we quantify to what extend flow asymmetries are reduced with the use of a pressure equalizer. In short,this paper teaches how to design and operate a multi-junction bubble distributor.2.Theory on the design and operation of a multi-junction bubble distributor2.1.DesignNon-breaking bubbles are one of the main sources of polydis-persity.A straightforward approach to ensure breakup at all suc-cessive junctions is to design the network such that l/w and Ca are kept the same at all junctions.Operating the device above the transition line(Ca crit=f(l/w))at thefirst junction then ensures breakup at all successive junctions.But,in the planar networks that are commonly used in thefield of microfluidics Ca and l/w can-not befixed at the same time.This is easily seen from the fact that theflow rate entering a junction hw i v i equals twice theflow rate in the two exiting channels hw i+1v i+1that lead to the next junctions, with h the channel height,w the channel width,v the bubble veloc-ity,and i the index of the junction.Hence,v iþ1¼1w iiþ1v i.Defining the capillary number based on the bubble velocity,the viscosity of the compartments between the bubbles,l,and the interfacialNomenclaturea i design constant for i th junction needed in Eq.(6)(–)b design parameter(–)c interfacial tension(N/m)g fraction of breaking bubbles(–)l dynamic slug viscosity(Pa s)Ca capillary number,l v/c(–)CV coefficient of variation(–)a,b constants in Leshansky’s equation for the critical capil-lary numberC constant needed in Eq.(3)C1ÀC4constants needed in Eq.(4)h channel height of planar device(m)i index of channel or junction(–)l bubble length(m)l bp bypass length(m)l s slug length(m)l average bubble length(m)r(l)standard deviation in bubble length(m)m number of non-breaking bubbles(–)n number of bubbles(–)q volumetricflow rate(m3/s)R hydrodynamic resistance(Pa s/m3)u(x)deviation in parameter xv i average channel velocity(single phaseflow)or bubble velocity(two phaseflow)in the i th generation(m/s)w i channel width of i th generation(m)546 D.A.Hoang et al./Chemical Engineering Journal236(2014)545–554tension,c,according to Ca=l v/c,we hencefind that the capillary number decreases at successive junctions according toCa iþ1¼1w iiþ1Ca i.Similarly,the volume of a bubbleflowing into ajunction$hw i l i equals twice the volume of the daughter droplesleaving the junction$hw i+1l i+1.Hence,l iþ1¼12w iw iþ1l i such that therelative length decreases at successive junctions according tol iþ1=w iþ1¼1w2i2iþ1l i=w i.This simple analysis shows thatfixing Ca re-quires a reduction in width by a factor2in successive junctions, whereas a21/2reduction is needed tofix the relative length l/w [29].Fixed l/w-designs[29]andfixed Ca-designs[30]have both been demonstrated,as well as designs in which the width of the channels isfixed such that both Ca and l/w decrease at successive junctions[34].These three design strategies are illustrated in Fig.1a–c for a network in which segmentedflow is distributed over four channels by breaking the incoming stream of bubbles at two successive generations of T-junctions.Of course,other choices are possible for w i/w i+1=2b,but for the sake of simplicity we limit the discussion to designs with afixed w(b=0,Fig.1a),afixed l/w (b=0.5,Fig.1b),and afixed Ca(b=1,Fig.1c).To compare these different designs,we calculate the values of Ca and l/w required in the feed channel(i)and in the channels downstream of thefirst junction(ii)to obtain a desired Ca and l/w in the output channels(iii).This desired point is indicated by a star in the(l/w,Ca)map sketched in Fig.1d and lies above the transition line.Below this line(shaded area),breakup does not occur.As shown for thefixed width device(b=0),relatively long bubbles or droplets need to be fed to thefirst junction at relatively high Ca.Both these requirements pose a problem,because long droplets or droplets might spontaneously breakup[29],while operating at high Ca leads to the formation of satellites during breakup[30].By contrast,thefixed Ca-design(b=1)requires a feed of short bubbles or droplets to thefirst junction,which are exceedingly difficult to break.For the example discussed here, the bubble length in channels(i)and(ii)is below the required length for pared to thefixed-width andfixed-Ca de-signs,thefixed l/w-design(b=0.5)can be operated at relatively low values of Ca and l/w,while ensuring that breakup occurs at all successive junctions.We therefore focus on thefixed relative length-design in this paper.We conclude this section on the design by illustrating the de-sign methodology for thefixed relative length-design based on a practical example.Suppose one aims to produce a gas–liquid seg-mentedflow in8parallel channels that each have a height and width of50l m,with bubbles having a length of200l m.One then uses a cascade with three generations.For a desired bubble veloc-ity in these exit channels of10cm/s,the corresponding capillary number can be calculated using theflow properties.Taking,for example,a viscosity of1mPa s and an interfacial tension of 5mN/m,Ca=2Â10À2.Knowing the relative length and capillary number in the8exit channels,one calculates the relatively length and capillary number in the channels leading to the T-junctions of the last generation andfinds l/w=4,Ca=2.8Â10À2.To ensure that bubbles break at all junctions of the device,it is sufficient to check whether the capillary number in the channels leading to the last generation of T-junctions is larger than the critical capillary num-ber for the desired relative length l/w=4.As explained later in Sec-tion 4.4,the critical capillary number can be calculated using Ca crit=0.98(l/w)À3.60.After confirming that Ca>Ca crit,the only thing left to do is to calculate the relative length and velocity of the bubbles that need to be fed to the multi-junction device.2.2.OperationThroughout this paper,we quantify the nonuniformity in bub-ble size based on the coefficient of variation CV.Unless stated otherwise,we use the following definition:CV¼rðlÞlð1Þwith l and r(l)the average bubble length and the standard deviation in bubble length.2.2.1.Influence of non-breaking bubbles on size uniformityWe now quantify the influence of non-breaking bubbles on the size uniformity.For a single T-junction,it is straightforward to cal-culate how the polydispersity is influenced in case m out of n incoming bubbles do not break.The coefficient of variation,CV out, of the bubbles leaving the two arms of the T-junction depends on the coefficient of variation,CV in,of the incoming bubbles,and on the breakup fraction defined as g=(nÀm)/n according toCV2outþ1CV2inþ1¼g1ÀgðÞ2þ1ð2ÞTo demonstrate the sensitivity of CV out on the break-up fraction,we calculate CV out for several values of g for the case CV in=0.This shows that1%non-breaking bubbles(g=0.99)already leads to a polydisperse size distribution with a value of CV out=0.07.For5% and10%non-breaking bubbles,the coefficients of variation are 0.15and0.21,respectively.This simple analysis hence shows the importance to ensure that all bubbles break.2.2.2.Influence offlow asymmetries due to fabrication errors on size uniformityEnsuring that all bubbles break is a necessary but not suffi-cient condition to ensure a narrow size distribution.We now fo-cus on the question how asymmetries inflow that are caused by fabrication errors influence the polydispersity.This analysisalso D.A.Hoang et al./Chemical Engineering Journal236(2014)545–554547reveals how polydispersity in bubble size at the exit of the paral-lel channels is influenced by the size uniformity of the bubbles fed to the bubble distributor.For the sake of simplicity,we start the analysis by considering a single T-junction.We hereby con-sider fabrications errors only in the height of the channels.For microchannels fabricated using soft lithography,this assumption is justified by the fact that tolerances in channel width or length are typically much smaller than tolerances in channel height.We assume that the height of one of the exit channels is h Àu (h ),while the height of the second exit channel is h +u (h ).The differ-ence in height leads a difference velocities,v Àu (v )and v +u (v ).Consequently,the lengths of the two daughter droplets follow from (v +u (v ))/(l +u (l ))=(v Àu (v ))/(l Àu (l ))[34].Similarly,the length of the compartments (slugs)between the bubbles or drop-lets after split-up follows from (v +u (v ))/(l s +u (l s ))=(v Àu (v ))/(l s Àu (l s )).For channels of equal length,the number of bubbles and compartments is n Àu (n )and n +u (n )in the channels with higher and lower velocity respectively,according to (v +u (v ))/(v Àu (v ))=(n Àu (n ))/(n +u (n )).To understand how the relative flow asymmetry,u (v )/v ,depends on the relative error in channel height u (h )/h ,the capillary number,the height-to-width ratio of the channel,h /w ,and the dimensionless length of the compart-ment between bubbles,we equate the pressure drop over the two exiting channels.To predict the pressure drop over a channel of width w and height h <w through which n bubbles of length l and n slugs of length l s flow at a velocity v ,we use a similar expression as in Refs.[46–48]D p ¼n 12l l s 1À0:63h 1h2v þnC c 2w þ2h3Ca ðÞ2=3ð3Þwith l the viscosity of the compartments between the bubbles,c the interfacial tension and C an order one constant [46,49,50].We hereby neglect the viscous pressure drop over the gas bubbles,and define the capillary number as Ca =l v /c .Substituting the expressions for the lengths of the bubbles and liquid compartments,the bubble velocity,the number of compartments,and the channel height,we find expressions for the two pressure drops over the two exiting channels.Equating these pressure drops and solving for u (v )/v under the assumption u (v )/v (1yieldsu ðv Þv¼C 3ÀC 1ðÞl sw Ca 1=3þðC 4ÀC 2ÞC 1þC 3ðÞl sCa 1=3ÀðC 2þC 4Þ=3ð4ÞwithC 1¼121À0:63h w 1þu ðh Þh h i w 2h21þu ðh Þh !À2C 2¼2C 1þw h 1þu ðh Þh!À1 !32=3C 3¼121À0:63h w1Àu ðh Þh h i w 2h 21Àu ðh Þh !À2C 4¼2C 1þw 1Àu ðh Þ!À1 !32=3As expected for the single phase limit (long slugs,high velocity)andsmall fabrication errors,this reduces to u ðv Þv %2þ0:63h w 1À0:63h wu ðh Þh.This simple model teaches how a small difference in channel heightleads to asymmetries in flow for a single T-junction.We now extend the analysis to a multi-junction device.For a cascade device with k generations,it is straightforward to show that the coefficient of variation for the bubbles collected at the 2k exiting channels,CV out ,depends on the coefficient of variation ofthe bubbles fed to the device,CV in ,and the asymmetries in flow at the different generations,(u (v )/v )i ,according toCV 2outþ1CV in þ1¼Y k i ¼11þu ðv Þv 2i !ð5ÞWe hereby used the simplifying assumption that the flow asymme-tries at the junctions in the same generation are identical.For thefixed relative length design considered in this study,with narrow-ing channels immediately after the T-junctions,the flow asymme-tries can be written asu ðv Þvi¼C 3ÀC 1ðÞa i l s w ÀÁ0Ca 1=30þðC 4ÀC 2ÞC 1þC 3ðÞa i l sw ÀÁ0Ca 1=30ÀðC 2þC 4Þ=3ð6Þwith a i ¼2Ài =6;l s ÀÁthe dimensionless length of the compartments between the bubbles fed to the multi-junction device,and Ca 0the capillary number based on the velocity in the feed channel.In the three-generation network used in this work,we do not narrow the channel in the third generation,such that a 1=2À1/6,a 2=2À2/6,and a 3=2À5/3.For this design,Fig.2a shows how the uniformity of sizeof the bubbles leaving the 8exit channels depends on ðl s 0=w 0ÞCa 1=3for three values of u (h )/h .For large ðl s 0=w 0ÞCa 1=30,the uniformity of548 D.A.Hoang et al./Chemical Engineering Journal 236(2014)545–554the bubble size is nearly constant and approaches flow uniformitiesfor single phase flow.For ðl s 0=w 0ÞCa 1=3approaching zero,the nonuni-formity sharply increases.The contribution of each generation to the nonuniformitiy in the size of bubbles leaving the device is shown in Fig.2b.This figure shows that flow asymmetries in the final gener-ation of T-junctions are the main cause of nonuniformities in bubble size for the design used in this work.In summary,the model (Eqs.(5)and (6))developed in this section enables one to predict the nonuniformity in bubble size at the exit of a multi-junction device caused by (i)nonunifor-mity in the size of bubbles fed to the distributor,and (ii)differ-ence in channel height due to fabrication errors.We note that this model is different from the model proposed by [29],who identified pressure pulses caused by bubbles entering down-stream channels as the main source of flow asymmetries.Since we consider flows at higher values of the capillary number (Ca >0.01)in this paper,the magnitude of such pressure pulses (c /w )[47],is negligible compared to the pressure drop over a channel (Eq.(3)).We can hence ignore pressure pulses generated by breaking bubbles or bubbles entering the narrowing channel segments.Influence of the bypass.Including a bypass around the T-junction can reduce flow asymmetries considerably.This is easily seen from an analysis based on hydrodynamic resistances as shown in Fig.3.The asymmetry in relative velocity can be expressed in terms of the flow rates,q br and q bl ,in the two branches between the T-junc-tion and the exits of the bypass,as u (v )/v =(q br Àq bl )/(q br +q bl ).It is straightforward to show that the asymmetry in velocity depends on the hydrodynamic resistances of the bypass,the two branches between the T-junction and the exit of the bypass,and the two channels leading to the exit of the device according tou ðv Þv¼R br ÀR bl þR l ÀR r ðÞR b R b þR l þR rR br þR bl þR l þR r ðÞbR b þR l þR rð7ÞFor a bypass with a low resistance (R b ?0),the flow assymmetry hence only depends on the difference in hydrodynamic resistance of the two short branches of the bypass u (v )/v =(R br ÀR bl )/(R br +R bl ).In case no bubbles are present in the short branches except the breaking bubble,flow asymmetries in a bypass device can be approximated by the single phase limit u ðv Þv %2þ0:63h w 1À0:63h wu ðh Þh de-rived before.For distances between the bubbles exceeding the dis-tance between the T-junction and the exit of the bypass (l s >l bp ),we hence expect that the coefficient of variation depends on the fabri-cation inaccuracy and is independent of the conditions as long as the device is operated above the critical capillary number.It is important to note that for slugs shorter than the length of the by-pass (l s <l bp ),bubbles preceeding the breaking bubble likely block the exit of the bypass.With the bypass shut off under these condi-tions,devices with and without a bypass obviously yield the same coefficient of variation.3.ExperimentalWe fabricated our devices in PDMS using standard soft lithogra-phy techniques [51].Channels are sealed against PDMS coated glass slides using an air plasma.The devices consist of a T-junction bubble maker,an additional liquid inlet,and three generations of T-junctions as shown in Fig.4a and b.While the size of the bubbles is controlled by the flow rate of gas q G and liquid q L injected at the bubble maker,the velocity or distance between the bubbles is con-trolled using a second liquid stream q L 2injected from the side channel shown in Fig.4a.We used a fixed relative length design to study the distribution of bubbles over the eight parallel exit chan-nels.The width of the feed channel is w 0=100l m.To fix the rela-tive length of the droplets,we narrowed the channels leading to the second and third generation of T-junctions to w 1=71l m and w 2=50l m,respectively.The fabrication inaccuracy in the widths of the channels is below 1l m.To quantify the effect of pressure equalizers,we studied the distribution of bubbles in devices with-out and with bypass channels around the T-junctions (Fig.4c).The height of the channels in the devices with and without bypass were h =41±1l m and h =43±1l m,respectively.We complementedbypassl bpFig.3.A bypass channel around in flow.This can be understood from analogy with the electrical circuit (b)(c)bypass12345678(a)q L2q Lq GA steady stream of bubbles is produced at a T-junction from a liquid injected at flow rates q G and q L .The additional liquid stream side channel at a rate q L 2enables the independent control of the the bubbles and their distance apart.Once spaced out,the bubbles distributed over 8parallel channels by splitting them at three successive (b)and with (c)a bypass channel.Scale bars:500l m.D.A.Hoang et al./Chemical Engineering Journal 236(2014)545–554549the experiments in the multi-junction devices with experiments performed in single T-junctions to reveal the influence of the height-to-width ratio of the channels on the transition line be-tween breakup and non-breakup.We used three single T-junction splitters with aspect ratios of h/w=0.27,0.59and0.94.We used HFE-7500(3M,l=1.2mPa s,c=16.2mN/m)and air as workingfluids,without the addition of surfactants.The liquid flow rates were controlled using two individual syringe pumps (Harvard pico plus11).Theflow rates were in the range 3<q L<20l m/min and4<q L2<100l m/min.A steady airflow was supplied from afixed pressure source and controlled using a reducing valve in the range between2and6bar.Air was injected into the microfluidic device through a4À7m long capillary tube with internal diameter of25l m.The pressure drop over this tube is much larger than the pressure drop over the chip.This ensures a steady airflow rate,which is independent of(temporal)events in the chip such as bubble breakup.We confirm that for the range of gas and liquidflow rates used in this work,we did not observefluc-tuations in the speed of bubbles caused by pressurefluctuations arising from the gas pressure source or the mechanics of the syr-inge pump.To image theflow,we used a high speed camera(Phan-tom V9.1,Vision Research)attached to an inverted microscope (Axiovert200M,Zeiss).We extracted the length of the bubbles, their distance apart,and their velocity from the images.We used a magnification and frame rate such that the inaccuracy in the length and velocity measurements is below2%.4.Results4.1.Influence of non-breaking bubbles on size uniformityIn afirst set of experiments,we studied the influence of non-breaking bubbles on size uniformity.To study this influence separately from the influence offlow asymmetries caused by fab-rication inaccuracies,we operated the device at sufficiently largevalues ofðl s=wÞ0ÁCa1=3such that the contribution offlow asymme-tries to the coefficient of variation is negligible.For typical fabrica-tion inaccuracies in this work(u(h)/h<0.02),this requires that weoperated the device beyondðl s=wÞ0ÁCa1=3>1:75as can be seenfrom Fig.2b.Based on the model in Section2.2.1,we expect that the coeffi-cient of variation is small in case all bubbles break(g=1).This, in turn,is expected when the device is operated such that the cap-illary number is beyond the critical capillary number at all T-junc-tions.For thefixed relative length design used in this study,the capillary number,Ca2,at thefinal generation of T-junctions is the smallest.We hence expect small coefficients of variation for Ca2> Ca crit.By contrast,CV out is expected to sharply increase for decreas-ing g.We tested these hypotheses by measuring CV out as a function of Ca.To this end,we recorded movies at the eight exit channels and measured the length of all bubblesflowing through each exit channel for a given time window.We adjusted Ca such that the length of the bubbles in the feed stream is comparable in all exper-iments(3.1<l0/w0<3.8).We used the average bubble lengths measured upstream of the last junctions to calculate the critical va-lue of the capillary number for each experiment based on Leshan-sky’s relation Ca crit=a(l/w)b,where we used a=0.98and b=À3.60as explained later in Section4.4.For capillary numbers below the critical capillary number,we indeedfind that a significant fraction of bubbles fed to the distrib-utor does not breakup as illustrated in the snapshot of the eight exit channels in Fig.5a.By contrast,all bubbles break(g=1)when operating the device beyond the critical capillary number(Fig.5b). The corresponding histograms of the bubble length measured at the eight exit channels show a large spread in bubble length for Ca<Ca crit,while a narrow size distribution is obtained for Ca>Ca crit as shown in Fig.5c.For these two examples,the corresponding values of the coefficient of variation based on all bubbles leaving the device are CV out=0.21and CV out=0.05, respectively.In addition to the two examples shown in Fig.5a,we further illustrate the influence of Ca on CV out for a wider range of Ca/Ca crit. For Ca2/Ca crit>1,wefind that the coefficient of variation is small(a)12345678(b)(c)exit 1exit 2100200300400exit 3exit 443012exit 6exit 7exit 8exit 5100200300400100200300400400NNNη =0.62η = 1η = 1η = 0.62η = 1η = 0.62η = 1η = 0.62η = 1η = 0.62η = 1η = 0.62η = 1η = 0.62η = 1η = 1500 μm500 μm4301243012430124301243012550 D.A.Hoang et al./Chemical Engineering Journal236(2014)545–554。

Handwritten Digit Recognition with a Back-propagation Network

Handwritten Digit Recognition with a Back-propagation Network
1 INTRODUCTION
The main point of this paper is to show that large back-propagation (BP) networks can be applied to real image-recognition problems without a large, complex preprocessing stage requiring detailed engineering. Unlike most previous work on the subject (Denker et al., 1989), the learning network is directly fed with images, rather than feature vectors, thus demonstrating the ability of BP networks to deal with large amounts of low level information. Previous work performed on simple digit images (Le Cun, 1989) showed that the architecture of the network strongly in uences the network's generalization ability. Good generalization can only be obtained by designing a network architecture that contains a certain amount of a priori knowledge about the problem. The basic design principle is to minimize the number of free parameters that must be determined by the learning algorithm, without overly reducing the computational power of the network. This principle increases the probability of correct generalization because

二分法的英文解释

二分法的英文解释

二分法的英文解释The binary search algorithm is a fundamental concept in computer science and mathematics. It is a powerful and efficient technique used to locate a specific item within a sorted collection of data. In this article, we will delve into the details of the binary search algorithm, exploring its mechanics, applications, and complexities.At its core, the binary search algorithm operates by repeatedly dividing the search interval in half. It begins by comparing the target value with the middle element of the array. If the target value matches the middle element, the search is complete, and the index of the element is returned. If the target value is less than the middle element, the search continues in the lower half of the array. Conversely, if the target value is greater than the middle element, the search proceeds in the upper half of the array. This process is repeated until the target value is found or until the search interval is empty.One of the key requirements for the binary search algorithm to work is that the data collection must be sorted in ascending order. This prerequisite enables the algorithm to exploit the properties of the sorted array, significantly reducing the search space with each iteration. By systematically eliminating half of the remaining elements at each step, binary search achieves a logarithmic time complexity of O(log n), where n is the number of elements in the array. This efficiency makes binary search particularly suitable for large datasets where linear search algorithms would be impractical.The binary search algorithm finds its applications in various domains, including but not limited to:1. Searching: Binary search is commonly used to quickly locate elements in sorted arrays or lists. Its efficiency makes it indispensable for tasks such as searching phone directories, dictionaries, or databases.2. Sorting: While binary search itself is not a sorting algorithm, it can be combined with sorting algorithms like merge sort or quicksort to efficiently search for elements in sorted arrays.3. Computer Science: Binary search serves as a foundational concept in computer science education, providing students with a fundamental understanding of algorithm design and analysis.4. Game Development: Binary search is utilized in game development for tasks such as collision detection, pathfinding, and AI decision-making.Despite its efficiency and versatility, binary search does have certain limitations. One significant constraint is that the data collection must be sorted beforehand, which can incur additional preprocessing overhead. Additionally, binary search is not well-suited for dynamic datasets that frequently change, as maintaining the sorted order becomes non-trivial.In conclusion, the binary search algorithm is a powerful tool for efficiently locating elements within sorted arrays. Its logarithmic time complexity and widespread applications make it a fundamental concept in computer science and mathematics. By dividing the search space in half with each iteration, binary search demonstrates the elegance and efficiency of algorithmic design. Whether used in searching, sorting, or other computational tasks, the binary search algorithm remains a cornerstone of algorithmic problem-solving.。

英文原文-小波变换

英文原文-小波变换

The Wavelet TransformThe Wavelet Transform is the new realm of a quick development in current mathematics, the theories is deep and apply very extensively.The concept of small wave transformation is BE been engaged in engineer J.Morlet of petroleum signal processing to put forward first in 1974 beginning of years by France, passed the keeping of physics effective demand of view and signal processing to empirically build up anti- play formula, could not get the approbation of mathematician at that time.Just such as 1807 France of hot learn engineer J.B.J.Fourier to put forward any functions can launch into the creative concept of the endless series of triangle function can not get famous mathematician grange, the approbation of place and A.M.Legendre is similar.Lucky of BE, as early as 70's, A.Calderon means the detection of axioms and Hardy space of atom the resolving did to theoretically prepare for the birth of small wave transformation with the thorough research of unconditional radicle, and J.O.Stromberg still constructed history the top is similar to the small wave in now very much radicle;Famous mathematician Y.Meyer by chance constructs a real small wave of in 1986 radicle, and cooperates with S.Mallat to build up the approval method of constructing the small wave radicle Zao after many dimensionses are analytical, small the wave analysis just start developing rapidly, among them, female mathematician I.Daubechies in Belgium composes of 《small wave ten speak(Ten Lectures on Wavelets) 》have an important push function to the universality of the small wave.It and Fourier transformation and window way Fourier the transformation(Gabor transformation) compares, these are a time and area transformation in the bureau of frequency, as a result can effectively withdraw an information from the signal, pass stretch and shrink to peaceably move to wait operation function to carry on many many difficult problems that the transformations that the dimensionses are thin to turn analysis(Multiscale Analysis), solve Fourier can not work out to the function or the signal, thus small wave the variety is praised as "mathematics microscope", it is the progresses of concordance analysis the development history top milestone type.The application of small wave analysis is to study with the theories of small wave analysis closely and combine together.Now, it has already obtained achievement that make person's focus attention in science and technology information industry realm.The electronics information technique is a realm of importance in six great high new techniques, its important aspect is portrait and signal processing.At present, the signal processing has already become the importance part that contemporary science technique works, the signal handles of purpose be:Accurate analysis, diagnosis, code compression and quantity to turn, quickly deliver or saving, by the square weigh to reach.(or instauration)Seeing from mathematics ground angle, signal and portrait processing can unify to see make is a signal processing(the portrait can see make is a two-dimensional signal),in small many applications of wave analytically many analysises, can return knot to handle a problem for signal.Now, is a stable constant signal to its property with the fulfillment, the ideal tool of processing still keeps being a Fu to sign leaf's analysis.But at physically applied in of the great majority signal right and wrong stabilize of, but be specially applicable to tool of stabilizing the signal not be small wave analysis.In fact the applied realm of small wave analysis is pretty much extensive, it includes:Many academicses of mathematics realm;Signal analytical, portrait processing;Quantum mechanics, theories physics;The military electronics resists to turn with the intelligence of weapon;Calculator classification with identify;The artificial of music and language synthesizes;The medical science becomes to be like and diagnoses;The earthquake investigates to explore a data processing;The breakdown diagnosis of the large machine etc.;For example, in mathematics, it has already used for number analysis,Construct the rapid number method, curve curved face structure, differential equation to solve, control theory etc..Analyze the filtering of aspect wave, Zao voice and compress, deliver etc. in the signal.The portrait compression, classification that handles aspect in the portrait, identify and diagnose, go to dirty wait.The decrease B that becomes to be like aspect in the medical science is super, CT, nuclear magnetic resonance become be like of time, raise a resolution etc..The Wavelet Transform is used for signal and portrait compression are small waves are an important aspect that analyzes an application.Its characteristics is to compress a ratio Gao, compress speed quick, compression behind can keep signal is as constant as the characteristic of portrait, and in the middle of delivering can with the anti- interference.Have a lot of methods according to the compression of small wave analysis, a little bit successfully have small wave radicle method with best pack, small wave area veins model method, small wave transformation zero trees compress, the small wave transformation vector compresses etc..The Wavelet Transform in the signal in of the application is also very extensive.It can used for a handling of boundary and filter wave, repeatedly analytical, letter the Zao separate and withdraw weak signal, beg identifying of form index number, signal and diagnosis and many dimensions edges in cent to examine...etc..The application in engineering technique etc..Include calculator sense of vision, calculator sketch to learn, the research and biomedical science in the curve design, swift flow and long range cosmos.Correspondby letter in the video frequency in, video frequency's coding a technique not only has to have the coding efficiency of Gao and it is born code of to flow to have various flexible.In this research realm, flow out to appear many new coding thoughts and technique, code calculate way according to the video frequency of the small wave transformation among them be have much of one of the technique of development foreground.This text carries on a classification research to the smallwave the area video frequency coding calculate way of typical model in the cultural heritage and get a dissimilarity of according to the function analysis of the video frequency coding calculate way of small wave transformation.The merit and shortcoming that contrast analysis calculate way respectively, point out small wave the area video frequency codes calculate way of research direction.The small wave transformation is a kind of tool, it data, function or calculate son to cut up into the composition of different frequency, then study with the method of decomposition to in response to under the dimensions of composition.This technical earlier period work is a difference to independently make in each research realm with different:Such as be engaged in an in harmony with analysis research in pure mathematics of just d Jia the atom of the ∞(1964) resolve;The physical educational circles hands the A Y ou of matter quantum mechanics research Ksen and a flock that Klander(1968) constructs concern with Tai and also have research hydrogen Paul of the atom man airtight Er function;(1985)The engineering field is like the design(1977) of nd to qMF filter of Estebarl and G Y ou, later on Sn, -th and Bam Ⅵtell(1986) vetterli(1986) the fork studied to have to strictly weigh to reach OMF of the characteristic a filter in the electrical engineering. the J M(1983) formally put forward the concept of small wave in the analysis in the earthquake data.About five in the last yearses, people carried on each above-mentioned work made by realm to synthesize and made it become a kind of method of without loss of generality that can be applicable to each realm.Let us temporary analyze a small wave method inside the scope to carry on a discussion in the signal.Signal at the small wave transformation(for example.the voice exert the flapping of pressure on the ear drum) in the area is decided by two three quantities:The dimensions(or frequency) in time:When the small Du transformation is 1 kind repeatedly the part repeatedly positioned while turning or being called of tool, this book the l chapter will relate repeatedly fixed position of meaning and it causes a person door biggest the reason of interest, afterward will carry on a description to the small wave of different model.。

Tutorial_Guide_IGG_82_1-Acrov5

Tutorial_Guide_IGG_82_1-Acrov5

TutorialsIGG™ v8.aDocumentation v8.aNUMECA International5, Avenue Franklin Roosevelt1050 BrusselsBelgiumTel: +32 2 647.83.11Fax: +32 2 647.93.98Web: ContentsTABLE OF CONTENTINTRODUCTIONTUTORIAL 1: Geometry Creation1-1 INTRODUCTION1-11-1.1 Introduction1-11-1.2 Prerequisites1-21-1.3 Preparation1-21-2 CARTESIAN POINT1-31-2.1 Create Cartesian Point1-31-2.2 Select Cartesian Point1-31-2.3 Delete Cartesian Point1-31-3 CURVES1-31-3.1 Create Curves1-31-3.2 Select Curves1-51-3.3 Visualize Curves1-51-3.4 Modify Curves1-61-3.5 Edit/Copy Curves1-71-3.6 Export Curves1-71-3 SURFACES1-81-3.1 Create Surfaces1-81-3.2 Select Surfaces1-101-3.3 Visualize Surfaces1-101-3.4 Modify Surfaces1-111-3.5 Edit/Copy Surfaces1-111-3.6 Export Surfaces1-11 TUTORIAL 2: 2D Airfoil Mesh Generation2-1 INTRODUCTION2-12-1.1 Introduction2-12-1.2 Prerequisites2-22-1.3 Presentation2-22-1.4 Preparation2-22-2 MESH GENERATION2-32-2.1 Define Project Configuration2-42-2.2 Define Geometry2-52-2.3 Create Blocks2-62-2.4 Define Clustering2-112-2.5 Generate Face Grid2-142-2.6 Control Mesh Quality2-162-2.7 Define Boundary Conditions2-172-2.8 Save Project2-18ContentsTUTORIAL 3: Pipe to Pipe Mesh Generation3-1 INTRODUCTION3-13-1.1 Introduction3-13-1.2 Prerequisites3-23-1.3 Presentation3-23-1.4 Preparation3-23-2 MESH GENERATION3-33-2.1 Define Geometry3-33-2.2 Create & Control Blocks3-53-2.3 Generate Block Grid3-133-2.4 Define Butterfly Topology3-143-2.5 Control Mesh Quality3-163-2.6 Define Boundary Conditions3-183-2.7 Define Full Non Matching Connection3-193-2.8 Save Project3-20TUTORIAL 4: Volute Mesh Generation4-1 INTRODUCTION4-14-1.1 Introduction4-14-1.2 Prerequisites4-24-1.3 Presentation4-24-1.4 Preparation4-24-2 MESH GENERATION4-34-2.1 Load Geometry4-34-2.2 Create & Control Blocks4-44-2.3 Generate Block Grid4-184-2.4 Control Mesh Quality4-194-2.5 Define Boundary Conditions4-204-2.6 Define Full Non Matching Connection4-224-2.7 Save Project4-23TUTORIAL 5: Axi Seal Leakage Mesh Generation5-1 INTRODUCTION5-15-1.1 Introduction5-15-1.2 Prerequisites5-25-1.3 Presentation5-25-1.4 Preparation5-25-2 MESH GENERATION5-35-2.1 Define Project Configuration5-35-2.2 Import Geometry5-45-2.3 Create & Control Blocks5-45-2.4 Define Clustering5-105-2.5 Control Mesh Quality5-135-2.6 Define Boundary Conditions5-155-2.7 Save Project5-18What’s in This Guide ?This Tutorial Guide contains a number of tutorials driving the user in IGG™ v8 to mesh different internal and external configurations. In each tutorial, features related to mesh generation are dem-onstrated.Tutorials 1 to 5 are detailed tutorials designed to introduce the beginner to IGG™ v8. These tutori-als provide explicit instructions for all steps of the mesh generation process. Tutorials 1 to 5 do not require any pre-requisite and can be treated separately, in any order. They address different types of applications, including both internal and external cases.Where to Find the Files Used in the Tutorials ?Each of the mesh generation starts from a geometry that is existing or is created. The appropriate files (and any other relevant files used in the tutorial) are stored on IGG™ v8 DVD-ROM, more precisely in the /DOC/_Tutorials directory.How to Use this Guide ?Depending upon your familiarity with computational fluid dynamics and your interest in some par-ticular configuration, you can use this tutorial guide in a variety of ways.For the BeginnerIf you are beginning user of IGG™, you should first read and solve tutorials 1 and 2, in order to familiarize yourself with the interface and basis of the mesh generation technique. You may then want to concentrate on a tutorial that demonstrates features that you are going to resolve. For exam-ple, if you are planning to mesh a volute, you should look at tutorial 4.For the Experienced UserIf you are an experienced user of IGG™, you can read and/or solve the tutorial(s) that demonstrate features that you are going to resolve. For example, if you plan to mesh a 2D airfoil, you should look at tutorial 2.Conventions Used in this GuideSeveral conventions are used in the tutorials to facilitate your learning process.Following a short introduction, each tutorial is divided into sections respectively related to the mesh generation steps from the geometry definition to the 3D mesh generation.Inputs required to execute the tutorials are restricted to the geometry, either in a ".dat" or CAD related format.The sequence of actions to be executed are described through a step-by-step approach, in the form of arabic numbers.Additional insight about some specific actions and/or features is frequently added to illustrate the tutorial further. This information is proposed for the purpose of clarity and completeness, and should not be executed. It appears in italicized type.Contact NUMECA support team at +32-2-647.83.11 or send an e-mail to sup-port@numeca.be for any question or information you may require. To allowNUMECA support to help you out within the shortest delays, please provide adetailed description of the observed behaviour and performed analysis.TUTORIAL 1:Geometry Creation1-1Introduction1-1.1IntroductionThe resolution of computational fluid dynamics (CFD) problems involves three main steps:•spatial discretization of the flow equations,•flow computation,•visualization of the results.To answer these questions, NUMECA has developed a F low IN tegrated E nvironment for internaland Turbomachinery assimilations. Called FINE™/Turbo, the environment integrates the followingtools:•IGG™ is an I nteractive G eometry modeler and G rid generator software, based on structured multi-block techniques,•AutoGrid™ is a three-dimensional Automated Grid generation software, dedicated to turboma-chinery applications. Similarly to IGG™, it is based on structured multi-block techniques,•Euranus is a state-of-the-art multi-block flow solver, able to simulate Euler and Navier-Stokes equations in the laminar, transitional and turbulent regimes,•CFView™ is a highly interactive flow visualization and post-treatment software,•FINE™ Graphical User Interface is a user-friendly environment that includes the different soft-wares. It integrates the concept of projects and allows the user to achieve complete simulations,going from the grid generation to the flow visualization, without the need of file manipulation.This tutorial is particularly adapted to the creation and modification of geometrical entities. Itmakes exclusive use of IGG™.In this tutorial you will learn how to:•Create Cartesian point,•Create and modify curve entities,•Create and modify surface entities,•Select and delete geometrical entities,Geometry Creation Introduction•Group/ungroup geometrical entities,•Save geometrical entities.1-1.2PrerequisitesThis tutorial does not require any particular prerequisite.1-1.3Preparation•Copy the files located in cdrom:\DOC\_Tutorials\IGG\Tutorial_1 to your working directory, where cdrom must be replaced by the name of your DVD-ROM.•Start IGG™ v8.xFor LINUX and UNIX systems, you can access IGG™ v8.x graphical user interface with thefollowing command lineigg -niversion 8x -print or igg -niversion autogrid8x -printFor WINDOWS systems, you can access IGG™ v8.x graphical user interface from the startmenu going to /Programs/NUMECA software/fine8x/IGG or /Programs/NUMECA software/autogrid8x/IGGMenu BarTool Bar3D ViewQuick Access PadControl Areakeyboard input areainformation areaYou’re now ready to start to create and modify geometrical entities!IGG™ v8 graphical user interface allows to visualize the geometry and mesh of the internal orexternal test case in a 3D view by default. The access to main menu and controls is proposedthrough a menu bar and a quick access pad, and is completed with a tool/icon bar and a control area(including the keyboard input area).Cartesian Point Geometry Creation1-2Cartesian Point1-2.1Create Cartesian Point1.Select the Geometry/Create Points/Cartesian Point menu to initiate the creation of aCartesian point2.Type the sequence <1 1 0> <Enter> in the keyboard input area. This action will create theCartesian point (black or white point is appearing in the graphics area)Cartesian points can also be defined as intersection between two selectedcurves or between a selected curve and a plane or between a selected curveand a surface (see User Manual for more details).3.Select the Geometry/Create Points/Cartesian Point menu to initiate the creation of a sec-ond Cartesian point4.Type the sequence <1 1 1> <Enter> in the keyboard input area. This action will create thesecond Cartesian point (second black or white point is appearing in the graphics area) 1-2.2Select Cartesian Point5.Select the Geometry/Select/Cartesian Points menu to select Cartesian points6.Move the mouse on the Cartesian point (1,1,1) and click-left on it when highlighted in blueto select it7.Click-right or <q> in the graphics area to end the selection1-2.3Delete Cartesian Point8.Select the Geometry/Delete/Cartesian Points menu to delete the selected Cartesian points(highlighted in blue)1-3Curves1-3.1Create CurvesThe following section describes how to:—create basic curves—use the keyboard or the mouse to input points—use the attraction featureThe below geometry, consisting of two polylines, one C-spline and one arc, will be created.Geometry Creation Curves9.Define a polyline curve:•Select the Geometry/Draw Polyline/Free menu (shortcut <p >) to initiate the creation of a polyline•Type the sequence <1 0 0> <Enter > in the keyboard input area . This action will create thefirst point of the polylineThe keystrokes are automatically echoed in the keyboard input area.•Enter a second point at position <1.2 0.5 0> and press <Enter >•Move the mouse near the Cartesian point. When close enough, the mouse will normally beattracted to this point if the attraction to points feature is enabled. If there is no attraction,press <a > in the graphics area. Then click-left to add this point to the polyline•Click-right or <q > in the graphics area to end the polyline creation•Repeat above steps to create another polyline passing through the points (0,0,0), (-0.2,0.5,0)and (0,1,0)10.Define a C-spline curve:•Select the Geometry/Draw CSpline/Free menu (shortcut <c >) to initiate the creation of aC-spline curve•Move the mouse near the point (0,0,0) of the second polyline. When close enough, themouse will normally be attracted to this point if the attraction to points feature is enabled. If there is no attraction, press <a > in the graphics area. Then click-left to add this point to the C-spline•Move the mouse somewhere between the points (0,0,0) and (1,0,0) and click-left to add apoint•Move the mouse near the point (1,0,0) of the first polyline. When close enough, the mousewill normally be attracted to this point if the attraction to points feature is enabled. If there is no attraction, press <a > in the graphics area. Then click-left to add this point to the C-spline•Click-right or <q > in the graphics area to end the C-spline creation11.Define a circular arc curve:•Select the Geometry/Circular Arc/Normal-Point-Point-Radius menu option to initiatethe creation of a circular arc. Several inputs will be requested to define the arcThe circular arc can be created using different methods (see User Manual for more details).•Enter <0 0 1> <Enter > to define the arc normalpolyline 1polyline2C-splinearcCurves Geometry Creation •Move the mouse near the Cartesian point. When close enough the point will be highlighted (if there is no attraction, press <a> in the graphics area). Click-left to define the arc startpoint•Move the mouse near the point (0,1,0) of the second polyline. When close enough the point will be highlighted (if there is no attraction, press <a> in the graphics area). Click-left todefine the arc end point•Enter <0.6> <Enter> to define the arc radius•Press <o> until the circle has the same shape as the one presented on above figure. Then click-left to create the arcClick-right or <q> in the graphics area to end the arc creation.1-3.2Select CurvesThe curve selection operation is used to activate one or more curves for subsequent operations ingeometry modelling or grid generation. When a curve is selected it appears highlighted in yellow(default). All the curves created in the previous steps are selected.12.Select the Geometry/Select/Curves option to initiate curve(s) selectionThe shortcut <s> can also be used to activate the option without accessing themenu.13.Press <a> to unselect all the curves, which become unhighlighted14.Move the mouse over the C-spline which is then highlighted. At the same time, the name,type of curve and approximate arc length of the curve appear in the information area15.Click-left to select it16.Repeat above step to select the first created polyline17.Click-right to quit the selectionSelection and deselection of all curves can be done by pressing <a> repeat-edly (toggle option).1-3.3Visualize CurvesWhen importing complex models, many curves may be created and visualized in IGG™, makingthe graphics unclear. It is possible to visualize only specific curves on the screen, hiding all others,in the following way:18.Select the Geometry/View/Curves option. A curve chooser appears with the name of allthe curves. All the names are highlighted since all the curves are visible19.Select the C-spline in the chooser (click-left on it) and press Apply. Only the C-splinecurve now appears in the view20.Select the first polyline in the chooser (click-left on it) while holding the <Ctrl> key. Thepolyline is highlighted in the chooser, together with the C-spline. Press Apply to visualizeboth curves21.Select the first and last curves in the chooser while holding the <Shift> key. All the curvesare now selected. Press Apply to visualize them all22.Close the chooserAfter selecting the curves by using the Geometry/Select/Curves menu, the selected curves can befurther investigated in the following way:Geometry Creation Curves23.Select the Geometry/View/Curve Orientation menu. The default orientation of theselected curves is shown. This orientation is important for other geometry modelling andgrid generation operations. These orientations can be hidden by selecting the menu onceagain (toggle option)24.Select the Geometry/View/Control Points menu. The control points of the selected curvesappear now. This options acts as a toggle (display on-off) on all selected curves25.Select the Geometry/Select/Control Points menu. A control point must be selected. Whenmoving the mouse near a control point, the point becomes highlighted. Click-left on a con-trol point to display the point coordinates in the information area26.Click-right to quit the option27.Select the Geometry/Distance menu (). A prompt appears to select two points betweenwhich the distance will be measured and displayed:•Press <c> to disable the attraction to curves (this can be verified by moving the cursor near the start point of the C-spline. Normally, there is no attraction to the curve. Otherwise, press<c> a second time)•Move and attract the cursor over the start point of the C-spline. If there is no attraction, press <a>. Click-left on curve to select the start point•When moving the mouse, the distance between the selected point and the cursor is indi-cated. Move the mouse over the last point of the C-spline. The cursor is attracted to thepoint and the distance is indicating d=1•Click-left to fix the distance on the screenThe above steps can be repeated to measure the distance between otherpoints.•Click-right to quit the option.1-3.4Modify CurvesExisting selected curves can be modified within IGG™ in the following way:28.Select the Geometry/Modify Curve/Add Control Point option to add control points onselected curve by click-left on itCurves Geometry Creation29.Select the Geometry/Modify Curve/Remove Control Point option to remove a controlpoint on selected curve by click-left on control point30.Select the Geometry/Modify Curve/Modify Point (On surface) option to move an exist-ing control point on selected curve (on surface) by click-left to select the point and click-left after moving the control point31.Select the Geometry/Modify Curve/Set Name... option to impose a userdefined name tothe selected entity (one curve should be selected)32.Select the Geometry/Modify Curve/Divide option to split the selected curve at a userde-fined location by click-left on it (one curve should be selected)33.Select the Geometry/Modify Curve/Reverse option to reverse the curve orientation plot-ted when selecting Geometry/View/Curve Orientation menu1-3.5Edit/Copy CurvesExisting selected curves can be moved or copied within IGG™ in the following way:34.Select the Geometry/Select/Curves menu to select all the curves (highlighted in yellow)35.Select the Geometry/Edit/Copy menu to copy all the selected entities with a translation,rotation, scaling or mirror operation36.Type <new> <Enter> to impose a userdefined prefix to the geometrical entities that will becreated37.Type <t> <Enter> to select a copy with a translation38.Type <1 0 0> <Enter> to impose the translation vectortranslation (1 0 0)The menus Geometry/Edit/Translate, Rotate, Scale or Mirror allow to moveand not to copy the selected geometry.1-3.6Export CurvesIt is possible to save during the work the curves created in the previous steps. Only the curvesselected are saved into a file:39.Select the Geometry/Select/Curves menu to select all the curves (highlighted in yellow)Geometry Creation Surfaces40.Select File/Export/Geometry Selection... menu. A file chooser is opened to specify the name of a file ".dat" (with corresponding Parasolid ™file "X_T"). This file can be readback using the File/Import/IGG Data... menu ().1-4Surfaces 1-4.1Create Surfaces In this section simple surface creation is described, starting from a set of curves. A new session will be opened to clear all previous drawings.41.Select File/New - yes to close the current project and open a new, empty, project.Opening a new project closes the current project without automatic saving.42.Define a lofted surface:•Select File/Import/IGG Data and choose the file "geometry_curves.dat" in the\DOC\_Tutorials\IGG\Tutorial_1 directory of the installation cdrom. Three curves are readand stored in the geometry repository•Select the curves using Geometry/Select/Curves (<s >) in the order indicated on the figure•Verify that the curves are well oriented by using the Geometry/View/Curve Orientationmenu otherwise you need to reverse the curves by using the Geometry/Modify Curve/Reverse menu in order to impose the same orientation to all the curves•Select the Geometry/Surface/Lofted menu in the Quick Access Pad . A NURBS surface,interpolating the curves is now created. Notice that two new curves, representing surfaceboundaries, are created. These curves automatically appear in the curve chooser (Geome-try/View/Curves ) when it is opened123Boundary curves automatically created1234Surfaces Geometry Creation43.Define a coons patch:A Coons surface is a surface interpolating 4 boundary curves using a bilinearinterpolation. To avoid overlapping with the lofted surface, the selected curveswill be copied and translated.•Select the four boundary curves (<s>) of the lofted surface, in the order indicated in the above figure•Select the Geometry/Edit/Copy menu in the Quick Access Pad. IGG™ interrogates whether the duplicated curves must be translated, rotated, scaled, mirror or not. To avoid overlappingwith the existing curves and surface, a translation will be performed•Type <new> <Enter> to impose a userdefined prefix to the geometrical entities that will be created•Type <t> <Enter> to select a copy with a translation•Type <1 1 1> <Enter> to impose the translation vectorThe selected curves are duplicated and the new curves are automaticallyselected (the other curves are now unselected)•Select the Quick Access Pad/Geometry/Surface/Coons menu. A new surface is created which interpolates the four selected curvesIt can be noticed that 4 additional curves have been created. These are curves following the parametricdirections of the surface and are used to provide a better visualization of the surface.44.Define a surface of revolution:A surface of revolution will be created by rotating a newly created curve aroundthe Y axis.•First create a C-spline (Geometry/Curve/CSpline) between the points (-0.5,-2,0.1), (-0.5,0,0.2) and (-0.5,2,0.1). These points were selected so that the surface of revolution thatwill be created intersects the lofted surface•Make this curve the only selected curve (Geometry/Select/Curves)•Select Geometry/Surface/Revolution in the Quick Access Pad to create a surface of revolu-tion by rotating this new curve around a line parallel to the Y axis. The rotation origin is takenso that the surface of revolution intersects the lofted surface•Type <0 1 0> <Enter> to select the rotation axis direction•Type <-0.5 0 -1> <Enter> to select the rotation axis origin•Type <300> <Enter> to select the angle of rotationGeometry Creation SurfacesAs it may be noticed, the curve used for the rotation constitutes the first boundary of the surface.Three other boundary curves are automatically created to delimitate the surface.1-4.2Select SurfacesThe surface selection operation is used to activate one or more surfaces for subsequent operations in geometry modelling (i.e surface-surface intersection) or grid generation (i.e. face grid mapping).When a surface is selected its boundary curves appear highlighted in red or yellow.45.Select the Geometry/Select/Surfaces menu to initiate surface(s) selectionThe <Ctrl-s> shortcut can also be used to activate the same option, withoutaccessing the menu.46.Press <a > to unselect all the surfaces (toggle option), which become unhighlighted (bound-ary curves are unhighlighted)47.Move the mouse over the lofted surface. The surface becomes highlighted in blue.48.Click-left to select the surface. The boundary curves remain now permanently in red or yel-low49.Repeat above steps to select the surface of revolution50.Click-right to quit the selectionSelection and deselection of all the visible surfaces can be done by pressing<a> repeatedly (toggle option).1-4.3Visualize SurfacesSurfaces stored in IGG ™ are by default visualized by displaying their boundaries. As soon as the boundary curves of a surface are visible, the surface is considered visible. The following step describes how to hide surfaces, hence hide their boundaries.51.Select the Geometry/View/Surfaces option. A surface chooser appears with the name ofall the surfaces in the geometry repository. All surfaces in the chooser are highlighted sincethey are all visible in the graphics area52.Select the lofted surface (click-left on it) in the chooser and press Apply . The lofted surface appears alone in the graphics area with all the previously created curvesboundary curvesSurfaces Geometry Creation53.Select the surface of revolution (click-left on it) in the chooser while holding the <Ctrl> key.The surface of revolution is highlighted in the chooser together with the lofted surface. PressApply to visualize both surfaces. Notice that the surface of revolution is now unselected inthe graphics area (highlighted in blue)54.Select the first and last surfaces (click-left on them) in the chooser while holding the <Shift>key. All surfaces are highlighted in the chooser. Press Apply to visualize them all in thegraphics area55.Close the chooser1-4.4Modify SurfacesWhen manipulating parametric surfaces, it is possible to create curves in the parametric directions ofthe surfaces. These curves can be used to better visualize the surfaces or for other geometry and gridmodelling operations.56.After selecting a surface, select the Geometry/Modify Surface/Representation menu.IGG™ requests the number of curves to be created in the u and v direction of each selectedsurface:•Type <15 15> <Enter> to plot 15 curves in both parametric directions of the selected surfaces•Repeat the previous step and specify 5 curves in each direction57.Select the Geometry/Modify Surface/Add uv Curves menu. Then a point must be selectedon the selected surfaces:•Move the mouse inside the limits of the selected surfaces. Two orthogonal curves appear at the mouse position. The attraction feature can be enabled, if needed•Click-left to add the two curves in the geometry repositoryThe curves created in the above steps are deleted when the surface is deleted,except if they are used by other entities.1-4.5Edit/Copy SurfacesExisting selected surfaces can be moved or copied within IGG™ as presented on the curves in section1-3.5.1-4.6Export SurfacesIt is possible to save during the work the curves and surfaces created in the previous steps. Only thecurves and surfaces selected are saved into a file:58.Select the Geometry/Select/Curves and Surfaces menu to select respectively the curves(highlighted in yellow) and the surfaces (highlighted in red or yellow)59.Select the File/Export/Geometry Selection... menu. A file chooser is opened to specify thename of a file ".dat" (with corresponding Parasolid™ file "X_T"). This file can be read backusing the File/Import/IGG Data... menu ()Geometry Creation SurfacesTUTORIAL 2:2D Airfoil MeshGeneration2-1Introduction2-1.1IntroductionThe resolution of computational fluid dynamics (CFD) problems involves three main steps:•spatial discretization of the flow equations,•flow computation,•visualization of the results.To answer these questions, NUMECA has developed a F low IN tegrated E nvironment for internaland Turbomachinery assimilations. Called FINE™/Turbo, the environment integrates the followingtools:•IGG™ is an I nteractive G eometry modeler and G rid generator software, based on structured multi-block techniques,•AutoGrid™ is a three-dimensional Automated Grid generation software, dedicated to turboma-chinery applications. Similarly to IGG™, it is based on structured multi-block techniques,•Euranus is a state-of-the-art multi-block flow solver, able to simulate Euler and Navier-Stokes equations in the laminar, transitional and turbulent regimes,•CFView™ is a highly interactive flow visualization and post-treatment software,•FINE™ Graphical User Interface is a user-friendly environment that includes the different soft-wares. It integrates the concept of projects and allows the user to achieve complete simulations,going from the grid generation to the flow visualization, without the need of file manipulation.A C-type block grid around an airfoil is proposed to explain the basic features of the major topol-ogy and grid generation modules within IGG™.The tutorial shows the successive steps that must be followed to generate a 2D mesh and to definethe boundary conditions required before starting a solver:•Set up a 2D project,•Import/Create geometry curves needed for meshing,•Define the topology before meshing,。

长翅型白背飞虱雌成虫翅的超微特征

长翅型白背飞虱雌成虫翅的超微特征

第 63 卷第 1 期2024 年 1 月Vol.63 No.1Jan.2024中山大学学报(自然科学版)(中英文)ACTA SCIENTIARUM NATURALIUM UNIVERSITATIS SUNYATSENI长翅型白背飞虱雌成虫翅的超微特征*伍俭儿,梁安文,冯博,胡杨,王方海中山大学生命科学学院,广东广州 510275摘要:白背飞虱Sogatella furcifera为水稻重要害虫,长翅型成虫能够远距离飞行迁移,扩散其危害的范围。

本研究利用扫描电镜观察研究了长翅型白背飞虱雌成虫翅的超微特征,发现:前、后翅的翅面中间薄而边缘厚,翅中部到端部的边缘有叠起的褶皱,前翅背面翅面上均匀地分布着许多小刺状突起,长度为(3.07±0.48)μm,而后翅背腹两面均着生有许多小刺状突起。

前翅的背面和腹面都存在毛形感器样结构,根据形态可分为TS-I和TS-Ⅱ两种:TS-I分布于腹面翅基部的翅脉处且与翅脉垂直,没有明显的基窝,数量为(4±1.41)根,长为(31.80±2.43)μm;TS-Ⅱ则分布于背面的翅脉上,数量为(5±1.41)根,长度为(57.25±21.84)μm,着生于有明显凹陷的基窝中。

前翅腹面边缘以及翅脉处还分布有钟形感器样结构,数量为(5.00±3.46)个;另外还发现一种锥形感器样结构,位于前翅腹面边缘,数量为(21.00±4.36)个,长(8.25±2.09)μm。

研究结果有助于从超微水平对白背飞虱翅的形态结构有个更深入的了解,进一步理解其迁飞扩散的能力,为寻找更好的防控措施打下基础。

关键词:白背飞虱Sogatella furcifera;长翅型;毛形感器样结构;钟形感器样结构;锥形感器样结构中图分类号:Q965 文献标志码:A 文章编号:2097 - 0137(2024)01 - 0066 - 05Ultrastructures of the wings fromthe long-winged female adult of Sogatella furciferaWU Jianer, LIANG Anwen, FENG Bo, HU Yang, WANG FanghaiSchool of Life Sciences, Sun Yat-sen University, Guangzhou 510275, ChinaAbstract:Sogatella furcifera is an important pest of rice. Long-winged adults can migrate over long distances and spread their harm. In this study, the ultramicroscopic characteristics of female adult plan‐thopper with long wings were studied by scanning electron microscopy. The results showed that: The middle of the fore and hind wing surface is thin and the edge is thick. The edge of the middle to the endof the wing has folded. There are many small spines evenly distributed on the back wing surface of the forewing, the length is(3.07± 0.48)μm, and there are many small spines on both sides of the hind wing. There were trichoid sensilla like apparatus on the dorsal surface and ventral surface of the fore‐wing, which could be divided into TS-I and TS-Ⅱ. TS-I distributed in the ventral wing base and perpen‐dicular to the ventral wing vein, and had no obvious basal fossa. The number of TS-I was 4±1.41, and the length was (31.80±2.43)μm. TS-Ⅱ was distributed on the dorsal vein of the wing, and the numberof TS-Ⅱ was 5±1.41, the length was (57.25±21.84)μm, and the TS-Ⅱ was located in the basal fossae with obvious depression. Campaniform sensilla like apparatuses were also distributed in the ventral edge of the forewing and in the veins, and the number was 5.00±3.46. In addition, a basiconic sensilla like apparatus with 21.00±4.36 in number and (8.25±2.09)μm in length was found on the ventral edgeDOI:10.13471/ki.acta.snus.2023E028*收稿日期:2023 − 05 − 10 录用日期:2023 − 10 − 25 网络首发日期:2023 − 12 − 05基金项目:广东省自然科学基金(2021A1515012402);广州市科技计划项目(202002030019)作者简介:伍俭儿(1970年生),女;研究方向:动物形态与解剖学;E-mail:******************通信作者:王方海(1965年生),男;研究方向:昆虫生物化学与分子生物学;E-mail:****************第 1 期伍俭儿,等:长翅型白背飞虱雌成虫翅的超微特征of the forewing. The results of this study are helpful to further understand the morphological structure of the white back planthopper wing at the ultrastructural level , and understand its ability to migrate and spread , and lay a foundation for better prevention and control measures.Key words : Sogatella furcifera ; long-winged ; trichoid sensilla like apparatus ; campaniform sensilla like apparatus ; basiconic sensilla like apparatus 白背飞虱Sogatella furcifera 是主要农作物水稻上的重要害虫,隶属于半翅目飞虱科(Zhou et al., 2017)。

参考文献(人工智能)

参考文献(人工智能)

参考文献(人工智能)曹晖目的:对参考文献整理(包括摘要、读书笔记等),方便以后的使用。

分类:粗分为论文(paper)、教程(tutorial)和文摘(digest)。

0介绍 (1)1系统与综述 (1)2神经网络 (2)3机器学习 (2)3.1联合训练的有效性和可用性分析 (2)3.2文本学习工作的引导 (2)3.3★采用机器学习技术来构造受限领域搜索引擎 (3)3.4联合训练来合并标识数据与未标识数据 (5)3.5在超文本学习中应用统计和关系方法 (5)3.6在关系领域发现测试集合规律性 (6)3.7网页挖掘的一阶学习 (6)3.8从多语种文本数据库中学习单语种语言模型 (6)3.9从因特网中学习以构造知识库 (7)3.10未标识数据在有指导学习中的角色 (8)3.11使用增强学习来有效爬行网页 (8)3.12★文本学习和相关智能A GENTS:综述 (9)3.13★新事件检测和跟踪的学习方法 (15)3.14★信息检索中的机器学习——神经网络,符号学习和遗传算法 (15)3.15用NLP来对用户特征进行机器学习 (15)4模式识别 (16)4.1JA VA中的模式处理 (16)0介绍1系统与综述2神经网络3机器学习3.1 联合训练的有效性和可用性分析标题:Analyzing the Effectiveness and Applicability of Co-training链接:Papers 论文集\AI 人工智能\Machine Learning 机器学习\Analyzing the Effectiveness and Applicability of Co-training.ps作者:Kamal Nigam, Rayid Ghani备注:Kamal Nigam (School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, knigam@)Rayid Ghani (School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213 rayid@)摘要:Recently there has been significant interest in supervised learning algorithms that combine labeled and unlabeled data for text learning tasks. The co-training setting [1] applies todatasets that have a natural separation of their features into two disjoint sets. We demonstrate that when learning from labeled and unlabeled data, algorithms explicitly leveraging a natural independent split of the features outperform algorithms that do not. When a natural split does not exist, co-training algorithms that manufacture a feature split may out-perform algorithms not using a split. These results help explain why co-training algorithms are both discriminativein nature and robust to the assumptions of their embedded classifiers.3.2 文本学习工作的引导标题:Bootstrapping for Text Learning Tasks链接:Papers 论文集\AI 人工智能\Machine Learning 机器学习\Bootstrap for Text Learning Tasks.ps作者:Rosie Jones, Andrew McCallum, Kamal Nigam, Ellen Riloff备注:Rosie Jones (rosie@, 1 School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213)Andrew McCallum (mccallum@, 2 Just Research, 4616 Henry Street, Pittsburgh, PA 15213)Kamal Nigam (knigam@)Ellen Riloff (riloff@, Department of Computer Science, University of Utah, Salt Lake City, UT 84112)摘要:When applying text learning algorithms to complex tasks, it is tedious and expensive to hand-label the large amounts of training data necessary for good performance. This paper presents bootstrapping as an alternative approach to learning from large sets of labeled data. Instead of a large quantity of labeled data, this paper advocates using a small amount of seed information and alarge collection of easily-obtained unlabeled data. Bootstrapping initializes a learner with the seed information; it then iterates, applying the learner to calculate labels for the unlabeled data, and incorporating some of these labels into the training input for the learner. Two case studies of this approach are presented. Bootstrapping for information extraction provides 76% precision for a 250-word dictionary for extracting locations from web pages, when starting with just a few seed locations. Bootstrapping a text classifier from a few keywords per class and a class hierarchy provides accuracy of 66%, a level close to human agreement, when placing computer science research papers into a topic hierarchy. The success of these two examples argues for the strength of the general bootstrapping approach for text learning tasks.3.3 ★采用机器学习技术来构造受限领域搜索引擎标题:Building Domain-specific Search Engines with Machine Learning Techniques链接:Papers 论文集\AI 人工智能\Machine Learning 机器学习\Building Domain-Specific Search Engines with Machine Learning Techniques.ps作者:Andrew McCallum, Kamal Nigam, Jason Rennie, Kristie Seymore备注:Andrew McCallum (mccallum@ , Just Research, 4616 Henry Street Pittsburgh, PA 15213)Kamal Nigam (knigam@ , School of Computer Science, Carnegie Mellon University Pittsburgh, PA 15213)Jason Rennie (jr6b@)Kristie Seymore (kseymore@)摘要:Domain-specific search engines are growing in popularity because they offer increased accuracy and extra functionality not possible with the general, Web-wide search engines. For example, allows complex queries by age-group, size, location and cost over summer camps. Unfortunately these domain-specific search engines are difficult and time-consuming to maintain. This paper proposes the use of machine learning techniques to greatly automate the creation and maintenance of domain-specific search engines. We describe new research in reinforcement learning, information extraction and text classification that enables efficient spidering, identifying informative text segments, and populating topic hierarchies. Using these techniques, we have built a demonstration system: a search engine forcomputer science research papers. It already contains over 50,000 papers and is publicly available at ....采用多项Naive Bayes 文本分类模型。

(完整版)英语语言学概论--整理

(完整版)英语语言学概论--整理

Chapter 1 Language语言1. Design feature (识别特征) refers to the defining properties of human language that distinguish it from any animal system of communication.2. Productivity(能产性) refers to the ability that people have in making and comprehending indefinitely large quantities of sentences in theirnative language.3. arbitrariness (任意性) Arbitrariness refers to the phenomenon that there is no motivated relationship between a linguistic form and itsmeaning.4. symbol (符号) Symbol refers to something such as an object, word, or sound that represents something else by association or convention.5. discreteness (离散性) Discreteness refers to the phenomenon that the sounds in a language are meaningfully distinct.6. displacement (不受时空限制的特性) Displacement refers to the fact that human language can be used to talk about things that are not in theimmediate situations of its users.7. duality of structure (结构二重性) The organization of language into two levels, one of sounds, the other of meaning, is known as duality ofstructure.8. culture transmission (文化传播) Culture transmission refers to the fact that language is passed on from one generation to the next throughteaching and learning, rather than by inheritance.9. interchangeability (互换性) Interchangeability means that any human being can be both a producer and a receiver of messages.1. ★What is language?Language is a system of arbitrary vocal symbols used for human communication. This definition has captured the main features of language.First, language is a system.Second, language is arbitrary in the sense.The third feature of language is symbolic nature.2. ★What are the design features of language?Language has seven design features as following:1) Productivity.2) Discreteness.3) Displacement4) Arbitrariness.5) Cultural transmission6) Duality of structure.7) Interchangeability.3. Why do we say language is a system?Because elements of language are combined according to rules, and every language contains a set of rules. By system, the recurring patterns or arrangements or the particular ways or designs in which a language operates. And the sounds, the words and the sentences are used in fixed patterns that speaker of a language can understand each other.4. ★ (Function of language.) According to Halliday, what are the initial functions of children’s language? And what are the threefunctional components of adult language?I. Halliday uses the following terms to refer to the initial functions of children’s language:1) Instrumental function. 工具功能2) Regulatory function. 调节功能3) Representational function. 表现功能4) Interactional function. 互动功能5) Personal function. 自指性功能6) Heuristic function. 启发功能[osbQtq`kf`h]7) Imaginative function. 想象功能II. Adult language has three functional components as following:1) Interpersonal components. 人际2) Ideational components.概念3) Textual components.语篇1. general linguistics and descriptive linguistics (普通语言学与描写语言学) The former deals with language in general whereas the latter isconcerned with one particular language.2. synchronic linguistics and diachronic linguistics (共时语言学与历时语言学) Diachronic linguistics traces the historical development of thelanguage and records the changes that have taken place in it between successive points in time. And synchronic linguistics presents an account of language as it is at some particular point in time.3. theoretical linguistics and applied linguistics (理论语言学与应用语言学) The former copes with languages with a view to establishing atheory of their structures and functions whereas the latter is concerned with the application of the concepts and findings of linguistics to all sorts of practical tasks.4. microlinguistics and macrolinguistics(微观语言学与宏观语言学) The former studies only the structure of language system whereas thelatter deals with everything that is related to languages.5. langue and parole (语言与言语) The former refers to the abstract linguistics system shared by all the members of a speech communitywhereas the latter refers to the concrete act of speaking in actual situation by an individual speaker.6. competence and performance (语言能力与语言运用) The former is one’s knowledge of all the linguistic regulation systems whereas the latteris the use of language in concrete situation.7. speech and writing (口头语与书面语) Speech is the spoken form of language whereas writing is written codes, gives language new scope.8. linguistics behavior potential and actual linguistic behavior (语言行为潜势与实际语言行为) People actually says on a certain occasion to acertain person is actual linguistics behavior. And each of possible linguistic items that he could have said is linguistic behavior potential.9. syntagmatic relation and paradigmatic relation(横组合关系与纵聚合关系) The former describes the horizontal dimension of a languagewhile the latter describes the vertical dimension of a language.10. verbal communication and non-verbal communication(言语交际与非言语交际) Usual use of language as a means of transmittinginformation is called verbal communication. The ways we convey meaning without using language is called non-verbal communication.1. ★How does John Lyons classify linguistics?According to John Lyons, the field of linguistics as a whole can be divided into several subfields as following:1) General linguistics and descriptive linguistics.2) Synchronic linguistics and diachronic linguistics.3) Theoretical linguistics and applied linguistics.4) Microlinguistics and macrolinguistics.2. Explain the three principles by which the linguist is guided: consistency, adequacy and simplicity.1) Consistency means that there should be no contradictions between different parts of the theory and the description.2) Adequacy means that the theory must be broad enough in scope to offer significant generalizations.3) Simplicity requires us to be as brief and economic as possible.3. ★What are the sub-branches of linguistics within the language system?Within the language system there are six sub-branches as following:1) Phonetics. 语音学is a study of speech sounds of all human languages.2) Phonology. 音位学studies about the sounds and sound patterns of a speaker’s native language.3) Morphology. 形态学studies about how a word is formed.4) Syntax. 句法学studies about whether a sentence is grammatical or not.5) Semantics. 语义学studies about the meaning of language, including meaning of words and meaning of sentences.6) Pragmatics. 语用学★The scope of language: Linguistics is referred to as a scientific study of language.★The scientific process of linguistic study: It involves four stages: collecting data, forming a hypothesis, testing the hypothesis and drawing conclusions.1. articulatory phonetics(发音语音学) The study of how speech organs produce the sounds is called articulatory phonetics.2. acoustic phonetics (声学语音学) The study of the physical properties and of the transmission of speech sounds is called acoustic phonetics.3. auditory phonetics (听觉语音学) The study of the way hearers perceive speech sounds is called auditory phonetics.4. consonant (辅音) Consonant is a speech sound where the air form the language is either completely blocked, or partially blocked, or where theopening between the speech organs is so narrow that the air escapes with audible friction.5. vowel (元音) is defined as a speech sound in which the air from the lungs is not blocked in any way and is pronounced with vocal-cord vibration.6. bilabials (双唇音) Bilabials means that consonants for which the flow of air is stopped or restricted by the two lips. [p][b] [m] [w]7. affricates (塞擦音) The sound produced by stopping the airstream and then immediately releasing it slowly is called affricates. [t X] [d Y] [tr] [dr]8. glottis (声门) Glottis is the space between the vocal cords.9. rounded vowel (圆唇元音) Rounded vowel is defined as the vowel sound pronounced by the lips forming a circular opening. [u:] [u] [OB] [O]10. diphthongs (双元音) Diphthongs are produced by moving from one vowel position to another through intervening positions.[ei][ai][O i] [Q u][au]11. triphthongs(三合元音) Triphthongs are those which are produced by moving from one vowel position to another and then rapidly andcontinuously to a third one. [ei Q][ai Q][O i Q] [Q u Q][au Q]12. lax vowels (松元音) According to distinction of long and short vowels, vowels are classified tense vowels and lax vowels. All the long vowelsare tense vowels but of the short vowels,[e] is a tense vowel as well, and the rest short vowels are lax vowels.1. ★How are consonants classified in terms of different criteria?The consonants in English can be described in terms of four dimensions.1) The position of the soft palate.2) The presence or the absence of vocal-cord vibration.3) The place of articulation.4) The manner of articulation.2. ★How are vowels classified in terms of different criteria?Vowel sounds are differentiated by a number of factors.1) The state of the velum2) The position of the tongue.3) The openness of the mouth.4) The shape of the lips.5) The length of the vowels.6) The tension of the muscles at pharynx.3. ★What are the three sub-branches of phonetics? How do they differ from each other?Phonetics has three sub-branches as following:1) Articulatory phonetics is the study of how speech organs produce the sounds is called articulatory phonetics.2) Acoustic phonetics is the study of the physical properties and of the transmission of speech sounds is called acoustic phonetics.3) Auditory phonetics is the study of the way hearers perceive speech sounds is called auditory phonetics.4. ★What are the commonly used phonetic features for consonants and vowels respectively?I. The frequently used phonetic features for consonants include the following:1) Voiced.2) Nasal.3) Consonantal.4) Vocalic.5) Continuant.6) Anterior.7) Coronal.8) Aspirated.II. The most common phonetic features for vowels include the following:1) High.2) Low.3) Front.4) Back.5) Rounded.6) Tense.1. phonemes (音位) Phonemes are minimal distinctive units in the sound system of a language.2. allophones (音位变体) Allophones are the phonetic variants and realizations of a particular phoneme.3. phones (单音) The smallest identifiable phonetic unit found in a stream of speech is called a phone.4. minimal pair (最小对立体) Minimal pair means words which differ from each other only by one sound.5. contrastive distribution (对比分布) If two or more sounds can occur in the same environment and the substitution of one sound for anotherbrings about a change of meaning, they are said to be in contrastive distribution.6. complementary distribution(互补分布) If two or more sounds never appear in the same environment ,then they are said to be incomplementary distribution.7. free variation (自由变异) When two sounds can appear in the same environment and the substitution of one for the other does not cause anychange in meaning, then they are said to be in free variation.8. distinctive features (区别性特征) A distinctive feature is a feature which distinguishes one phoneme from another.9. suprasegmental features (超切分特征) The distinctive (phonological) features which apply to groups larger than the single segment are knownas suprasegmental features.10. tone languages (声调语言) Tone languages are those which use pitch to contrast meaning at word level.11. intonation languages (语调语言) Intonation languages are those which use pitch to distinguish meaning at phrase level or sentence level.12. juncture (连音) Juncture refers to the phonetic boundary features which may demarcate grammatical units.1. ★What are the differences between English phonetics and English phonology?1) Phonetics is the study of the production, perception, and physical properties of speech sounds, while phonology attempts to account forhow they are combined, organized, and convey meaning in particular languages.2) Phonetics is the study of the actual sounds while phonology is concerned with a more abstract description of speech sounds and tries todescribe the regularities of sound patterns.2. Give examples to illustrate the relationship between phonemes, phones and allophones.When we hear [pit],[tip],[spit],etc, the similar phones we have heard are /p/. And /p/ and /b/ are separate phonemes in English, while [ph] and [p] are allophones.3. How can we decide a minimal pair or a minimal set?A minimal pair should meet three conditions:1) The two forms are different in meaning.2) The two forms are different in one sound segment.3) The different sounds occur in the same position of the two strings.4. ★Use examples to explain the three types of distribution.1) Contrastive distribution. Sounds [m] in met and [n] in net are in contrastive distribution because substituting [m] for [n] will result in achange of meaning.2) Complementary distribution. The aspirated plosive [ph] and the unaspirated plosive [p] are in complementary distribution because theformer occurs either initially in a word or initially in a stressed syllable while the latter never occurs in such environments.3) Free variation. In English, the word “direct” may be pronounce in two ways: /di’rekt/ and /dia’rekt/, and the two different sounds /i/ and /ai/can be said to be in free variation.5. What’s the difference between segmental features and suprasegmental features? What are the suprasegmental features in English?I. 1) Distinctive features, which are used to distinguish one phoneme from another and thus have effect on one sound segment, are referred toas segmental features.2) The distinctive (phonological) features which apply to groups larger than the single segment are known as suprasegmental features.3) Suprasegmental features may have effect on more than one sound segment. They may apply to a string of several sounds.II.The main suprasegmental features include stress, tone, intonation and juncture.6. What’s the difference between tone languages and intonation language?Tone languages are those which use pitch to contrast meaning at word level while intonation languages are those which use pitch to distinguish meaning at phrase level or sentence level7. ★What’s the difference between phonetic transcriptions and phonemic transcriptions?The former was meant to symbolize all possible speech sounds, including even the most minute shades of pronunciation, while the latter was intended to indicate only those sounds capable of distinguishing one word from another in a given language.1. morphemes (语素) Morphemes are the minimal meaningful units in the grammatical system of a language.allomorphs (语素变体) Allomorphs are the realizations of a particular morpheme.morphs (形素) Morphs are the realizations of morphemes in general and are the actual forms used to realize morphemes.2. roots (词根) Roots is defined as the most important part of a word that carries the principal meaning.affixes (词缀) Affixes are morphemes that lexically depend on roots and do not convey the fundamental meaning of words.free morphemes (自由语素) Free morphemes are those which can exist as individual words.bound morphemes (粘着语素) Bound morphemes are those which cannot occur on their own as separate words.3. inflectional affixes (屈折词缀) refer to affixes that serve to indicate grammatical relations, but do not change its part of speech.derivational affixes (派生词缀) refer to affixes that are added to words in order to change its grammatical category or its meaning.4. empty morph (空语子) Empty morph means a morph which has form but no meaning.zero morph (零语子) Zero morph refers to a morph which has meaning but no form.5. IC Analysis (直接成分分析) IC analysis is the analysis to analyze a linguistic expression (both a word and a sentence) into a hierarchicallydefined series of constituents.6. immediate constituents(直接成分) A immediate constituent is any one of the largest grammatical units that constitute a construction.Immediate constituents are often further reducible.ultimate constituents (最后成分) Ultimate constituents are those grammatically irreducible units that constitute constructions.7. morphological rules (形态学规则) The principles that determine how morphemes are combined into new words are said to be morphologicalrules.8. word-formation process (构词法) Word-formation process mean the rule-governed processes of forming new words on the basis of alreadyexisting linguistic resources.1. ★What is IC Analysis?IC analysis is the analysis to analyze a linguistic expression (both a word and a sentence) into a hierarchically defined series of constituents.2. How are morphemes classified?1) Semantically speaking, morphemes are grouped into two categories: root morphemes and affixational morphemes.2) Structurally speaking, they are divided into two types: free morphemes and bound morphemes.3. ★Explain the interrelations between semantic and structural classifications of morphemes.a) All free morphemes are roots but not all roots are free morphemes.b) All affixes are bound morphemes, but not all bound morphemes are affixes.4. What’s the difference between an empty morph and a zero mor ph?a) Empty morph means a morph that has form but no meaning.b) Zero morph refers to a morph that has meaning but no form.5. Explain the differences between inflectional and derivational affixes in term of both function and position.a) Functionally:i.Inflectional affixes sever to mark grammatical relations and never create new words while derivational affixes can create new words.ii.Inflectional affixes do not cause a change in grammatical class while derivational affixes very often but not always cause a change in grammatical class.b) In term of position:i.Inflectional affixes are suffixes while derivational affixes can be suffixes or prefixes.ii.Inflectional affixes are always after derivational affixes if both are present. And derivational affixes are always before inflectional suffixes if both are present.6. What are morphological rules? Give at least four rules with examples.The principles that determine how morphemes are combined into new words are said to be morphological rules.For example:a) un- + adj. ->adj.b) Adj./n. + -ify ->v.c) V. + -able -> adj.d) Adj. + -ly -> adv.1. syntagmatic relations (横组关系) refer to the relationships between constituents in a construction.paradigmatic relations (纵聚合关系) refer to the relations between the linguistic elements within a sentence and those outside the sentence.hierarchical relations (等级关系) refer to relationships between any classification of linguistic units which recognizes a series of successively subordinate levels.2. IC Analysis (直接成分分析) is a kind of grammatical analysis, which make major divisions at any level within a syntactic construction.labeled IC Analysis(标记法直接成分分析) is a kind of grammatical analysis, which make major divisions at any level within a syntactic construction and label each constituent.phrase markers (短语标记法) is a kind of grammatical analysis, which make major divisions at any level within a syntactic construction, and label each constituent while remove all the linguistic forms.labeled bracketing (方括号标记法) is a kind of grammatical analysis, which is applied in representing the hierarchical structure of sentences by using brackets.3. constituency (成分关系)dependency (依存关系)4. surface structures (表层结构)refers to the mental representation of a linguistic expression, derived from deep structure by transformationalrules.deep structures (深层结构) deep structure of a linguistic expression is a theoretical construct that seeks to unify several related structures. 5. phrase structure rules (短语结构规则)are a way to describe a given language's syntax. They are used to break a natural language sentencedown into its constituent parts.6. transformational rules (转换规则)7. structural ambiguity (结构歧义)1. What are the differences between surface structure and deep structure?They are different from each other in four aspects:1) Surface structures correspond directly to the linear arrangements of sentences while deep structures correspond to the meaningful groupingof sentences.2) Surface structures are more concrete while deep structures are more abstract.3) Surface structures give the forms of sentences whereas deep structures give the meanings of sentences.4) Surface structures are pronounceable but deep structures are not.2. Illustrate the differences between PS rules and T-rules.1) PS rules frequently applied in generating deep structures.2) T-rules are used to transform deep structure into surface structures.3. What’s the order of generating sentences? Do we st art with surface structures or with deep structures? How differently are theygenerated?To generate a sentence, we always start with its deep structure, and then transform it into its corresponding surface structure.Deep structures are generated by phrase structure rules (PS rules) while surface structures are derived from their deep structures by transformational rules (T-rules).4. What’s the difference between a compulsory constituent and an optional one?Optional constituents may be present or absent while compulsory constituents must be present.5. What are the three syntactic relations? Illustrate them with examples.1) Syntagmatic relations2) Paradigmatic relations.3) Hierarchical relations.1. Lexical semantics (词汇语义学) is defined as the study of word meaning in language.2. Sense (意义) refers to the inherent meaning of the linguistic form.3. Reference (所指) means what a linguistic form refers to in the real world.4. Concept (概念) is the result of human cognition, reflecting the objective world in the human mind.5. Denotation (外延) is defined as the constant ,abstract, and basic meaning of a linguistic expression independent of context and situation.6. Connotation (内涵) refers to the emotional associations which are suggested by, or are part of the meaning of, a linguistic unit.7. Componential analysis (成分分析法) is the way to decompose the meaning of a word into its components.8. Semantic field (语义场) The vocabulary of a language is not simply a listing of independent items, but is organized into areas, within whichwords interrelate and define each other in various ways. The areas are semantic fields.9. Hyponymy (上下义关系) refers to the sense relation between a more general, more inclusive word and a more specific word.10. Synonymy (同义关系) refers to the sameness or close similarity of meaning.11. Antonymy (反义关系) refers to the oppositeness of meaning.12. Lexical ambiguity (词汇歧义)13. Polysemy (多义性) refers to the fact that the same one word may have more than one meaning.14. Homonymy (同音(同形)异义关系) refers to the phenomenon that words having different meanings have the same form.15. Sentence semantics (句子语义学) refers to the study of sentence meaning in language.1. What’s the criterion of John Lyons in classifying semantics into its sub-branches? And how does he classify semantics?In terms of whether it falls within the scope of linguistics, John Lyons distinguishes between linguistic semantics and non-linguistic semantics.According John Lyons, semantics is one of the sub-branches of linguistics; it is generally defined as the study of meaning.2. What are the essential factors for determining sentence meaning?1) Object, 2) concept, 3) symbol, 4) user, 5) context.3. What is the difference between the theory of componential analysis and the theory of semantic theory in defining meaning of words?4. What are the sense relations between sentences?1) S1 is synonymous with S2.2) S1 entails S2.3) S1 contradicts S2.4) S1 presupposes S2.5) S1 is a tautology, and therefore invariably true.6) S1 is a contradiction, and therefore invariably false.7) S1 is semantically anomalous.1. Speech act theory (言语行为理论)2. Cooperative principle and its maxims (合作原则及其准则)3. Politeness principle and its maxims (礼貌原则及其准则)4. Conversational implicature (会话含义)5. Indirect speech act (间接言语行为)6. Pragmatic presupposition (语用学预设)7. Relevance theory (关联理论)8. Illocutionary act (言外行为)9. (Horn’s) Q-Principle and R-Principle10. Perfrmative verbs (施为句动词)1. Make comments on the different definitions of pragmatics.2. What are the main types of deixis?3. Explain the statement: context is so indispen sable in fully understanding interpreting the speaker’s meaning.4. How are Austin’s and Searle’s speech act theories related to each other?5. What’s the relationship between CP and PP?6. What do you know about presupposition triggers in English? Explain them briefly with examples.7. What is ostensive-referential communication?8. Explain the obvious presupposition of speaker who say each of the following:1) When did you stop beating your wife?2) Where did Tom buy the watch?3) Your car is broken.9. What do you think of the fol lowing statement? “Tom participated in spreading rumors” entails “Tom engaged in spreading rumors”.Chapter 9 话语分析1. text(语篇) = discourse 语篇是指实际使用的语言单位,是一次交际过程中的一系列连续的话段或句子所构成的语言整体。

协作移动机器人-前因和方向外文文献翻译、中英文翻译、外文翻译

协作移动机器人-前因和方向外文文献翻译、中英文翻译、外文翻译

Cooperative Mobile Robotics: Antecedents and DirectionsY. UNY CAOComputer Science Department, University of California, Los Angeles, CA 90024-1596ALEX S. FUKUNAGAJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109-8099ANDREW B. KAHNGComputer Science Department, University of California, Los Angeles, CA 90024-1596Editors: R.C. Arkin and G.A. BekeyAbstract. There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting cooperative behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of cooperative robotics have been reported, and supporting theory is still in its formative stages. In this paper, we give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. We describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations.Keywords: cooperative robotics, swarm intelligence, distributed robotics, artificial intelligence, mobile robots, multiagent systems1. PreliminariesThere has been much recent activity toward achieving systems of multiple mobile robots engaged in collective behavior. Such systems are of interest for several reasons:•tasks may be inherently too complex (or im-possible) for a single robot to accomplish, or performance benefits can be gained from using multiple robots;•building and using several simple robots can be easier, cheaper, more flexible and more fault-tolerant than having a single powerful robot foreach separate task; and•the constructive, synthetic approach inherent in cooperative mobile robotics can possibly∗This is an expanded version of a paper which originally appeared in the proceedings of the 1995 IEEE/RSJ IROS conference. yield insights into fundamental problems in the social sciences (organization theory, economics, cognitive psychology), and life sciences (theoretical biology, animal ethology).The study of multiple-robot systems naturally extends research on single-robot systems, butis also a discipline unto itself: multiple-robot systems can accomplish tasks that no single robot can accomplish, since ultimately a single robot, no matter how capable, is spatially limited. Multiple-robot systems are also different from other distributed systems because of their implicit “real-world” environment, which is presumably more difficult to model and reason about than traditional components of distributed system environments (i.e., computers, databases, networks).The term collective behavior generically denotes any behavior of agents in a system having more than one agent. the subject of the present survey, is a subclass of collective behavior that is characterized by cooperation. Webster’s dictionary [118] defines “cooperate” as “to associate with anoth er or others for mutual, often economic, benefit”. Explicit definitions of cooperation in the robotics literature, while surprisingly sparse, include:1. “joint collaborative behavior that is directed toward some goal in which there is a common interest or reward” [22];2. “a form of interaction, usually based on communication” [108]; and3. “[joining] together for doing something that creates a progressive result such as increasing performance or saving time” [137].These definitions show the wide range of possible motivating perspectives. For example, definitions such as (1) typically lead to the study of task decomposition, task allocation, and other dis-tributed artificial intelligence (DAI) issues (e.g., learning, rationality). Definitions along the lines of (2) reflect a concern with requirements for information or other resources, and may be accompanied by studies of related issues such as correctness and fault-tolerance. Finally, definition (3) reflects a concern with quantified measures of cooperation, such as speedup in time to complete a task. Thus, in these definitions we see three fundamental seeds: the task, the mechanism of cooperation, and system performance.We define cooperative behavior as follows: Given some task specified by a designer, a multiple-robot system displays cooperative behavior if, due to some underlying mechanism (i.e., the “mechanism of cooperation”), there is an increase in the total utility of the system. Intuitively, cooperative behavior entails some type of performance gain over naive collective behavior. The mechanism of cooperation may lie in the imposition by the designer of a control or communication structure, in aspects of the task specification, in the interaction dynamics of agent behaviors, etc.In this paper, we survey the intellectual heritage and major research directions of the field of cooperative robotics. For this survey of cooperative robotics to remain tractable, we restrict our discussion to works involving mobile robots or simulations of mobile robots, where a mobile robot is taken to be an autonomous, physically independent, mobile robot. In particular, we concentrated on fundamental theoretical issues that impinge on cooperative robotics. Thus, the following related subjects were outside the scope of this work:•coordination of multiple manipulators, articulated arms, or multi-fingered hands, etc.•human-robot cooperative systems, and user-interface issues that arise with multiple-robot systems [184] [8] [124] [1].•the competitive subclass of coll ective behavior, which includes pursuit-evasion [139], [120] and one-on-one competitive games [12]. Note that a cooperative team strategy for, e.g., work on the robot soccer league recently started in Japan[87] would lie within our present scope.•emerging technologies such as nanotechnology [48] and Micro Electro-Mechanical Systems[117] that are likely to be very important to co-operative robotics are beyond the scope of this paper.Even with these restrictions, we find that over the past 8 years (1987-1995) alone, well over 200papers have been published in this field of cooperative (mobile) robotics, encompassing theories from such diverse disciplines as artificial intelligence, game theory/economics, theoretical biology, distributed computing/control, animal ethology and artificial life.We are aware of two previous works that have surveyed or taxonomized the literature. [13] is abroad, relatively succinct survey whose scope encompasses distributed autonomous robotic systems(i.e., not restricted to mobile robots). [50] focuses on several well-known “swarm” architectures (e.g., SWARM and Mataric’s Behavior-based architecture –see Section 2.1) and proposes a taxonomy to characterize these architectures. The scope and intent of our work differs significantly from these, in that (1) we extensively survey the field of co-operative mobile robotics, and (2) we provide a taxonomical organization of the literature based on problems and solutions that have arisen in the field (as opposed to a selected group of architectures). In addition, we survey much new material that has appeared since these earlier works were published.Towards a Picture of Cooperative RoboticsIn the mid-1940’s Grey Walter, along with Wiener and Shannon, studied turtle-like robots equipped wit h light and touch sensors; these simple robots exhibited “complex social behavior” in responding to each other’s movements [46]. Coordination and interactions of multiple intelligent agents have been actively studied in the field of distributed artificial intelligence (DAI) since the early 1970’s[28], but the DAI field concerned itself mainly with problems involving software agents. In the late 1980’s, the robotics research community be-came very active in cooperative robotics, beginning with projects such as CEBOT [59], SWARM[25], ACTRESS [16], GOFER [35], and the work at Brussels [151]. These early projects were done primarily in simulation, and, while the early work on CEBOT, ACTRESS and GOFER have all had physical implementations (with≤3 robots), in some sense these implementations were presented by way of proving the simulation results. Thus, several more recent works (cf. [91], [111], [131])are significant for establishing an emphasis on the actual physical implementation of cooperative robotic systems. Many of the recent cooperative robotic systems, in contrast to the earlier works, are based on a behavior-based approach (cf. [30]).Various perspectives on autonomy and on the connection between intelligence and environment are strongly associated with the behavior-based approach [31], but are not intrinsic to multiple-robot systems and thus lie beyond our present scope. Also note that a recent incarnation of CEBOT, which has been implemented on physical robots, is based on a behavior-based control architecture[34].The rapid progress of cooperative robotics since the late 1980’s has been an interplay of systems, theories and problems: to solve a given problem, systems are envisioned, simulated and built; theories of cooperation are brought from other fields; and new problems are identified (prompting further systems and theories). Since so much of this progress is recent, it is not easy to discern deep intellectual heritages from within the field. More apparent are the intellectualheritages from other fields, as well as the canonical task domains which have driven research. Three examples of the latter are:•Traffic Control. When multiple agents move within a common environment, they typically attempt to avoid collisions. Fundamentally, this may be viewed as a problem of resource conflict, which may be resolved by introducing, e.g., traffic rules, priorities, or communication architectures. From another perspective, path planning must be performed taking into con-sideration other robots and the global environment; this multiple-robot path planning is an intrinsically geometric problem in configuration space-time. Note that prioritization and communication protocols – as well as the internal modeling of other robots – all reflect possible variants of the group architecture of the robots. For example, traffic rules are commonly used to reduce planning cost for avoiding collision and deadlock in a real-world environment, such as a network of roads. (Interestingly, behavior-based approaches identify collision avoidance as one of the most basic behaviors [30], and achieving a collision-avoidance behavior is the natural solution to collision avoidance among multiple robots. However, in reported experiments that use the behavior-based approach, robots are never restricted to road networks.) •Box-Pushing/Cooperative Manipulation. Many works have addressed the box-pushing (or couch-pushing) problem, for widely varying reasons. The focus in [134] is on task allocation, fault-tolerance and (reinforcement) learning. By contrast, [45] studies two boxpushing protocols in terms of their intrinsic communication and hardware requirements, via the concept of information invariants. Cooperative manipulation of large objects is particularly interesting in that cooperation can be achieved without the robots even knowing of each others’ existence [147], [159]. Other works in the class of box-pushing/object manipulation include [175] [153] [82] [33] [91] [94] [92][114] [145] [72] [146].•Foraging. In foraging, a group of robots must pick up objects scattered in the environment; this is evocative of toxic waste cleanup, harvesting, search and rescue, etc. The foraging task is one of the canonical testbeds for cooperative robotics [32] [151] [10] [67] [102] [49] [108] [9][24]. The task is interesting because (1) it can be performed by each robot independently (i.e., the issue is whether multiple robots achieve a performance gain), and (2) as discussed in Section 3.2, the task is also interesting due to motivations related to the biological inspirations behind cooperative robot systems. There are some conceptual overlaps with the related task of materials handling in a manufacturing work-cell [47]. A wide variety of techniques have been applied, ranging from simple stigmergy (essentially random movements that result in the fortuitous collection of objects [24] to more complex algorithms in which robots form chains along which objects are passed to the goal [49].[24] defines stigmergy as “the production of a certain behaviour in agents as a consequence of the effects produced in the local environment by previous behaviour”. This is actually a form of “cooperation without communication”, which has been the stated object of several for-aging solutions since the corresponding formulations become nearly trivial if communication is used. On the other hand, that stigmergy may not satisfy our definition of cooperation given above, since there is no performance improvement over the “naive algorithm” –in this particular case, the proposed stigmergic algorithm is the naive algorithm. Again, group architecture and learning are major research themes in addressing this problem.Other interesting task domains that have received attention in the literature includemulti-robot security systems [53], landmine detection and clearance [54], robotic structural support systems (i.e., keeping structures stable in case of, say ,an earthquake) [107], map making [149], and assembly of objects using multiple robots [175].Organization of PaperWith respect to our above definition of cooperative behavior, we find that the great majority of the cooperative robotics literature centers on the mechanism of cooperation (i.e., few works study a task without also claiming some novel approach to achieving cooperation). Thus, our study has led to the synthesis of five “Research Axes” which we believe comprise the major themes of investigation to date into the underlying mechanism of cooperation.Section 2 of this paper describes these axes, which are: 2.1 Group Architecture, 2.2 Resource Conflict, 2.3 Origin of Cooperation, 2.4 Learning, and 2.5 Geometric Problems. In Section 3,we present more synthetic reviews of cooperative robotics: Section 3.1 discusses constraints arising from technological limitations; and Section 3.2discusses possible lacunae in existing work (e.g., formalisms for measuring performance of a cooperative robot system), then reviews three fields which we believe must strongly influence future work. We conclude in Section 4 with a list of key research challenges facing the field.2. Research AxesSeeking a mechanism of cooperation may be rephrased as the “cooperative behavior design problem”: Given a group of robots, an environment, and a task, how should cooperative behavior arise? In some sense, every work in cooperative robotics has addressed facets of this problem, and the major research axes of the field follow from elements of this problem. (Note that certain basic robot interactions are not task-performing interactions per se, but are rather basic primitives upon which task-performing interactions can be built, e.g., following ([39], [45] and many others) or flocking [140], [108]. It might be argued that these interactions entail “control and coordination” tasks rather than “cooperation” tasks, but o ur treatment does not make such a distinction).First, the realization of cooperative behavior must rely on some infrastructure, the group architecture. This encompasses such concepts as robot heterogeneity/homogeneity, the ability of a given robot to recognize and model other robots, and communication structure. Second, for multiple robots to inhabit a shared environment, manipulate objects in the environment, and possibly communicate with each other, a mechanism is needed to resolve resource conflicts. The third research axis, origins of cooperation, refers to how cooperative behavior is actually motivated and achieved. Here, we do not discuss instances where cooperation has been “explicitly engineered” into the robots’ behavior since this is the default approach. Instead, we are more interested in biological parallels (e.g., to social insect behavior), game-theoretic justifications for cooperation, and concepts of emergence. Because adaptability and flexibility are essential traits in a task-solving group of robots, we view learning as a fourth key to achieving cooperative behavior. One important mechanism in generating cooperation, namely,task decomposition and allocation, is not considered a research axis since (i) very few works in cooperative robotics have centered on task decomposition and allocation (with the notable exceptions of [126], [106], [134]), (ii) cooperative robot tasks (foraging, box-pushing) in the literature are simple enough that decomposition and allocation are not required in the solution, and (iii) the use of decomposition and allocation depends almost entirely on the group architectures(e.g. whether it is centralized or decentralized).Note that there is also a related, geometric problem of optimizing the allocation of tasks spatially. This has been recently studied in the context of the division of the search of a work area by multiple robots [97]. Whereas the first four axes are related to the generation of cooperative behavior, our fifth and final axis –geometric problems–covers research issues that are tied to the embed-ding of robot tasks in a two- or three-dimensional world. These issues include multi-agent path planning, moving to formation, and pattern generation.2.1. Group ArchitectureThe architecture of a computing sys tem has been defined as “the part of the system that remains unchanged unless an external agent changes it”[165]. The group architecture of a cooperative robotic system provides the infrastructure upon which collective behaviors are implemented, and determines the capabilities and limitations of the system. We now briefly discuss some of the key architectural features of a group architecture for mobile robots: centralization/decentralization, differentiation, communications, and the ability to model other agents. We then describe several representative systems that have addressed these specific problems.Centralization/Decentralization The most fundamental decision that is made when defining a group architecture is whether the system is centralized or decentralized, and if it is decentralized, whether the system is hierarchical or distributed. Centralized architectures are characterized by a single control agent. Decentralized architectures lack such an agent. There are two types of decentralized architectures: distributed architectures in which all agents are equal with respect to control, and hierarchical architectures which are locally centralized. Currently, the dominant paradigm is the decentralized approach.The behavior of decentralized systems is of-ten described using such terms as “emergence” and “self-organization.” It is widely claimed that decentralized architectures (e.g., [24], [10], [152],[108]) have several inherent advantages over centralized architectures, including fault tolerance, natural exploitation of parallelism, reliability, and scalability. However, we are not aware of any published empirical or theoretical comparison that supports these claims directly. Such a comparison would be interesting, particularly in scenarios where the team of robots is relatively small(e.g., two robots pushing a box), and it is not clear whether the scaling properties of decentralization offset the coordinative advantage of centralized systems.In practice, many systems do not conform toa strict centralized/decentralized dichotomy, e.g., many largely decentralized architectures utilize “leader” agents. We are not aware of any in-stances of systems that are completely centralized, although there are some hybrid centralized/decentralized architectures wherein there is a central planner that exerts high-levelcontrol over mostly autonomous agents [126], [106], [3], [36].Differentiation We define a group of robots to be homogeneous if the capabilities of the individual robots are identical, and heterogeneous otherwise. In general, heterogeneity introduces complexity since task allocation becomes more difficult, and agents have a greater need to model other individuals in the group. [134] has introduced the concept of task coverage, which measures the ability of a given team member to achieve a given task. This parameter is an index of the demand for cooperation: when task coverage is high, tasks can be accomplished without much cooperation, but otherwise, cooperation is necessary. Task coverage is maximal in homogeneous groups, and decreases as groups become more heterogeneous (i.e., in the limit only one agent in the group can perform any given task).The literature is currently dominated by works that assume homogeneous groups of robots. How-ever, some notable architectures can handle het-erogeneity, e.g., ACTRESS and ALLIANCE (see Section 2.1 below). In heterogeneous groups, task allocation may be determined by individual capabilities, but in homogeneous systems, agents may need to differentiate into distinct roles that are either known at design-time, or arise dynamically at run-time.Communication Structures The communication structure of a group determines the possible modes of inter-agent interaction. We characterize three major types of interactions that can be sup-ported. ([50] proposes a more detailed taxonomy of communication structures). Interaction via environmentThe simplest, most limited type of interaction occurs when the environment itself is the communication medium (in effect, a shared memory),and there is no explicit communication or interaction between agents. This modality has also been called “cooperation without communication” by some researchers. Systems that depend on this form of interaction include [67], [24], [10], [151],[159], [160], [147].Interaction via sensing Corresponding to arms-length relationships inorganization theory [75], interaction via sensing refers to local interactions that occur between agents as a result of agents sensing one another, but without explicit communication. This type of interaction requires the ability of agents to distinguish between other agents in the group and other objects in the environment, which is called “kin recognition” in some literatures [108]. Interaction via sensing is indispensable for modeling of other agents (see Section 2.1.4 below). Because of hard-ware limitations, interaction via sensing has often been emulated using radio or infrared communications. However, several recent works attempt to implement true interaction via sensing, based on vision [95], [96], [154]. Collective behaviors that can use this kind of interaction include flocking and pattern formation (keeping in formation with nearest neighbors).Interaction via communicationsThe third form of interaction involves explicit communication with other agents, by either directed or broadcast intentional messages (i.e. the recipient(s) of the message may be either known or unknown). Because architectures that enable this form of communication are similar tocommunication networks, many standard issues from the field of networks arise, including the design of network topologies and communications protocols. For ex-ample, in [168] a media access protocol (similar to that of Ethernet) is used for inter-robot communication. In [78], robots with limited communication range communicate to each other using the “hello-call” protocol, by which they establish “chains” in order to extend their effective communication ranges. [61] describes methods for communicating to many (“zillions”) robots, including a variety of schemes ranging from broadcast channels (where a message is sent to all other robots in the system) to modulated retroreflection (where a master sends out a laser signal to slaves and interprets the response by the nature of the re-flection). [174] describes and simulates a wireless SMA/CD ( Carrier Sense Multiple Access with Collision Detection ) protocol for the distributed robotic systems.There are also communication mechanisms designed specially for multiple-robot systems. For example, [171] proposes the “sign-board” as a communication mechanism for distributed robotic systems. [7] gives a communication protocol modeled after diffusion, wherein local communication similar to chemical communication mechanisms in animals is used. The communication is engineered to decay away at a preset rate. Similar communications mechanisms are studied in [102], [49], [67].Additional work on communication can be found in [185], which analyzes optimal group sizes for local communications and communication delays. In a related vein, [186], [187] analyzes optimal local communication ranges in broadcast communication.Modeling of Other Agents Modeling the intentions, beliefs, actions, capabilities, and states of other agents can lead to more effective cooperation between robots. Communications requirements can also be lowered if each agent has the capability to model other agents. Note that the modeling of other agents entails more than implicit communication via the environment or perception: modeling requires that the modeler has some representation of another agent, and that this representation can be used to make inferences about the actions of the other agent.In cooperative robotics, agent modeling has been explored most extensively in the context of manipulating a large object. Many solutions have exploited the fact that the object can serve as a common medium by which the agents can model each other.The second of two box-pushing protocols in[45] can achieve “cooperation without commun ication” since the object being manipulated also functions as a “communication channel” that is shared by the robot agents; other works capitalize on the same concept to derive distributed control laws which rely only on local measures of force, torque, orientation, or distance, i.e., no explicit communication is necessary (cf. [153] [73]).In a two-robot bar carrying task, Fukuda and Sekiyama’s agents [60] each uses a probabilistic model of the other agent. When a risk threshold is exceeded, an agent communicates with its partner to maintain coordination. In [43], [44], the theory of information invariants is used to show that extra hardware capabilities can be added in order to infer the actions of the other agent, thus reducing communication requirements. This is in contrast to [147], where the robots achieve box pushing but are not aware of each other at all. For a more com-plex task involving the placement of five desks in[154], a homogeneous group of four robots share a ceiling camera to get positional information, but do not communicate with each other. Each robot relies on modeling of otheragents to detect conflicts of paths and placements of desks, and to change plans accordingly.Representative Architectures All systems implement some group architecture. We now de-scribe several particularly well-defined representative architectures, along with works done within each of their frameworks. It is interesting to note that these architectures encompass the entire spectrum from traditional AI to highly decentralized approaches.CEBOTCEBOT (Cellular roBOTics System) is a decentralized, hierarchical architecture inspired by the cellular organization of biological entities (cf.[59] [57], [162] [161] [56]). The system is dynamically reconfigurable in tha t basic autonomous “cells” (robots), which can be physically coupled to other cells, dynamically reconfigure their structure to an “optimal” configuration in response to changing environments. In the CEBOT hierarchy there are “master cells” that coordinate subtasks and communicate with other master cells. A solution to the problem of electing these master cells was discussed in [164]. Formation of structured cellular modules from a population of initially separated cells was studied in [162]. Communications requirements have been studied extensively with respect to the CEBOT architecture, and various methods have been proposed that seek to reduce communication requirements by making individual cells more intelligent (e.g., enabling them to model the behavior of other cells). [60] studies the problem of modeling the behavior of other cells, while [85], [86] present a control method that calculates the goal of a cell based on its previous goal and on its master’s goal. [58] gives a means of estimating the amount of information exchanged be-tween cells, and [163] gives a heuristic for finding master cells for a binary communication tree. Anew behavior selection mechanism is introduced in [34], based on two matrices, the priority matrix and the interest relation matrix, with a learning algorithm used to adjust the priority matrix. Recently, a Micro Autonomous Robotic System(MARS) has been built consisting of robots of 20cubic mm and equipped with infrared communications [121].ACTRESSThe ACTRESS (ACTor-based Robot and Equipments Synthetic System) project [16], [80],[15] is inspired by the Universal Modular AC-TOR Formalism [76]. In the ACTRESS system,“robotors”, including 3 robots and 3 workstations(one as interface to human operator, one as im-age processor and one as global environment man-ager), form a heterogeneous group trying to per-form tasks such as object pushing [14] that cannot be accomplished by any of the individual robotors alone [79], [156]. Communication protocols at different abstraction levels [115] provide a means upon which “group cast” and negotiation mechanisms based on Contract Net [150] and multistage negotiation protocols are built [18]. Various is-sues are studied, such as efficient communications between robots and environment managers [17],collision avoidance [19].SWARM。

十种教学方法(英语教学)

十种教学方法(英语教学)

Great importance is given to precise native-like pronunciation. Use of the mother tongue by the teacher is permitted, but discouraged among and by the students. Successful responses are reinforced; great care is taken to prevent learner errors. There is a tendency to focus on manipulation of the target language and to disregard content and meaning.
Questions are answered in the target language. Grammar is taught inductively--rules are generalized from the and experience with the target language. Verbs are used first and systematically conjugated much later after some oral mastery of the target language. Advanced students read literature for comprehension and pleasure. Literary texts are not analyzed grammatically. The culture associated with the target language is also taught inductively. Culture is considered an important aspect of learning the language.

5g网络的原理和自动驾驶的英语作文

5g网络的原理和自动驾驶的英语作文

5g网络的原理和自动驾驶的英语作文全文共6篇示例,供读者参考篇1The Awesome World of 5G and Self-Driving CarsHave you ever been stuck in traffic and wished your car could just drive itself? Or tried to watch a video on your phone but it kept buffering because the internet was too slow? Well, two amazing new technologies called 5G and self-driving cars might be able to help with those problems!Let's start with 5G. The "G" stands for "generation" and it refers to the different types of networks that allow you to use the internet on your phone or other devices. The older 3G and 4G networks could only handle so much data at once, kind of like a small bucket. But 5G is like a huge pool that can hold way more data!How does 5G work? It uses super-high frequency radio waves to transmit data much faster than before. These radio waves are kind of like invisible lasers zipping the data through the air. But because they are high frequency, they can't travel as far. So instead of having one big cell tower broadcasting thesignal over a large area, 5G uses lots of small cell stations installed on things like light poles.Another cool thing about 5G is that it has much lower lag time, which is the delay between sending data and it arriving. This makes it perfect for things that need real-time responses like online gaming, video calls, or self-driving cars!Speaking of self-driving cars, they rely heavily on having a super-fast 5G connection to work properly. A self-driving car is kind of like a robot that can drive itself around without a human driver. It uses cameras, sensors, and artificial intelligence (AI) computers to see the road, follow traffic laws, and navigate to wherever you want to go.The cameras and sensors act like the car's eyes, constantly taking pictures and scanning the surroundings. The AI computer brain analyzes all this data and figures out what actions the car needs to take, like accelerating, braking, or turning. It creates a 3D map of everything around the car so it knows exactly where it is and what's happening nearby.But for the self-driving system to work seamlessly, it needs frequent updates from things like traffic data, maps, and traffic signal information. That's where the super-fast 5G connectioncomes in. With low lag time, the car can get real-time updates so its AI can make split-second decisions, just like a human driver.Self-driving cars could make travel so much easier and safer in the future! You could just get in and tell it where to go while you read, play games, or even take a nap during the drive. And since self-driving cars are programmed to follow all traffic rules precisely, there would be far fewer accidents caused by human errors like speeding, running red lights, or distracted driving.There are still some challenges to work out, like handling extreme weather conditions or unpredictable situations on the road. But companies are working hard to improve the technology. Maybe someday, every car will be self-driving!Both 5G and self-driving cars rely on cutting-edge technologies that sound like science fiction. But they are very real and will likely change how we use devices and travel in amazing ways. From blisteringly fast mobile internet to vehicles that can drive themselves, the future is looking pretty awesome and convenient! Who knows what other mind-blowing advancements we'll see next?篇25G Networks and Self-Driving Cars - The Future is Here!Hi everyone! Today I want to talk about two really cool technologies that are changing the world - 5G networks and self-driving cars. These might sound like complicated topics, but I'll do my best to explain them in a simple way.Let's start with 5G networks. You've probably heard of 4G, which is what most of our smartphones use right now to connect to the internet. Well, 5G is the next generation and it's a huge upgrade! It's like going from an old dial-up internet connection to blazing-fast fiber optic broadband.With 5G, data can be transmitted much faster and with hardly any delay (what grown-ups call "low latency"). This means you can download movies in seconds, have super smooth video calls, and play online games without any lag. Pretty awesome, right?But 5G isn't just for cooler phone stuff. It's going to power a lot of new technologies that rely on connecting many devices to the internet and each other. One of those technologies isself-driving cars!Self-driving cars, also called autonomous vehicles, are cars that can drive themselves without a human driver. They use a bunch of different sensors like cameras, radar, and lasers to "see" their surroundings. Powerful computers take all that sensor dataand use it to navigate roads, avoid obstacles, and get you to your destination safely.For self-driving cars to really work well, they need anultra-fast and reliable way to communicate with other cars on the road, as well as devices in the city's infrastructure like traffic lights. That's where 5G comes in!With 5G's high speeds and low latency, self-driving cars can constantly send and receive critical data about things like their location, speed, and planned route. They can warn each other about hazards, negotiate intersections, and coordinate their movements smoothly. It's like a super-advanced version of the cars talking to each other!Another way 5G will help self-driving cars is by allowing them to download huge databases of maps and traffic information in an instant. These cars have to know every road, lane, sign, and traffic pattern like the back of their hands. With 5G, they can quickly get up-to-date data on road conditions, construction areas, and more.Speaking of construction, 5G will also connect self-driving cars to machines like cranes and excavators at work sites. The cars can know exactly where those machines are operating anddrive extra carefully in those areas. It's like the cars and machines are on the same team, working together.All of this connectivity is what will make self-driving cars a reality on normal city streets. They'll be able to safely navigate through complex traffic situations by communicating with other cars, traffic signals, workers, and more - all in the blink of an eye thanks to 5G.In fact, some cities have already started testing self-driving buses and taxi services using early 5G networks. From what I've read, the rides are incredibly smooth and passengers feel really safe. I can't wait until we have self-driving school buses!Imagine how much easier our lives could be if our parents didn't have to spend hours stuck in traffic every day. Withself-driving cars communicating over 5G, traffic jams could be a thing of the past. Cars could cooperate to merge seamlessly, reroute around accidents, and just flow smoothly overall.Basically, 5G and self-driving cars are going to completely transform how we get around cities. No more stressful driving, wasting time sitting in traffic, or worrying about directions. We'll just hop in the car, kick back, and let it whisk us safely to our destination while we work, play games, or just relax.And that's not all - these technologies could also help reduce pollution by driving more efficiently and enabling more electric and hybrid vehicles. Fewer emissions is great news for the environment!I could honestly keep going on and on, but I think you get the main idea. The powerful combination of 5G connectivity and autonomous driving is opening up a new world of possibilities for transportation. A world with less traffic, less stress, and less environmental impact.It's the kind of futuristic dream that seemed impossible when I was a little kid watching sci-fi movies. But now, thanks to the hard work of brilliant engineers and scientists, that future is quickly becoming a reality.5G and self-driving cars are revolutionizing how we'll get around and interact with technology. I can't wait to see what other amazing innovations come next. The 21st century is going to be a thrilling ride!篇35G and Self-Driving Cars: The Future is Here!Hi everyone! Today I want to tell you about two really cool technologies that are changing the world - 5G networks and self-driving cars. These might sound like complicated topics, but I'll explain them in a simple way that even kids like us can understand. Get ready to have your mind blown!Let's start with 5G networks. You've probably heard of 4G, which is what our phones and other devices use to connect to the internet right now. Well, 5G is the next generation of wireless networks, and it's a huge upgrade! Imagine a world where you can download movies in seconds, play online games with zero lag, and video chat with crystal-clear quality. That's what 5G promises to deliver.But how does it work? 5G uses higher radio frequencies than previous networks, which means it can transmit data much faster. It's like having a superhighway for information instead of a regular road. And 5G also has something called "small cells," which are tiny cell towers that can be placed almost anywhere to provide better coverage and capacity.One of the coolest things about 5G is that it's not just for our phones and tablets. It will also power the Internet of Things (IoT), which is a fancy way of saying that all kinds of devices and objects can be connected to the internet. Imagine your fridgeordering groceries for you when you're running low, or your smart home adjusting the temperature and lights automatically based on your preferences. With 5G, these kinds of futuristic scenarios could become a reality.Now, let's talk about self-driving cars. These are vehicles that can drive themselves without a human driver, using a combination of sensors, cameras, and advanced computer systems. It might sound like something straight out of a sci-fi movie, but self-driving cars are already being tested on real roads!The way self-driving cars work is by constantly scanning their surroundings and using complex algorithms to make decisions about steering, acceleration, and braking. They can detect obstacles like pedestrians, other vehicles, and traffic signals, and react accordingly. Some self-driving cars even have special features like "pedestrian protection," which means they can automatically brake or steer away from people in the road.One of the biggest benefits of self-driving cars is safety. Human error is responsible for most car accidents, butself-driving cars don't get distracted, tired, or make poor decisions like humans do. They can also communicate with each other and with traffic systems to optimize routes and avoidcongestion, which could reduce emissions and save time and fuel.But just imagine how cool it would be to hop into aself-driving car, tell it where you want to go, and then sit back and relax while it does all the work! You could read, play games, or even take a nap during your commute. And for people with disabilities or the elderly, self-driving cars could provide newfound independence and mobility.Both 5G networks and self-driving cars are revolutionizing the way we live, work, and move around. They represent the cutting edge of technology and innovation, and they're just the beginning of what's possible in the future.As kids, we're growing up in an amazing time where science fiction is becoming reality. Who knows what other mind-blowing inventions and breakthroughs we'll see in our lifetimes? Maybe one day, we'll have flying cars powered by 6G networks, or robots that can do our chores for us. The possibilities are endless!So let's embrace these new technologies with open minds and excitement. The future is coming, and it's going to be awesome!篇4The Wonders of 5G and Self-Driving CarsDo you ever feel like the world is moving too fast? Well, buckle up because things are about to get even faster and cooler with 5G networks and self-driving cars!Let's start with 5G. You might have heard your parents or teachers talking about it, but what exactly is it? 5G stands for the 5th generation of wireless communication technology. It's like the latest and greatest version of the internet, but for your phone and other devices.Imagine you're trying to download a movie or a big game on your tablet. With the old 4G network, it would take forever, and you'd probably get bored waiting. But with 5G, it's like having a super-fast internet connection that can download those huge files in the blink of an eye!How does 5G work its magic? It uses higher radio frequencies than previous networks, which means it can carry more data at faster speeds. It's kind of like having a superhighway for your internet traffic instead of a regular road.But that's not all! 5G also has lower latency, which means there's less delay between when you send a request and when you get a response. This is really important for things like online gaming, where even a tiny delay can mean the difference between winning and losing.Now, let's talk about self-driving cars – the coolest thing since sliced bread! You've probably seen them in movies or cartoons, but they're becoming a reality thanks to amazing technology.A self-driving car is a vehicle that can sense its environment and navigate without human input. It uses a bunch of sensors, cameras, and other gadgets to "see" the road, detect obstacles, and make decisions on where to go and how to get there.Imagine being able to sit back, relax, and let the car do all the driving for you! No more worrying about traffic jams, getting lost, or falling asleep at the wheel. The car will take you where you need to go, safely and efficiently.But how does it work? Well, self-driving cars rely on a bunch of different technologies working together. First, there are the sensors that gather data about the car's surroundings, like cameras, radar, and lidar (which is like radar but with lasers!).Then, there's the computer system that processes all this data and makes decisions based on it. This system uses complex algorithms and artificial intelligence to understand the environment, plan a route, and control the car's movements.One of the coolest things about self-driving cars is that they can communicate with each other and with the infrastructure around them. This is where 5G comes in handy! With itssuper-fast speeds and low latency, 5G can allow cars to share information and coordinate their movements in real-time, making driving even safer and more efficient.Imagine a world where cars can "talk" to each other and to traffic lights, road signs, and even pedestrians! They could warn each other about obstacles, accidents, or traffic jams, and adjust their routes accordingly. It's like having a team of super-smart drivers working together to get everyone where they need to go quickly and safely.So, get ready for a future where you can stream movies at lightning speed while your car does all the driving for you! It might sound like science fiction, but with 5G and self-driving cars, it's just around the corner.篇5Certainly! Here's an essay of around 2000 words on "The Principles of 5G Networks and Autonomous Driving," written in English from a child's perspective:The Future is Here: 5G Networks and Self-Driving Cars!Hi there! My name is Emma, and I'm 10 years old. Today, I'm going to tell you all about two super cool technologies that are changing the world: 5G networks and autonomous vehicles (that's a fancy way of saying self-driving cars)!Let's start with 5G networks. Have you ever heard your parents complain about slow internet or dropped calls? Well, 5G is here to solve that problem! You see, our phones, tablets, and other devices use something called a "network" to connect to the internet and make calls. The older networks, like 3G and 4G, were like narrow pipes – they could only handle so much data at once. But 5G is like a huge water slide! It can move a ton of data really, really fast.How does 5G work its magic? It uses higher radio frequencies than older networks, which means it can transmit more data at once. But these high frequencies have a hard time going through walls and other obstacles. So, 5G networks use something called "small cells" – tiny base stations that are placed closer together to boost the signal.Another cool thing about 5G is that it has way less delay (or "latency") than older networks. That means when you tap on something, it happens almost instantly! This is really important for things like online gaming, where even a tiny delay can mess up your experience.But 5G isn't just about faster internet and smoother streaming. It's also helping to power the next big thing:self-driving cars!Imagine being able to hop into a car, tell it where you want to go, and then just sit back and relax while it drives you there safely. That's the idea behind autonomous vehicles, and 5G is a key part of making them work.You see, self-driving cars need to constantly communicate with something called a "cloud" – a massive network of computers that processes all the data the car collects from its sensors (like cameras and radar). The car sends this data to the cloud, and the cloud tells the car what to do next: speed up, slow down, turn left, and so on.But for this to work smoothly, the car needs a super fast and reliable internet connection – and that's where 5G comes in! Its lightning-quick speeds and low latency mean that the car can send and receive data from the cloud almost instantly, allowing itto make split-second decisions and react to its surroundings in real-time.Self-driving cars also use something called"vehicle-to-everything" (or "V2X") communication. This lets them "talk" to other cars, traffic lights, and even pedestrians, helping them navigate safely and avoid collisions.And then there's the software that makes sense of all this data and decides how the car should respond. This software uses something called "machine learning" – a type of artificial intelligence that can learn and improve itself over time, just like how you get better at a video game the more you play it.It's all super complicated stuff, but the end result is a car that can drive itself safer than most human drivers! And with 5G helping to keep these cars connected and communicating, we could see a future where traffic jams, accidents, and even the need to own a car become things of the past.But even with these challenges, the future of 5G and autonomous driving looks incredibly exciting! Just imagine being able to work, play games, or even take a nap while your car whisks you off to your destination. Or think about how much easier it could be for people with disabilities or the elderly to get around.And that's not even mentioning the potential environmental benefits of self-driving cars! Since they can drive more efficiently and communicate with each other, they could help reduce traffic congestion and emissions.So, there you have it – a kid's-eye view of two technologies that are helping to shape the world of tomorrow. Whether you're a tech-lover like me or just someone who's curious about the future, I hope you found this look at 5G networks andself-driving cars interesting and easy to understand.Who knows, maybe by the time I'm an adult, we'll all be zipping around in autonomous vehicles, streaming movies on lightning-fast 5G connections! The possibilities are endless, and I can't wait to see what the future holds. Thanks for reading, and happy exploring!篇6The Future is Here: 5G Networks and Self-Driving CarsHey there, kids! Do you ever feel like technology is moving so fast that it's hard to keep up? Well, you're not alone! But don't worry, because today we're going to talk about two really cool things that are changing the world: 5G networks and self-driving cars.Let's start with 5G networks. You might be wondering, "What's a 5G network, and why is it so special?" Well, a 5G network is like a super-fast internet that can send and receive information much quicker than the networks we use today. It's kind of like when you upgrade from dial-up internet to broadband – everything just becomes way faster and smoother!But how does it work? Imagine that information is like a bunch of toy cars that need to get from one place to another. With older networks, like 3G and 4G, the roads were pretty narrow and could only fit a few cars at a time. But with 5G, it's like having a massive superhighway with lots of lanes, so many more cars (or bits of data) can travel at once without getting stuck in traffic jams.Another cool thing about 5G is that it uses higher radio frequencies than older networks. These frequencies are like invisible waves that can carry information much farther and faster. It's kind of like when you're trying to send a message to your friend across the playground – if you shout really loud, your friend can hear you from a long way away!Now, let's talk about self-driving cars. You've probably seen them in movies or on TV, and they might seem like somethingstraight out of the future. But the truth is, self-driving cars are already here, and they're getting smarter every day!So, how do these cars work without a human driver? Well, they use a bunch of different technologies like cameras, sensors, and special software that helps them "see" the world around them. It's kind of like having a bunch of extra eyes and ears that can detect everything from other cars and pedestrians to traffic lights and road signs.But that's not all! Self-driving cars also use something called "machine learning" to get better at driving over time. It's like when you practice a sport or an instrument – the more you do it, the better you get. The car's software learns from every trip it takes, and it can use that information to make better decisions on the road.Now, you might be wondering, "Why do we needself-driving cars? Can't humans just keep driving?" Well,self-driving cars can actually make our roads much safer. They don't get distracted or tired like human drivers, and they can react much faster to dangerous situations. Plus, they can help people who can't drive, like the elderly or people with disabilities, get around more easily.But wait, there's more! Self-driving cars can also help reduce traffic and pollution. Since they can communicate with each other and with traffic lights, they can coordinate their movements and avoid getting stuck in traffic jams. And since they drive more efficiently, they can save a lot of fuel and produce fewer emissions.Now, you might be thinking, "Wow, 5G networks andself-driving cars sound amazing! But how do they work together?" Well, it's like a perfect match made in technology heaven!Self-driving cars need to constantly communicate with other cars, traffic lights, and even the roads themselves to stay safe and efficient. And 5G networks provide the super-fast and reliable connections that these cars need to share information inreal-time.It's like having a group of friends trying to coordinate a game of tag. If you can't communicate quickly and clearly with each other, the game gets really confusing and chaotic. But with 5G, it's like having a super-fast walkie-talkie that lets everyone stay in sync and have a great time!But even with these challenges, the future looks incredibly exciting! Imagine a world where you can stream movies or playgames without any lag, or where you can sit back and relax while your car takes you safely to your destination. It's like something out of a sci-fi movie, but it's becoming a reality right before our eyes!So, what do you think about 5G networks and self-driving cars? Are you excited about the possibilities, or do you have some concerns? Either way, it's important to stay curious and keep learning about these amazing technologies. Who knows, maybe some of you will grow up to be the engineers, programmers, or scientists who help make the future even brighter!。

五篇文章和五大中心

五篇文章和五大中心

五篇文章和五大中心英文回答:Five Essential Essays on AI and the Five Essential Focal Points.The field of artificial intelligence (AI) is rapidly evolving, posing both opportunities and challenges. To navigate this landscape effectively, it is crucial to delve into foundational essays that provide insights into AI's multifaceted nature. In this article, we present five essential essays that offer diverse perspectives on AI, complemented by a discussion on five central focal points that encapsulate the key dimensions of AI research and development.1. "AI: A Modern Approach" (Stuart Russell and Peter Norvig)。

This widely acclaimed textbook offers a comprehensiveoverview of AI, covering foundational concepts, algorithms, and applications. It provides a solid starting point for understanding the field's theoretical and practical aspects.2. "Superintelligence: Paths, Dangers, Strategies" (Nick Bostrom)。

5g未来的连通性英语作文

5g未来的连通性英语作文

5g未来的连通性英语作文5G FUTURE CONNECTIVITYIn the future world, every object will have a sensor, and 5G will be used to realize data interaction. People, plants, machines, mobile phones, transportation tools, household appliances, etc. will have independent IP, and all objects will be controllable, communicated, positioned, and work together. Almost everything in the world will be connected, beyond the limits of space and time.China is overtaking at a curve! The Internet has given China a chance to overtake at corners in the fourth industrial revolution! Baidu seeks to connect "people and information"; Alibaba seeks to connect "people and goods"; Tencent's pursuit is to connect "people and people" BAT. The pursuit is to link "people", "information" and "goods" together! These three represent human behaviors: social interaction, perception and trading. Once they are connected, they can play a combined effect of 1+1+1 greater than 3! Fission and fusion can occur at any time, with instant polymerization and unlimited tension!The driverless vehicle is a kind of intelligent vehicle, also known as wheeled mobile robot. It mainly relies on the intelligent driver with computer system as the main part in thevehicle to achieve the goal of driverless. "The so-called Internet of Things, commonly speaking, is to install chips on every object in life, and then connect them through a wireless system to control all devices at home and outdoors through a single terminal. Breakthroughs have been made in feasibility and practicality.Now China's 5G technology has stood at the top of the world, leading the world, and has a higher voice and rule making power! Great, my country!。

  1. 1、下载文档前请自行甄别文档内容的完整性,平台不提供额外的编辑、内容补充、找答案等附加服务。
  2. 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
  3. 3、如文档侵犯您的权益,请联系客服反馈,我们会尽快为您处理(人工客服工作时间:9:00-18:30)。

Contents1-4 Forward5 Contributors6 I. BASIC SCIENCES 8A. Immune Mechanisms81. Antigens and Allergens2. MHC3. HLA System4. Immunoglobulins5. Immunogenetics6. T Cell ReceptorComplement and Kinin Systems8. Acute Phase Reactants9. Innate ImmunityB. Anatomy and Cellular Elements of the Immune System 91.Lymphoid Organs2. Skin3. Lymphocytes4. B cells5. T cellsa. Th1 and Th26. Monocytes, Macrophages, Dendritic Cells7. NK Cells8. Mast Cells and Basophils9. Eosinophils10. Neutrophils11. Platelets and RBC’sC. Regulators of Cell Actions and Interactions 111. Adhesion Molecules2. Cytokines, chemokines, growth factor3. Cytokines and the lungs4. Defensins5. Beta Adrenergic Receptor6. LigandsD. Inflammatory Mediators 121. Neuropeptides2. Neuroendocrine Interactions3. PAF4. Histamine5. Arachadonic Acid Products6. Nitric Oxide7. Immunomodulatory agents (mechanisms)E. Immune Responses 131. IgE Mediated2. IgG, M and A Mediated3. IgD Mediated4. Immune Complex Reactions15. Cell mediated immunity, granuloma formation; contact sensitivity6. Cytotoxic Cell7. Memory and AnergyF. Mucosal Immunity 141. Basic Mechanisms: GALT, BALT, Secretary IgA, IgE2. Nonspecific: Lysozyme, mucus, salivaG. Transplant Immunology 141. Graft Rejection2. Graft vs Host DiseaseH. Tumor Immunology 141. Tumor Antigens, Antibodies, Cellular ResponsesI. Immunoregulation141. Immune Tolerance2. Idiotypic Network3. Autoimmunity and Autoimmune Antibodies4. ApoptosisJ. Diagnostic Laboratory Immunology 15 K. Research Principles 151. Experimental Design2. Data Interpretation/biostatisticsII. CLINICAL SCIENCES17A. Allergic Disorders 171. Upper Airway Diseasea. Rhinitisb. Sinusitis/nasal polyposis1) Nasal polyposis2) Sinusitisc. Laryngeal disordersd. Allergy skin testing (methods and interpretation)e. Nasal challenge and assessment of nasal secretionsf . Ear disorders2. Eye Diseases 193. Dermatologic Diseases 19a. Urticaria and angioedemab. Atopic dermatitisc. Bullous skin diseasesd. Drug rashese. E. multiforme, E. nodosumf.Other immunologic disordersg.Dermatopathology/immunoflorescenceh.Mastocytosis4.Lower Respiratory Tract Diseases 21a. Asthma1)Epidemiology, prevention2)Prevalence, morbidity, mortality, statistics3) Genetics4) Inflammation and pathophysiology25) Exercise induced6) Aspirin-induced7) Occupational8) ABPA9) Infections10) Asthma and pregnancyb. COPDc. Cough syndromesd. Immotile ciliae. Pulmonary function testingf.Bronchial provocationg.Sputum and BAL analysis5.Drug Allergy 246. Adverse Reactions To Ingestants 24a.Food Allergy/Intolerance, Gluten Sensitivityb.Eosinophilic Gastroenteritisc.Oral Challenge7. Anaphylaxis 25a. Epinephrine8. Insect Hypersensitivity259. Therapeutic Modalities25a.Environmental controlb.Pharmacotherapy1)Antihistamines2)Adrenergic agonists3)Corticosteroids4)Leukotriene modifiers5)Delivery devices6)Monoclonal antibodiesc.Immunotherapyd.Other therapiese.Unproven therapiesf.Inappropriate therapies10. Pollen And Mold Identification And Cross Reactivity28B.Immunodeficiency 28plement282.Primary Immunodeficiencies 29a.SCIDb.DiGeorge syndromec.Ataxia telangectasiad.Wiskott-Aldriche.Selective IgA deficiencyf.Hyper IgMg.Hyper IgEh.Hypo/agammaglobulinemiai.Novel immunodeficienciesj.X-linked lymphoproliferative diseasek.ALPS31. Evaluation and interpretation of lab tests3. Acquired Immunodeficiencies 31a.AIDSb.Non-AIDSc.Evaluation and interpretation of lab tests4. Leukocyte Disorders 32a.CGDb.Myeloperixodase deficiencyDd.Chediak-Higashie.Hypereosinophilic syndromesf.Neutrophil function defectsg.Evaluation and interpretation of lab testsC.Immunoregulatory Disorders 331.Autoimmunity33a.SLE and other connective tissue diseasesb.Immune endocrinopathiesc.Gastrointestinal diseasesd.Neuropaties and neuromuscular diseasese.Immunohematologic diseasesf.Immunologic eye diseasesg.Evaluation and interpretation of lab tests2.Vasculitis333.Transplantation and GVH334.Immune Related Malignancies 33a.Plasma cell dyscrasia, multiple myelomab.Other gammopathies and amyloidosis5.Reproductive Immunology346.Immunomodulation34a.Immunosuppressantsb.Immune reconstitutionc.Gammaglobulin and monoclonal antibodiesd.Cytokine receptor and antagonistse.Vaccinesf.Plasmapheresis and cytopheresisg.Recombinant molecules7.Infections348.Research And Ethics 34Joint Task Force On Practice Parameters 364ForwardDear Allergy/Immunology Fellows-in-training:The Training Program Director’s Committee of the American Academy of AllergyAsthma and Immunology is pleased to present the 2001 TPD Reading List.The headings are based on the TPD Core Curriculum outline and the list is intended as a supplement to other learning activities. The articles listed are a compilation of journal articles suggested by the TPD contributors listed on the following page, and through our constant review and scanning of the A/I literature. The articles cited are mostly recent publication, as well as some articles that are considered benchmark work.You may note that some headings do not have citations. This is either due to the lack of submissions or publications of new articles on the topic. To fill the gaps, we suggest that you refer to the previous years TPD Reading Lists, or submit to us newer publications that you may review on the topic. Besides the usual format that lists the citations, this year we have experimented with a new format that we hope will be more beneficial to you. The new format includes either adding a commentary based on a summary of the work cited (the basic science section) or the complete abstract (the clinical science section). We would like your feed-back as to which format is preferable. The citations have been compiled using the “endnote 4.0” program. If you have access to “endnote 4.0” we can e-mail you the endnote library upon request.The TPD Reading List will be posted on the AAAAI web site that you can access at . A copy of the articles that are more difficult to find will be kept at the AAAAI. If you have difficulty obtaining some of them in complete text, please contact Cynthia Schopf at the AAAAI.We would like to thank the program directors and fellows-in-training who have submitted articles for the TPD Reading List. We would also like to thank in advance those who did not submit articles, as we are sure that they will contribute to future TPD Reading Lists. For that purpose, we would like to suggest to have the future TPD Reading List more interactive. We would like to receive from you the articles you feel every other fellow-in-training should read. We will compile them and post frequent updates to the TPD Reading List. Make your submissions preferably by e-mail to assaa0@ , or by mail to Amal Assa’ad, MD, Division of Pulmonary Medicine, Allergy and Immunology, Children’s Hospital Medical Center, 3333 Burnet Ave, Cincinnati, OH 45229.With our best wishes for a bright career in Allergy and Immunology,Amal Assa’ad, MD, FAAAAI Michael Kaplan, MD, FAAAAIChildren’s Hospital Medical Center, Cincinnati, OH Kaiser Permanente, Los Angelos, CA5Contributors 1)Charles Bassett, M.D.Long Island College Hospital, Brooklyn, NY2)Allan Becker, MDUniversity of Manitoba Winnipeg, Manitoba, Canada3)Leonard Bielory, MDUMDNJ-New Jersey Medical School, Newark, NJ4)David Berstein, MDUniversity of Cincinnati, Cincinnati, OH5) Mariana Castells, M.D., Ph.D.Harvard Medical School, Boston, MA6)W.K. Dolen, MDMedical College of Georgia, Augusta, GA7)Mark Dykewicz, MDSt Louis University Medical School, St Louis, MO8)Marianne Fieri, M.D.Nassau County Medical Center, New York, NY9)Larry Hagan, MDWillford Hall Medical Center, Lackland AFB, TX10)Harumi Jyonouchi, MDUniversity of Minnesota, Minneapolis, MN11)David Khan, MDUniversity of Texas Southwestern Medical Center, Dallas, TX 12)Charles Kirkpatrick, M.D.University of Colorado Health Sciences Center, Denver, CO 13)Betty Lew, MDUniversity of Tennessee, Memphis, TN14)Stephen McGeady, MDThomas Jefferson University, Wilmington, DE15)Dean Metcalfe, M.D.National Institute of Health, Baltimore, MD616)Michael Simon, M.D.VA Medica Center, Detroit, MI17)Eliseo Villalobos, MD (fellow)Children’s Hospital of Pittsburg, Pittsburg, PA18)Laurianne Wild, MDTulane University Medical Center, New Orleans, LA19)Michael Zacharisen, MDMedical College of Wisconsin, Milwaukee, WI20)Ed Zarotti, MDHenry Ford Health System, Detroit, MI21)Members of the Division of Pulmonary Medicine, Allergy and Clinical Immunology, Children’sHospital Medical Center, Cincinnati, OHa)Gurjit Khurana Hershey, MD, Ph Db)Nives Zimmermann7I. Basic SciencesA. Immune Mechanisms1. Antigens and AllergensKurup and Banerjee. Fungal allergens and peptide epitopes. Peptides 2000;21:589-99Simon-Nobbe, et al. IgE-binding epitopes of enolases, a class of highly conserved fungal allergens. J Allergy Clin Immunol 2000;106:887-895Akdis and Blaser. Regulation of specific immune responses by chemical and structural modifications of allergens. Int Arch Allergy Immunol 2000;121:261-9Aalberse. Structural biology of allergens. J Allergy Clin Immunol 2000;106:228-38 Korematsu, et al. C8/119S mutation of major mite allergen Derf-2 leads to degenerate secondary structure and molecular polymerization and induces potent and exclusive Th1 cell differentiation. J Immunol 2000; 165:2895-9022. MHCMartinsohn, et al. The gene conversion hypothesis of MHC evolution: a review [published erratum appears in Immunogenetics 2000 Jun;51(7):613]. Immunogenetics 1999;50:168-2003. HLA SystemKlein and Sato. The HLA system. First of two parts. N Engl J Med 2000; 343:702-9Klein and Sato. The HLA system. Second of two parts. N Engl J Med 2000;343:782-64. ImmunoglobulinsEstes DM; Tuo W; Brown WC; Goin J. Effects of type I/type II interferons and transforming growth factor-beta on B-cell differentiation and proliferation. Definition of costimulation and cytokine requirements for immunoglobulin synthesis and expression. Immunol 1998;95:604-11.Kawano Y, Noma T. Role of Interleukin-2 and interferon-gamma in inducing production of IgG subclasses in lymphocytes of human newborns. Immunol 1996;88:40-8.5. ImmunogeneticsJones AM, Gaspar HB. Immunogenetics: Changing the face of immunodeficiency. J. Clin Pathol 2000 53:60-656. T Cell ReceptorTeyton L, Apostolopoulos V, Cantu C 3rd, Celia H. Function and dysfunction of T cell receptor: structural studies. Immunol Res 2000;21:325-30.Cantor H. T-cell receptor crossreactivity and autoimmune disease. Adv Immunol 2000;75:209-3387. Complement and Kinin SystemsLambris JD, Reid KB, Volanakis JE The evolution, structure, biology, and pathophysiology of complement. Immonol Today. 1999; 20:207-118. Acute Phase ReactantsDu Clos TW. Function of C-reactive Protein. Ann Int Med 2000;32:274-8.9. Innate ImmunitySongl W, Sarrias MR, Lambris JD. Complement and innate immunity. Immunopharmacology 2000;49:187-198.Medzhitov R, Janeway C. Innate Immunity. N. Engl. J. Med 2000;343:338-344.Aderem and Ulevitch. Toll-like receptors in the induction of the innate immune response.Nature 2000; 406:782-7B.Anatomy and Cellular Elements of the Immune System1.Lymphoid OrgansCyster JG. Chemokines and cell migration in secondary lymphoid organs. Science 1999;286:2098-102.2. SkinHassan-Zahraee M; Wu J; Gordon J. Rapid synthesis of IFN-gamma by T cells in skin may playa pivotal role in the human skin immune system. Int Immunol 1998;1599-612.3. LymphocytesHayday AC. [gamma][delta] cells: a right time and a right place for a conserved third way of protection. Annu Rev Immunol 2000;18:975-1026.Isomaki, et al. Expression of soluble human signaling lymphocytic activation molecule in vivo. J Allergy Clin Immunol 1999; 103:114-84. B cellsPatke CL, Shearer WT. gp120- and TNF-alpha-induced modulation of human B cell function: proliferation, cyclic AMP generation, Ig production, and B-cell receptor expression. J Allergy Clin Immunol 2000;105:975-982.5. T cellsPrescott, et al. Development of allergen-specific T-cell memory in atopic and normal children [see comments]. Lancet 1999;353:196-200a. Th1 and Th2Mosmann, et al. Two types of murine helper T cell clone. I. Definition according to profiles of lymphokine activities and secreted proteins. J Immunol 1986;136:2348-57Commentary: A benchmark article.96. Monocytes, Macrophages, Dendritic CellsGrakoui et. al. The immunologic synapse: a molecular machine controlling T-cell activation Movies of this rearrangement are on the world wide web Vignola AM, Gjomerkaj M, Arnoux B, Bosquet J. Monocytes. J. Allergy Clin Immunol 1998; 101:149-52.McLellan AD, Kampgen E. Functions of myeloid and lymphoid dendritic cells. Immunol Lett 2000;72:101-5.Banchereau J, Briere F, Caux C, Davoust J, et al. Immunobiology of dendritic cells. Annu Rev Immunol 2000;18:767-811.7. NK CellsLieberman N, Mandelboim O. The role of NK cells in innate immunity. Adv Exp Med Biol. 2000;479:137-45.Peritt, et al. Differentiation of human NK cells into NK1 and NK2 subsets. J Immunol 1998; 161:5821-48. Mast Cells and BasophilsForsythe P, Ennis M. Clinical consequences of mast cell heterogeneity. Inflamm Res 2000;49:147-54.Dvorak AM. Cell biology of the basophil. Int Rev Cytol 1998;180:87-236.Tkaczyk, et al. In vitro and in vivo immunostimulatory potential of bone marrow-derived mast cells on B- and T-lymphocyte activation. J Allergy Clin Immunol 2000; 105:134-42Lorentz, et al. Human intestinal mast cells are capable of producing different cytokine profiles: role of IgE receptor cross-linking and IL-4. J Immunol 2000; 164:43-89. EosinophilsGleich GJ. Mechanisms of eosinophil-associated inflammation. J Allergy Clin Immunol 2000;105:651-63.10. NeutrophilsJohnston RB Jr. Function and cell biology of neutrophils and mononuclear phagocytes in the newborn infant. Vaccine 1998;16:1363-8.Berliner N. Molecular biology of neutrophil differentiation. Curr Opin Hematol 1998;5:49-53.11. Platelets and RBC’sKlouche M, Klinger MH, Kuhnel W, et al. Endocytosis, storage and release of IgE by human platelets: Differences in patients with type I allergy and non-atopic subjects. J Allergy Clin Immunol 1997;100:235-41.10C.Regulators of Cell Actions and Interactions1. Adhesion MoleculesPanattieri RA Jr. Cellular and molecular mechanisms regulating airway smooth muscle proliferation and cell adhesion molecule expression. Am J Respir Crit Care Med 1998;158:S133-40.Bochner BS. Cellular Adhesion and its antagonism. J.Allergy Clin Immunol 1997;100:581-5.2. Cytokines, chemokines, growth factorLuster AD. Chemokines – Chemotactic Cytokines that mediate inflammation. N Eng. J Med 1998;338:436-45.Leonard WJ, Lin JX. Cytokine receptor signaling pathways. J Allergy Clin Immunol 2000;105:877-88.Rothenberg & Zimmermann. Eosinophil chemokines. In: Chemokines in allergic disease. Editor Rothenberg. Marcel Dekker, Inc. 2000 p151-171Cyster, J. G. Chemokines and cell migration in secondary lymphoid organs. Science 199; 286:2098-21023. Cytokines and the lungsDoucet, et al. Interleukin (IL) 4 and IL-13 act on human lung fibroblasts. Implication in asthma. J Clin Invest 1998; 101:2129-39Hakonarson, et al. Autocrine interaction between IL-5 and IL-1beta mediates altered responsiveness of atopic asthmatic sensitized airway smooth muscle. J Clin Invest 1999; 104:657-67Hakonarson, et al. Regulation of TH1- and TH2-type cytokine expression and action in atopic asthmatic sensitized airway smooth muscle. J Clin Invest 1999; 103:1077-87Humbert, et al. IL-4 and IL-5 mRNA and protein in bronchial biopsies from patients with atopic and nonatopic asthma: evidence against "intrinsic" asthma being a distinct immunopathologic entity. Am J Respir Crit Care Med 1996; 154:1497-5044. DefensinsYang et. al. Beta-defensins: linking innate and adaptive immunity through dendritic and T cell CCR6 [see comments] Science 1999; 286:525-285. Beta Adrenergic ReceptorIsrael E. Drazen JM, Liggett SB, Boushey HA, et al. The Effect of Polymorphisms of the beta(2)-Adrenergic Receptor on the Response to Regular Use of Albuterol in Asthma. Am J Resp Crit Care Med 2000;162:75-80.11Nagatomo T, Koike K. Recent advances in structure, binding sites with ligands and pharmacological function of beta-adrenoceptors obtained by molecular bilogy and molecular modeling. Life Sci 2000;66:2419-26.6. LigandsAnderson AC, Waldner H, Turchin V. Jabs C, et al. Autoantigen-responsive T cell clones demonstrate unfocused TCR cross-reactivity toward multiple related ligands: implications for autoimmunity. Cell Immunol. 2000;202:88-96.Surh CD, Ernst B, Lee DS, Dummer W, LeRoy E. Role of self-major histocompatibility complex/peptide ligands in selection and maintenance of a diverse T cell repertoire. Immunol Res 2000;21:331-9D.Inflammatory Mediators1. NeuropeptidesForsythe P, McGarieg LP, Heaney LG, et al. Sensory Neuropeptides induce histimine release from bronchoalveolar lavage cells in both nonasthmatic coughers and cough variant asthmatics. Clin Exp Allergy 2000; 30:225-32.van Hagen PM, Hofland LJ, ten Bokum AM, et al. Neuropeptides and their receptors in the immune system. Ann Med 1999;Suppl 2:15-22.2. Neuroendocrine InteractionsSternberg, EM. Interactions between the immune and neuroendocrine systems. Prog Brain Res. 2000;122:35-42.3. PAFBanyon Y, Alonso A, Hernandez M, et al. Mechanisms of cell signaling in immune mediated inflammation. Cytokines Cell Mol Ther 1998;4:275-86.4. HistamineNovak I, Falus A. Molecular biology and role of histamine in physiological and pathological reactions. A review. Acta Biol Hung. 1997;48:385-94.5. Arachadonic Acid ProductsWenzel, SE. Inflammation, leukotrienes and the pathogenesis of the late asthmatic response. Clin Exp Allergy. 1999;29:1-3.Devillier P, Baccard N, Advenier C. Leukotrienes, Leukotriene receptor antagonists and leukotriene synthesis inhibitors in asthma: an update. Part I: synthesis, receptors and role of leukotrienes in asthma. Pharmacol Res. 1999 40:3-13.6. Nitric OxideLiaudet L; Soriano FG; Szabo C. Biology of nitric oxide signaling. Crit Care Med 2000;28(4 Suppl):N37-52.7. Immunomodulatory agents (mechanisms).12Mashi KN. Immunomodulatory agents for prophylaxis and therapy of infections. Int J Antimicrob Agents 2000;14:181-191.Klinman DM; Barnhart KM; Conover J. CpG motifs as immune adjuvants. Vaccine 1999;17:19-25.E.Immune Responses1. IgE MediatedKinet JP. The high-affinity IgE receptor (Fc epsilon RI): from physilogy to pathology. Ann Rev Immunol 1999;17:931-72.Bacharier and Geha. Molecular mechanisms of IgE regulation. J Allergy Clin Immunol 2000; 105:S547-58Cameron, et al. Local synthesis of epsilon germline gene transcripts, IL-4, and IL-13 in allergic nasal mucosa after ex vivo allergen exposure. J Allergy Clin Immunol 2000;106:46-522. IgG, M and A MediatedHexam JM, Carayannopoulos L, Capra JD. Structure and function of lgA. Chem Immunol 1997;65:73-87.Isaacs JD; Greenwood J; Waldmann H Therapy with monoclonal antibodies. II. The contribution of Fc gamma receptor binding and the influence of C(H)1 and C(H)3 domains on in vivo effector function. J. Immunol 1998;161:3862-9.3. IgD MediatedHonkawa K, Nishizumi H, Umemori H, et al T(h)Z cytokine dependence of IgD production by normal human B cells. Int Immunol 1999;11:1819-284. Immune Complex ReactionsSchippereli JA. Complement and Immune complexes. Res. Immunol 1996; 147:109-10 A review.5. Cell mediated immunity, granuloma formation; contact sensitivityRuth JH, Warmington KS, Shang X, Lincoln P, et al. Interleukin 4 and 13 participation in mycobacterial (type-1) and schistosomal (type-2) antigen-elicited pulmonary granuloma formation: multiparameter analysis of cellular recruitment, chemokine expression and cytokine networks. Cytokine, 2000;12:432-44.Hoyne GF, Dallman MJ, Lamb, JR. T-cell regulation of peripheral tolerance and immunity: the potential role for Notch signaling. Immunology, 2000;100:281-8.Grabbe S, Schwarz T. Immunoregulatory mechanisms involved in elicitation of allergic contact hypersensitivity. Immunol Today 1998;19:37-44.6. Cytotoxic CellShresta S; Pham CT; Thomas DA; Graubert TA; Ley TJ. How do cytotoxic lymphocytes kill their targets? Curr Opin Immunol 1998;10:581-7.137. Memory and AnergyFarber DL. T cell memory: heterogeneity and mechanisms. Clin Immunol 2000;95:173-81.F.Mucosal Immunity1. Basic Mechanisms: GALT, BALT, Secretary IgA, IgECampbell N; Yio XY; So LP; Li Y; Mayer L . The intestinal epithelial cell: processing and presentation of antigen to the mucosal immune system. Immunol Rev 1999;172:315-24.Tschernig T; Pabst R. Bronchus-Associated Lymphoid Tissue (BALT) is not present in the normal adult lung but in different diseases. Pathobiology 2000; 68:1-8.2. Nonspecific: Lysozyme, mucus, salivaJeffery PK; Li D. Airway mucosa: secretory cells, mucus and mucin genes [see comments]. Eur Respir J 1997;10:1655-62.Tenovuo J. Antimicrobial function of human saliva – how important is it for oral health? Acta Odontol Scan. 1998;56:250-6.G.Transplant ImmunologyBush WW. Overview of transplantation immunology and the pharmacotherapy of adult solid organ transplant recipients: focus on immunosuppression. AACN Clin Issues. 1999;May;10(2):253-69;quiz 304-6.1. Graft RejectionKabelitz D. Apoptosis, graft rejection, and transplantation tolerance. Tranplantation. 1998;65:869-75.2. Graft vs Host DiseaseFerrara JL. Pathogenesis of acute graft-versus-host disease: cytokines and cellular effectors. J. Hematother Stem Cell Res. 2000;9:299-306.H.Tumor Immunology1. Tumor Antigens, Antibodies, Cellular ResponsesNishimura T, Naku;I M, Sato M, Iwakabe K, et al. A critical role of Th1-dominant immunity in tumor immunology. Cancer Chemother Pharmacol 2000;46suppl:S52-61.Sogn JA. The status of tumor immunology and cancer immunotherapy. Introduction. Immunol Invest 2000; 29:81-4I.Immunoregulation1. Immune ToleranceNagler-Anderson C. Tolerance and immunity in the intestinal immune system. Crit Rev Immunology 2000;20:103-20.Carosella ED; Dausset J; Rouas-Freiss N. Immunotolerant functions of HLA-G. Cell Mol Life Sci 1999;55:327-33.142. Idiotypic NetworkSherer Y, Shoenfeld Y Idiotypic network dysregulation: a common etiopathogenesis of diverse autoimmune diseases. Appl Biochem Biotechnol 2000;83:155-62; discussion 297-313. Shoenfeld Y, George J. Induction of autoimmunity. A role for the idiotypic network. Ann N Y Acad 1997;815:342-9.3. Autoimmunity and Autoimmune AntibodiesAlbert LJ and Inman RD. Molecular mimicry; and Autoimmunity. N Engl J Med 1999; 341:2068-74.Dighiero G. Natural autoantibodies, tolerance and autoimmunity. Ann NY Acad Sci 1997;815:182-92.4. ApoptosisVaux DL. Immunopathology of apoptosis - introduction and overview. Springer Semin Immunopathol 1998;19:271-8.J.Diagnostic Laboratory ImmunologyThe objective of this section is to understand the principles and methodology of diagnostic laboratory immunology techniques related to humoral and cellular elements of the imune system and histocompatibility markers. The Training Program Directors’ Committee recommends knowledge in the following areas:a.Serological: ELISA, RIA, RID, nephelometry, immunoblots, HPLC, isoelectric focusing,immunoelectrophoresis, EID, protein, electrophoresis.b.Cellular: flow, cytometry, chemotaxis, phagocytosis, killing, lymphocyte proliferation.c.Histochemistry and Immunofluorescence:d.Molecular: Northern, Southern and Western blots, PCR, ligase chain reactions, crossoverbreakpoint analysis.e.Hybridomas and Monoclonal Antibodies:General ReferencesRose NR, deMacario EC, Fahey JL, Freedman H, PennGM (eds). Manuel of Clinical Laboratory Immunology, 4th ed. Washington DC, Amer Soc for Microbiol 1992.Abbas AK, Lichtman AH, Pober JS. Cellular and Molecular Immunology, 4th ed. WB Saunders, Philadelphia 2000 (Highly recommended by recent AI graduates. Ed)Fleisher TA, Tomar RH. Introduction to diagnostic laboratory immunology. JAMA 1997;278(22):1823-34.Specific TestsHahn BH. Antibodies to DNA. N Engl J Med 1998;338:1359-68.K.Research Principles1. Experimental DesignShaywitz DA; Martin JB; Ausiello DA. Patient-oriented research: principles and new approaches to training. AM J Med 2000;109:136-140.15Grover FL; Shroyer AL. Clinical science research. J Thorac Cardiovasc Surg 2000;119:S11-21.2. Data Interpretation/biostatisticsConn HO. Interpretation of data from multiple trials: a critical review. J Intern Med1997;241:177-83.16II. CLINICAL SCIENCESA.ALLERGIC DISORDERSAllergy and Asthma. Nature 1999; 402S: B1-B391.UPPER AIRWAY DISEASEa.RhinitisConnell. Quantitative intranasal pollen challenges. 3. The priming effect in allergic rhinitis. J Allergy 1969; 43:33-44Ray, et al. Direct expenditures for the treatment of allergic rhinoconjunctivitis in 1996, including the contributions of related airway illnesses. Journal of Allergy & Clinical Immunology 1999; 103:401-7Nash, et al. Optimizing quality of care and cost effectiveness in treating allergic rhinitis in a managed care setting. Am J Manag Care 2000; 6:S3-15; quiz S19-20Linneberg, et al. The prevalence of skin-test-positive allergic rhinitis in Danish adults: two cross-sectional surveys 8 years apart. The Copenhagen Allergy Study [In Process Citation]. Allergy 2000; 55:767-72b.Sinusitis/nasal polyposis1) Nasal polyposis:Kowalski, et al. Differential metabolism of arachidonic acid in nasal polyp epithelial cells cultured from aspirin-sensitive and aspirin-tolerant patients. Am J Respir Crit Care Med 2000; 161:391-8 Picado, et al. Cyclooxygenase-2 mRNA is downexpressed in nasal polyps from aspirin- sensitive asthmatics. Am J Respir Crit Care Med 1999; 160:291-62) Sinusitis:Brooks, et al. Medical management of acute bacterial sinusitis. Recommendations of a clinical advisory committee on pediatric and adult sinusitis. Ann Otol Rhinol Laryngol Suppl 2000; 182:2-20 Hamilos. Chronic sinusitis. J Allergy Clin Immunol 2000; 106:213-27Lavigne, et al. Prognosis and prediction of response to surgery in allergic patients with chronic sinusitis. J Allergy Clin Immunol 2000; 105:746-51Huang. The risk of sinusitis in children with allergic rhinitis. Allergy Asthma Proc 2000; 21:85-8Engels, et al. Meta-analysis of diagnostic tests for acute sinusitis. J Clin Epidemiol 2000; 53:852-6217Schubert. Medical treatment of allergic fungal sinusitis. Ann Allergy Asthma Immunol 2000; 85:90-7; quiz 97-101Temple and Nahata. Pharmacotherapy of acute sinusitis in children. Am J Health Syst Pharm 2000; 57:663-8Mabry. What we now know about allergic fungal sinusitis. J Respir Dis 2000; 21:23-31Merrett and Pfeiffer. Maxillary sinusitis as an indicator of respiratory health in past populations. Am J Phys Anthropol 2000; 111:301-18ryngeal disordersAndrianopoulos, et al. PVCM, PVCD, EPL, and irritable larynx syndrome: what are we talking about and how do we treat it? J Voice 2000; 14:607-18d.Allergy skin testing (methods and interpretation)Antico, et al. Assay of prick test inoculum volume. II. Average values and individual variability. Ann Allergy Asthma Immunol 2000; 85:145-9Antico, et al. Assay of prick test inoculum volume. I. Use and reliability of a gamma camera-based method. Ann Allergy Asthma Immunol 2000; 85:140-4Valyasevi and Van Dellen. Frequency of systematic reactions to penicillin skin tests [In Process Citation]. Ann Allergy Asthma Immunol 2000; 85:363-5Zweiman, et al. Sequential patterns of inflammatory events during developing and expressed skin late-phase reactions. J Allergy Clin Immunol 2000; 105:776-81e.Nasal challenge and assessment of nasal secretionsAssanasen, et al. Natural and induced allergic responses increase the ability of the nose to warm and humidify air [In Process Citation]. J Allergy Clin Immunol 2000; 106:1045-52Naclerio. Dose-dependent effects of intranasal steroids: how relevant? [editorial] Ann Allergy Asthma Immunol 2000; 85:248-9Baroody, et al. Comparison of the response to histamine challenge of the nose and the maxillary sinus: effect of loratadine. J Appl Physiol 1999; 87:1038-47Baroody, et al. Relationship between histamine and physiological changes during the early response to nasal antigen provocation. J Appl Physiol 1999; 86:659-68Frieri, et al. Effect of mometasone furoate on early and late phase inflammation in patients with seasonal allergic rhinitis. Ann Allergy Asthma Immunol 1998; 81:431-718。

相关文档
最新文档