Newcastle upon Tyne, NE1 7RU, UK. WRAPPING THE FUTURE
世界知名球队足球场一览
世界知名球队⾜球场⼀览阿姆斯特丹·阿雷纳球场所在国家:荷兰所在城市:阿姆斯特丹所属俱乐部:阿贾克斯(Ajax)俱乐部主场:阿姆斯特丹·阿雷纳球场(Amsterdam Arena)球场容量:51859⼈建成年份:1996年阿兹台克球场所在地:墨西哥城球场名字:阿兹台克球场 Azteca位置:墨西哥墨西哥城时间:1966年容量:107000⼈墨西哥美洲队和内卡哈公⽜队的主场安菲尔德球场球场名称:安菲尔德球场(Anfield Stadium)修建时间:1878年⼊驻时间:1892年球场位置:英格兰利物浦竣⼯使⽤:1884年9⽉草坪⾯积:101.2⽶×67.6⽶主队:利物浦容量:45362上座记录:61905⼈利迷领地看台容量:12390⼈辉煌百年看台容量:1411⼈安菲尔德路看台容量:9116⼈球场主看台容量:9575⼈其他附属看台容量:2454⼈主席台座位数量:344⼈残疾⼈座位数量:80⼈安联球场所在地:德国慕尼⿊落成时间:2005年6⽉主队:拜仁慕尼⿊施⼯时间:2002年10⽉21⽇⾄2005年4⽉30⽇拥有者:Allianz Arena München Stadion GmbH 营运商:Allianz Arena München Stadion GmbH 球场表层:草地建设费⽤:3亿4000万欧元建筑师:Herzog & de MeuronArupSpor揭幕时间:2005年5⽉31⽇球场容量:66000(其中坐席59416个)下层看台:20000坐席中层看台:24000坐席上层看台:22000坐席残疾⼈席位:⼤约200个商务席:2200个包厢:106个车位:11000个其中体育场内⼤约1200个体育场⼤⼩:258 m x 227 m x 50 m体育场周长:840m占地⾯积:37600 m使⽤⾯积:171000 m傲赴沙尔克球场所在地:德国盖尔森基兴落成时间:2001年8⽉13⽇容量:53804⼈(其中坐席48426个)主队:沙尔克04柏林奥林匹克球场体育场:柏林奥林匹克体育场主队:柏林赫塔类型:翻新耗资:2亿4200万欧元体育场容量:74220⼈总座位数:66021席伯纳乌球场所在地:西班⽛马德⾥外⽂名字:Estadio Santiago Bernabéu落成时间:1947年容量:94497⼈(其中坐席72523个),另计:12万⼈主队:皇家马德⾥德尔·阿尔卑球场球场名称:德尔·阿尔卑球场(Stadio Delle Alpi)城市:都灵国家:意⼤利所属球队:尤⽂图斯建成时间:1990年容纳⼈数:71012⼈球场⾯积:105×68⽶新闻媒体位:508个室内停车位:3900个公共汽车位:100个摩托车位:500个照明灯光:2500lux光明球场球场名称:光明球场所有者:本菲卡容量:65000⼈所属国家:葡萄⽛所在城市:⾥斯本地址:Avenida General Norton de Matos 1500 Lisboa 价值:1.49亿欧元建成⽇期: 2003-10-25巨龙体育场官⽅英⽂名字:Estadio do Dragao主队:波尔图容纳观众:52000⼈凯尔特⼈公园球场英⽂名字:Celtic Park Stadium主队:苏超球队格拉斯哥凯尔特⼈队地址:位于格拉斯哥的帕特海德区建成:1892年于1995年重建容量:60832个座位设计者:阿奇博尔·德雷切⽼特拉福德球场所在地:英格兰曼彻斯特英⽂名字:Old Trafford落成时间:1909年容量:76000⼈主队:曼联罗马奥林匹克球场主队:意甲的罗马、拉齐奥建成:上世纪30年代,最初⽬的也是为了举办奥运会。
Writing a paper - 7 Results - 2. processing data
Fourth possibility
See if the data fit Michaelis-Menten kinetics and, if so, obtain the values of the parameters.
rate of reaction/ mol s -1
2.0 1.5 1.0 0.5 0.0 0 1 2 3 4
First possibility: „The rate of reaction is 0.3 mol s-1 when the substrate concentration is 0.2 mM. It increases to 0.7 mol s-1 when [substrate] = 0.5 mM, .....‟ Only repetition. This is a waste of time.
*Institute of Plant Sciences, Karl-Franzens University of Graz, Schubertstrasse 51, A-8010 Graz, Austria, ‡School of Biology, University of Newcastle upon Tyne, Newcastle upon Tyne NE1 7RU, United Kingdom; and §Hattori Botanical Laboratory, Kochi Branch, 2576-27 Edagawa, Inocho, Agawagun, Kochi 781-2120, Japan
substrate conc. /mM
0 0.2 0.5 1 /mol s-1
0 0.3 0.7 1.0 1.3 1.5 1.6
Personal References
Gregory A. RiccardiCurriculum VitaeFebruary, 2005Born: May 11, 1952Place: Houston, TexasMarital Status: Married, three childrenEducationPh.D., State University of New York at Buffalo, 1980, Computer Science.M.S., State University of New York at Buffalo, 1976, Computer Science.B.S., Florida State University, Tallahassee, Florida, 1974, Mathematics.Professional PositionsProfessor, Department of Computer Science, Florida State University, 1996–present.Associate Professor, Department of Computer Science, Florida State University, 1986–1996. Assistant Professor, Department of Computer Science, Florida State University, 1981–1986. Assistant Professor, Department of Computer Science, University of Southwestern Louisiana, Lafayette, Louisiana, January 1978–August 1981.Professional HonorsThe William R. Jones Most Valuable Mentor Award 2001, Florida Scholars Fund and McKnight Foundation.University Teaching Award, Florida State University, 1997.Teaching Incentive Program Award, Florida State University, 1994.Personal ReferencesProf. Lois Wright Hawkes, Dept. of Computer Science, FSU, hawkes@Prof. Paul Watson, School of Computing Science, University of Newcastle upon Tyne, Newcastle upon Tyne, United Kingdom, NE1 7RU. Paul.Watson@Prof. Shamkant Navathe, College Of Computing, Georgia Institute Of Technology, 801 Atlantic Dr., NW, Atlanta, GA 30332-0280. sham@Research and Creative ActivityBooks1.Riccardi, Greg, Database Management with Web Site Development Applications, 2003,Addison-Wesley.An introductory database textbook that is intended for use with students who are not computer programmers. It presents a full gamut of introductory database topics,including conceptual modeling, ER diagramming, the relational model, relational algebra,normalization, and SQL. In addition it shows students how these techniques can be usedto create sophisticated Websites using JavaScript, ASP and the Microsoft IIS server.2.Riccardi, Greg, Principles of Database Systems: With Internet and Java Applications, 2001, Addison-Wesley.A database textbook that takes advantage of the increasing importance of the Internet toinformation systems. This book fills a void in database textbooks. It is applicationoriented and covers the full lifecycle of information systems development anddeployment. It is aimed specifically at undergraduate Computer Science majors taking anupper-division course in database systems.3.Folk, Michael J., Bill Zoellick, and Greg Riccardi, File Structures: An Object-Oriented Approach withC++, Addison-Wesley, 1998.This is my revision of File Structures, second edition by Folk and Zoellick. I updated the material in the second edition and completely replaced all of the programming examples. I was ableto introduce an object-oriented approach to storing and retrieving information.Approximately half of the book was completely rewritten and the rest was substantially revised. I wrote full implementations of all of the file structure techniques and includedthem in the book.It was my goal to produce a book that teaches object-oriented design and programming in the context of a complex data structure problem domain. The book is being used in coursesaround the country.The progressive presentation of the object-oriented material begins with the simplest classes and I/O in C++. New features of file structures, new features of C++, and new featuresof object-oriented design are introduced together. Class inheritance is developedtogether with an approach to using buffers for I/O. Virtual functions are introduced aspart of the solution to the problem of allowing a variety of buffer techniques. Templatesin C++ are used to support indexing. A complex class structure is used to support co-sequential processing.The careful development of these classes allows the presentation of very complex structures, such as B trees, in very simple terms. The full implementation of B tree indexes,including a test program, is only 10 pages of C++ code. This is made possible by theclasses that are presented earlier in the book.Publications in Refereed Journals and Conference Proceedings1.Ehlmann, B.K., G.A. Riccardi, N.D. Rishe, and J. Shi, “Specifying and Enforcing AssociationSemantics via ORN in the Presence of Association Cycles, IEEE Transactions on Knowledge and Data Engineering, November/December 2002 (Vol. 14, No. 6), pp. 1249-1257.2.Riccardi, G. A., S.J. Eaves III, and L.C. Dennis, “Managing Scientific Computations with a Java-based Schema Extension Facility,” Proceedings of 2000 ACM Symposium on Applied Computing, Como, Italy, March 19–21, 2000.3.Ehlmann, B.K. and G.A. Riccardi, “An Integrated and Enhanced Methodology for Modelingand Implementing Object Relationships,” Journal of Object Oriented Programming, SIGS publications, 10(2), 18 ms. pages, May, 1997.4.Ehlmann, B.K. and G.A. Riccardi, “Object Relator Plus, A Practical Tool for DevelopingEnhanced Object Databases”, Proceedings of ICDE 97, the 13th International Conference on Data Engineering, Birmingham, England, April, 1997.5.Ehlmann, B.K. and G.A. Riccardi, “A Comparison of ORN to Other Declarative Schemes forSpecifying Relationship Semantics ,” Information and Software Technology, Elsevier Science, 38(7), July, 1996, 455–465.6.Huang, W. and G.A. Riccardi, “Modeling and Implementing Dynamic, Object-Oriented Views,”Proceedings of the 1995 International Conference on Applications of Databases, San Jose, California, December, 1995.7.Dragovitsch, Zhao, Dennis, and Riccardi, “PvmGeant–A Parallel Simulation Code for the CLASDetector at CEBAF,” International Journal of Supercomputer Applications and High Performance Computing, v.9, 1995.8.Johnson, K., J. Bauer, G. Riccardi, K. Drogemeier, and M. Xue, “Distributed Processing of aRegional Prediction Model,” Monthly Weather Review, 1994.9.Ehlmann, B.K. and G.A. Riccardi, “A Notation for Expressing Aggregate Relationships in anObject-Oriented Data Model,” Proceedings of the International Conference on Applications of Databases, Vadstena, Sweden, W. Litwin and T. Risch (Eds.), Lecture Notes in Computer Science, Springer-Verlag, 1994, pp. 62–67.10.X. Zhao, P. Dragovitsch, L. Dennis, and G. Riccardi, “Parallel Simulation Code for the CLASDetector at CEBAF,” CLUSTER WORKSHOP '93, Dec.6–9, 1993, Tallahassee, FL.11.Ehlmann, B.K., L.C. Dennis, and G.A. Riccardi, “An Object-based Conceptual Model of aNuclear Physics Experiments Database,” Nuclear Instruments and Methods in Physics Research, A325, 1993, pp. 294–308.12.Ehlmann, B.K., G.A. Riccardi, and L.C. Dennis, “Representing Non-Inheritance Relationshipsin an Object-Oriented, Scientific Database,” International Conference on Scientific and Statistical Databases, 1992, pp. 99–109.13.Riccardi, G.A., and B.K. Ehlmann, “Object-Oriented Development of Scientific Databases, anExample from Experimental Physics,” Proceedings of the First Software Engineering Research Forum, Tampa, Florida, Nov. 7–8, 1991, pp. 277–286.14.Riccardi, G.A., C. Bauer, and H. Lim, “Boundary Processing in a Vectorized Model of LatticeGas Hydrodynamics,” with Bauer and Lim, Physica D47, 1991, pp. 281–295. Report on dealing with boundaries and obstacles in the vector lattice gas algorithm.15.Riccardi, G.A., C. Bauer, and H. Lim, “A Vectorized Cellular Automata Model of Fluid Flow,”Proceedings of the NATO Advanced Research Workshop on Lattice Gas Methods for PDEs. Los Alamos, NM, January 15, 1990.16.Riccardi, G.A., B. Traversat, and U. Chandra, “A Machine Independent Approach to ParallelProgramming,” Proceedings of PARBASE–90: International Conference on Databases, Parallel Architectures, and their Applications, IEEE Computer Society Press, March, 1990. Technical Report FSU-SCRI-89-108.17.Riccardi, G.A., C. Bauer, and H. Lim, “A Vector Algorithm for Lattice Gas Hydrodynamics,”International Journal of Supercomputer Applications, v. 3, no. 4, Winter, 1989, pp. 64–67. Report on a strategy for representing a hydrodynamics algorithm on vector computers.18.Riccardi, G.A., and P. Schow, “Adaptation of the ISODATA Clustering Algorithm for VectorSupercomputer Execution,” Proceedings of Supercomputing 88, v. 2, February, 1989.19.Riccardi, G.A., U. Chandra, F. Hannedouche, and J. Vagi, “Aftran: Array Fortran ProgrammingLanguage,” Computer Physics Communications, 1988. Technical report FSU-SCRI-89T-16. A description of the Aftran programming language.20.Riccardi, G.A., “Runtime Environments for Parallel Applications,” Mini-track overview,Proceedings of the 21st Hawaii International Conference on System Sciences, v.1, Software Track, IEEE, January, 1988.21.Baker, T.P., and G.A. Riccardi, “Implementing Ada Exceptions,” IEEE Software, September,1986. A precise description of the use and implementation of exceptions in Ada. The first publication to cover the topic comprehensively.22.Hook, A., G.A. Riccardi, and M. Vilot, “Ada Compiler Performance Benchmarks,” Proceedings ofthe Ada Europe Conference 1986, Cambridge University Press, 1986.23.Baker, T.P., and G.A. Riccardi, “Ada Tasking: From Semantics to Efficient Implementation,”IEEE Software, March 1985. Refereed Journal. A precise semantics of the Ada model of concurrent program execution. pp. 34–46.24.Riccardi, G.A., and T.P. Baker, “A Runtime Supervisor to support Ada Tasking: Rendezvousand Delays,” with T.P. Baker, Proceedings of the 1985 International Conference on Ada, Paris, France, May, 1985, Cambridge University Press. Refereed Conference. A detailed report on the semantics of interprocess communication in the Ada programming language. pp. 329–342.25.Baker, T.P., and G.A. Riccardi, “A Runtime Supervisor to Support Ada Task Activation,Execution and Termination,” Proceedings of the Conference on Ada Applications and Environments, IEEE Computer Society, 1984. A detailed description of Ada Tasking semantics. pp. 14–22. 26.Riccardi, G.A., “The Independence of Control Structures in Programmable Numberings of thePartial Recursive Functions,” Zeitschrift fur Mathematische Logik and Grundlagen der Mathematik, 1982. Refereed Journal. The solution of some difficult problems in Recursive Function Theory which are related to programing language semantics. pp. 287–296.27.Riccardi, G.A., “The Independence of Control Structures in Abstract Programming Systems,”Journal of Computer and System Sciences, Vol. 22, No. 2, April, 1981. Refereed Journal. An approach to studying Programming Language Semantics with recursive function theory. pp. 107–143. Refereed Journal Publications of the Jefferson Lab CLAS CollaborationThe following publications are written by members of the CEBAF Large Angle Calorimeter (CLAS) collaboration at the Continuous Electron Beam Accelerator Facility (CEBAF) at the ThomasJefferson National Laboratory. All full members of the collaboration participate in the production of the data and analyses leading to these papers and are included in the list of authors.1.The CLAS Collaboration: J. Price, et al, “Exclusive Photoproduction of the Cascade (Xi)Hyperons,” , submiited to Physical Review C, 9/2004.2.The CLAS Collaboration: S. Niccolai, et al, “Complete measurement of three-bodyphotodisintegration of $^3$He for photon energies between 0.35 and 1.55 GeV,” accepted by Physical Review C, 10/2004.3.The CLAS Collaboration: K. Joo, et al, “Measurement of the Polarized Structure Functionsigma(LT') for p(e(vec),e'pi+)n in the Delta resonance region,” accepted by Physical Review C, 9/2004.4.The CLAS Collaboration: C. Hadjidakis, M. Guidal, et al, “Exclusive rho0 mesonelectroproduction from hydrogen at CLAS,” accepted by PLB, 11/2004.5.The CLAS Collaboration: D. Protopopescu, et al, “Survey of A_LT' asymmetries in semi-exclusive electron scattering on He4 and C12,” accepted by Nuclear Physics A, 11/2004.6.The CLAS Collaboration: A.V. Stavinsky, K.R. Mikhailov, R. Lednicky, A.V. Vlassov, et al,“Proton source size measurements in the eA --> e'ppX reaction,” Physical Review Letters93, 2004.7.The CLAS Collaboration: M. Mirazita, et al, “Complete Angular Distribution Measurements ofTwo-Body Deuteron Photodisintegration between 0.5 and 3 GeV,” Physical Review C70, 2004. 8.The CLAS Collaboration: P. Rossi, et al, “Onset of asymptotic scaling in deuteronphotodisintegration,” Physical Review Letters94, 2004.9.The CLAS Collaboration: V. Kubarovsky, L. Guo, et al, “Observation of an exotic baryon with${S=+1}$ in photoproduction from the proton,” Physical Review Letters92, 2004.10.The CLAS Collaboration: K. McCormick, et al, “Tensor Polarization of the phi mesonPhotoproduced at High t,” Physical Review C 69, 2004.11.The CLAS Collaboration: R. Niyazov, et al, “Two-Nucleon Momentum Distributions Measuredin 3He(e,e'pp)n,” Physical Review Letters92,2004.12.The CLAS Collaboration: S. Stepanyan, et al, “Observation of an Exotic S = +1 Baryon inExclusive Photoproduction from the Deuteron,” Physical Review Letters91, 2003.13.The CLAS Collaboration: R. Fatemi, et al, “Measurement of the Spin Structure Functions in theResonance Region for Q2 from 0.15 to 1.6 GeV2,” Physical Review Letters91, 2003.14.The CLAS Collaboration: J. W. C. McNabb, et al, “Hyperon Photoproduction in the NucleonResonance Region,” Physical Review Letters 69, 2004.15.The CLAS Collaboration: H. Avakian, et al, “Measurement of Beam-Spin Asymmetries fore(pol)p -> e'pi+ X in the Deeply Inelastic Regime,” Physical Review Letters 69, 2004.16.The CLAS Collaboration: K. Joo, et al, “Measurement of Polarized Structure Functionsigma(LT') for p(e(vec),e'p)pi0 from single pi0 electroproduction in the Delta resonance region,”Physical Review C68, 2003.17.The CLAS Collaboration: A. Biselli, et al, “Study of the Delta(1232) using single and doublepolarization asymmetries,” Physical Review C68, 035202, 2003.18.The CLAS Collaboration: K. Sh. Egiyan, et al, “Observation of Nuclear Scaling in the A(e,e')Reaction at xBjorken > 1,” Physical Review C68, 035202, 200319.The CLAS Collaboration: M. Ripani, et al, “ep --> e'p pi+ pi- and baryon resonance analysis,”Physical Review Letters91, 2002.20.The CLAS Collaboration: J. Yun, et al, “Measurement of Inclusive Spin Structure Functions ofthe Deuteron with CLAS,” Physical Review C67, 2003.21.The CLAS Collaboration B. Mecking, et al, “The CEBAF Large Acceptance Spectrometer,”Nuclear Instruments and Methods, 503/3, 200322.The CLAS Collaboration D. Carman, et al, “First Measurement of Transferred Polarization inthe Exclusive e(pol)p -> e'K+Lambda(pol) Reaction,” Physical Review Letters, 90, 2003.23.The CLAS Collaboration: M. Osipenko, et al, "A Complete Measurement of the F2 ProtonStructure Function in the Resonance Region and the Evaluation of the Moments," Physical Review D67, 2003.24.The CLAS Collaboration: M. Battaglieri, et al, “Photoproduction of the omega meson on theproton at large mementum transfer,” Physical Review Letters90, 2002.25.The CLAS Collaboration: M. Dugger, et al, “eta photoproduction on the proton for photonenergies from 0.75 to 1.95 GeV,” Physical Review Letters89, 2002.26.The CLAS Collaboration: R. DeVita, et al, “First Measurement of the Double Spin Asymmetryin e(pol)p(pol) -> e'pi+n in the Resonance Region,” Phys. Rev. Lett. 88, 082001 (2002); Erratum 88, 082001 (2002).27.The CLAS Collaboration: K. Joo, et al, “Q2 Dependence of Quadrupole Strength in gamma* ->Delta +(1232),” Physical Review Letters88, 122001 (2002).28.The CLAS Collaboration: M. Battaglieri et al, “Photoproduction of Rho_0 Meson on the Protonat Large Momentum Transfer,” Physical Review Letters87 172002 (2001). LANL preprint: hep-ex/0107028.29.The CLAS Collaboration: S. Barrow et al, “Electroproduction of the Lambda(1520) Hyperon,”Physical Review C 64, 044601 (2001). LANL preprint: hep-ex/0105029.30.The CLAS Collaboration: S. Stepanyan et al, “Observation of exclusive deeply virtual Comptonscattering in polarized electron beam asymmetry measurements,” (10 October 2001) Physical Review Letters87, 182002 (2001). LANL preprint: hep-ex/0107043.31.The CLAS Collaboration: K. Lukashin, et al, “Exclusive electroproduction of phi mesons at 4.2GeV.” Physical Review C 63. 065205-1 (23 October 2001); LANL preprint: hep-ex/0101030. 32.The CLAS Collaboration: R. Thompson et al, “The ep --> e'p(eta) Reaction At and Above theS11(1535) Baryon Resonance,” Physical Review Letters86, 1702 (2001). LANL preprint: hep-ex/0011029.33.The CLAS Collaboration: E. Anciant, et al, “Photoproduction of phi(1020) Mesons on theProton at Large Momentum Transfer.” Physical Review Letters85, 4682 (2000).Articles in Books1.Riccardi, G.A., “Supercomputers,” Macmillan Encyclopedia of Computers, 1992.Publications in Non-refereed Conference Proceedings1.P. Dragovitsch, Xuwei Zhao, L. Dennis, and G. Riccardi, “The Parallelized GEANT CodePvmGeant for the CLAS Detector at CEBAF,” Conference on the Intersection of Particle and Nuclear Physics, June 1–6, 1994, St.Petersburg, FL.2.Riccardi, G.A., U. Chandra, F. Hannedouche, and J. Vagi, “Aftran: Array Fortran ProgrammingLanguage,” with Conference on Computing in High Energy Physics, Oxford, April, 1989.3.P. Dragovitsch, Xuwei Zhao, L. Dennis, and G. Riccardi, “High Performance Geant Simulationsof the CLAS Detector at CEBAF,” Division of Nuclear Physics Fall Meeting of the American Physical Society, October 26–29, 1994, Williamsburg, VA.4.McKinley, K., and G.A. Riccardi,”An Implementation of Ada Data Structures,” Proceedings of the23rd Annual Conference of the Southeast Region ACM, Nashville, Tennessee, April, 1985. Not refereed. A preliminary report from a Master's Thesis.5.Belkhouche, B., J. Urban, and G.A. Riccardi, “Synthesizing Abstract Data Types Specifications,”Proceedings of the 20th Southeast Regional ACM Conference, April, 1982. pp. 176–181.Software and Technology Projects1.MorphBank morphology and taxonomy database and Web system, 2004-present.A system to collect, annotate, analyze and manage information for systematic taxonomics andmorphology for biologists at FSU and elsewhere. Our group has been actively leading aninternational effort to achieve interoperability among the several taxonomic imagedatabases. We have developed and published data schemas and Web sites in support ofour efforts. NSF support for this project is pending.2.Global Grid Forum Database Access and Integration Services (DAIS) Working Group, 2002-present.Contributed to development of standards and specifications for data access in the Grid community. I am a primary author of the base specification document and havecontributed to the relational and XML database access specifications. I have participatedin many conferences and workshops and made significant contributions to the directionand technology of this successful group.3.CEBAF Experiments Database, 1989–present.A database to manage the data acquisition, data analysis, and software for the ContinuousElectron Beam Accelerator Facility (CEBAF), a $500 million Dept. of Energy projectcurrently under construction in Virginia. This is utilizing an object-oriented database toprovide the capability of integrating both standard meta-data management and the dataanalysis and data acquisition aspects of the facility. In collaboration with Physics facultymembers Larry Dennis and Adam Sarty, FAMU faculty member Bryon Ehlmann, SCRIresearchers Peter Dragovitsch and Stephen Barrow, postdoctoral researcher DavidMeekins, graduate students, Samuel Eaves, Dmitriy Blaginin, Qing Zhang, HongweiWang, Troy Cochran, and Jonathon Felder.4.Co-director of the development of the FSU Ada Compiler, 1982–1986.Directed the Code Synthesis and Runtime System phases of the compiler development. The complete software system consists of approximately 60,000 lines of code. Incollaboration with Ted Baker and graduate students Tom Leonard, Sheila O'Connell,Kathy McKinley, Ken Spaulding, and Jim Groh.5.FSU Ada Compiler Validation, 1986.Result was successful processing of the 2500 Ada Validation Tests. This is the first University sponsored Compiler for Ada to complete the validation process. In collaboration withTed Baker and graduate students Tom Leonard, Sheila O'Connell, Kathy McKinley, KenSpaulding, and Jim Groh.Research Reports and Technology Specifications1.Mario Antonioletti, Malcolm Atkinson, Amy Krause, Simon Laws, Susan Malaika, Norman WPaton, Dave Pearson, Greg Riccardi, “Web Services Data Access and Integration (WS-DAI) Specifications,” GGF Data Area Working Paper, /projects/dais-wg/document/ Grid_Data_Service_Specification/en/5, March, 2004.2.Greg Riccardi, Mahadevan Subramanian, Shailendra Misra, Simon Laws, “GGF10 DAIS UsageScenarios,” DAIS Working Document, February, 20043.Greg Riccardi, “A Proposal for Aggregating DAIS Service Requests,” DAIS WorkingDocument, January, 2004.4.Greg Riccardi, “GGF9 DAIS Usage Scenarios,” DAIS Working Document, October, 2003.5.Greg Riccardi, “DAIS Data Service Interactions and the SkyQuery Portal,” DAIS WorkingDocument, August, 2003.6.Malcolm Atkinson, Simon Laws and Greg Riccardi, “Rationale for the Data Access andIntegration Architecture,” DAIS Working Document, August, 2003.7.Greg Riccardi, “Client Programming Interfaces and Examples,” DAIS Working Document,August, 2003.8.Greg Riccardi, “Model Examples: Simple Client-Service Interactions,” DAIS WorkingDocument, July, 2003.9.M. Antonioletti, M.P. Atkinson, N. P. Chue Hong, A. Krause, S. Malaika, G. McCance, S. Laws,J. Magowan, N.W. Paton, G. Riccardi, “Grid Data Service Specification,” ,” DAIS Working Document, June 2003.10.Greg Riccardi, “Sample Mappings from DAIS Conceptual Model to Service Instances,” DAISWorking Document, June, 2003.11.Neil P Chue Hong, Amy Krause, Susan Malaika, Gavin McCance, Simon Laws, James Magowan,Norman W Paton, Greg Riccardi, “Grid Database Service Specification Primer,” DAIS Working Document, May, 2003.12.A. Krause, S. Malaika, G. McCance, J. Maguire, N. Paton, G. Riccardi, “Grid Database ServiceSpecification,” DAIS Working Document, September, 2002.13.Dragovitsch, P., L.C. Dennis and G.A. Riccardi, “A Computer System for Data Analysis andData Acquisition for the CEBAF Large Acceptance Spectrometer,” SCRI Technical Report FSU-SCRI-92-63.14.Riccardi, G.A., A. Sharieh and J. Carr, “Adaptation of the Lanczos Method for ParallelExecution,” SCRI Technical Report FSU-SCRI-91-153, June, 1991.15.Sharieh, A., G.A. Riccardi and J. Carr, “Parallel Implementation of the Lanczos Method,” SCRITechnical Report FSU-SCRI-91-35, March, 1991.16.Riccardi, G.A., B. Traversat, and U. Chandra, “A Machine Independent Approach to ParallelProgramming,” SCRI Technical Report FSU-SCRI-89-108.17.Riccardi, G.A., C. Bauer and H. Lim, “A Vectorized Cellular Automata Model of Fluid Flow,”SCRI Technical Report FSU-SCRI-89T-53, 1989.18.Dekeyser, Georgiopoulos, Hannedouche, Riccardi, Vagi, and Youssef, “Aftran: Array FortranProgramming Language,” SCRI Technical Report FSU-SCRI-89T-16, 1989.19.Dekeyser, Georgiopoulos, Hannedouche, Riccardi, Vagi, and Youssef, “The Aftran VectorPreprocessor Project,” SCRI Technical Report FSU-SCRI-88T-43, 1988. “A Master–slave Model of Parallel Processing,” with Chandra and Traversat, SCRI Technical Report FSU-SCRI-88T-134, 1988.20.Riccardi, G.A., D. Druding, and D. Kopriva,”Multiprocessing of Multi-domain SpectralMethods on the ETA-10 Supercomputer,” SCRI Technical Report FSU-SCRI-88T-33, March, 1988.21.Riccardi, G.A., and P. Schow, “Adaptation and Performance of the ISODATA ClusteringAlgorithm on the Cyber 205 and ETA-10 Supercomputers,” SCRI Technical Report FSU-SCRI-88T-32, March, 1988.22.Riccardi, G.A., and M.I. McGinnis, “Hermes10–Message Passing on the ETA-10,” SCRITechnical Report FSU-SCRI-88T-31, March, 1988.23.Hook, A., G.A. Riccardi, and M. Lake, “Analyses of Reported Problems with Validated AdaCompilers,” IDA Paper P-1954. October, 1986.24.Riccardi, G.A., and T.P. Baker, “A Run-time Supervisor to Support Ada Tasking: Part 2,Rendezvous and Delays,” FSU Ada Project Report 83-7, May, 1983. A detailed design document for the FSU Ada Compiler Project. Revised and published (6).25.Riccardi, G.A., and T.P. Baker, “A Run-time Supervisor to Support Ada Tasking: Part 1, TaskActivation, Execution and Termination,” with T.P. Baker, FSU Ada Project Report 83-6, May, 1983. A detailed design document for the FSU Ada Compiler Project. Revised and Published (2).pp. 1–17.26.Baker, T.P., and G.A. Riccardi, “The Florida State University Ada Compiler Effort,” F.S.U. AdaProject Report number 82-3. Research Technical Report. A paper describing the major strategies employed in the F.S.U. Ada Compiler Project. pp. 1–10.Research Grants and Contracts1.Ronquist, F., G. Riccardi, R. van Engelen, A. Mast, and G. Erickson, “MorphBank: Web ImageDatabase Technology for Comparative Morphology and Biodiversity Research,” submitted to NSF June, 2004, rated “Outstanding.” Requested $2,500,000.2.Eugenio, P. and G. Riccardi, “Support for Experimental Nuclear Physics at CSIT,” funded byU.S. Dept. of Energy for $450,000 for the period November, 2004–October, 2007.3.Dennis, L.C., G. A. Riccardi, and P. Eugenio, “Support for Experimental Nuclear Physics atCSIT,” funded by U.S. Dept. of Energy for $580,000 for the period November, 2001–October, 2004.4.Dennis, L.C., and G. A. Riccardi, “Support for Experimental Nuclear Physics at CSIT,” fundedby U.S. Dept. of Energy for $598,000 for the period October, 1998–September, 2001.5.Dennis, L.C., G. A. Riccardi, and P. Dragovitsch, “Support for Experimental Nuclear Physics atSCRI,” funded by U.S. Dept. of Energy for $614,000 for the period October, 1995–September, 1998.6.Olson, Riccardi, and others, “Grand Challenge Application on HENP Data,” submitted to USDept. of Energy Grand Challenge program. Award announced February, 1997. Total funding of $2.4 million for 3 years awarded to Lawrence Berkeley National Lab. Joint project with Lawrence Berkeley National Lab, Argonne National Lab, Brookhaven National Lab, Florida State University, UCLA, University of Tennessee, and Yale University.7.Riccardi, G.A., “Central and Remote Databases for DUI Information.” software developmentcontract funded by the Florida Dept. of Highway Safety and Motor Vehicles for the period of October, 1996–September, 1997 for $37,000.8.Riccardi, G.A., “Central and Remote Databases for DUI Information.” software developmentcontract funded by the Florida Dept. of Highway Safety and Motor Vehicles for the period of April, 1996–April, 1997 for $100,000.9.Riccardi, G.A., L.C. Dennis, and P. Dragovitsch, “Support for Experimental Nuclear Physics atSCRI,” funded by U.S. Dept. of Energy for $308,000 for the period October, 1992–September, 1995.10.Riccardi, G.A. and J.J. O'Brien, “Massively Parallel Computation for Ocean Modelling,” fundedby the Office of Naval Research for $320,000 for the period March, 1993–March, 1996.11.Riccardi, G.A., Computer Science Section of the F.S.U. Supercomputer Computations ResearchInstitute proposal funded by the U.S. Department of Energy for 1991.12.Riccardi, G.A., Computer Science Section and Massively Parallel Computing Section of theSCRI five year proposal funded by the U.S. Department of Energy for the period 1989–1994. 13.Riccardi, G.A., Computer Science Section of the F.S.U. Supercomputer Computations ResearchInstitute proposal funded by the U.S. Department of Energy for 1990.14.Riccardi, G.A., Computer Science Section of the F.S.U. Supercomputer Computations ResearchInstitute proposal funded by the U.S. Department of Energy for 1989.15.Riccardi, G.A., Computer Science Section of the F.S.U. Supercomputer Computations ResearchInstitute proposal funded by the U.S. Department of Energy for 1988.16.Riccardi, G.A., “A Prototype Ada Compiler Evaluation System,” Institute for Defense Analysis,funded for $30,000 for the period of May, 1985 to December, 1985.17.Baker, T.P., and G.A. Riccardi, “An Extension to the Ada Compiler Project,” U.S. AFATL,Eglin AFB, funded for $300,000 for the period August, 1984 to September, 1985.18.Baker, T.P., and G.A. Riccardi, “An Extension to the Ada Compiler Project,” USAF ArmamentDivision, Eglin Air Force Base, funded for $300,000 for the period August, 1983 to September, 1984.。
世界大学200强
世界高校200强1 Harvard University US 643 17 17 50 243 1000 哈佛2 California University Berkeley US 665 6 7 7 169 880.2 加利福尼亚3 Massachusetts Institute of Technology US 484 13 18 28 221 788.94 California Institute of Technology US 236 19 17 45 400 738.95 Oxford University UK 560 57 18 30 45 731.86 Cambridge University UK 541 65 19 31 46 725.47 Stanford University US 420 9 13 28 197 688.08 Yale University US 347 53 20 65 81 582.89 Princeton University US 353 18 18 19 133 557.510 ETH Zurich CH 170 72 25 4 266 553.711 London School of Economics UK 257 79 100 27 6 484.412 Tokyo University JP 371 3 3 30 60 482.013 Chicago University US 254 31 18 58 71 444.014 Imperial College London UK 237 60 51 55 27 443.715 University of Texas at Austin US 183 9 8 8 202 421.516 Australian National University AU 212 48 31 9 105 417.717 Beijing University CN 322 9 11 35 3 391.8 北京大学!!18 National University Singapore SG 266 35 46 10 18 385.919 Columbia University US 213 10 18 56 75 384.120 University of California, San Francisco US 21 5 0 39 300 376.521 McGill University CA 132 84 42 11 84 364.122 Melbourne University AU 207 49 51 12 23 353.223 Cornell University US 202 10 16 19 91 348.824 University of California, San Diego US 96 3 6 7 208 331.525 Johns Hopkins University US 107 16 13 68 116 330.826 University of California, Los Angeles US 180 2 8 12 106 316.427 Ecole Polytechnique FR 144 25 55 23 59 315.528 Pennsylvania University US 142 14 23 31 87 306.929 Kyoto University JP 207 3 3 25 57 303.730 Ecole Normale Super Paris FR 105 11 22 100 51 298.431 Michigan University US 173 17 11 19 65 293.332 Ecole Polytechnique Fédérale de Lausanne CH 56 100 67 13 44 289.433 Monash University AU 136 49 64 8 19 286.034 University College London UK 108 48 40 44 36 284.235 Illinois University US 152 3 3 15 100 281.636 New South Wales University AU 140 49 47 19 12 275.737 Toronto University CA 131 24 16 6 88 272.538 Carnegie Mellon University US 129 35 25 24 37 259.439 Hong Kong University HK 96 74 14 8 50 249.540 Sydney University AU 124 49 29 11 24 245.241 Indian Institute of Technology IN 209 3 2 13 8 241.742 Hong Kong University of Sci & Tech HK 135 37 15 8 38 240.643 Manchester University & UMIST UK 130 40 23 19 19 238.544 School of Oriental and African Studies UK 62 70 77 20 0 235.845 Massachusetts University US 118 1 4 7 99 235.746 British Columbia University CA 114 24 14 6 65 230.447 Heidelberg University DE 124 11 33 12 41 228.348 Edinburgh University UK 118 32 21 22 29 227.649 Queensland University AU 95 49 25 6 42 223.950 Nanyang University SG 123 32 47 9 0 217.151 Tokyo Institute of Technology JP 118 3 13 27 50 217.052 Duke University US 61 12 11 56 66 212.653 Catholic University Louvain BE 104 26 41 17 19 212.654 Brussels Free University BE 54 41 57 10 36 205.155 RMIT University AU 60 49 80 8 0 203.956 Adelaide University AU 69 49 29 5 45 202.757 Paris VI, Pierre et Marie Curie FR 99 7 39 15 33 198.758 Sussex University UK 73 51 23 11 32 196.259 Purdue University US 105 25 14 8 36 194.060 Tech University Berlin DE 83 11 39 2 50 191.161 Brown University US 46 39 14 19 65 188.962 Tsing Hua University CN 140 9 7 24 3 188.963 Copenhagen University DK 111 18 14 19 22 188.764 Erasmus University Rotterdam NL 70 27 11 11 63 188.465 Georgia Institute of Technology US 117 4 11 9 39 185.766 Wisconsin University US 104 0 8 18 48 184.567 Auckland University NZ 76 49 30 7 15 183.568 Macquarie University AU 45 49 62 5 15 182.369 Osaka University JP 78 3 5 28 63 181.870 St Andrews University UK 39 42 57 19 19 181.071 Sorbonne Paris FR 124 3 43 5 0 180.872 University of California, Santa Barbara US 64 9 3 6 93 180.673 Northwestern University US 61 4 12 27 71 180.474 Washington University US 48 16 8 18 82 177.075 Boston University US 78 12 19 17 45 176.676 Curtin University of Technology AU 35 50 79 6 0 176.277 Vienna Technical University AT 83 19 45 16 6 175.478 Delft University of Technology NL 106 20 12 20 12 174.279 New York University US 90 8 10 19 41 173.280 Warwick University UK 70 49 25 9 14 170.681 Yeshiva University US 2 14 15 31 103 170.282 Minnesota University US 59 10 5 11 79 169.683 Eindhoven University of Technology NL 45 20 12 11 77 169.584 Chinese University Hong Kong HK 81 30 16 12 25 169.285 G?ttingen University DE 72 11 13 4 64 168.586 Rochester University US 49 10 8 49 48 167.887 Trinity College, Dublin IE 57 45 29 8 24 167.088 Case Western Reserve University US 23 4 11 49 75 166.889 Malaya University MY 50 29 68 15 0 166.490 Alabama University US 27 10 4 8 112 166.091 Bristol University UK 59 38 16 17 31 165.992 Lomonosov Moscow State University RU 97 9 15 31 5 161.693 Hebrew University Jerusalem IL 81 5 11 16 44 161.494 Vienna University AT 77 19 30 5 25 161.295 Technical University Munich DE 72 11 32 23 18 160.796 Western Australia University AU 36 49 29 10 31 160.197 King's College London UK 34 44 27 24 26 160.198 Amsterdam University NL 68 17 14 10 46 159.899 Munich University DE 82 11 26 12 24 159.7100 Queen Mary, University of London UK 41 47 30 23 13 158.8 101 Oslo University NO 81 21 18 13 21 158.5102 National Taiwan University TW 100 10 11 11 22 157.8103 Bath University UK 25 45 39 22 21 155.5104 Tufts University US 17 10 15 26 81 153.9105 Texas A&M University US 78 12 3 6 49 153.2106 Iowa University US 23 10 11 5 99 152.6107 Colorado University US 38 17 3 10 79 151.9108 Massey University NZ 41 49 42 5 8 150.6109 Washington University, St Louis US 38 10 10 13 76 150.3 110 Chalmers University of Technology SE 71 17 22 11 25 150.2 111 Sains Malaysia University MY 26 27 78 15 0 149.6112 Glasgow University UK 59 33 10 15 27 148.5113 University of Technology, Sydney AU 46 49 39 7 0 146.1 114 Otago University NZ 25 49 42 10 15 145.9115 Brandeis University US 13 26 15 12 75 145.6116 Michigan State University US 81 10 7 8 35 145.1117 North Carolina University US 37 9 3 17 75 144.3118 Virginia University US 53 6 10 17 54 144.0119 Seoul National University KR 83 6 20 9 21 144.0120 Utrecht University NL 58 16 9 11 45 143.9121 Paris XI, Orsay FR 47 11 31 10 40 142.6122 Royal Institute of Technology SE 37 19 30 4 47 142.5123 Maastricht University NL 24 20 51 20 23 142.0124 Stuttgart University DE 61 11 39 17 10 141.7125 Humboldt University Berlin DE 69 11 23 7 28 141.3126 Birmingham University UK 41 36 19 14 26 140.5127 Aarhus University DK 59 18 13 26 20 140.0128 Durham University UK 52 33 10 11 28 139.3129 Helsinki University FI 75 11 7 13 28 138.6130 Penn State University US 64 10 5 10 44 138.4131 Leiden University NL 24 20 13 12 65 137.9132 Strasbourg University FR 29 11 40 9 45 137.6133 Leeds University UK 54 31 17 15 16 136.9134 Maryland University US 35 20 5 14 58 136.7135 Bonn University DE 56 11 37 13 14 135.0136 Stony Brook, State of New York University US 26 7 10 11 75 134.3 137 York University UK 36 39 16 16 22 133.3138 Dartmouth College US 18 13 12 20 65 132.5139 Stockholm University SE 40 19 30 3 35 131.9140 Uppsala University SE 43 19 30 11 24 131.5141 Utah University US 51 10 13 14 40 131.0142 La Trobe University AU 27 49 23 4 25 130.8143 Waterloo University CA 50 25 12 5 35 130.6144 Toulouse University FR 31 8 40 5 42 130.4145 Technical University of Denmark DK 49 18 15 23 20 128.6146 Rice University US 35 10 7 25 48 128.5147 Hamburg University DE 66 11 17 9 20 127.3148 Mcmaster University CA 28 24 13 11 47 127.3149 Kiel University DE 27 11 15 3 67 127.0150 Sheffield University UK 38 33 15 15 22 126.9151 Liverpool University UK 32 39 14 13 25 126.8152 Karlsruhe University DE 47 11 29 9 26 126.0153 Tohoku University JP 48 6 2 27 39 125.7154 China University of Sci & Tech CN 85 5 1 24 6 125.2155 Montpellier 1 University FR 43 11 31 5 31 124.8156 Vanderbilt University US 20 2 5 39 55 124.6157 Frankfurt University DE 51 11 30 6 22 124.1158 Technion - Israel Institute of Technology IL 78 0 1 12 30 124.0 159 Madrid Autonomous University ES 62 19 11 8 19 123.7160 Korea Advanced Institute of Sci & Tech KR 86 7 19 8 0 123.5161 Tasmania University AU 27 49 22 6 15 123.3162 La Sapienza University IT 89 4 5 4 16 121.5163 Pohang University of Sci & Tech KR 22 14 18 8 56 120.9164 Innsbruck University AT 31 19 38 6 23 120.8165 Georgetown University US 38 10 10 13 46 120.6166 Alberta University CA 28 24 23 13 28 120.4167 Nagoya University JP 45 3 3 19 47 120.0168 Dundee University UK 9 42 21 14 31 119.4169 Würzburg University DE 11 11 15 6 72 118.8170 Nottingham University UK 24 39 20 13 19 118.0171 Lund University SE 36 19 6 11 40 117.3172 Technische Hochschule Darmstadt DE 39 11 28 2 33 116.9173 Emory University US 12 1 8 43 48 116.6174 Indiana University US 29 0 10 6 68 115.9175 University of California, Santa Cruz US 14 5 2 4 87 115.6176 Helsinki University of Technology FI 61 20 8 15 8 115.4177 Université de Montréal CA 35 24 23 14 14 114.2178 Freiburg University DE 26 11 29 14 29 113.0179 Newcastle Upon Tyne University UK 19 33 19 20 19 112.6180 University of Southern California US 40 15 14 4 35 111.4181 Lancaster University UK 23 44 16 7 18 111.3182 University of California, Davis US 27 1 4 10 65 110.8183 Arizona University US 35 5 9 10 49 110.6184 RWTH Aachen DE 60 11 27 9 0 110.5185 Queen's University Belfast UK 16 54 16 5 16 110.3186 Bologna University IT 76 4 8 4 14 109.8187 Norwegian University of Sci & Tech NO 30 23 19 22 12 109.6188 Tulane University US 27 10 20 33 16 108.9189 Leicester University UK 5 32 21 17 29 107.4190 Rutgers State University US 24 25 5 10 40 107.3191 Nijmegen University NL 22 20 12 33 17 107.1192 Nanjing University CN 73 4 2 16 7 106.3193 Southampton University UK 12 45 11 16 18 105.9194 Aberdeen University UK 6 38 22 16 20 105.7195 National Autonomous University of Mexico MX 68 7 0 25 1 104.5196 Fudan University CN 61 8 13 15 4 104.5197 Bremen University DE 35 11 21 2 32 104.4198 City University of Hong Kong HK 40 47 3 10 0 103.6199 Virginia Polytechnic Inst US 56 10 7 11 17 103.0200 Rensselaer Polytechnic Inst US 24 19 9 9 38 102.9。
View Of North East England
圣· 詹姆斯公园球场
(St James'Park)
十大鬼宅之一:
在泰恩河畔纽 卡斯尔附近的 吉布塞德庄园, 这是一座18世 纪的森林庄园, 据说一位不幸 的女伯爵“鬼 魂”经常现身
Berwick—upon--Tweed
(哈德良长城) Hadrian’s Wall was built on the orders of the Emperor Hadrian.The primary function of Hadrian’s Wall was to keep out the Picts. Hadrian’s Wall IS 117 KM long and is built in stone. In places it is six meters high and three meter wide.
View Of North East England
Newcastle---upon--- Tyne & Berwick---upon---Tweed
Situated on the north bank of the River Tyne, Newcastle is linked to Gateshesd by a series of seven bridges and the two centers form an exciting destination that is positively buzzing with creativity and energy.
Байду номын сангаас
1.The green bridge called 泰恩大铁桥 ( Tyne Bridge )
基于改进Delaunay算法的树冠三维重构单木因子提取
0521 修回日期: 20120626 收稿日期: 2012* 国家高技术研究发展计划 ( 863 计划) 资助项目( 2009AA12Z327 ) 和 “十二五” 国家科技支撑计划资助项目( 2012BAH34B01 ) Email: top_speed2@ 163. com 作者简介: 巩垠熙, 博士生, 主要从事林业装备工程与地理信息系统研究 , Email: fengzhongke@ 126. com 通讯作者: 冯仲科, 教授, 博士生导师, 主要从事精准林业 、 测绘与 3S 技术集成研究,
[1 ]
引言
由于森林环境的复杂多变、 树木空间结构的不 规则性以及传统人工测树的粗放, 以往的单木因子
测算效率和精度都不甚理想
, 但随着地面三维激 光扫描技术的日益成熟和成本降低, 其作为一种实 现高精度量测并快速构建目标物体空间结构的技术 [2 ] 进 方法, 可以实现树木结构的高精度快速重建 ,
Amended Delaunay Algorithm for Single Tree Factor Extraction Using 3D Crown Modeling
Gong Yinxi1 He Cheng1 Feng Zhongke1 Li Wenzhao2 Yan Fei1
( 1 . College of Forestry,Beijing Forestry University,Beijing 100083 ,China 2 . College of Civil Engineering and Geosciences,Newcastle University,Newcastle Upon Tyne NE17 RU,UK)
Abstract: Crown structure is complex and has huge amount of point cloud data. In order to achieve more accurate and more efficient measurement of crown surface area and volume,the characteristics of existing algorithms were analyzed and an improved triangular mesh surface reconstruction algorithm which is based on spatial division block priority mechanism was proposed for the reconfiguration of the crown surface. A precise and efficient factor extraction method for crown surface area and volume was formed. Crown point cloud data obtained through ground 3D laser scanning system was used. Through the traditional artificial method ,cloud point measurement method, the classics digital elevation model algorithm and the proposed algorithm,the crown surface and volume of the experimental subjects was calculated respectively. The inter comparison of the algorithm results fully meets the calculation accuracy. The time consumption of the proposed algorithm only accounts for 41% of the traditional way and 62% of digital elevation model method,which appears to greatly improve the operation efficiency. Key words: Crown Improved Delaunay algorithm TLiDAR Single tree factor Point cloud data
卡-梅综合征:干扰素的危险性和应用己酮可可碱的成功治疗
卡-梅综合征:干扰素的危险性和应用己酮可可碱的成功治疗De La Hunt M.N.;虎小毅【期刊名称】《世界核心医学期刊文摘:儿科学分册》【年(卷),期】2006(2)5【摘要】A girl aged 3 months presented with thrombocytopenia and bruising around a large vascular malformation of her posterior abdominal wall. Treatment was started with corticosteroids and platelet replacement, but with no improvement and a platelet count persistently less than10×109/L over 3 weeks, α-interferon was added. There was an immediate increase in bruising, a fall in platelet count, and an increase in platelet transfusion requirement until interferon was discontinued 11 days later. After a further week, the platelet count returned to the levels before interferon, but the patient did not develop any further symptoms. The platelet count remained low with no clinical change until pentoxifylline was start ed at the age of 15 months. The platelet count rose to 117×109/L within 4 days and remai- ned more than 100×109/L thereafter. The patient is now 7 years old and has had no recurrence since stopping the pentoxifylline at the age of 5 years. Although thrombocytopenia is a recognized side effect of interferon therapy, this very dangerous complication has not been previously reported using interferon for the Kasabach-Merritt syndrome.【总页数】1页(P48-48)【关键词】α-干扰素;卡-梅综合征;己酮可可碱;治疗;血小板减少症;血小板计数;血管畸形;皮质激素;血小板量【作者】De La Hunt M.N.;虎小毅【作者单位】Department of Paediatric Surgery, Royal Victoria Infirmary, Newcastleupon-Tyne, NE1 4LP, United Kingdom【正文语种】中文【中图分类】R512.62;R732.2【相关文献】1.注射用己酮可可碱中己酮可可碱含量及有关物质的高效液相色谱法测定 [J], 尹德忠;吴耀国;赵红侠2.反相高效液相色谱法测定己酮可可碱氯化钠注射液中己酮可可碱的含量 [J], 张延岭;赵丽;马玉贞;宋超;巩丽萍3.高效液相色谱法测定己酮可可碱肠溶片中己酮可可碱含量 [J], 孟祥云;代文婷;高雷;邢海燕;陈进4.己酮可可碱治疗急性呼吸窘迫综合征疗效观察 [J], 刘骏达;黄晓庆;黄林喜;丁宏辉5.卡-梅综合征:干扰素的危险性和应用己酮可可碱的成功治疗 [J], 虎小毅(译)因版权原因,仅展示原文概要,查看原文内容请购买。
HYDROLOGICAL PROCESSES
Modelling long-term contaminant migration in a catchment at ®ne spatial and temporal scales using the UP systemW.T.Sloan*and J.EwenWater Resource Systems Research Laboratory,Department of Civil Engineering,University of Newcastle upon Tyne,Newcastle upon Tyne,NE17RU,UKAbstract:A method has been developed to simulate the long-term migration of radionuclides in the near-surface of a river catchment,following their release from a deep underground repository for radioactive waste.Previous (30-year)simulations,conducted using the SHETRAN physically based modelling system,showed that long-term (many decades)simulations are required to allow the system to reach steady state.Physically based,distributed models,such as SHETRAN,tend to be too computationally expensive for this task.Traditional lumped catchment-scale models,on the other hand,do not give su ciently detailed spatially distributed results.An intermediate approach to modelling has therefore been developed which allows ¯ow and transport processes to be simulated with the spatial resolution normally associated with distributed models,whilst being computa-tionally e cient.The approach involves constructing a lumped model in which the catchment is represented by a number of conceptual water storage compartments.The ¯ow rates to and from these compartments are prescribed by functions that summarize the results from physically based distributed models run for a range of characteristic ¯ow regimes.The physically based models used were,SHETRAN for the subsurface compartments,a particle tracking model for overland ¯ow and an analytical model for channel routing.One important advantage of the method used in constructing the lumped model is that it makes down scaling possible,in the sense that ®ne-scale information on the distributed hydrological regime,as simulated by the physically based distributed models,can be inferred from the variables in the lumped model that describe the hydrology at the catchment scale.A 250-year ¯ow simulation has been run and the down scaling process used to infer a 250-year time-series of three-dimensional velocity ®elds for the subsurface of the catchment.This series was then used to drive a particle tracking simulation of contaminant migration.The concentration and spatial distribution of con-taminants simulated by this model for the ®rst 30years were in close agreement with SHETRAN results.The remaining 220years highlighted the fact that some of the most important transport pathways to the surface carry contaminants only very slowly so both the magnitude and spatial distribution of concentration in surface soils are not apparent over the shorter SHETRAN simulations.Copyright #1999John Wiley &Sons,Ltd.KEY WORDS catchment modelling;contaminant transport;up scaling;down scaling;environmental impact assessment;radionuclidesHYDROLOGICAL PROCESSES Hydrol.Process .13,823±846(1999)*Correspondence to Dr W.T.Sloan,Department of Civil Engineering,Cassie Building,University of Newcastle,Newcastle upon Tyne,NE17RU,UK.Contract grant sponsor:UK Nirex Ltd;NERC.824W.T.SLOAN AND J.EWENINTRODUCTIONHydrologists are increasingly being called upon to develop models of hydrology and solute transport for river basins that can be used to assess the e ects of environmental change over very long time periods.This has been prompted by two main concerns:®rst,the e ect on water resources of a probable impending change in the earth's climate(Houghton et al.,1996);secondly,the e ect of more immediate anthropogenically induced change in land use and pollution levels.In the past,river basin models aimed at addressing these concerns have often been developed at the behest of policy makers,under the in¯uence of advice from scientists regarding current technical capabilities.As a consequence,the demands made of the models and their ability to meet these demands have usually been well matched.Recently,however,policy makers have taken a much more active role in setting the underlying fundamental research agendas for environmental scientists,as an increased awareness of environmental issues within the public at large has forced governments to investigate openly the long-term environmental e ects of their policies.As a result,the detailed technical questions being posed by policy makers often go beyond the capabilities of the currently available modelling tools to produce answers(Harvey and White, 1995),and environmental modellers are,therefore,having to conduct research into new approaches to predicting the long-term e ects of environmental change.One example of such research stems from issues arising in relation to the disposal of low and intermediate level radioactive wastes.Within the UK,it is proposed to bury the waste in a repository deep below the earth's surface,and United Kingdom Nirex Limited(Nirex)has been given responsibility for developing a deep geological repository(Nirex,1995).While most radionuclides would decay in situ within a repository,on the time-scale of thousands to tens of thousands of years,some radionuclides could escape and be transported in groundwater to the earth's surface.A key component of assessing the post-closure safety of a repository is the evaluation of the radiological risks to individuals who might be exposed to released radionuclides(Environ-ment Agency et al.,1997).An important part of assessing this risk is to quantify the e ects of competing dilution and accumulation processes in the near-surface(the top few tens of metres)on the concentrations and spatial distribution of radionuclides in surface soils and surface waters(Nirex,1995).The complex nature of the interactions between these processes makes their e ects impractical to assess without the use of numerical models.Furthermore,the spatial distribution of contaminants may take many years to become fully developed and,therefore,the models used must be capable of simulating long time periods. Lumped,catchment-scale models have been developed to simulate the e ects of environmental change over very long time periods(e.g.Cosby et al.,1985);large catchments are often represented by an array of such models(e.g.Whitehead et al.,1998).However,these do not give®ne-scale,spatially distributed information on,say,the distribution of contaminants over the surface of a catchment.Conversely,the physically based distributed modelling systems currently available,such as SHETRAN(Ewen,1995),do supply spatially distributed information,but tend to be very computationally expensive;a fact that has precluded their use in very long-term simulations for the assessment of environmental change.Therefore, what is needed for long-term simulation is an intermediate approach to modelling,which gives some of the detail of physically based models yet is as practical as lumped catchment models for simulating behaviour over hundreds of years.This paper demonstrates the theory and application of the UP system(the name derives from upscaled physically-based)which uses such an intermediate approach.The UP system is computationally e cient and has been developed to simulate hydrology and solute and sediment transport at a®ne temporal resolution and a variety of spatial scales,ranging from the catchment scale(tens of square kilometres)to the continental scale.It is currently being used in a variety of research applications including environmental impact assessment,and is being coupled with a general circulation model(GCM)(as part of the TIGER project funded by the Natural Environmental Research Council,UK). The system is described in Ewen(1997)and has been developed further for the long-term modelling of water ¯ow and solute transport in a catchment.The ability of the UP system to produce some of the detail normally associated with physically based distributed models whilst remaining computationally e cient isdemonstrated here by showing that the results it gives for the ®rst 30years of a 250-year simulation are comparable with those from a 30-year SHETRAN simulation.The simulation described here is for a catchment with unchanging physical properties.However,the UP approach is very ¯exible,and similar simulations can readily be run for catchments undergoing prescribed changes in physical properties or climate.THE UP MODELLING APPROACHAt the core of the UP system is a computationally e cient catchment-scale model for water ¯ow,described as an UP element (Figure 1;adapted from Ewen,1997),which represents a catchment by a number of (conceptual)water storage compartments.Typically,the area of land represented by an UP element is less than 100km 2.For applications to a large river basin,the basin is represented by a mosaic of UP elements,the boundaries of which can lie on natural watersheds or a regular grid.The runo predicted from each UP element is routed by a model that describes the storage and ¯ow behaviour of the entire river basin channel network.The methodology for linking UP elements to represent large river basins is described elsewhere (Kilsby et al .,1996;Sloan et al .,1997).The UP elementIn traditional lumped catchment hydrological models,a catchment is represented by a number of conceptual water storage compartments.The standard approach involves using simple functions to relate the ¯ows into and out of each compartment to variables that describe the state of that compartment (e.g.volume of water stored).In some such models,the forms of the relationships between the ¯ows and variables relyonFigure 1.A schematic diagram of an UP elementMODELLING LONG-TERM CONTAMINANT MIGRATION 825826W.T.SLOAN AND J.EWENthe use of`e ective parameters'to describe the physical properties of the compartment.For example,in a compartment representing groundwater,the function may use a spatially averaged value of saturated hydraulic conductivity.The most appropriate functional forms and the best way of estimating e ective parameters is a topic that is vigorously debated in the hydrological literature under the headings of`e ective parameters',`upscaling'and`the scale problem'(e.g.Beven,1995;Bloschl and Sivapalan,1995).The UP system employs an altogether more pragmatic approach to characterizing the¯ows to and from the various compartments of an UP element,which to a large extent bypasses the debate mentioned above.The approach di ers from others in that it starts from the premise that physically based distributed models parameterized using spatially distributed data at the®nest scale available(ing high resolution digital elevation maps,DEMs)are currently the best available tools.Consequently,the¯ows between the compart-ments of an UP element should,as far as is practical,be characterized using simulation results from such models.To achieve this,an appropriate physically based distributed model is applied to each of the compartments for a range of characteristic physical conditions,and the results from this are used to create a summary data set for the state of the compartment(e.g.amount of water stored)and for the¯ows to and from the compartment.This summary data set is used to derive functions for the¯ows that depend upon the variables that describe the compartment's internal state(e.g.groundwater discharge as a function of ground-water storage),and it is these summary functions that control the behaviour of the compartment in an UP element.For convenience,the process of creating the functions from the detailed physically based model results is called upscaling.Where possible,the functions take the form of simple algebraic equations,but,where it is di cult to®nd an appropriate simple continuous functional form to describe a summary data set,a discrete transfer function or look-up table is used.The use of transfer functions to describe hydrological processes in a lumped manner is well documented(Chow et al.,1988).Look-up tables are less widely used.These store values of the function at a number of discrete values of the independent variables and the function is then evaluated at any arbitrary value of the independent variables by interpolating between the tabulated values. The UP element in Figure1can,therefore,be thought of as a framework for combining a set of simple models,which take the form of simple algebraic equations,look-up tables and transfer functions,derived from detailed physically based model results.One advantage of the UP approach to upscaling is that it makes downscaling possible,in the sense that it allows some details of the®ne-scale distributed hydrological response within each compartment to be inferred from the variables that describe the state of that compartment at the(large)scale of an UP element. For example,suppose the rate of discharge from the groundwater compartment of an UP element is governed by a single-valued function of its storage,which is derived by running a®nite di erence model of groundwater¯ow,on a®ne mesh,for a number of characteristic¯ow conditions.Then,for each character-istic condition,the distributed groundwater behaviour(e.g.¯ow pathways or distribution of water) simulated by the®nite di erence model can be mapped to a particular range of values of storage.In an UP simulation,the storage in the groundwater compartment varies continuously in response to recharge and discharge,and the distributed groundwater behaviour at any time can be taken to be the characteristic¯ow condition that corresponds to the range of storage in which the current value of storage lies.The practice of inferring the®ne-scale hydrological behaviour from the compartment state variables relies on there being a one-to-one mapping between them.Often,however,it is di cult to®nd a single state variable that fully meets this requirement.For example,it is possible that at two di erent times of the year the same total volume of water is stored in an aquifer but that its distribution in space is di erent.In such a case a second state variable is needed,and for the example presented here a suitable choice was found to be the time of year.The successful application of the UP system hinges on appropriate choices of distributed physically based models and of the functions used in the upscaling process;these can vary between applications depending on the ultimate goal.Hence,prior to giving details of the upscaling and downscaling processes,it is helpful to put them into context by®rst describing the issue that is being addressed.LONG-TERM SIMULATION OF RADIONUCLIDE MIGRATIONThe SHETRAN physically based distributed catchment modelling system (Ewen,1995)is being used to simulate the near-surface migration of contaminants in a range of hypothetical catchments representing a site that has been investigated by Nirex for the UK's deep underground radioactive waste repository.This work has included a series of simulations conducted on hypothetical catchments intended to represent an area of land into which,at some time in the far future,radionuclides from a deep repository could be released.The overall aim is to give a general representation of the steady-state migration of 36Cl and 129I for a range of di erent climate conditions.In the Nirex (1995)assessment the hypothetical catchment was one broadly based on the present-day lower catchments of the rivers Ehen and Calder,in West Cumbria,UK.Here,the sea level was deemed to have fallen and the modelled catchment included a former sea bed (Nirex,1997):a low relief landscape overlain by perforated clay sediments.SHETRAN simulates contaminant migration in these catchments with ®ne temporal and spatial resolution.It is,however,computationally expensive and,as a consequence,it is impractical to conduct simulations over very long time periods.Some experimental simulations of periods over 100years have been run,but a typical practical simulation length is 30years.Some of the subsurface pathways for radionuclide migration do not develop fully within 30years,so the UP system is used to run 250-year simulations,by which time all the pathways have developed fully.Notwithstanding that the application is for boreal climate conditions (Nirex,1997),ground and surface water freezing are not represented in the simulations presented here.The catchmentA single hypothetical catchment from the SHETRAN simulation series was selected to demonstrate the UP system.Some details of the modelled catchment,including the land use,vegetation and surface soils are given in Nirex (1995).The catchment is 17km long by 3km wide,covering an area of 46km 2(Figure 2).Its length was based on the width of the present-day coastal plain,plus an estimate of the width of the present-day o shore region that would be exposed by a 40m sea-level fall.The catchment geology consists of Quaternary drift deposits overlying sandstone of the Sherwood Sandstone Group (SSG).A simple `layer-cake'representation of the Quaternary drift deposits was used,which for the majority of thecatchmentFigure 2.Ground surface elevations and channel networkMODELLING LONG-TERM CONTAMINANT MIGRATION 827comprises:surface soils (0±1.5m depth);upper sand (1.5±10m depth);silty clay (10±14m depth);lower sand (14±20m depth);sandstone (below 20m).There are two breaks in the clay layer,where the lower sand extends upwards to 10m below ground.One break lies directly beneath the tributary channel,and the other a short distance from the main channel (Figure 3).The clay acts as a partially con®ning layer,it has a saturated hydraulic conductivity of 10À4m day À1,so the breaks in it have a signi®cant e ect on the hydraulic coupling between the sandstone and the ground surface.A deep,substantial sandstone aquifer lies below the catchment,and the contributing regional ground-water ¯ows from the deeper aquifer are represented by a constant up¯ow at the base of the catchment at a rate,averaged over the catchment,equivalent to 94.6mm year À1.The spatial distribution of this up¯ow is shown in Figure 4.The rainfall and other meteorological data for the catchment are based on data for the Kotioja catchment,located inland near the northern coast of the Gulf of Bothnia,Finland.These data were obtained from the Finland National Board of Waters and the Environment.They consist of six years of hourly precipitation,potential evaporation and temperature records.In the application,the data are repeated cyclically,as a six-year block,throughout the 250-year simulation period.For SHETRAN,the catchment was discretized into 184grid elements of 1km by 0.25km,and a no-¯ow condition was speci®ed at all lateral boundaries,except at the channel outlet.UPSCALINGThe catchment is treated as a single UP element and three di erent physically based models are used in the upscaling process to produce summary functions for the compartments of the UP element:an analytical model for channel routing,a particle tracking model for overland ¯ow and SHETRAN for subsurface ¯ow.Evaporation time-series from SHETRAN were used directly in the UP simulation,so the canopy compartment of the UP element was not used.A split sample approach was used to validate the UP model of the catchment.The ®rst three years of meteorological data were used to construct the summary functionsin Figure 3.Location of the breaks in the clay layer828W.T.SLOAN AND J.EWENthe form of look-up tables.These three years will be called the calibration period.The second three years of the data were then used to validate the functions by comparing the UP results with the ¯ows simulated by SHETRAN for that period.Subsurface watersThere are three subsurface compartments in an UP element:groundwater,inter¯ow and the unsaturated zone [in Ewen (1997)the unsaturated zone is further split into the root zone and percolation zone,but this splitting is not used here].The state of the subsurface is described by the state variables for these three compartments and the rates of ¯ow into and out of the compartments are described by functions of these state variables.The functions take the form of look-up tables and are derived from data sets that summarize SHETRAN results for the three-year calibration period.Fully three-dimensional ¯ow through variably saturated heterogeneous porous media is represented in SHETRAN (Parkin,1996),and the entire subsurface of the catchment is partitioned by a ®ne three-dimensional ®nite-di erence irregular grid,so the state of the system at any time is fully described by the quantity of water in the ®nite-di erence cells and the rates of ¯ow across the cell boundaries.Partitioning the subsurface.Before creating the summary data sets,it was ®rst necessary to identify the regions in the subsurface of the catchment that exhibit the characteristics of groundwater,inter¯ow and unsaturated zones,so that they could be associated with the appropriate compartments of an UP element.This was achieved by analysing the time-series of cell soil moisture contents and boundary ¯ow rates.The set of boundary ¯ows for all the cells in the SHETRAN grid at one instant in time corresponds to a three-dimensional velocity ®eld and the time-series of such sets corresponds to a time-series of velocity ®elds.Inter¯ow .Common to most de®nitions of inter¯ow is that it is associated with water emanating from the subsurface of a catchment,giving a hydrograph storm response that is more rapid than that associated with groundwater discharge.Bonell (1995)catalogues the physical processes that are thought to give rise to inter¯ow and outlines attempts at modelling them.SHETRAN is capable of simulating some ofthe Figure 4.Regional aquifer up¯ow (ms À1)MODELLING LONG-TERM CONTAMINANT MIGRATION 829processes that are thought to contribute to inter¯ow,such as the creation of perched water tables and lateral ¯ow in the unsaturated zone.Two techniques were used to identify regions of the subsurface that experience inter¯ow:one based on ®nding the most likely pathways for fast shallow ¯ow,and the other based on ®nding regions where the velocities change in sympathy with the discharge at the ground surface during a storm event.In preparation for the use of these two techniques,a time-series of the total rate of discharge from the subsurface was calculated from the time-series of SHETRAN velocity ®elds for the three-year calibration period.For the ®rst technique,the mean velocity ®eld associated with peak discharge rates from the subsurface was calculated.The ¯ow pathways associated with this mean velocity ®eld were then determined by tracking a pulse of water incident on the catchment.This was achieved by representing the pulse by a set of uniformly distributed particles and following these as they moved through the mean velocity ®eld.The catchment boundary is impermeable and,therefore,all the particles eventually emerged at the catchment surface or in the channel.The inter¯ow region is assumed to be associated with rapid subsurface ¯ow,so the total travel time of each particle was recorded and those particles with travel times less than a predetermined `cut-o 'value were designated as rapid.The inter¯ow region was then assumed to be associated with those SHETRAN cells through which rapid particles had travelled.The choice of cut-o value for travel time is subjective;12hours was selected after inspecting several discharge hydrographs.In the second technique,the aim is to identify the SHETRAN cells that are unsaturated prior to a storm,but that saturate quickly during the storm and contribute to discharges from the subsurface.This was achieved using the time-series of the vertical component of water velocity for each cell.For cells deep in the subsurface,or in areas of the catchment that are continuously unsaturated,the magnitude of the vertical velocity changes,but its direction rarely changes.However,in cells thath saturate quickly during a storm event there is downward ¯ow initially,but when the cell becomes saturated there is usually upward ¯ow.An example of this type of response is shown in Figure 5.It is assumed that before a cell responding in this manner can contribute to discharge from the subsurface,all the cells between it and the surface must also exhibit upward ¯ow.For this technique,cells are labelled as inter¯ow cells if they meet three criteria:®rst,the average duration of continuous upward ¯ow,post-storm,is less than a particular value,in this case 12hours;secondly,the number of times that there is a period of continuous upward ¯ow corresponds to the number of storms;and thirdly,all cells between it and the surface meet the ®rst two criteria.The two techniques are considered to be complementary and a cell was assumed to be an inter¯ow cell if it was identi®ed as such by either technique.The inter¯ow regions identi®ed in this manner are shown in Figure 6.Unsaturated zone .Cells in the subsurface are classi®ed as being unsaturated if they are not classed as inter¯ow cells and remain unsaturated at all times.Regions identi®ed in this manner are shown in Figure6.Figure 5.Typical rainfall response of the vertical component of velocity in cells in the inter¯ow region830W.T.SLOAN AND J.EWENGroundwater .When superimposed,the inter¯ow,unsaturated zone and the groundwater regions should cover the subsurface without overlapping or leaving gaps.Therefore,the groundwater regions comprise all parts of the subsurface not covered by either the inter¯ow or unsaturated regions (Figure 6).Functions for the subsurface compartments.Having identi®ed the inter¯ow,unsaturated and groundwater regions,the ¯ows to and from them (numbered 4,5,7and 8in Figure 1)have to be characterized by a set of functions.A function is also required to describe the fraction of the catchment's total surface area saturated by discharging subsurface water,since this controls the rate of saturation excess runo .All the functions depend upon state variables for the subsurface compartments,and all take the form of look-up tables.Table I describes the look-up tables used for the subsurface ¯ows and saturated area in the UP element.Two state variables were required for each compartment.The ®rst state variable is depth of water stored in the compartment.The relationship between groundwater discharge (¯ow 5)and storage in thegroundwaterFigure 6.Subsurface regions for UP modelling identi®ed using characteristic velocity ®elds from SHETRANMODELLING LONG-TERM CONTAMINANT MIGRATION 831compartment,for example,exhibited annual hysteresis (Ewen,1997),and Table I shows that the second state variable,which controls the hysteresis,is time of year.Values of the groundwater discharge were stored in a look-up table at 5Â12co-ordinates of these two variables;5ordinates for depth of water and 12for time of year.During an UP simulation,the groundwater discharge rate corresponding to the current value of storage and time of year is evaluated by linearly interpolating between the discharge values stored in the table at the co-ordinates closest to the current values.Figures 7to 11show the quality of the functions by comparing UP and SHETRAN results for the three-year calibration period.Surface waterThe ¯ow of surface water across the catchment is modelled using separate transfer functions for overland and channel ¯ow.Transfer functions are based on the assumption that the system is linear so that the response at the output to the system,O (t ),to a continuous input,I (t ),is given byO t t 0I t u t Àt d t 1 where,u (t ),the impulse transfer function,is the response of the system at time t to a unit impulse at time 0.The heterogeneity in the properties of the catchment surface,the non-linearity of the St Venant equations (which describe overland ¯ow)and the variation in storm antecedent conditions (such as the area of the catchment saturated at the surface)all ensure that the overland ¯ow response is non-linear.Therefore,it is not possible without great approximation to derive a single transfer function that is applicable across the full range of antecedent conditions and ¯ow regimes.However,it is practical to assume linearity within small ranges in the antecedent conditions and ¯ow regimes and derive a transfer function for each of these.The method used in the UP system exploits this,and uses multiple transfer functions,each of which apply over a small range of antecedent conditions and ¯ow rates.Table I.Summary of the look-up tables used in the subsurface compartments of the UP element (the ¯ow numbers are shown on Figure 1)FlowDependent variable State variables Number of ordinates Figure number 4Discharge from inter¯ow regions (a)Depth of water stored (b)Mean in®ltration rate to the inter¯ow region during the previous 12hours(a)5(b)1075Discharge from groundwater regions (a)Depth of water stored (b)Time of year(a)5(b)1287Percolation from the unsaturated zone (a)Depth of water stored (b)Instantaneous in®ltration rate(a)5(b)1098Discharge from the groundwater to the inter¯ow regions (a)Depth of water stored in the inter¯ow regions (b)Mean in®ltration rate to the inter¯ow regions during the previous 12hours(a)5(b)1010Not represented on the diagram Fraction of the total catchment area saturated by discharging subsurface waters (a)Depth of water stored in the inter¯ow regions Mean depth of water stored in the groundwater regions (b)Mean in®ltration rate to the inter¯ow regions during the previous 12hours (a)5(b)1011832W.T.SLOAN AND J.EWEN。
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足球俱乐部地址(国家队地址)
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Maria 23 PT - 3030330 COIMBRAPORTUGALbriosa@intercesso.ptSC Beira-MarApartade 1067 PT - 3810191 AVEIROPORTUGALrpbeiramar@CF Os BelenensesEstádio do Restelo PT - 1449025 BELEM-LISBOAPORTUGALcfbelem@clix.ptSL BenficaManuel Lino RODRIGUES VILARINHOPORTUGALwebmaster@slbenfica.ptBoavista FCRua "O Primeiro de Janeiro" PT - 4101001 PORTOPORTUGALbfc.fut.sad.dgeral@mail.telepac.ptSC BragaEstadio Primeiro de Maio Apartado 12 PT - 4711909 BRAGA PORTUGALmail@scbraga.ptGil Vicente FCRua D. Diogo Pinheiro 25 Apartado 197 PT - 4750282 BARCELOS PORTUGALgilvicentefc@mail.telepac.ptVitória Guimar?esAntónio Alberto Coimbra PIAMENTA MACHEDOPORTUGALgeral@vitoriasc.ptUD LeiriaEstadio Minicipal Dr. Magalhaes Pessoa PT - 2400 LEIRIAPORTUGALudl@net.ptCS MarítimoRua D. Carlos I. 13 PT - 9054504 FUNCHALPORTUGALcsmaritimo@Moreirense FCAvenida Comendador Joaquim Almeida Freitas 20 PT - 4815270 MOREIRA DE CONEG OSPORTUGALmoreirense-fc@cllx.ptCD NacionalRua do Esmeraldo 46 PT - 9000051 FUNCHALPORTUGALclub@FC Pa?os de FerreiraRua Captt?o Do Praca Apartado 26 PT - 4594909 PA?OS DE FERREIRA PORTUGALfcpf@FC PortoTorre das Antas Fern?o de Magalh?es 1862 - 14o PT - 4350158 PORTO PORTUGALfutebolsad@fcporto.ptCD Santa ClaraRua Comandante J. de Sousa 21 PT - 9500047 PONTA DELGADAPORTUGALsantaclara@sapo.ptVitória SetúbalEstadio do Bonfim Apartado 132 PT - 2902882 SETúBAL PORTUGALvfc-sad@netcabo.ptSporting Clube de PortugalEstadio JoséAlvalade Apartado 42099 PT - 1601801 LISBOA PORTUGALmsg.sad@scp.ptVarzim SCRua Santos Minho 28-1°PT - 4490549 POVOA DO VARZIM PORTUGALvarzim@欧洲足联UEFARoute de geneve 46P.O. BOX 1260 Ny0n 2SWITZERLAND网址:电子信箱:info@意大利足协Italian Football FederationVia Gregorio Allegri,14 C.P.2405 IT-00198 ROMAITALY电子信箱:figc.segreteria@figc.it网址:www.figc.it意大利球队AC米兰Associazione Calcio MilanOVia Filippo Turati 3, IT-20121 MILANOITALY电子信箱:milan@lega.calcio.it网址:国际米兰Internazionale Football ClubVia Durini 24, IT-20122 MILANOITALY电子信箱:internazionale@lega-calcio.it网址:www.inter.it尤文图斯Juventus Football ClubCorso Galileo Ferraris 32 IT-10128 TORINO ITALY电子信箱:juventus@lega-calcio.it网址:罗马Associazione Sportiva Romavia di Trigoria, km. 3,600 IT- 00128 ROMA ITALY电子信箱:roma@lega-calcio.it网址:www.asromacalcio.it拉齐奥SocietàSportiva LazioVia Augusto Valenziani 10 IT-00187 ROMA ITALY电子信箱:zio@cirio.it网址:www.sslazio.it切沃Associazione Calcio Chievo VeronaVia Luigi Galvani 3 IT-37138 VERONA ITALY电子信箱:chievoverona@lega-calcio.it网址:www.chievoverona.it博洛尼亚Bologna Football ClubVia Casteldebole 10,IT- 40132 BOLOGNA ITALY电子信箱:bologna@lega-calcio.it网址:www.bolognafc.it佩鲁贾Associazione Calcio PerugiaLocalitàPian di Massiano,IT- 06125 PERUGIA ITALY电子信箱:perugia@lega-calcio.it网址:www.perugiacalcio.it亚特兰大Atalanta Bergamasca CalcioVia A.Pitentino 14/a, IT-24124 BERGAMO ITALY电子信箱:atalanta@lega-calcio.it网址:www.atalanta.it帕尔玛Associazione Calcio ParmaVia Partigiani d'Italia 1, IT-43100 PARMA ITALY电子信箱:parma@lega-calcio.it网址:www.acparma.it都灵Torino CalcioVia Maria Vittoria 1, IT-10122 TORINO ITALY电子信箱:torino@lega-calcio.it网址:www.toro.it皮亚琴察Piacenza Football ClubVia Gorra 25, IT-29100 PIACENZA ITALY电子信箱:piacenza@lega-calcio.it网址:www.piacenzacalcio.it布雷西亚Brescia Calc ioVia Luigi Bazoli 10, IT-25127 BRESCIA ITALY电子信箱:brescia@lega-calcio.it网址:www.bresciacalcio.it乌迪内斯Udinese Calcioviale A Candolini 2,IT- 33100 UDINE ITALY电子信箱:udinese@lega-calcio.it网址:www.udinese.it科莫Como CalcioV.iale Sinigaglia, 2 IT-22100 COMO ITALY电子信箱:info@calciocomo1907.it网址:www.lega-calcio.it莫德纳Modena Football ClubVia Giardini 474 IT- 41100 MODENA ITALY电子信箱:modena@lega-calcio.it网址:雷吉纳Reggina CalcioVia Tommaso Gulli 1, IT-89127 REGGIO CALABRIA ITALY电子信箱:reggina@lega-calcio.it网址:www.regginacalcio.it恩波利Empoli Football ClubPiazza Matteotti, 29 IT-50053 EMPOLIITALY电子信箱:empoli@legacalc io.it网址:www.empolicalcio.it维罗纳VeronaPiazzale Olimpia, Cancello E, 37138 VERONAITALY网址:www.hellasverona.it莱切LecceVia Templari 11, 73100 LECCEITALY网址:lecce.it佛罗伦萨FiorentinaPiazza Girolamo Savonarola 6, 50132 FIRENZE ITALY网址:www.acfiorentina.it22威尼斯VeneziaVia Ceccherini 19, 30174 MESTRE (VE)ITALY网址:www.veneziacalcio.it巴里BariStrada Torrebella, 70124 BARIITALY网址:www.asbari.it桑普多利亚SampdoriaCampetto 2-16123 GéNOVAITALY网址:www.sampdoria.it维琴察VicenzaVia Schio, 21-36100 VICENZAITALY网址:www.vicenzacalcio.it那不勒斯NapoliVia Vicinale Paradiso 70-80126 NAPOLI ITALY网址:www.calcionapoli.it卡里亚里CagliariPiazza Deffenu, 09125 CAGLIARIITALY网址:www.cagliaricalcio.it莎拉尼塔那SalernitanaVia Lungomare Marconi, 18-84129 SALERNO ITALY网址:www.salernitana.it帕勒莫PalermoViale del Fante 11, 90146 PalermoITALY网址:www.calciopalermo西班牙足协Real Federacion Espanola de FutbolCalle Alberto Bosch,13 A,Partado Postal 347,E-28014 MADRID SPAIN电子信箱:rfef@tsai.es网址:http://rfef.sportec.es/main.htm西班牙俱乐部巴伦西亚Valenc ia CFEdif. Alameda,Senda de Senent 14,ES-46023 VALENCIA SPAIN电子信箱:mestalla@valenciacf.es网址:www.valenciacf.es皇家马德里Real Madrid CFEstadio Santiago Bernabeu Avda. Concha Espina 1 ES-28036 SPAIN电子信箱:internacional@realmadrid.es网址:www.realmadrid.es皇家贝蒂斯Real Betis BalompiéAvda. de Heliopolis s/n, ES-41012 SEVILLASPAIN电子信箱:realbetisbalompie@realbetisb网址:www.realbetisbalompie.es皇家社会Real SociedadPaseo de Anoeta 1,ES-20014 SAN SEBASTIANSPAIN电子信箱:prensa@网址:www.real-sociedad-sad.es马拉加Málaga CFPaseo de Martiticos Estadio la Roseleda ES-29011 Málaga SPAIN电子信箱:administracion@malagacf.es网址:www.malagacf.es6巴拉多利德Real ValladolidAvda. del Mundial 82 s/n,ES-47014 VALLADOLID SPAIN电子信箱:realvalladolid@realvalladolid.es网址:www.realvalladolid.es7塞尔塔维戈RC Celta de VigoAvenida de Balaidos s/n,ES-36210 VIGOSPAIN电子信箱:web@网址:奥萨苏纳Club Atlético OsasunaEstadio del sadar s/n ES-31006 PAMPLONASPAIN电子信箱:osasuna@osasuna.es网址:www.osasuna.es阿拉维斯Deportivo AlavésPaseo de Cervantes s/n,ES-01007 VITORIA-GASTEIZ SPAIN电子信箱:deportivoalavessad@网址:比利亚雷尔Villarreal Club de Fútbol S.A.D.Camino Miralcamp s/n ES-12540 VILLARREAL SPAIN电子信箱:villarrealcf@villarrealcf.es网址:www.villarrealcf.es马德里竞技Club Atlético de MadridP. Virgen del Puerto 67. Es- 28005 MADRID SPAIN电子信箱:comunicacion@clubatleticodemadrid网址:巴列卡诺Rayo VallecanoAvda. Payaso Fofo s/n,ES-28018 MADRID SPAIN电子信箱:info@rayovallecano.es网址:www.rayovallecano.es巴塞罗那FC BarcelonaAvda. Aristides Maillol s/n,ES-08028 BARCELONA SPAIN电子信箱:secretaria@网址:乌尔瓦R.C. Recreativo de HuelvaAvda,del Decano ES-21001 HUELVASPAIN电子信箱:recreativohuelva@网址:塞维利亚Sevilla F.CAvda. Eduardo Dato s/n,ES-41005 SEVILLA SPAIN电子信箱:sevillafc@sevillafc.es网址:www.sevillafc.es桑坦德竞技Real Racing Club SantanderReal Racing Club s/n ES-39005 SANTANDERSPAIN电子信箱:oficinas@realracingclub.es网址:www.realracingclub.es毕尔巴鄂竞技Athletic Club BilbaoAlameda Mazarredo 23 ES- 48009 BILBAOSPAIN电子信箱:prensa@athletic-club.es网址:www.athletic-club.es拉科鲁尼亚RC Deportivo La Coru?aPlaza de Pontevedra 19 ES-15003 A CORUNASPAIN电子信箱:deportivo@网址:西班牙人RCD EspanyolPasseig Olimpic, 15-19, ES-08038 BARCELONA SPAIN电子信箱:info@网址:皇家马洛卡Rcd MallorcaCami dels reis s/n ES-07011 PALMA DE MALLORCA SPAIN电子信箱:prensa@rcdmallorca.es网址:www.rcdmallorca.es拉斯帕尔马斯Las PalmasC/ Pío Xll, 29. 35005 Las PalmasSPAINwww.udlaspalmas.es奥维耶多Real OviedoC/ Palacio Valdés 9, 1 33002 OviedoSPAIN特内里费TenerifeCallejón del Combate, 1, 1 38002 Santa Cruz de Tenerife SPAIN巴达约斯BadajozAvenida La Granadilla, s/n 06011 BadajozSPAIN阿尔巴塞特AlbaceteAvenida de la Estación, 5. 02001 AlbaceteSPAINwww.albacete-bp.es皇家穆尔西亚Real MurciaRonda de Garay, 14. 30003 MurciaSPAINwww.realmurcia.es希洪体育Sporting GijónEscuela de Fútbol de Mareo 33390 Gijón SPAIN萨拉格萨ZaragozaEduardo Ibarra 6. 50009 Zaragoza SPAIN科尔多巴CórdobaAvenida El Arcángel, s/n. 14010 Córdoba SPAIN瑞典足协Swedish Football AssociationBox 1216, SE-171 23 Solna, Sweden www.svenskfotboll.se2AIKAIK SolnaPO BOX1257 SE-17124 SOLNA SWEDENwww.aik.se3卡马尔Kalmar FFPO Box 169 SE-39122 KALMAR SWEDENwww.kalmarff.nu4伯艾斯Landskrona BoISPO BOX654 SE-26125 LANDSKRONA SWEDENHalmstads BKPO BOX223 SE-30106 HALMSTADSWEDENwww.halmstadsbk.se6HammarbyHammarbyPO BOX11064 SE-10061 STOCKHOLMSWEDENwww.hammarbyfotboll.se7HelsingborgsHelsingborgs IFPO BOX2074 SE-25002 HELSINGBORGSWEDENwww.hif.se8GIFGIF SundsvallPO BOX311 SE-85105 SUNDSVALLSWEDENwww.gifsundsvall.se9TrelleborgsTrelleborgs FFHejderidaregatan 2,SE-231 44 TRELLEBORGSWEDENwww.tff.m.se10 挪威足协Norwegian Football AssociationUllevaal stadion,Sognsveien75j,Serviceboks1,Ullevaal Stn,NO-0840 OSLO NORWAY11Odds BKPO BOX1605 NO-3705 SKIENwww.oddgrenland.no12SK BrannPO BOX161 Minde NO-5826 BERGENNORWAYwww.brann.no13Bryne FKPO BOX 257 NO-4349 BRYNENORWAYwww.brynefk.no14Sogndal ILPO BOX164 NO-5801 SOGNDALNORWAYwww.sil-fotball.no15 SFKSFK LynPO BOX3814 NO-0805 OSLONORWAYwww.lyn.no16IK StartPO BOX1533 Lundsiden NO-4688 KRISTIANSAND NORWAYwww.ikstart.no17Molde FKJulusundveien 14 NO-6412 MOLDENORWAYwww.moldefk.no18Moss FKPO BOX47 NO-1501 MOSSNORWAYwww.mossfk.no19Viking FKPO BOX 4051 Tasta NO-4092 STAVANGER NORWAY20 丹麦足协Danish Football AssociationIdr ttens hus,Br ndby Stadion20 DK-2605 BR NDBY DENMARKwww.dbu.dk21Aalborg BKHornevej2 DK-9220 AALBORG S?/td>DENMARKwww.aalborg-bk.dk22Akademisk BoldklubGladsaxevej200 DK-2860 SORGDENMARK23FC MidtjyllandMercurvej501 DK-7400 HERNINGDENMARKwww.fc-mj.dk24Odense BKPO BOX344 Sdr,Boulevard 172 DK-5100 ODENSE DENMARKwww.ob.dk25Esbjerg fBGl,Vardevej88 DK-6700 ESBJERGDENMARKhttp//esbjergfb.dht.dk26Silkeborg IFPO BOX 11 Ansvej 110 DK-8600 SILKEBORGDENMARKwww.sif-support.dk27 FarumPO BOX189 DK-3520 FARUMDENMARKwww.farum-boldklub.dk28 Viborg FFPO BOX214 Farvervej 1 DK-8800 VIBORGDENMARKwww.viborgff.dk12、斯洛文尼亚足协Football Association of SloveniaCerinova 4 PP 3986 SI-1001 LJUBLJANASlovenianzs@nzs.si13、NK ?martnoSmartno ob Paki 72 SI - 3327 SMARTNO OB PAKISloveniamksmartno@14、NK DravogradTrg 4. julija 7 SI - 2370 DRAVOGRADSloveniankdravograd@nklub-dravograd.si15、NK GoricaDrustuo Mladi Nogometas Gorica Cesta IX. Korpusa 35 SI - 5250 SOLKAN Sloveniand.hit@16、NK KoperIstrska cesta 67 SI - 6000 KOPERSloveniafc-koper@17、NK LjubljanaUlica Milic inskega 2 SI - 1000 LJUBLJANA Slovenia18、NK MariborMladinska Ulica 29 SI - 2000 MARIBORSloveniainfo@19、NK MuraKopaliska ulica 45 SI - 9000 MURSKA SOBOTA Sloveniasnkmura@20、NK Olimpija LjubljanaPO Box 2620 Vodovodna 20 SI - 1001 LJUBLJANA Sloveniainfo@21、NK PrimorjePO Box 3 Goriska cesta 44 SI - 5270 AJDOV?CINA Sloveniankprimorje@22、NK PublikumCesta na Grad 12 SI - 3000 CELJESloveniank-publikum@23、NK Rudar VelenjePO Box 7 Cesta na Jezero 7 SI - 3320 VELENJE Sloveniankrudar@24、NK KorotanTrg 36 SI - 2391 PREVALJESloveniandprevalje-korotan1@土耳其足协Turkish Football AssociationKonaklar Mah. Ihlamurlu Sok. 9 4. Levent TR-80620 ISTANBUL TURKEYtff@Adanaspor ASResatbey Mah. Stadyum Cad. 8/2 TR - ADANATURKEYcagdas.ergin@.trAltay GKKutlu Aktas Tesisleri 690 TR - 35221 GAZIEMIR IZMIR TURKEYaltayspor@MKE AnkaragücüTandogan Meydani TR - 06570 ANKARATURKEYinfo@.trBesiktas JKSüleyman Seba Cad. Besiktas Plaza B TR - 80680 ISTANBUL TURKEYinfo@.trBursasporVakifk?y Orhan Ozselek Tesisleri Yildirim TR - 16375 BURSA TURKEYbursaspor@.trDenizlisporKenan Evren Bulvari 9 TR - DENIZLITURKEYamin@DiyarbakirsporBüyüksehir Belediyesi TR - 21300 DIYARBAKIRTURKEYinfo@ElazigsporElazigspor Sosyal Tesisleri Malatya Yolu 10km TU - 23200 ELAZIGTURKEYFenerbah?e SKFenerbah?e Tesisleri Kiziltoprak Kadik?y TR - 81030 ISTANBULTURKEYposta@加拉塔萨雷Galatasaray SKHasnun Galip Sok. N. 7-9-11 Beyoglu TR - 80700 ISTANBULTURKEYinfo@.trGaziantepsporCelal Dogan Tesisleri Dülükbaba Ormanlari Girisi Karsisi Sehitkamil TR - 27010 GAZIA NTEPTURKEY.tr/Gen?lerbirligi SK?iftlik Cad. 30 Bestepe TR - 06570 ANKARATURKEY.tr/G?ztepeGaziosmanpasa Bul. 3/710 Cankaya TR - IZMIRTURKEYinfo@.trIstanbulspor ASBasin Ekspres Yolu Star Sokak 2 Ikitelli TR - 34540 ISTANBULTURKEYKocaelisporLeyla Atakan Kültür Parki Fuar MüdürlügüKarsisi Ytong Bina TR - 41040 KOCAELI TURKEYmurat@MalatyasporOrdu Pinarbasi Tesisleri TR - 44050 MALATYATURKEYinfo@.trSamsunsporTesisleri Dogubank TR - 55080 SAMSUNTURKEYsamsunspor55@TrabzonsporMehmet Ali Yilmaz Tesisleri TR - 61000 TRABZONTURKEYtrabzon@.tr1希腊足协Hellenic Football FederationSyngrou Avenue 137 GR-171 21 ATHENESHELLENICepo@epo.gr2AEK队AEK Athens FCTritis Septemvriou Street 144 GR - 11251 ATHENSHELLENICinfo@aekfc.gr3Akratitos FCAkratitos Stadium Konstadinoupolis Street GR - 13341 ANO LIOSIAHELLENICHELLENICakratitos@akratitos.gr4阿锐斯Aris Thessaloniki FCAigaiou Street 36 GR - 55133 THESSALONIKIHELLENIC@arisfc.gr5Egaleo FCIera Odos Street 286-288 Sintrivani Center GR - 12243 EGALEO HELLENICpaaea@acci.gr6PAS Giannina FCDompoli Street 8 GR - 45332 IOANNINAHELLENICpasgiann@otenet.gr7英尼克斯Ionikos FCDafnis Street 5 & Vournova GR - 18122 ANO KORIDALLOS HELLENICefsta@ana.gr8Iraklis FCPO Box 22475 Mikras National Stadium GR - 55102 THESSALONIKI HELLENICinfo@iraklis-fc.gr9 Kallithea GSAgion Panton Street 32 GR - 17671 KALLITHEAHELLENICidinos@forthnet.gr10 OFI队OFI Crete FCSkafidara Gazi GR - 71500 IRAKLIONHELLENICofhpae@internet.gr11 奥林匹亚克斯Olympiakos Piraeus FCAlexandra's Square GR - 18534 PIRAEUSHELLENICinfo@olympiakos.gr12 帕纳海科Panahaiki FCPandanassis Street 7 GR - 26221 PATRAHELLENICinfo@panahaiki.gr13帕尼欧尼斯Panionios FCI. Chrisostomou 1 GR - 17121 NEA SMIRNIHELLENICinfo@panionios.gr14 帕纳辛纳克斯Panathinaikos FCHerodou Attikou Street 12A Marousi GR - 15124 ATHENS HELLENICpaepao@hellasnet.gr15 PAOKFC PAOK ThessalonikiMikras Asias-Toumba Stadium GR - 54351 THESSALONIKI HELLENICpae@paok-hellas.gr16朴罗得夫提科Proodeftiki FCGrigoriou Labraki Street 68 GR - 18454 NIKAIA HELLENIC17 Xanthi FCSkoda Xanthi FC Sports Center Pigadia GR - 67100 XANTHI HELLENICinfo@skodaxanthifc.grNiceParc des Sports C. Ehrmann 177, route de Grenoble 06200 Nice FRANCEwww.ogcnice.fr2欧塞尔队AJ AuxerreBP 349, FR-89006 AUXERRE CedexFRANCEwww.aja.tm.fr3甘冈队En Avant Guingamp15 Boulevard Clemenceau, BP 66, 22200 GuingampFRANCE4巴黎圣日尔曼队Paris Saint-Germain FC110 Avenue Victor Hugo, FR-92514 BOULOGNE-BILLANCOURT Cedex FRANCEwww.psg.fr5朗斯队RC LensStade Felix Bollaert, Avenue A. Maes, BP 236, FR-62304 LENS FRANCEwww.rclens.fr6里昂队Olympique Lyonnais350 Avenue Jean Jaures, FR-69007 LYONFRANCE7波尔多队FC Girondins de BordeauxRue Juliot Curie BP 33, 33186 Le Haillan8马赛队Olympique de Marseille25 Rue Negresko, BP 124, FR-13267 MARSEILLEFRANCE9摩纳哥队AS MonacoStade Louis II, 7 Avenue des Castellans, BP 698, MC-98014 MONACO Cedex FRANCEwww.asm-foot.mc10索绍队Football club Sochaux-MontbeliardFC Sochaux-Montbeliard, Bungalow Stade Bonal, 25200 MontbeliardFRANCEwww.fcsochaux.fr11阿雅克修队Athletic Club AjaccienStade Francois-Coty, Zl du Vazzio 20090 AjaccioFRANCE12蒙彼利埃队Montpellier Herault Sports ClubStade de la Mosson, 645 Avenue Heidelberg, 34000 MontpellierFRANCE13勒阿弗尔队Le Havre Athletic Football Club Association32 rue de la Cavee-Verte, 76620 Le HavreFRANCEwww.hac.asso.fr/14巴斯蒂亚队SC BastiaStade Armand-Cesari Furiani, BP 640, FR-20601 BASTIA Cedex FRANCEwww.sc-bastia.fr15斯特拉斯堡队RC Strasbourg12 Rue de l'ExtenwoerthFRANCEwww.rcstrasbourg.fr1 法罗群岛足协Faroe Islands Football AssociationGundadalur PO Box 3028 FO-110 TóRSHAVNFAROE ISLANDSfsf@football.fo2 B36 TórshavnPO Box 1136 FO - 110 TóRSHAVNFAROE ISLANDSb36@b36.fo3 B68 Toftirc/o Mr. Niclas Davidsen FO - 650 TOFTIRFAROE ISLANDSb-68@post.olivant.fo4 GíG?tuPO Box 4 FO - 510 G?TAFAROE ISLANDSgigota@gigotu.fo5 HB TórshavnPO Box 1333 FO - 110 TóRSHAVNFAROE ISLANDShb@post.olivant.fo6 KíKlaksvíkPO Box 204 FO - 700 KLAKSVíKFAROE ISLANDSki-klaksvik@ki-klaksvik.fo7 NSíRunavíkPO Box 173 FO - 620 RUNAVíKFAROE ISLANDSinfo@nsi.fo8 SkálaFO - 480 SKALAFAROE ISLANDSskala@post.olivant.fo9 TB Tv?royriPO Box 35 FO - 800 TV?ROYRIFAROE ISLANDS10 VB VágurPO Box 134 FO - 900 VáGURFAROE ISLANDSvb@vb1905.fo11卢森堡足协Luxembourg Football Federation68, rue de Gasperich LU-1617 LUXEMBOURG LUXEMBOURGflf@football.lu12 FC Avenir BeggenPO Box 25 LU - 7201 WALFERDANGE LUXEMBOURG/fcavenir13 F91 DudelangePO Box 278 LU - 3403 DUDELANGE LUXEMBOURG.lu/14 CS GrevenmacherRue de la Congregation 3 LU - 1352 LUXEMBOURG LUXEMBOURG15 FC Swift HesperangeRue Gruewereck 19 LU - 6734 GREVENMACHER LUXEMBOURG16 AS Jeunesse EschPO Box 45 LU - 4001 ESCH-SUR-ALZETTE LUXEMBOURGhttp://www.jeunesse-esch.lu/17 FC Sporting MertzigRue de la Colmarberg 19 LU - 9169 MERTZIG LUXEMBOURG18 FC MondercangeRue de Luxembourg 35 LU - 5752 FRISANGE LUXEMBOURG19 FC Progrès NiedercornRue Batty Weber 9 LU - 4684 DIFFERDANGE LUXEMBOURG20 FC Victoria RosportRue Giesenbour 11 LU - 6583 ROSPORT LUXEMBOURG21 US RumelangePO Box 3 LU - 3701 RUMELANGE LUXEMBOURG22 US LuxembourgPO Box 1614 LU - 1016 LUXEMBOURG LUXEMBOURG23 FC Wiltz 71PO Box 47 LU - 9501 WILTZLUXEMBOURG1、冰岛Knattspyrnusamband Islands Football Association of Iceland Laugardal IS-104 REYKJAVIKIcelandksi@ksi.is2、FH Hafnarfj?rdurKaplakriki IS - 220 HAFNARFJORDURIcelandfotbolti@fhingar.is3、Fram ReykjavíkPO Box 8006 Safamyri 28 IS - 128 REYKJAVíKIcelandknattspyrna@fram.is4、FylkirFylkisvegur 6 IS - 110 REYKJAVíKIcelandknd@5、GrindavíkUngmennafélag Grindavíkur Austurvegi 3 IS - 240 GRINDAVíK Icelandumfg@centrum.is6、íA AkranesPO Box 30 Jadarsbakkar IS - 300 AKRANESIcelandkfia@aknet.is7、íBV Vestmann?yjarHamarsvegi IS - 900 VESTMANNAEYJARIcelandibvfc@eyjar.is8、KA AkureyriKnattspyrnufelag Akureyrar Knattspyrnudeild KA-Heimilid vid Dalsbraut IS - 600 AKURE YRIIcelandgassi@ka-sport.is9、KeflavíkPO Box 122 Keflavík Knattspyrnudeild IS - 230 REYKJANESB?RIcelandkef-fc@keflavik.is10、KR ReykjavíkPO Box 7065 Knattspyrnufélag Reykjavíkur Frostaskjóli 2 IS - 127 REYKJAVíK Icelandsiggihelga@kr.is11、Thór AkureyriIthróttafélagid Thór Knattspyrnudeild Hamri v/Skardshlíd IS - 603 AKUREYRIIcelandboltinn@thorsport.is俄罗斯足协Football Union of RussiaLuzhnetskaja Nab. 8 RU-119992 MOSCOWRUSSIArfs@roc.ru2、FC Chernomorets Krasnodarskiy KrayUl. Sovetov 55, RU-353 900 NOVOROSSYISKRUSSIAwww.chernomorets.nvrsk.ru3、PFC CSKA MoskvaUl. Leningradski Prospect 39 RU - 125167 MOSCOWRUSSIAcska@cska-football.ru4、FC Dinamo MoskvaUl. Leningradsky Prospekt 36 RU - 125167 MOSCOW RUSSIAinfo@fcdynamo.ru5、FC Krylya Sovetov SamaraUl. Shushenskaia 50-A RU - 443011 SAMARARUSSIAsoccer@samaramail.ru6、FC Lokomotiv MoskvaB. Cherkizovskaya Street 125 RU - 107553 MOSCOW RUSSIAfcloko@rol.ru7、罗斯托夫FC RostovUl. Pervoi Konnoi Armii 4a RU - 344029 ROSTOV-NA-DONU RUSSIArsm@fc-rostselmash.ru8、罗特队SC Rotor VolgogradProspect Lenina 76 RU - 400005 VOLGOGRADRUSSIAadmin@rotor-volgograd.ru9、FC Rubin KazanVtoraya Leningradskaya str.6. 420127 KAZANRUSSIAfkrubin@mail.ru10、FC Saturn Moskovskaya OblastGorodskoi Park Ramenskoye RU - 140103 MASCOW REGION RUSSIAsaturn-fc@saturn-fc.ru11、FC Shinnik YaroslavlPloschad Truda RU - 150000 YAROSLAVLRUSSIAshinnik@yaroslavl.ru12、FC Spartak MoskvaSpartakovskaya Street 7 RU - 107066 MOSCOWRUSSIAinfo@spartak.dol.ru13、FC Spartak-Alania VladikavkazUl. Shmulevicha 6 RU - 362007 VLADIKAVKAZRUSSIAiz2000@hotbox.ru14、鱼雷队FC Torpedo MoskvaUl. Luzhniki 24 RU - 119048 MOSCOWRUSSIAtorpedo@torpedo.ru15、FC Torpedo-Metallurg MoskvaUl. Vostochnaya 4 korp. 2 kab. 107 RU - 109280 MOSCOW RUSSIAinfo@torpedo-zil.ru16、FC Uralan ElistaUl. Lenina 218 RU - 358000 ELISTA KALMYKIYARUSSIAuralan@techline.ru17、FC Zenit St. PeterburgUl. Nekrasova 3/5 RU - 191104 ST. PETERSBURGRUSSIAinfo@fc-zenit.ru18、尼斯队NiceParc des Sports C. Ehrmann 177, route de Grenoble 06200 NiceFRANCEwww.ogcnice.fr19、欧塞尔队AJ AuxerreBP 349, FR-89006 AUXERRE CedexFRANCEwww.aja.tm.fr20、甘冈队En Avant Guingamp15 Boulevard Clemenceau, BP 66, 22200 GuingampFRANCE21、巴黎圣日尔曼队Paris Saint-Germain FC110 Avenue Victor Hugo, FR-92514 BOULOGNE-BILLANCOURT Cedex FRANCEwww.psg.fr22、朗斯队RC LensStade Felix Bollaert, Avenue A. Maes, BP 236, FR-62304 LENS FRANCEwww.rclens.fr23、里昂队Olympique Lyonnais350 Avenue Jean Jaures, FR-69007 LYONFRANCE24、波尔多队FC Girondins de BordeauxRue Juliot Curie BP 33, 33186 Le HaillanFRANCE北爱尔兰足协Irish Football Association IFA20 Windsor Avenue GB-BELFAST BT9 6EE IRELAND保加利亚足协Bulgarian Football UnionKarnigradska Str. 19 BG-1000 SOFIA BULGARIAwww.bfunion.bg普罗夫迪夫队PFC Botev PlovdivBulevard Iztotchev 10 BG - 4000 PLOVDIV BULGARIA/clubs/botev瓦尔纳队PFC Cherno More VarnaNikola Vaptzarov Street 9 BG - 9000 VARNA BULGARIA/clubs/chernomore布鲁各斯队PFC Chernomorets BurgasChernomorets Stadium BG - 8000 BURGAS BULGARIA/clubs/chernomorec索非亚队PFC CSKA SofiaDragan Tzankov Boulevard 3 BG - 1000 SOFIA BULGARIAwww.cska.bg多布鲁扎队PFC Dobrudzha Dobrich25 Septemvri Bulevard 10 BG - 9300 DOBRICH BULGARIA里特斯队PFC Litex LovechPO Box 75 Targovska Street 12 BG - 5500 LOVECH BULGARIAwww.fclovech.bg普罗夫迪夫队PFC Lokomotiv PlovdivLokomotiv Stadium Lauta District BG - 4000 PLOVDIV BULGARIA/clubs/lokomotivlokomotivpd@罗克莫迪PFC Lokomotiv SofiaRojen Boulevard 23 BG - 1220 SOFIABULGARIA/clubs/loko_sf都普尼扎PFC Marek DupnitzaSamoransko chausse 9 BG - 2600 DUPNITZABULGARIA那夫特克PFC Naftex BurgasPO Box 42 Neftochimik Stadium JK Lazur BG - 8000 BURGAS BULGARIA/clubs/neftohimik斯拉维亚PFC Slavia SofiaKoloman Street 1 BG - 1618 SOFIABULGARIA/clubs/slavia瓦尔纳PFC Spartak VarnaSelioglu Street 39 BG - 9000 VARNA BULGARIA/clubs/spartakvarnaspartak@netel.bg1、比利时足协Belgian Football Association/Ave houba de Strooper 145,BE-1020 BRUXELLES/ BELGIANurbsfa.kbvb@2、安德莱赫特RSC Anderlecht/Avenue Thm Verbeeck 2 BE-1070 BRUXELLES/ BELGIANsecretariat@rsca.be3、根特KAA Gent/Bruiloftstraat 42 BE-9050 GENTBRUGGE/ BELGIANadmin@kaagent.be4安特威浦R. Antwerp FC/Oude Bosuilbaan 54A,BE-2100 DEURNE/ BELGIANrantwerpfc@pandora.be5、巴尔人KSK Beveren/Klapperstraat 151bis,BE-9120 BEVERENWAAS/ BELGIANinfo@kskbeveren.be6、。
Journal of Environmental Management
Journal of EnvironmentalManagementVol. 40, No. 4, April 1994ISSN: 0301-4797EISSN: 1095-8630SELECT:Al l I ssuesTable of Contents•Article(PDF)The Use of Classified Landsat-5 Thematic Mapper Imagery in the Characterization of Landscape Composition: a Case Study in Northern Englandpp. 357-377 (doi:10.1006/jema.1994.1028)A. J. Cherrill, A. Lane, R. M. FullerCentre for Land Use and Water Resources Research, The University, Newcastle upon Tyne, NE1 7RU, U.K., Institute of Terrestrial Ecology, Merlewood Research Centre, Grange over Sands, Cumbria, LA11 6JU, U.K. and Institute of Terrestrial Ecology, Monks Wood, Abbots Ripton, Huntingdon, Cambs, PE17 2LS, U.K.AbstractEarth-orbiting remote-sensing satellites are becoming increasingly used as sources of land cover data in land use planning and resource inventory. The present study compares land cover data derived from a maximum-likelihood classification of spectral reflectance data from the Landsat-5 Thematic Mapper (TM)sensor with that obtained by field survey of a sample of169 1-km2 grid squares in northern England.Selection of grid squares was stratified within classes of an environmental landscape classification. Landscapes included in the study ranged from coastal and urban, through pastoral and arable, to upland forestry, bogs and moorland. The land cover composition of Landsat and field cover maps was compared at the 1-km grid-square resolution. Results were interpreted with the aid of an a priori comparison of the definitions of the cover types recognized in the two survey methods.The study demonstrates that classified TM data can provide accurate estimates of the land cover composition of1-km squares. Differences between the cover maps derived from Landsat and ground survey often reflected the subjectivity of cover type definitions, although mis-classification of pixels falling on complex boundaries and linear features wasnoted. The use of remotely-sensed data in land use research is discussed in light of the results and it is concluded that the Landsat cover classification tested in the present study has great potential in the fields of land use planning and environmental monitoring. Copyright1994, 1999 Academic PressKeywords: Landsat, Thematic Mapper, cover classifications, cover definitions, ground survey。
英国2023入境卡中英文对照
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德甲足球俱乐部球队地址
德国足协DFBOtto-Schneisse.660528 Frankfurt/Main Germany纽伦堡FC Nurnebrg ValznerwiherstarBe.200 90480 Nurnberg Germany勒沃库森Bayer 04 Leverkusen BismarkstraBe 122-124 51373 Leverkusen Germany亚琛Alemannia Aachen Sonnenweg 1152070 AachenGermanySC Freiburg Schwarzwaldstr.193 79117 FreiburgGermany波鸿Vfl Bochum(Auer Postfach 10282244728 BochumGermany多特蒙德Borussia Dortmund Rheinlanddamm 207 - 209 44137 Dortmund Germany温特哈兴UnterhahcingAm Sportpark 182008 UnterhachingGermany菲尔特Greuther FurhtLaubenweg 6090765 FurthGermany奥厄FC Erzgebirge AuePostfach 130408273 AueGermany柏林赫塔Hertha BSC BerlinHanns-Braun-StraBe, Friesenhaus 2 14053 BerlinGermany汉诺威96Hannover 96Artuhr-Menge-Ufer 530169 HannoverGermany沙尔克FC Schalke 04Ernst-Kuzorra Weg 145891 GelsenkirchenGermany汉堡Hamurger SV Autogrammkartenstelle Sylvesterallee 722525 HamburgGermany门兴格拉德巴赫Borussia Monchengladbach Hennes-Weisweiler-Allee 141179 MonchengladbachGermany比勒菲尔德Arminia BielefeldMelanchthonstr. 31a33615 BielefeldGermany柏林联队1. FC Union Berlin e.V.An der Wuhlheide 26312555 BerlinGermany拜仁慕尼黑FC Bayern MunchenSaberner Str. 5181547 MunchenGermany法兰克福Eintracht FrankfurtMorfelder LandstraBe 36260528 Frankfurt am MainGermany斯图加特VFB StuttgartMercedesstra?e. 10970372 StuttgartGermany沃尔夫斯堡VFL WolfsburgIn den Allerwiesen 138446 WolfsburgGermany奥格斯堡FC AugsburgDonauworther StraBe 170, 86154 Augsburg Germany杜伊斯堡MSV DuisburgMargaretenstraBe 5 - 7, 47055 DuisburgGermany不莱梅SV Werder BremenFranz-Bohmert-StraBe 1c, 28205 BremenGermany奥芬巴赫踢球者Kickers OffenbachEngelbert Kraus, Wilhelm-Rontgen-Str. 11,63150Germany圣保利FC St. PauliAuf dem Heiligengeistfeld20359 HamburgGermany霍芬海姆TSG 1899 HoffenheimSilbergasse 4574889 Sinsheim-HoffenheimGermany马格德堡SC MagdeburgFriedrich-Ebert-Str. 6839114 MagdeburgGermanyEintracht BraunschweigHamburger Str. 21038112 BraunschweigGermany美因茨FSVMainz Martin Luther King Weg55122 MainzGermany拉姆Philipp Lahmc/o Roman GrillRathausstr. 3983734 BaldhamGermany德国前传奇巨星布雷默Andreas BrehmeFrundsbergstr. 44a82064 StraBlachGermany卡恩Oliver Kahnc/o Playce AGOsterwaldstr. 1080805 MünchenGermany诺沃特尼Nowotny,Jensc/o Human BrandsPeter-Hecker-Str. 2351519 OdenthalGermany贝肯鲍尔Franz Beckenbauer-StiftungPostfach 70022081302 MünchenGermany德国乒乓球协会Deutscher T ischtennis-BundOtto-Fleck-Schneise 12, 60528 Frankfurt 德国篮球协会Deutscher Basketball Bund Pressestelle Schwanenstra?e 6-10 58089 HagenGermany德国老球星Hansi MüllerPfarr?ckerstr. 6271336 Waiblingen/NeustadtGermany德国网球巨星贝克尔Boris Becker & Co.Sports - Marketing - SalesRuessenstr. 6CH - 6341 BaarSwitzerland德国乒乓球明星波尔T imo Boll,Erlenring 16 ,61118 Bad VilbelGermany德国老球星布莱特纳Paul Breitner,Eichendorffstr. 10 ,85649 BrunnthalGermany74年冠军队成员Bernd HolzenbeinAm Forsthaus Gravenbruch 52, 63263 Neu-Isenburg Germany德国老球星Manfred Kaltz,Dorotheenstr. 139,22299 HamburgGermany德国老球星Dieter BurdenskiFasanenweg 30,28816 StuhrGermany赫鲁贝什Horst HrubeschKleinellenberg 2 ,29562 SuhlendorfGermany托尼舒马赫Harald SchumacherSurther Hauptstrasse 196 ,50999 KolnGermany奥根塔勒Klaus Augenthaler,Eichhornchenweg 18,85598 Baldham Germany埃芬博格Stefan EffenbergBWM Communications GmbHGrimmstr. 4 ,80336 MünchenGermany萨默尔Matthias Sammerc/o Deutscher Fu?ball-Bund,Otto-Fleck-Schneise 6,60492 Frankfurt/Germany施魏因斯泰格Sebastian SchweinsteigerSport SchweinsteigerRosenheimer Str. 1083080 OberaudorfDeutschland迈耶Sepp MaierLindenstraBe 12, 85664 HohenlindenGermany德国总统伍尔夫Christian WulffBundespr?sidialamtSpreeweg 110557 BerlinGermanyAc米兰AC MilanVia T urati.320121 MilanItaly国际米兰Inter MilanVia Durini 2420122 MilanoItaly罗马AS RomaFrancesco T ottiVia di T rigoria km 3.600I-00128 RomaItaly尤文图斯Juventus T urinCorso Galileo Ferraris 3210128 T orinoItaly弗洛伦撒AC Fiorentina,Viale Manfredo Fanti 4, I-50137 Firenze Italy切尔西Chelsea FCStamford Bridge, Fulham Road,GB - London S W 61 H SEnglnad纽卡斯尔Newcastle UnitedSt Jam es’ parkNewcastle-Upon-T yneNE1 4STEngland曼联Manchester UnitedSir Matt Busby WayM16 0RA ManchesterEngland西汉姆West Ham United Football Club,Boleyn Ground, Green Street, Upton Park, London, E13 9AZ England巴塞罗那FC BarcelonaAv. Aristides Maillol s/n08028 BarcelonaSpain瓦伦西亚FC ValenciaCalle Pintor Monleón 446023 ValenciaSpain费耶诺德Feyenoord Rotterdam ,Van Zandvlietplein 3,Postbus 9635 , 3007 AP Rotterdam Holland阿贾克斯Ajax AmsterdamPostbus 229441100 DK AmsterdamNiederlande维也纳快速Rapid WienPostfach 2001140 WienAutstria萨尔茨堡红牛Red Bull SalzburgStadionstr. 1/3A-5071 Wals-SiezenheimAustria里昂Olympique Lyon 350Avenue Jean-Jaures69007 Lyon成龙Jackie Chanc/o Jackie & Willie Productions Ltd.145 Waterloo RoadKowloon, Hong KongChinaF1前传奇巨星Niki LaudaNicki Luftfahrt GmbHOfficepark 1/ T op B03A- 1300 Wien - FlughafenAustria博尔特Usain Boltc/o PACE Sports Management6 The Causeway, T eddington, Middlesex, T W 1 1 0 H E, England英国网球明星穆雷Andy Murrayc/o ACE Group21 Quayside LodgeWilliam Morris WayLondonSW6 2UZUK塞尔维亚网球明星伊万诺维奇Ana Ivanovicc/o DH-Management AGHoleestr. 82CH - 4054 BaselSwitzerlandF1车手苏蒂尔Adrian Sutilc/o cmg Client Management GroupKaiser-Wilhelm-Ring 4140545 Düsseldorf克里斯特尔斯Kim Clijstersc/o GolazoSchoebroekstraat 8, B-3583 Paal-Beringen, Belgien。
Newcastle upon Tyne, NE1 7RU, UK. A Visual Language for Parallel, Object-Oriented Programmi
School of Computing Science,University of Newcastle upon TyneA Visual Language for Parallel, Object-Oriented Programming P.A.Lee,M.D.Hamilton,S.ParastatidisTechnical Report SeriesCS-TR-826February2004Copyright c 2004University of Newcastle upon TynePublished by the University of Newcastle upon Tyne, School of Computing Science,Claremont Tower,Claremont Road, Newcastle upon Tyne,NE17RU,UK.A Visual Language for Parallel, Object-Oriented ProgrammingP.A. Lee, M.D. Hamilton, S. ParastatidisSchool of Computing Science, University of Newcastle upon TyneNewcastle upon Tyne, NE1 7RU, UKAbstractThis paper introduces the HiPPO (High Performance Par-allel Object-oriented) language. HiPPO is unique in its combination of a visual syntax with an object-oriented computation model based on the flow of object references. The paper describes some of the notations used in the lan-guage with particular emphasis on the features provided to support the exploitation of parallelism. Aspects of the run-time support for HiPPO programs will also be described. INTRODUCTIONOver many years, research has addressed the problems of designing and implementing software systems. Supporting tools have been developed, but the increasing demands of applications have kept the need for new tools and para-digms ahead of their supply. The object-oriented paradigm is often exploited by software engineers, and is supported extensively in design tools, database systems and pro-gramming languages. Object-orientation is seen as a highly beneficial engineering methodology, and interest in it con-tinues apace even in high-performance applications where optimal efficiency is often preferred at the expense of over-all software engineering [1, 2].While object-orientation can significantly help the software engineer in some areas, support for exploiting parallelism remains relatively traditional in that the programmer is generally left to explicitly exploit and manage parallel threads of control. Object-oriented libraries and patterns can help [3], but designing and implementing parallel sys-tems remains a complex task. Part of a solution may lie in the provision of graphical or visual design systems and languages, which seem particularly appropriate for parallel software systems since they permit the user to break away from textual (sequential) representations and to construct a more parallel solution to a problem using the two (or more) dimensions of a visual space. Ideally, the graphical lan-guage will naturally support the expression of parallel solu-tions to a problem, while the semantics implicitly handle many of the aspects of exploiting parallelism that hitherto have had to be dealt with explicitly by the programmer. This paper introduces the HiPPO (High Performance Paral-lel Object-oriented) visual language being developed at Newcastle. Following on from earlier PhD research [4] HiPPO is unique in its combination of a visual syntax with an object-oriented computation model based on the flow of object references. It is not a research objective in HiPPO to (re-)invent object-oriented features. So, classes, inheri-tance, dynamic binding, etc. in HiPPO are not novel, and are not discussed further. Our interests are in the visual notations for expressing parallel object-oriented computa-tions, and in the flow-of-object-references model. The next sections describe aspects of the HiPPO notation, with par-ticular emphasis on the support provided for specifying potential parallelism, and the features provided by the Inte-grated Development Environment (IDE) that is an integral part of the HiPPO system.HIPPO IDEThe HiPPO IDE comprises two main parts:•the class designer that supports the declaration of new classes: their interface, method type signatures, and thetypes of the objects that will comprise the state of in-stances of the class (these objects are termed DataMembers in HiPPO and are always considered pri-vate); and•the graph designer that allows the implementation of the methods to be specified visually using the HiPPOnotation.Figure 1 (at the end of this paper) is a screenshot of the class designer, showing part of the definition of the Builtin Containers namespace together with part of the definition ofa user-defined Math namespace containing a Matrix class.This example class provides the abstraction of a two-dimensional array containing floating point numbers, and supports a number of methods including Matrix (the con-structor), initElements, and multiply. Some input and output arguments for the methods are also shown. For example, multiply takes an input argument matrixB and generates an output argument resultMatrix. All of the arguments are fully typed, with the Item properties window in Figure 1 show-ing these details for the matrixB input argument for multiply.In the class designer window, data members are labelled with a D – so, every instance of Matrix has data members, actualRows, numRows and numColumns. The object actual-Rows is a 1-d array of 1-d arrays of numbers that comprise the rows of the matrix.The window pane on the left-hand side of Figure 1 shows the set of template icons that can be dragged-and-dropped onto a graph implementation to construct the visual imple-mentations of the methods, an example of which is given below. Microsoft Visio® has been used as the basis for the IDE with Visual Basic for Applications and C# additions that implement the HiPPO features.HIPPO EXAMPLETo set the scene for the descriptions that follow, Figure 2 shows the HiPPO graph for an example implementation of the multiply method of class Matrix. Briefly, this method performs the equivalent of result = A.multiply(B) by decom-posing the current matrix object and the result matrix into1their corresponding rows, and then in parallel multiplying each row by all of the columns in the second matrix to form a row of answers in the result matrix (this latter part of the computation is a sub-graph that is not shown in Figure 2).A number of features (e.g. checking the sizes of the matri-ces involved for compatibility) have been omitted to sim-plify the example. The execution semantics of this examplewill be explained below.Figure 2. HiPPO Graph for multiply MethodTHE HIPPO VISUAL LANGUAGE: OVERVIEWThe HiPPO language, like several others, is graph-based, with boxes representing parts of a computation connected by arcs that control the computation in some fashion. Be-yond this simple framework, however, there are many de-sign decisions that face the visual language designer [5]. One of the main decisions concerns the arcs, and what they represent and carry. In the HeNCE visual language [6, 7], arcs carry control-flow signals that enable the execution of computations. In CODE [8, 9], arcs carry data values and the availability of data triggers computations (a data-flow model). Since a data-flow model was felt to provide a more natural model for implicit parallelism, it was chosen as the primary model for HiPPO arcs. However, HiPPO also pro-vides control-flow arcs for specifying additional sequenc-ing constraints on computations, although these are only expected to be of limited use (e.g. to sequence two printing operations correctly).Although HiPPO adopts a data-flow model, the model is different to many other data-flow languages in that it is references to objects (termed object handles) that flow through arcs rather than copies of data values. The HiPPOprogrammer operates in a shared object environment, where everything is an object, and all of the objects being manipulated are potentially available to all parts of the computation.The choice of a shared object-oriented computation model has a number of ramifications both for the visual language notation and for the run-time support. This section will concentrate on the language issues, and a later section will briefly address the run-time issues. The adoption of a shar-ing model (versus a value copying or message-passing model) has the standard advantages and disadvantages: the sharing paradigm is more familiar and easier to use, but requires care to be taken over the synchronized use of shared entities to avoid unintended side-effects due to con-current accesses from parallel threads, while the distrib-uted/copying paradigm removes the need for detailed syn-chronization features and the possibility of inter-thread interference, but is less familiar and adds complexity and overhead from the need to copy and distribute data for processing, and to merge results together subsequently. In HiPPO many of the low-level synchronization requirements of the sharing model are delegated to the run-time system and do not require explicit manipulation by the program-mer. (The run-time system is also responsible for imple-menting the semantics of shared objects when executing ona distributed-memory computing platform, as will be dis-cussed subsequently.)In the multiply example, the three matrices involved can be shared across the parallel computations. All that needs to be communicated are object handles, rather than (larger) sets of data values comprising all or parts of the matrices being manipulated. The synchronization of accesses to the shared matrix objects or their constituent data members is not specified by the programmer but is handled by the run-time system. Moreover, the result matrix can be updated directly with the results of the multiplication, rather than requiring an additional stage to be specified by the programmer con-cerned with receiving and merging separate sets of results.It is recognized that an experienced programmer can pro-vide additional information about objects and their use that can be used to optimize performance. One example is cate-gorising read versus write accesses, which can be used to optimize object locking strategies. HiPPO permits the user to provide such information – the Item Properties window in Figure 1 shows this for the input argument matrixB which is specified as being read-only. In addition, the multiply method itself has also been specified as being read-only since it does not change the state of the matrix object to which it is being applied. With such information, the com-piler and run-time system can optimise the locking strate-gies applied implicitly to the shared objects, and could even choose to replicate objects if this could give performance advantages (for instance, if the parallel platform was a dis-tributed memory system).HiPPO also allows the user to indicate when objects being used as arguments can be cloned (controlled by the selec-23tion boxes illustrated in the Item properties window in Fig-ure 1). Cloning essentially provides an object-copying mechanism, which can be used by the programmer to ex-plicitly generate new objects that can be used in parallel with the original object. Cloning information can also be used for optimization purposes – for example, to pass the value of an object of type integer rather than an object han-dle. Once made, all of these choices are indicated graphi-cally in the HiPPO implementation graphs via different icon borders and colours, although the exact notation is not important for this paper.The boxes on the graphs specify the computation parts of the solution. In HeNCE and CODE, the boxes contain tra-ditional procedural statements/expressions (e.g. in C or Fortran). However, in HiPPO these computations represent the invocation of a method on an object. Other boxes in HiPPO have more special-purpose roles, such as represent-ing the creation of new objects, and conditional, iterative and parallel computations. These features are described in the following sections.Object Invocation NotationObject-oriented computations are based on the notion of applying methods/operations to identified objects. Thus a visual notation has to enable the object to which a method is being applied (termed the controlling object) to be dis-tinguished from any objects that are arguments to the method call. In HiPPO this distinction is achieved by hav-ing attach points at the left-hand (or right-hand) end of a method-call box to represent the controlling object. The arc that connects to this attach point will carry the controlling object handle at run-time. Arcs carrying the object handles that are arguments intersect the top horizontal part of the box, while results produced by methods leave via the bot-tom of the box. Examples are shown in Figure 3, where the method being applied (multiply , decrement and notEqual ) has been selected via the IDE when the method call icon is dragged onto a graph, and an object handle of the appropri-ate type is the controlling object.Figure 3. Example Method InvocationsWith the form of attach point shown in the graph on the left-hand side of Figure 3, the HiPPO semantics for the attached arc are that the object handle is broadcast down the arc to invoke parallel computations. In this example thetwo multiply methods could be invoked in parallel. A method-call box with this form of attach point is referred to as a non-blocking method call . This is another HiPPO fea-ture that supports the specification of parallelism. The user may select a different form of attach point that changes the semantics to transmit the controlling handle down the arc only when the computation in the box has completed – a so-called blocking method call , where the attach point has a break in the middle of the icon. An example is given on the right-hand side of Figure 3, where the method call decre-ment is applied to an Integer object, and the handle for that object will not flow to the notEquals box until that method invocation has completed.Computation Firing RuleThe firing rule in HiPPO is that a computation such as a method call will be enabled for execution when object han-dles are available on the attach point and on all of the input arguments. It is the flow of object handles that primarily determines the parallelism that is available at run-time, rather than requiring the programmer to explicitly control parallelism, the standard advantage of a data-flow model of computation. Thus, when the graph in Figure 2 is executed, there are a number of computations that could be fired in parallel (e.g. those labelled DM Get , the meaning of which is explained below).Object Handle Sources and SinksInput and output formal and actual arguments in textual languages provide a means for linking the actual objects in a calling program with the formal object names used inside the called method. In addition, methods also require access to the objects that constitute the state (the data members). HiPPO provides icons for specifying this behaviour.When the graph representing a method is being defined, the IDE automatically generates “source” boxes representing the input argument parameters – that labelled matrixB in Figure 2 is an example. The IDE also introduces “sink” boxes as the destination for arcs containing result handles (see Figure 2). Result object handles will not flow back to the enclosing graph until all of the activities in the graph have completed. It is the responsibility of the compiler and run-time system to achieve this behaviour.A special graph node called this can be used on a graph to introduce a handle for the current object (i.e. the object to which the method is being applied). To provide access to the data member objects, a special-purpose node called DataMember Get can be used with the “this object” arc as its controlling object flowing to the attach point, and the IDE permits the user to select which data member object is re-quired, using an interface similar to that shown in Figure 1. The IDE provides a version of DataMember Get without the attach point which provides direct access to the data mem-bers of the current object, and thus simplifies a graph by removing the need for the this node and connecting arcs. Figure 2 demonstrates both forms of the DataMember Get node (labelled DM Get ). When executed, that without the attach point generates a handle for the numRows data mem-ber of the Matrix object to which multiply is being applied. The DM Get node with the attach point is used to get a han-dle for the numColumns data member of the argument ma-trixB, access to which is permitted since that argument is an instance of the same class as the multiply method.Corresponding to the DataMember Get nodes there are DataMember Set nodes (with and without the attach point) which can be used to specify the storing of an object handle in the identified data member object. These set nodes are most commonly used in constructors to initialize the data members.Another source of object handles comes from the genera-tion of new objects. HiPPO provides New nodes for this purpose, and when the New template is dragged onto a graph the IDE permits the user to select the class and par-ticular constructor required. Any arguments required by the constructor appear on the graph as described earlier for method calls. An example of the use of New is shown in Figure 2 for the creation of a new instance of Matrix to hold the results of the multiply.HiPPO permits copies of object handles to be generated using the Copy Handle node, an example of which is shown in Figure 2 directly under the input parameter box. Visual simplification of arc flows can be achieved by combining copied handles with Break/Continue nodes, examples of which also appear in Figure 2 (labelled MatB).The final source of object handles in HiPPO is provided by Literal nodes. These nodes correspond to the specification of literal number and string values in traditional languages. The example in Figure 3 will generate an integer object initialised to the value 53 for use in the comparison opera-tor.Special-Purpose NodesWhile the method call node is the primary source of com-putation in a HiPPO graph, a number of special purpose nodes provide graphical support for additional control over computations. These nodes support:•Conditional execution•Parallel computations; and•Repeated (iterative) computation.Conditional ExecutionVisual languages require notational support to specify the conditional execution of graphs. In HiPPO this requirement is supported through the Condition node. When the Condi-tion node template is dragged onto a graph, the IDE auto-matically creates two sub-graphs. One of these is associated with the ‘true’ execution path, and the other with ‘false’. The controlling object for instances of this node is a Boo-lean, and when a condition node fires at run-time, the value of this Boolean determines which of these two sub-graphs is executed. Arguments and results can be defined as part of the condition node – these are created as part of the sub-graphs by the IDE.Parallel Computations: Decomposers and For Each NodeA common pattern in parallel software is the need to applya computation to a set of data values of the same type(commonly referred to as data parallelism or parameter spreading). Typical examples include applying some com-putation to all of the elements in an array, or all of the ele-ments in a list, or applying some methods to a stream of objects being returned from a query to an object database.Such examples are obvious sources of parallelism, and hence a useful feature to be supported in a parallel design system. Such support requires:• A means for specifying the computations that occur (in parallel) – in HiPPO, this is achieved using the FOREACH node.• A means for generating the independent object handles that these parallel computations can operate on - herethe concept of a decomposer object is introduced.Although similar in its functionality to the foreach state-ment provided in other object-oriented languages (e.g. C#[10]) and to the support for iterators in other languages,HiPPO differs in that, firstly, it allows the user to define multiple ways of decomposing an object, and secondly the computations within the body of the FOR EACH can be exe-cuted in parallel. (The term decomposer was chosen to dif-ferentiate HiPPO’s parallel activity from the sequential activity associated with iterators.)To demonstrate these facilities, the Matrix example imple-ments a parallelisation and decomposition strategy which permits a row from A to be multiplied by matrix B to forma row of the result matrix, and for these computations to bepotentially executed in parallel. The use of the FOR EACH node and decomposers is as follows.Any class that can be decomposed has to provide a special method that returns an instance of a class that implements the built-in IDecomposer interface. This interface requires three member functions to be available, which are invoked automatically at run-time to: initialise the decomposer (re-set); generate the handle for the next object that can be op-erated on (current); and to move to the next object and to return a Boolean indicating whether the end has been reached (moveNext).Thus, the first step for a user is to select a decomposer method. The IDE handles this selection by recognising that only special kinds of methods, labelled as decomposers with a “musical note” icon, can be selected for this node.Figure 1 shows that the Matrix class has a decomposer named decomposerForMult that has been defined specifi-cally for the multiply method. The result of the selection is demonstrated in Figure 2 by the decomposeForMult box, which returns as a result a decomposer-object handle for an instance of a class DecomposeForMult private to the Matrix class that provides the decomposition specific to the im-plementation of Matrix. These decomposer classes do not have to be private – this is just a characteristic of this ex-ample.4When a user then drags an instance of the FOR EACH tem-plate onto a graph, this may have an attach point, a prede-fined first argument, optional other arguments, and an asso-ciated sub-graph that implements the computation that can be executed in parallel. The attach point provides any nec-essary synchronisation dependency between the FOR EACH and the rest of the graph, as usual. The handle for the de-composer-object has to be attached to the first argument on the FOR EACH and is used at run-time to generate a stream of objects each of which can be processed in parallel (po-tentially) by the body of the FOR EACH. The IDE arranges for the generated object handle, together with any argu-ments that are specified as part of the FOR EACH node, to appear on the sub-graph as arguments, the computations on which can then be defined.The FOR EACH example in the multiply graph in Figure 2 shows matrixB as such an argument, while Figure 4 below shows the sub-graph computation. Essentially, this sub-graph receives the object handle generated from the de-composer, which in the matrix example is a two-element array containing handles for two 1-d array objects, the first of which is the row from the source (A) matrix and the sec-ond being the handle for the corresponding row of the re-sult matrix. Extracting these two 1-d object handles, the sub-graph computation then invokes a method that imple-ments matrix * vector => vector. The advantage of the shared object model in HiPPO is demonstrated here by the fact that this sub-graph computation is updating a row of the result matrix in place, and complexities arising from the need to identify rows and columns in the decomposition of the source matrix and the re-composition of results into theresult matrix do not arise.Figure 4. Multiply Sub-GraphUsing this structure permits a user to define multiple forms of decomposition for any class. Other decomposers for Ma-trix could be provided to generate the sequence of 1-d ar-rays that comprise the rows, or columns, or even a stream of numbers that are the elements in the matrix. Having the ability to flexibly define decompositions of objects, espe-cially for container objects, is a vital feature in a parallel object-oriented language.Iterative Computations: Loop NodeA loop node is provided in HiPPO to represent sequentialiterative computations. The node can take any number of arguments and its implementation is defined using 4 sub- graphs:1.Pre-loop: This graph is executed once (before the firstexecution of the iteration graph). Its main use is to ini-tialise values and create objects which control the itera-tion and termination of the loop.2.Condition: This graph is executed before the iterationgraph and dictates when the loop terminates. It returnsa single Boolean result. If that result is true, the itera-tion graph can be executed. Otherwise, the loop hascompleted.3.Iteration: This graph represents the body of the loop.4.Post-Iteration: This graph is executed after each exe-cution of the iteration graph. Its main use is to updatethe objects controlling the loop.Figure 5 demonstrates the use of the loop node from part of the initElements method of Matrix. Although not shown, this method uses a decomposer to generate handles for the rows of a matrix and a FOR EACH node to generate instances of the computations shown in Figure 5(a). The iteration graph that is the body of this loop is given in Figure 5(b), where loopCounter is the loop control object that was created bythe pre-loop graph (not shown).Figure 5. (a) Graph for initialising a row, (b) Sub-graphfor loop bodyRUN-TIME SUPPORT ISSUESNIP is a run-time system designed and developed at the University of Newcastle upon Tyne [11-14] that provides an execution environment for implicitly parallel, object-oriented programming languages like HiPPO. NIP offers a shared-object memory space, and run-time constructs for the identification of potentially parallel computations that language compilers can use.NIP dynamically manages the degree of parallelism ex-posed by applications to efficiently utilise the computa-tional resources offered by the underlying hardware plat-form which may be shared- or distributed-memory based.NIP also takes responsibility for the concurrency and cach-5ing related issues that may arise through the use of the shared-object space.By targeting the NIP execution model, the HiPPO compiler is freed from having to produce code that explicitly man-ages parallelism and deals with architecture related issues. NIP TaskletThe NIP run-time system employs lazy task creation and dynamic load-balancing techniques to utilise the available computational resources. The NIP lazy task creation tech-nique is based around the Tasklet construct. A Tasklet represents one or more potentially parallel pieces of com-putation, which may vary from a single method call to a for-each computation. The language system can use Task-lets in order to expose parallelism, while the responsibility of the NIP run-time system is to convert those Tasklets into actual parallel tasks. It is computationally cheaper to ex-pose parallelism using Tasklets rather than actually create parallel tasks (e.g. threads) [13]. Furthermore, applications can expose a very high degree of parallelism without hav-ing to worry about task switching costs, allocation of com-putational resources, or any other task-management costs. The computational costs of actually creating a parallel task will only be incurred when resources become available. When computational resources become available anywhere on the parallel system, a Tasklet is located and a new task is created from it. If the results from the potentially parallel computations associated with a Tasklet are required, a syn-chronisation point is introduced. When such a synchronisa-tion point is met during the execution flow of a task, com-putations associated with the Tasklet that have not been converted to tasks are executed in-line (i.e. in the context of the task that met the synchronisation point).NIP Object-based Distributed Shared MemorySince NIP offers a shared-object space execution environ-ment, it is necessary to implement an abstraction layer to be used on distributed-memory multiprocessor architectures. The NIP Distributed Shared Memory (NIPDSM) is an all-in-software, virtual, shared-object memory system. NIPDSM makes use of advanced, dynamic caching tech-niques and a relaxed memory consistency model with se-quential consistency semantics to provide improved per-formance [11].Given that a relaxed memory consistency model is used, NIPDSM requires assistance from the HiPPO compiler in order to maintain the consistency of the objects’ state. This is achieved through read lock, write lock, and unlock direc-tives that the HiPPO compiler must produce whenever an object is accessed. The NIPDSM locking mechanism is integrated with the caching and entry consistency mecha-nisms for better performance [11].HiPPO to NIPThe lifecycle of a HiPPO application includes the design process (HiPPO class designer), the implementation proc-ess (HiPPO graph designer), the compilation process (HiPPO compiler), and the execution process (NIP run-time). The HiPPO compiler is responsible for converting the HiPPO graphs to NIP-aware code. XML is extensively used by all the tools in the HiPPO suite (Figure 6).The current implementation of the HiPPO compiler pro-duces C++ code with NIP directives. It does so by parsing the XML file created by the HiPPO IDE, which represents the graphs and type information of an application. The HiPPO compiler traverses the application graph and creates Tasklets and NIPDSM objects.Creating Tasklets from GraphsAll of the computational graph nodes attached to an arc can be exposed as NIP Tasklets. Additionally, as the HiPPO compiler traverses the application graph, it may create new NIP Tasklets according to the following rules:• A copy handle graph node is encountered. All of the computational graph nodes attached to the new arcs can be potentially executed in parallel with each other.In the example of Figure 7, the arc carrying the handle to matrixA object is split into two arcs suggesting that the two multiply methods can be executed in parallel.As a result, two new Tasklets are created for each method call.Taslket tasklet1 =new Tasklet(multiply, matrixA, matrixB) Tasklet tasklet2 =new Tasklet(multiply, matrixA, matrixB) ... // Some other computationtasklet1.synchronise()tasklet2.synchronise()Figure 7. Tasklets from a copy handleFigure 6. HiPPO Application Lifecycle6。
《拿破仑英文介绍》课件
1808年7月
拿破仑任命自己的哥哥约 瑟夫为西班牙国王,将自 己的妹夫缪拉任命为那不 勒斯国王。
1810年4月
拿破仑与奥地利皇帝弗朗 茨二世的女儿玛丽·路易丝 结婚,成为了欧洲最强大 的帝王之一。
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Napoleon's Fall and Influence
The battles of Austerlitz, Waterloo, and Borodino were some of the most famous battles of the Napoleonic Wars and marked key turning points in the confls Legacy
The Napoleonic Code
法律与秩序
Napoleon's Napoleonic Code provided a legal framework that established order and stability in France and its conquered territories.
01
1798-1801
Napoleon led an invasion of Egypt, seeking to expand French
influence in the region and counter British influence in the
Mediterranean.
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Key Events
Historians have debated Napoleon's legacy, with some viewing him as a great military leader and others criticizing his authoritarianism.
ReaxFF_A_Reactive_Force_Field_for_Hydrocarbons
ReaxFF:A Reactive Force Field for HydrocarbonsAdri C.T.van Duin,†,|Siddharth Dasgupta,‡Francois Lorant,§and William A.Goddard III*,‡Department of Fossil Fuels and En V ironmental Geochemistry,Drummond Building,Uni V ersity of Newcastle,Newcastle upon Tyne NE17RU,United Kingdom,Materials and Process Simulation Center,Beckman Institute(139-74),Di V ision of Chemistry and Chemical Engineering,California Institute of Technology,Pasadena,California91125,and Institut Franc¸ais du Pe`trole,Geology and Geochemistry Research Di V ision,1-4A V enuede Bois-Preau,92852Rueil-Malmaison,FranceRecei V ed:December4,2000;In Final Form:March30,2001To make practical the molecular dynamics simulation of large scale reactive chemical systems(1000s ofatoms),we developed ReaxFF,a force field for reactive systems.ReaxFF uses a general relationship betweenbond distance and bond order on one hand and between bond order and bond energy on the other hand thatleads to proper dissociation of bonds to separated atoms.Other valence terms present in the force field(angleand torsion)are defined in terms of the same bond orders so that all these terms go to zero smoothly as bondsbreak.In addition,ReaxFF has Coulomb and Morse(van der Waals)potentials to describe nonbond interactionsbetween all atoms(no exclusions).These nonbond interactions are shielded at short range so that the Coulomband van der Waals interactions become constant as R ij f0.We report here the ReaxFF for hydrocarbons.The parameters were derived from quantum chemical calculations on bond dissociation and reactions of smallmolecules plus heat of formation and geometry data for a number of stable hydrocarbon compounds.We findthat the ReaxFF provides a good description of these data.Generally,the results are of an accuracy similaror better than PM3,while ReaxFF is about100times faster.In turn,the PM3is about100times faster thanthe QC calculations.Thus,with ReaxFF we hope to be able to study complex reactions in hydrocarbons.1.IntroductionThe accuracy and speed of modern quantum chemistry(QC) methods allow the geometries,energies,and vibrational energies to be predicted quite accurately for small molecules.However, QC is not yet practical for studying the dynamic properties of larger molecules and solids.Consequently,it is useful to have accurate force fields(FF)to quickly evaluate the forces and other dynamical properties such as the effects of mechanical shock waves or diffusion of small molecules in polymer and mesoporous zeolites.Indeed,for hydrocarbons a number of FF, particularly MM3,1-3provide accurate predictions of geometries, conformational energy differences,and heats of formation. Generic FF such as DREIDING4and UFF5allow predictions for broad classes of compounds,particularly when coupled to charge equilibration6(Q Eq)or other methods for predicting charges.However,in general,these force fields do not describe chemical reactivity.An exception is the Brenner potential,7 which leads to accurate geometries for ground states of hydrocarbons,but is formulated in such a way that it can describe bond breaking.Unfortunately,the Brenner formalism does not include the van der Waals and Coulomb interactions that are very important in predicting the structures and properties of many systems.In addition,the actual potential curves for bond breaking and reactions are often quite poorly described with the Brenner potential.Generalizations of the Brenner FF have included such nonbonded forces,8but without repairing the fundamental problems in the shapes of the dissociation and reactive potential curves.Two other bond-order-dependent force field methods are noteworthy.The Bond Energy Bond Order(BEBO)method was proposed by Johnston9,10based on Pauling’s relation between bond length and bond order.11The fundamental assumption behind this method is that the path of lowest energy on going from reactant to product is one that conserves total bond order. Originally used for the H+H2reaction surface,it is a very good approximation to more complicated empirical forms such as LEPS surface.12-13While it has recently been extended to more complex reactions,14-15it remains mainly useful for H atom transfer reactions in a linear collision geometry.The VALBOND method formulated by Landis and colleagues is based on the strength functions of hybrid orbitals.The motivation comes from the need to fit large distortions in the softer angle terms of valence force fields,as well as describing multiple equilibrium angles in transition metal complexes(e.g., the90°and180°angles in square planar complexes).Assuming that different ligand atoms,lone pairs,and radical electrons have implicit preference for p-character,VALBOND uses Lewis structure-based allocations to assign hybridizations and the geometries are obtained by minimizing defects in the hybrid orbitals.For a simple force field,it does remarkably well on structures and vibrational frequencies for a wide range of small molecules and transition metal complexes.16-18These methods, however,do not fully address the need to have full chemistry of the breaking and forming bonds,in addition to a proper description of the fully bonded equilibrium geometry of complex molecules.In this paper,we develop a general bond-order-dependent potential in which the van der Waals and Coulomb forces are*Author to whom correspondence should be addressed.E-mail:wag@.†University of Newcastle.‡California Institute of Technology.§Institut Franc¸ais du Pe`trole,Geology and Geochemistry ResearchDivision.|E-mail: A.C.T.van-Duin@.9396J.Phys.Chem.A2001,105,9396-940910.1021/jp004368u CCC:$20.00©2001American Chemical SocietyPublished on Web09/22/2001included from the beginning and the dissociation and reaction curves are derived from QC calculations.In spirit it is derived from the central force concept used earlier by spectroscopists 19but abandoned because a single harmonic potential between all atom pairs was inadequate for complex molecules.We have kept the central force formalism,where all atom pairs have nonbonded interactions,because it dissociates smoothly,but add local perturbations (bond,angle,torsion,etc.)to describe the complex molecules more accurately.We have attempted to obtain accurate descriptions of quantum phenomena such as resonance,unsaturated valences in radical systems,and chemical reactions.While the current work is restricted to hydrocarbons this approach is easily extended to any molecular system of any class of compounds.In a future paper we will report on our extension to CHNO-systems.Section 2describes the general form of the reactive force field (denoted ReaxFF)and the procedure for optimizing the parameters.Section 3presents the results for a number of systems.Section 4discusses these results,and Section 5presents the conclusions.2.Force FieldSimilar to empirical nonreactive force fields,the reactive force field divides the system energy up into various partial energy contributions,as demonstrated by eq 1.The potential energy functions associated with each of these partial energy contributions are described below.Tables 1-6list the parameters used in these potential functions.2.1.Bond Order and Bond Energy.A fundamental as-sumption of ReaxFF is that the bond order BO ′i j between a pair of atoms can be obtained directly from the interatomic distance r ij as given in eq 2and plotted in Figure 1.Equation 2consists of three exponential terms:(1)the sigma bond (p bo,1and p bo,2)which is unity below ∼1.5Åbut negligible above ∼2.5Å;(2)the first pi bond (p bo,3and p b0,4)which is unity below ∼1.2Åand negligible above ∼1.75Å,and (3)the second pi bond (p bo.5and p bo,6)which is unity below ∼1.0Åand negligible above ∼1.4Å.This leads to a carbon -carbon bond with a maximum bond order of 3.For carbon -hydrogen and hydrogen -hydrogen bonds,only the sigma-bond contribution is considered,leading to a maximum bond order of 1The bond orders BO ′i j are corrected for overcoordination and for residual 1-3bond orders in valence angles using the scheme described in eqs 3a -f.While the 1-3bond order correction,described in eqs 3e and 3f,is applied to all the bonds in the molecule,the overcoordination correction (eqs 3b -d)is only applied to bonds containing two carbon atoms.The final bond orders in the molecule are obtained by multiplying the bond orders from Equation 2by the correction factors from eq 3.Figure 2shows the effects of eqs 3a -f on the bond orders in an ethane molecule in which the C -C bond length is reduced from its equilibrium values of about 1.53Åto 1.0Å.This creates overcoordination on both the carbon and the hydrogen atoms,as the sum of bond orders around all atoms exceeds their valences (4for carbon and 1for hydrogen).As Figure (2)shows,application of Equations (3a -f)removes all of the 1-3bond orders,correcting the overcoordination on the hydrogen atoms,and,in addition,corrects most of the additional overcoordinationTABLE 1:General Parametersparameter value descriptionequation λ150.0overcoordination bond order correction 3c λ215.61overcoordination bond order correction 3d λ3 5.021-3bond order correction 3e,f λ418.321-3bond order correction 3e,f λ58.321-3bond order correction 3e,f λ6-8.90overcoordination energy 6λ7 1.94undercoordination energy 7a λ8-3.47undercoordination energy 7a λ9 5.79undercoordination energy 7b λ1012.38undercoordination energy 7b λ11 1.49valence angle energy 8b λ12 1.28valence angle energy 8b λ13 6.30valence angle energy 8c λ14 2.72valence angle energy 8c λ1533.87valence angle energy 8c λ16 6.70valence angle energy 8d λ17 1.06valence angle energy 8d λ18 2.04valence angle energy 8d λ1936.0penalty energy 9a λ207.98penalty energy 9a λ210.40penalty energy 9b λ22 4.00penalty energy 9b λ23 3.17torsion energy 10b λ2410.00torsion energy 10c λ250.90torsion energy 10c λ26-1.14conjugation energy 11a λ27 2.17conjugation energy 11b λ281.69van der Waals energy12bE system )E bond +E over +E under +E val +E pen +E tors +E conj +E vdWaals +E Coulomb (1)TABLE 2:Atom Parameters As Used in Equations 2,6,7,12,13,and 14abond radiiunder/over coordinationCoulomb parameters heat increments units r o År o,πÅr o,ππÅp over kcal/molp under kcal/molηEV EV γÅI kcal/mol C 1.399 1.266 1.23652.229.47.41 4.120.69218.6H0.656-117.59.142.260.3754.3ar o (ij ))1/2[r o (i )+r o (j)].Figure 1.Interatomic distance dependency of the carbon -carbon bond order.BO ′ij )exp [p bo,1‚(r ijr o)p bo,2]+exp [p bo,3‚(r ijπr o)p bo,4]+exp [p bo,5‚(r ijππr o)p bo,6](2)ReaxFF:A Reactive Force Field for HydrocarbonsJ.Phys.Chem.A,Vol.105,No.41,20019397on the carbon atoms.Val i in eqs 3a -3f is the valency of atom i (Val i )4for carbon,Val i )1for hydrogen).∆′i is the degree of deviation of the sum of the uncorrected bond orders around an atomic centerfrom its valency Val i ,as described in eq 4.Equation 5is used to calculate the bond energies from the corrected bond order BO ij .2.2.Atom Under-/Overcoordination.From the valencetheory of bonding we know that the total bond order of C should not exceed 4and that of H should not exceed 1,except in hypervalent cases.However,as Figure 2shows,even after correction of the original bond orders BO ′i j a degree of overcoordination may remain in the molecule.To handle this we have added an overcoordination penalty term to the force field.2.2.1.O V er-Coordination.For an overcoordinated atom (∆i >0),eq 6imposes an energy penalty on the system.The form of eq 6,ensures that E over will quickly vanish to zero for under-coordinated systems (∆i <0).∆i is calculated using eq 4,using the corrected bond orders BO ij from eq 3instead of the uncorrected bond orders from eq 2.2.2.2.Under-Coordination.For an under-coordinated atom(∆i <0),we want to take into account the energy contribution for the resonance of the π-electron between attached under-coordinated atomic centers.This is done by eqs 7a,b where E under is only important if the bonds between under-coordinated atom i and its under-coordinated neighbors j partly have π-bond character (BO ij,π>0as calculated from the last two terms of eq 2).2.3.Valence Angle Terms.Just as for bond terms,it is important that the energy contribution from valence angle terms goes to zero as the bond orders in the valence angle goes to zero.Equations 8a -d are used to calculate the valence angle energy contribution.We use the bond-order-dependent form in eq 8a to calculate energy associated with deviations in valence angle Θijk from its equilibrium value Θo .The f 7(BO )term as described in eq 8b ensures that the valence angle energy contribution disappears smoothly during bond dissociation.Equation 8c deals with the effects of over/undercoordination in central atom j on the valence angle energy.The equilibrium angle Θo for Θijk depends on the sum of π-bond orders (SBO)around the central atom j as described in eq 8d.Thus,theTABLE 3:van der Waals Parameters Used in Equation 12aatom units r vdW Å kcal/mol R γw ÅC 3.9120.086210.71 1.41H3.6490.019410.065.36aArithmetic combination rules are used for all van der Waals parameters.TABLE 4:Bond Parameters (D e in kcal/mol)As Used in Equations 2and 3bond D e p be,1p be,2p bo,1p bo,2p bo,3p bo,4p bo,5p bo,6C -C 145.20.3180.65-0.097 6.38-0.269.37-0.39116.87C -H 183.8-0.45412.80-0.0137.65H -H168.4-0.31010.25-0.0165.98Figure 2.(a)Effect of the bond order correction in eq 2on the C -C and C -H bond orders in an ethane molecule in which the C -C bond is shortened to 1.0Åwith the rest of the geometry fixed.(b)Effects of shortening of the C -C bond length in ethane to 1.0Åon the relaxed C -H bond lengths as calculated by DFT and ReaxFF.Equilibrium C -C and C -H bond lengths are in italics and brackets.BO ij )BO ′ij ‚f 1(∆′i ,∆′j )‚f 4(∆′i ,BO ′ij )‚f 5(∆′j ,BO ′ij )(3a)f 1(∆i ,∆j ))12‚(Val i +f 2(∆′i ,∆′j )Val i +f 2(∆′i ,∆′j )+f 3(∆′i ,∆′j )+Val j +f 2(∆′i ,∆′j )Val j +f 2(∆′i ,∆′j )+f 3(∆′i ,∆′j ))(3b)f 2(∆′i ,∆′j ))exp(-λ1‚∆′i )+exp(-λ1‚∆′j )(3c)f 3(∆′i ,∆′j ))1λ2‚ln {12‚[exp(-λ2‚∆′i )+exp(-λ2‚∆′j )]}(3d)f 4(∆′i ,BO ′ij ))11+exp(-λ3‚(λ4‚BO ′ij ‚BO ′ij -∆′i )+λ5)(3e)f 5(∆′j ,BO ′ij ))11+exp(-λ3‚(λ4‚BO ′ij ‚BO ′ij -∆′i )+λ5)(3f)∆′i )∑j )1n bondBO ′ij -Val i(4)E bond )-D e ‚BO ij ‚exp[p be,1(1-BO ij p be,1)](5)E over )p over ‚∆i ‚(11+exp(λ6‚∆i ))(6)E under )-p under ‚1-exp(λ7‚∆i )1+exp(-λ8‚∆i )‚f 6(BO ij ,π,∆j )(7a)f 6(BO ij ,π,∆j ))11+λ9‚exp(λ10‚∑j )1neighbors(i )∆j ‚BO ij ,π)(7b)9398J.Phys.Chem.A,Vol.105,No.41,2001van Duin et al.equilibrium angle changes from around 109.47°for sp 3hybrid-ization (π-bond )0)to 120°for sp 2(π-bond )1)to 180°for sp (π-bond )2)based on the geometry of the central atom j and its neighbors.In addition to including the effects of π-bonds on the central atom j ,eq 8d also takes into account the effects of over-and under-coordination in central atom j (∆j )on the equilibrium valency angle,including the influence of a lone electron pair.The functional form of eq 8d is designed to avoid singularities when SBO )0and SBO )2.The angles in eqs 8a -d are in radians.To reproduce the stability of systems with two double bondssharing an atom in a valency angle,like allene,an additional energy penalty,as described in eqs 9a and 9b,is imposed forsuch systems.Equation 9b deals with the effects of over/undercoordination in central atom j on the penalty energy.2.5.Torsion Angles.Just as with angle terms we need to ensure that dependence of the energy of torsion angle ωijkl accounts properly for BO f 0and for BO greater than 1.This is done by eqs 10a -c.The V 2-cosine term in eq 10a depends on the bond order of the central bond BO jk .In torsion angles with a central double bond (BO jk )2)the V 2-term is at its maximum (about 30kcal/mol,see Table 6).If BO jk deviates from 2the magnitude of the V 2-term rapidly diminishes.The valence-angle-dependent term sin(Θijk )‚sin(Θjkl )in eq 10a ensures that the torsion energy contribution disappears when either of the two valence angles (Θijk or Θjkl )approaches π.To avoid excessive torsion contributions in systems containing two attached over-coordinated sp 3-carbon atoms,like an ethane molecule in which the central C -C bond length is reduced from its equilibrium value of about 1.52Åto 1.35Å,we include eq 10c,which reduces the influence of BO jk on the V 2-term in eq 10a when atoms j and k are over-coordinated [∆j >0,∆k >0].Equation 10b describes the smooth disappearance of the torsion energy contribution when one of the bonds in the torsion angle dissociates.2.6.Conjugated Systems.Equations 11a and 11b describe the contribution of conjugation effects to the molecular energy.A maximum contribution of conjugation energy is obtained when successive bonds have bond-order values of 1.5as in benzene and other aromatics.2.7.Nonbonded van der Waals Interactions.In addition to valence interactions which depend on overlap,there are repulsive interactions at short interatomic distances due to Pauli principle orthogonalization and attraction energies at long distances due to dispersion.These interactions,comprised ofTABLE 5:Valence Angle Parameters As Used in Equations 8a -dvalence angle units Θo,o degree k akcal/mol k b(1/radian)2p v,1p v,2C -C -C 71.31a 35.4 1.370.010.77C -C -H 71.5629.65 5.29H -C -H 69.9417.37 1.00C -H -C 028.5 6.00H -H -C 00 6.00H -H -H27.96.00aThis value leads to an equilibrium angle of 180-71.31)108.69°for the single-bond C -C -C valence angle (eq 8d).TABLE 6:Torsion and Conjugation Parameters (V 2and V 3in kcal/mol)As Used in Equations 10a -ctorsion angle a V 2V 3p t C -C -C -C 21.70.00-2.42C -C -C -H 30.50.58-2.84H -C -C -H26.50.37-2.33aTorsion angles not defined in this table (i.e.,C -H -C -C)are assigned torsion barrier energies of 0kcal/mol.E val )f 7(BO ij )‚f 7(BO jk )‚f 8(∆j )‚{k a -k a exp[-k b (Θo -Θijk )2]}(8a)f 7(BO ij ))1-exp(-λ11‚BO ij λ12)(8b)f 8(∆j ))2+exp(-λ13‚∆j )1+exp(-λ13‚∆j )+exp(p V ,1‚∆j )‚[λ14-(λ14-1)‚2+exp(λ15‚∆j )1+exp(λ15‚∆j )+exp(-p V ,2‚∆j )](8c)SBO )∆j -2‚{1-exp [-5‚(12∆j)λ16]}+∑n )1neighbors(j )BO jn ,π∆j ,2)∆j if ∆j <0∆j ,2)0if ∆j g 0SBO2)0if SBO e 0(8d)SBO2)SBO λ17if 0<SBO <1SBO2)2-(2-SBO)λ17if 1<SBO <2SBO2)2if SBO >2Θ0)π-Θ0,0‚{1-exp[-λ18‚(2-SBO2)]}E pen )λ19‚f 9(∆j )‚exp[-λ20‚(BO ij -2)2]‚exp[-λ20‚(BO jk -2)2](9a)f 9(∆j ))2+exp(-λ21‚∆j )1+exp(-λ21‚∆j )+exp(λ22‚∆j )(9b)E tors )f 10(BO ij ,BO jk ,BO kl )‚sin Θijk ‚sin Θjkl[12V 2‚exp {p l(BO jk-3+f 11(∆j ,∆k ))2}‚(1-cos 2ωijkl )+12V 3‚(1+cos 3ωijkl )](10a)f 10(BO ij ,BO jk ,BO kl ))[1-exp(-λ23‚BO ij )]‚[1-exp(-λ23‚BO jk )]‚[1-exp(-λ23‚BO kl )](10b)f 11(∆j ,∆k ))2+exp[-λ24‚(∆j +∆k )]1+exp[-λ24‚(∆j +∆k )]+exp[λ25‚(∆j +∆k )](10c)E conj )f 12(BO ij ,BO jk ,BO kl )‚λ26‚[1+(cos 2ωijkl -1)‚sin Θijk ‚sin Θjkl ](11a)f 12(BO ij ,BO jk ,BO kl ))exp [-λ27‚(BO ij -112)2]‚exp [-λ27‚(BO ij -112)2]‚exp [-λ27‚(BO kl -112)2](11b)ReaxFF:A Reactive Force Field for HydrocarbonsJ.Phys.Chem.A,Vol.105,No.41,20019399van der Waals and Coulomb forces,are included for all atom pairs,thus avoiding awkward alterations in the energy descrip-tion during bond dissociation.In this respect,ReaxFF is similar in spirit to the central valence force fields that were used earlier in vibrational spectoscropy.To account for the van der Waals interactions we use a distance-corrected Morse-potential (eqs 12a,b).By including a shielded interaction (eq 12b),excessively high repulsions between bonded atoms (1-2interactions)and atoms sharing a valence angle (1-3interactions)are avoided.Figure 3shows how the bond energies,derived from eq 5,combine with the van der Waals interactions for diatomic C -C,C -H,and H -H systems to give a dissociation energy curve.2.8.Coulomb Interactions.As with the van der Waalsinteractions,Coulomb interactions are taken into account between all atom pairs.To adjust for orbital overlap between atoms at close distances a shielded Coulomb potential is used.Atomic charges are calculated using the Electron EquilibrationMethod (EEM)approach.20-21The EEM charge derivation method is similar to the Q Eq scheme;6the only differences,apart from parameter definitions,are that EEM does not use an iterative scheme for hydrogen charges (as in Q Eq)and that Q Eq uses a more rigorous Slater orbital approach to account for charge overlap.However,the γij in eq 13can be optimized to reproduce the Q Eq orbital overlap correction.The initial values for the EEM-parameters ( ,η,and γ,Table 2)were taken fromNjo et al.,22but these parameters were allowed to change during the FF optimization procedure.Intraatomic contributions of atomic charges,to account for the energy required to polarize the atoms,are taken into account in the energy scheme,23thus allowing a straightforward expansion of the force field for ionic compounds.With the EEM-parameter values from Table 2,ReaxFF assigns a charge of -0.113to the carbon atoms in cyclohexane and charges of +0.050and +0.063to the equatorial and axial hydrogens,respectively.A Mulliken distribution,from a DFT calculation with the 6-31G**-basis set,results in charges of -0.174,+0.0859,and 0.0876to the cyclohexane carbon,equatorial and axial hydrogens while the Q Eq method 6gets a -0.24,+0.104,+0.137charge distribution.2.9.Force Field Optimization Procedure.The FF was optimized using a successive one-parameter search technique as described by van Duin et al.24In general,our aim was to reproduce heats of formation to within 4.0kcal/mol,bond lengths to within 0.01Å,and bond angles to within 2°of their literature values.To use the QC data in the FF optimization procedure,structures relating to these data were added to the FF training set.All molecules used in the heat of formation and geometry data comparisons were continuously energy minimized during the FF optimization while the structures relating to the QC data were kept fixed or were optimized with appropriate bond length or torsion angle restraints.3.Results3.1.Non-Conjugated Systems.3.1.1.Energy and Geometry Reproduction.Figure 4a and Table 7show how well the ReaxFF reproduces the heat of formation for nonconjugated closed shell molecules.The heat of formation predictions for ReaxFF are compared with those of the semiempiricalMOPAC-method,Figure 3.Interatomic distance dependency of the carbon -carbon,carbon -hydrogen,and hydrogen -hydrogen bond-and van der Waals-energy terms of diatomic C -C,C -H,and H -H systems.Energy contributions from Coulomb interactions and energy effects related to under and overcoordination are ignored in the total energy curve.E vdWaals )D ij ‚{exp [R ij ‚(1-f 13(r ij )r vdW )]-2‚exp[12‚R ij ‚(1-f 13(r ij )r vdW)]}(12a)f 13(r ij ))[r ij λ29+(1λw)λ28]1/λ28(12b)E Coulomb )C ‚q i ‚q j[r ij 3+(1/γij )3]1/3(13)Figure parison of calculated heats of formation with experi-mental data for nonconjugated (a),conjugated (b),and radical systems (c).9400J.Phys.Chem.A,Vol.105,No.41,2001van Duin et al.using the PM3-parameters39and with those of the nonreactive MM3force field.Heats of formation data were calculated from the total system energy,as determined from eq1,by adding the terms described in eq14.POP in eq14reflects the contribution of high-energy conformations,defined as the difference in heat of formation between the most stable conformation and the mixture of conformations.These high-energy conformation contributions,which are primarily signifi-cant for the larger(C6+)monocyclic saturated ring system in the training set,are also listed in Table7.I C and I H in eq14are the heat increments for the carbon and hydrogen atoms, respectively,as given in Table2.n C and n H are the number of carbon and hydrogen atoms in the molecule.4RT is added to account for translation,rotation,and pV-work in nonlinear polyatomic molecules.The values for the heat increments were determined by calculating the system energies of the compounds in the force field training set,addition of the POP and4RT-contribution and subsequent optimization of I C and I H to minimize the difference between calculated and literature heats of formation.As a result,the heat increments values bear no direct physical meaning,as,apart from the heats of formation of the elements,they also contain corrections for vibrational and zero-point energy.Table8shows the ReaxFF geometry data reproduction for nonconjugated molecules.3.1.2.Reproduction of Quantum Chemical Data.Figures5-7 show the carbon-carbon dissociation energies for ethane, ethylene,and ethyne as obtained from DFT calculations,the Brenner FF,PM3,and ReaxFF.The DFT calculations were performed at the B3LYP-level using the6-31G**basis set, which includes Generalized Gradient Corrections and exactTABLE7:Heat of Formation(kcal/mol)from ReaxFF for Non-conjugated Systemscompound H f(calc)H f(exp)a-POP diff cyclohexane-30.65-29.49-1.16 ethane-18.33-20.02 1.69 isobutane-30.62-32.07 1.45 neopentane-40.91-40.18-0.73 anti-n-butane-29.69-30.20b0.31 ethylene8.7512.55-3.80 propene 2.64 4.78-2.14 allene40.2346.40c-6.17 hydrogen8.850.008.85 cyclopentane-17.59-18.450.86 trans-decaline-45.14-43.52-1.62 cis-decaline-41.13-40.45-0.68 cyclobutene42.5437.50 5.04 cyclopentene 6.358.56d-2.21 cyclohexene-2.57-1.20-1.37 norbornane-8.00-12.42 4.42 norbornene20.6721.52-0.85 ethyne63.0654.508.56 propyne46.4344.20 2.23 cyclobutane 2.89 6.80-3.91 cyclopropane18.8212.70 6.12 protoadamantane-20.38-20.54e0.16 cis-hydrindane-30.11-30.410.30 perhydroquinacene-21.40-22.000.60 1,1-dimethylcyclopentane-31.80-33.33 1.53 2,2,3,3-tetramethylbutane-49.56-53.65 4.09 gauche-butene-2.31-0.50-1.81 cyclopropene88.3566.2322.12 cycloheptane-27.99-28.44f0.45 cyclooctane-28.51-30.12g 1.61 cyclononane-30.76-32.26h 1.50 cyclodecane-36.62-37.56I0.94 bicyclo[2.2.2]octane-23.80-23.68-0.12 cis-bicyclo[3.3.0]octane-21.77-22.200.43 bicyclo[3.3.1]nonane-31.32-30.50-0.82 trans-bicyclo[3.3.0]octane-14.06-15.91 1.85 di-tert-butylmethane-55.13-57.60 2.47 diamantane-37.30-34.87e-2.43 tst-perhydroanthracene-58.12-58.210.09 adiene19.8725.24-5.37 carbene93.8498.00-4.16 methane-14.25-17.80 3.55a Experimental heats of formation were taken from Pedley et al.25 unless noted otherwise.b POP)-0.20kcal/mol.c ref26.d ref27.e ref 28.f POP)-0.21kcal/mol.g POP)-0.36kcal/mol.h POP)-0.52 kcal/mol.i POP)-0.68kcal/mol.TABLE8:Geometry Predictions from ReaxFF(bond lengths inÅ,angles in degrees)for Non-Conjugated Systems compound bond/anglej calcd expt ethane a a 1.555 1.53b 1.1198 1.10ab110.6110bb′108.3107 ethylene b a 1.312 1.337b 1.117 1.08ab121.0121.8bb′118.0116.4 ethyne c a 1.241 1.202b 1.104 1.06 hydrogenc a0.780.7414 cyclohexaned a 1.551 1.54b 1.121 1.10aa′111.2111.0bb′103.7107.0 cyclopentene e a 1.324 1.348b 1.552 1.52c 1.564 1.55ab111.9112.8bc103.1103.3 cyclohexene f a 1.343 1.34b 1.546 1.50c 1.561 1.53 norbornane g ab90.993.9 norbornene h ab90.195.3bc101.196.12,2,3,3-tetramethylbutane i a 1.553 1.54b 1.569 1.58a ref20.b ref30.c ref31.d ref32.e refs33-34.f ref35.g ref36.h ref37.i ref38.j See Figure24for bond and angledefinitions.Figure5.Ethane C-C bond dissociation.Crosses indicate the data used in the force field parametrization.∆Hf)Esystem+4RT+POP+nCIC+nHIH(14)ReaxFF:A Reactive Force Field for Hydrocarbons J.Phys.Chem.A,Vol.105,No.41,20019401。
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School of Computing Science,University of Newcastle upon TyneWRAPPING THE FUTURETom Anderson,Brian Randell and Alexander RomanovskyTechnical Report SeriesCS-TR-852July2004Copyright c 2004University of Newcastle upon TynePublished by the University of Newcastle upon Tyne,School of Computing Science,Claremont Tower,Claremont Road,Newcastle upon Tyne,NE17RU,UK.WRAPPING THE FUTURETom Anderson, Brian Randell and Alexander RomanovskySchool of Computing Science, University of Newcastle upon Tyne, UKAbstract:Enclosing a component within a software “wrapper” is a well-established way of adapting components for use in new environments. This paper presents anoverview of an experimental evaluation of the use of a wrapper to protectagainst faults arising during the (simulated) operation of a practical and criticalsystem; the specific context is a protective wrapper for an off-the-shelfsoftware component at the heart of the control system of a steam raising boiler.Encouraged by the positive outcomes of this experimentation we seek toposition protective wrappers as a basis for structuring the provision of faulttolerance in component-based open systems and networks. The paperaddresses some key issues and developments relating wrappers to theprovision of dependability in future computing systems.Key words:dependability; off-the-shelf components; fault tolerance; protective wrapping.Many siren voices, and some harsh economic facts, argue in favour of off the shelf (OTS) components as a way to reduce the costs of software system development. Compared with bespoke design and development, the OTS option offers a number of potential benefits, including: immediate availability, proven in use, low price due to amortisation. The increasing scale and complexity of modern software systems is a powerful driver for modularity in design, which clearly chimes with a structured and therefore such a component (or sub-system) based approach.The need for economy is often most keenly felt in expensive systems, and this can certainly be the case for systems that have critical requirements (such as safety-critical systems). But it is in the nature of these systems that they really must deliver on their requirements; their operational behaviour must exhibit dependability; they must do what they are supposed to do, and must not do what is prohibited (well, almost always). With a completely bespoke development, designers can strive very hard to achieve a2Tom Anderson, Brian Randell and Alexander Romanovsky dependable system, and regulators can obtain access to extensive information on the development process (as well as the delivered product) in order to evaluate a documented justification that the system will meet its critical requirements (for example, a safety case). Utilisation of an OTS software component is likely to inhibit this evaluation, since – in the extreme case – the component may have to be viewed as a black box, with no information on its inner workings or its development; the proven-in-use evidence for the component’s suitability may, or may not, be valid, but such evidence cannot be relied upon if it is merely anecdotal or does not relate to an identical use environment.So, consider the situation where use of an OTS software component is feasible and there is a strong financial reason for doing so, but the component’s behaviour needs to be trusted, and we have insufficient evidence to justify that trust. How can we proceed? The approach to be considered in this paper is a simple application of diversity to provide an architectural solution. The OTS component will be enclosed in a bespoke protective wrapper [Voa98, Arl02], a purpose designed additional component that intercepts all inputs to, and outputs from, the OTS component in order to monitor its behaviour. The aim is for the wrapper to deal with any problems arising from inadequate behaviour of the OTS component, ideally masking any such deleterious effects from the rest of the system. This is thus a special case of the more general use of software wrapping, a technology that has a long history of use as a means of adapting existing components for use in new environments.1.THE DOTS PROJECTDOTS – “Diversity with OTS components” – is a joint project at CSR (Centre for Software Reliability) in Newcastle and City Universities, funded by the UK EPSRC. Work at Newcastle is exploring architectural approaches to diversity in the presence of OTS items, while colleagues at City concentrate on assessment of the benefits that can be expected.Our architectural exploration has concentrated on protective wrapper technology, a phrase that gives an appealing technical ring to this simplistic approach of enveloping a possibly suspect component. However, despite its apparent simplicity, there are a range of issues to consider and questions to be asked. We believe that our work gives some encouragement that positive answers may be given to the following questions:•is protective wrapper technology feasible in practical systems?•can protective wrappers detect and respond successfully to erroneous situations in practical systems?Wrapping the Future3 In order to draw conclusions for practical systems we sought realism in our investigation. Experimentation with a real-world critical system would be fraught with peril, so we made use of a software model of a real-time software system. To maximise realism we adapted a model taken directly from industry: a Honeywell-supplied industrial grade simulation of a steam boiler and its associated control system. Written in Simulink [Mat], the model represents a real steam raising system in which a coal-fired boiler responds to demands for steam under the operational authority of an automated control system; the control system consists of a PID (i.e. Proportional, Integral and Derivative) controller together with a range of smart sensors, actuators, and configuration controls (collectively referred to as the ROS (rest of system)), as illustrated in Figure 1.Figure 1. Boiler System and Control SystemWe chose to treat the PID controller as an OTS item, and then developed a (simulated) protective wrapper that can monitor and, when appropriate, modify all input/output signals between the PID controller and the rest of the control system. As a purely protective wrapper there was no intention to adjust or upgrade the PID controller’s behaviour at the interface; the aim was simply to provide fault-tolerant elements that can detect and recover from errors. In designing the wrapper we only had access to limited information about the operation of the boiler and the control system; furthermore we deliberately ignored any details of the inner working of the PID controller, treating it as a black box. Ideally we would have wished for access to a full external specification of the PID controller, but the lack of this made our position even more realistic.In creating our own, approximate, specification for the PID controller we built up a set of Acceptable Behaviour Constraints (ABCs) [Pop01] which stipulate what may be considered as acceptable behaviour at the interface between the PID controller and the rest of the control system.4Tom Anderson, Brian Randell and Alexander Romanovsky 2.ERROR DETECTIONGiven the limitations of the scenario we were exploring our strategy for error detection was necessarily based on a systematic application of generic criteria. Erroneous situations can arise anywhere in the system, but the wrapper can only check for symptomatic “cues” at the interface to the PID controller. The wrapper was programmed to check inputs to the PID controller cyclically against constraints established as ABCs (missing, invalid, unacceptable, marginal or suspect values from the sensors or configuration variables). Similarly, outputs from the PID controller were also checked against ABCs (missing, invalid or unacceptable values intended for the actuators). Thus we were attempting to deal with both the PID’s monitoring and its control activities.To help inform the next stage of wrapper design we categorised these error cues as follows:•unavailability of signal (inputs or outputs),•signal violating specified constraints (usually out of range errors),•excessive signal oscillations (in amplitude or frequency).Additionally, we recognised that with respect to the safety of the system, some erroneous situations are much more acute than others. In a steam boiler, a key parameter is the “drum level”; this parameter measures the mass of water contained in the boiler drum more accurately than the “water level” (which is also monitored, of course). Too little water and the boiler tubes are exposed to heat stress, too much and water could go over the header causing corrosion. The danger of excessive steam pressure is obvious and explosive. Thus detected errors that concerned either steam pressure or the quantity of water in the drum were designated as needing an immediate and effectual response. (A boiler operated via a PID controller is one of the most widely deployed systems, installed in many industrial facilities and residential houses, for the safe and reliable generation of steam and/or hot water. Nevertheless, critical incidents in these systems lead to deaths and injuries every year [Nat03].)3.ERROR RECOVERYThe purpose of error recovery is to transform a system state that contains errors to one that does not. Backward recovery returns the system to a previous state, prior to the incidence of error, and is unlikely to be available for OTS components. So our protective wrapper attempts to implement application-specific forward recovery, which does not discard the currentWrapping the Future5 state. Exception handling provides a general framework for such forward recovery.We implemented three elementary recovery actions:•H1: reset signal to normal value and alert operator•H2: wait t, if error goes away no action taken; otherwise send alarm to operator and wait T, no further action if error goes away; otherwise invoke H3 {delay times t and T chosen by the wrapper designer}•H3: shut system down and send alarm to operator.We then devised a rationale for a recovery strategy in which:•all errors for PID controller outputs invoke H1•all errors from configuration controls invoke H1•all PID input errors (except drum level and steam pressure) invoke H2•excessive signal oscillation errors concerning drum level and steam pressure invoke H2•all other errors concerning drum level and steam pressure invoke H3. [Adopting this (or any other) recovery strategy for an actual boiler plant would, of course, require safety analysis and justification.]In our experimental situation, having implemented a protective wrapper with a detection and recovery capability we need to observe how well the system responds. Initial test exercises gave very positive indications, and we have just completed a first phase of setting up a range of fault injection scenarios, running these, and recording the outcomes. Our fault injection scenarios involve signal communication faults (bias, random noise, stuck-at previous, stuck-at random) and faults that impinge directly on the algorithms of the PID controller (transient zeros, control parameter overwrites). A preliminary examination of the experimental data generated indicates that the wrapper has been very effective in reducing serious failures of the boiler system.4.PROTECTIVE WRAPPING – WHAT NEXT?Thus far we merely claim to have built a reasonably realistic, albeit rather simplistic, demonstrator of a protective wrapper in action to enhance the dependability of an industrial OTS component, with encouraging early results. The exercise of working with the demonstrator has helped us to address a number of specific concerns, which we consider in more detail elsewhere [And03a, And03b, And03c]. However, and much more significantly, we now discern a salient role for wrapper technology as a means for structuring, designing and building future ICT systems. We believe that protective wrapping has considerable promise as a uniform approach for incorporating fault tolerance into new and existing complex6Tom Anderson, Brian Randell and Alexander Romanovsky systems, particularly when these are organised and created as integrative networks of interacting components.Openness is often considered to be one of the defining characteristics of the ICT systems that are expected to be widely deployed in future – systems that will support mobile access and that are pervasive of society; systems that deliver ambient “intelligence” in terms of services, information, processing and communication; networks of heterogeneous systems/components which interact with (and depend upon) other networks; sub-networks that combine and decompose dynamically. Openness allows on-line composition, reconfiguration, evolution and upgrading, performed on the basis of a dynamic analysis of the available information representing possible changes. This flexibility is made possible by features that can be used dynamically to select or devise optimal configurations, and then to realise these configurations by locating, deploying and integrating the appropriate components. Openness is usually understood in the widest possible sense, in that it should allow systems to deal with changes in: requirements, location (mobility), quality of service (QoS) characteristics, the environment, component behaviour, users’ expectations, users’behaviour, etc. Clearly this must include dealing with changes due to accidental or malicious faults.There is a significant challenge in identifying and developing fault tolerance solutions that fit the specific characteristics of open systems; protective wrapping has considerable potential to be one of the fundamental fault tolerance techniques needed, primarily because it sits well with the open network based approach but also because it provides such a simple but general starting point. Of course, there are numerous issues that will need to be examined further before that potential can be converted into a fully effective approach. Among these issues we can draw attention to:•wrapper deficiencies – the role of a protective wrapper is to improve system dependability by providing an error detection and recovery capability, but there is always a risk in including defensive mechanisms for fault tolerance that by adding an additional software component new opportunities for erroneous computation may arise; the best general guidance is to keep wrappers as simple as possible•formal development of wrappers – the need to minimise the risk of a protective wrapper introducing additional fault modes is not only a driver for simplicity in wrapper design, but also for adherence to stringent and rigorous development practice; we see a basis for progress here based on contracts derived from constraint-based specification of component interfaces (e.g. ABCs), and by exploiting compositional semantics •timing issues – there is considerable scope for considering how best a protective wrapper should stipulate and monitor deadlines, and react toWrapping the Future7 delays; strategies and protocols from distributed systems work will need to be adapted for open networks•scoping issues – the most simplistic image of a protective wrapper gives it full access to all communications across the wrapped component’s interface and no access to any variables elsewhere in the system (either internal to the wrapped component or in its environment), but any realistic implementation is likely to deviate from this artifice; it will rarely be feasible or necessary to control each and every component interaction, access to internal values (though often undesirable and/or inhibited by lack of knowledge) may be possible and of benefit in special circumstances, and supplementary information about external conditions could be an invaluable guide to the operation of the wrapper (both for error detection and response)•wrapper interactions – a set of protective wrappers in a network of wrapped components may need to be able to communicate and interact in order to best achieve their several and collective dependability objectives; imposing constraint and mediation on inter-wrapper communication is likely to involve approaches based on interactive consistency solutionsThe above list of bulleted topics could be extended almost indefinitely, for instance with issues from specific dependability domains (safety and security, for example) and more general systems engineering concerns (modelling and requirements, for example) but instead we move on, to relate the technology of protective wrapping to anticipated developments in the dependability of systems more generally.A recently-commissioned Foresight document [Jon04] identified a number of core directions for future research in dependability, including: dependability-explicit systems, cost-effective formal methods, architecture theory, and adaptivity. In the remainder of this paper we outline how advances in these four areas could impact on protective wrapper technology, and vice-versa.Dependability-explicit system development [Kaâ00] is an emerging area of research which supports the explicit incorporation of dependability-related information into system development artefacts right through the development life-cycle, starting from the earliest phases of development, and continuing through to on-line support for maintaining, updating and exporting this dependability information within the operational system (with reference to the current state of the system and its environment). Examples of dependability information are fault descriptions, expected normal/abnormal behaviour, redundancy resources, mappings between errors and handlers, abnormal situations that components are capable of handling, failure frequency data, etc. Protective wrapping fits this approach extremely8Tom Anderson, Brian Randell and Alexander Romanovsky well, since such data will be relevant for informing decisions by the wrappers relating to error detection and recovery, potentially allowing the evolution of wrappers in response to changes in system and environment behaviour, and after network reconfiguration. Furthermore, wrappers are an obvious candidate mechanism for processing the dependability information, and publishing it across the network.Research on cost-effective formal methods will contribute to overall system dependability by accumulating a set of advanced tools (operating within an open platform) for cutting-edge formal development methods focussed on fault tolerance, mobility and adaptivity. Formal models of future open systems will enable wrappers to be rigorously described, and the systems containing them to be formally analysed. A key research objective is the development of tools that can analyse the models of a system and a specific component, from that analysis determine requirements for a protective wrapper for the component, and then generate the wrapper model – with the long term objective that this analysis and generation can be performed fully automatically as an adaptive open system evolves.Architecture theory research aims to provide methods for reasoning about dependability concerns at an architectural level much earlier in system development. Protective wrappers provide a major structuring approach that embodies fault tolerance capabilities (including confinement of error propagation, and exception handling), but they will need to have adequate architectural support. In particular, there is a need to introduce recursive architectural solutions that can integrate wrappers within the architectural styles that will be typical for future open systems. Wrappers will then serve as a cardinal structure for introducing and managing redundancy at the architectural level. The focus should be on preserving architectural representations throughout all development phases until runtime execution to enable dynamic changes of architecture to be made online to improve overall system dependability.It seems clear that future systems will need to have adaptivity, so that they can respond to changing environments, altered patterns of use, modified requirements and more. They will need to be dynamically upgradeable and reconfigurable; they will need to have a capacity for adjustment and evolution. Despite this mutability, users will demand that the dependable delivery of service be sustained. Wrappers could provide the fundamental structure supporting component-level adaptation and evolution; protective wrappers could embody fault tolerant defences in support of dependable operation.Wrapping the Future9 5.CONCLUSION – ONLY A BEGINNING!Protective wrappers offer a simplicity of concept and a generality of applicability that is attractive and encouraging. But it must be acknowledged that this welcome simplicity defers many of the difficult issues to the next stage of research and development.We close this paper with the observation that all computing systems are (eventually) embedded in groups of humans – that is, in society. Members of society will need future computing systems to be wrapped as a protective mechanism and, in turn, it may be appropriate (in effect) to wrap the users to protect the systems. Very basic protective wrappers are already essential to shield us from the excesses created by something as trivial as spam e-mails! ACKNOWLEDGEMENTThis work was partially supported by the UK EPSRC DOTS project. REFERENCES[And03a] T. Anderson, M. Feng, S. Riddle, A. Romanovsky. Error Recovery for a Boiler System with OTS PID Controller, CS Technical Report 798, May 2003, School of Computing Science, Univ. of Newcastle (presented at ECOOP 2003, Darmstadt).[And03b] T. Anderson, M. Feng, S. Riddle, A. Romanovsky. Protective Wrapper Development. Proc.2nd Int. Conf. on COTS-Based Software Systems, Ottawa, Canada, February 2003, pp. 1-14.[And03c] T. Anderson, M. Feng, S. Riddle, A. Romanovsky. Investigative Case Study: Protective Wrapping of OTS items in Simulated Environments. CS Technical Report 821, December 2003, School of Computing Science, Univ. of Newcastle (submitted to COMPSAC 2004).[Arl02] J. Arlat, J.-C. Fabre, M. Rodríguez, F. Salles. Dependability of COTS Microkernel-Based Systems. IEEE Trans. on Computers. 51, 2, 2002, pp. 138-163.[Jon04]C. B. Jones, B. Randell. Dependable Pervasive Systems. 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