Durab_methodology

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泡沫混凝土的应用与质量控制

泡沫混凝土的应用与质量控制杨小芳;赵芊;兰长贵【摘要】目前市场上的建筑保温材料,多为有机泡沫保温材料,如EPS泡沫板等.有机泡沫保温材料有保温效果好、重量轻、易施工等优点.但其防火性能差,施工时稍有不慎,就会发生重特大火灾事故.而泡沫混凝土,是一种新型的无机保温材料,其显著特点是不燃烧,成本低,寿命长,保温效果也较好,能满足建筑保温的要求.所以,泡沫混凝土很适合应用在建筑保温中.结果表明,在泡沫混凝土屋面保温施工中,严格执行施工工艺,采用标准的质量控制方法,就能达到合格的施工质量.实际应用表明:泡沫混凝土完全可以取代EPS板,用在建筑屋面保温中,可大大降低火灾损失.【期刊名称】《四川建材》【年(卷),期】2012(038)004【总页数】3页(P25-27)【关键词】建筑工程;泡沫混凝土;屋面保温;质量控制【作者】杨小芳;赵芊;兰长贵【作者单位】河南理工大学基建处,河南焦作454000;河南理工大学监理所,河南焦作454003;河南理工大学后勤集团,河南焦作454000【正文语种】中文【中图分类】TU528.20 前言2008年，济南奥体中心屋面两次发生火灾，造成很大的经济损失，2009年2月，中央电视台新址在建北楼发生火灾，过火面积达10万m2，造成人员一死一伤，直接经济损失1.1亿元［1］。

2010年，上海“11·15”特大火灾，造成58人死亡、许多人受伤的惨剧，以上火灾事故发生的原因很多，有一个相同点是都用了有机保温材料，目前使用较多的是挤塑板(XPS)、聚苯板(EPS)及硬泡聚氨酯等，它们的特点是保温性能好，质地轻，易施工，成本低。

缺点是防火性能差，按新标准确定的阻燃等级为E级，属可燃性建筑材料［2］。

而泡沫混凝土，也叫泡沫水泥，是一种不燃材料，具有绿色环保、与建筑物同寿命等优势;和泡沫玻璃、泡沫陶瓷、岩棉、玻璃棉等其它无机保温材料相比，又具有造价低、可现浇、投资小、原料来源广等优势，因此，推广泡沫混凝土是一件利国利民的好事，从未来建筑保温发展趋势来看，泡沫混凝土很有可能成为用量最大的保温材料之一［3］。

Second Language Acquisition and Language Teaching

Second Language Acquisition and Language TeachingTRAGANTUniversityAfter discussing theeighties, in which focus on thef our macro-options of focus-on-form interventions and their theoretical motivationsare presented, followed by recent researchdepending on individual factors and the learning context.K E Y W O R D S: focus on form, form-focused instruction, input processing, input enhancement, negative feedback, form-focused output, explicitcorrespondence: Departamento de Filologia Inglesa y Alemana, Universidad de Barcelona, Gran Via de les Corts Catalanes, 585,08007 Barcelona. Tel.righfs reserved. 2004, pp. 197-219198 Tragan!INTRODUCTIONThe relationship between SLA and language teaching is not by any means a straightfoward one nor is there a consensus about how much of an influence SLAthey took within the context of a B.A. and ana uthors inof pedagogic utility).Contradictory information about the impact of SLA research on teachers, like that found in MacDonald al.'s conclusions to their study, is not uncommon in the literature written at the turn of the1990; Mitchell,Crookes, 1997; Markee, 1997). However, these diverging stances are much better understood if one is aware that they originate from rather fundamental differences in the conception of teaching that these two groups of researchers hold (as conceptualized by Freeman, 1996).Those critica1 of the role of mainstream SLA researchmoment-to-moment decisions ('teaching as interpretation'). Resulting from these views of teaching, basic SLA research hasat the expense of behaviour, something which, according to him, teachers are primarily concerned with. These areothers, maintain thatmainstream SLA research, together with the positivist research methodology that tends to go with it,vol. 4199rights 2004, pp. 197-219According to Krashen (1 that was needed was comprehensible input and motivation. He made a fundamental distinction betweenvery engrained among teachers, to the point that Lightbown (2000) reports that in the late eighties 'everybody' believed in comprehensible input and the benefits of group work. Similarly, she mentions that the teachers in her environment took it for granted that it was not good to point out students'version of CLT. According to this version, communicative activities are an integral part of instruction where students' attention Scholarsso well tuned to the needs of the teacherswereEven thoughproblems, has of his hypothesesitcanDevice (LAD) lacks any especification as to how it may work empirically. For Mitchell and Myles (1model, when in fact those hypothesesof itsevidence had little impact on L2 pedagogyServicio de Publicaciones. Universidad de Murcia. rights reserved. pp. 197-21 94Uv ol. 420359U2004, pp. 197-219targct structure can be expected to arise naturally and frequently in performing the task, evento use thetargctc oncludes from his revision of studies that use structure-based production tasks that, at least inquestions-syntacticMcDonough, 2000). Structure-based production tasks asthe pedagogical intervention takes place as a reaction to students'output and ittechniques that can be used to get learners to self-correct.especially attractive optionthere is the perception of a growing emphasis on cognitive processes.areteaching. More recently, Schmidt's work on attention (2001) has reframed the concept of 'noticing' within a broader cognitive approach.IJES, vol. 4 (1 ), 2004, pp. 197-2 19Second und L u n~~~u g ethere are other applied linguists who hold alternative views. According to Robinson (1 of a central executive, where attentional resources are allocated. comes into play in hisintervene in language processing. Similarly, Truscott (1 998)is the relationship between metalinguistic or explicit knowledge and L2 acquisition and performance. As mentioned(1998) believes L2 learning should onproczduralized and automatizedt horough reviews on research onup to the late nineties (Doughty 1998; Longthatbyan Iiiformation Processing strategy and subsequently a number of structured input activities (botli referential and affective). On the other hand, TI has involved an initial explanationServicio de Publicaciones. Universidad de Murcia. rights reserved. IJES, vol. 4followed by mechanical andand used discrete-point tests to measure production. In this respect, Benati's recent work (2001) is of especial interest in that it dealt with another Romance language (Italian) and included a less structured oral production task. The results obtained are in line with findings in previous research in that the PI group's gains were shown to be superior to those of the TI group in the interpretation task but not in theobtained inexercises in TI, the only difference being that language production is not required.research involves input enhancement. Previous studies that compared the effectiveness of visually enhanced vs. non-enhanced i nput yielded limited results for this mode off orms. This isenhanced input seems to insuficient to focus the leamers' attention on the targetforms, even if exposure to enhanced texts was considerablewhere the effects of input enhancement versus output-input activities on leaming were compared,Vinther's work (2003).to process form as well as-focused output has mainly of a descriptive nature. A representative study is that conducted byServicio de Publicaciones. Universidad de Murcia. rights reserved. 2004, pp. 197-219Second ondthe validity of dictogloss as a task thattalk both Fortune and Thorp (2001)level. Descriptive analysis of students' talk Swain about thegrammar aspects the dictogloss intends to elicit. In fact, Swain (1 998) reports that her students rarely focused on the targeted linguistic form but on theirto insert appropriate function and linking words as well as inflectional morphemes, seemed to be a more effective procedure to get learners to focus more often on the targetedpiece of r esearch that measured performance in post-tests (Izumi, 2002). The distinctivethem inoutput seemed not to take place at the expense of comprehension as measured by a summary students were asked to write in theirform canmode of to a scarcity of previous research thatinvestigated the isolated effects of this type of interactional moves. While previous research consistently showed the availability of negative feedback in NS-NNS task-based interaction as well as in teacher-student classroom interaction, the focus of on theevaluation of its shown thatrecasts contribute to the leamers' interlanguage development, as m easured by performance tests. Long, Inagaki and Ortega (1 998) showed that recasts were more beneficial than models on forms with relatively high communicative value. More recently, Leeman (2003) has providedvalue. The superiority of negative feedback wasServicio de Publicaciones. Universidad de Murcia. rights reserved. 2004,pp. 197-219208 Trugunf(ean experimental study, conducted by Mackey, Oliver and Leemanthe part of the studentsand phonological feedback than morphosyntactic feedback. In Ohta's workto them by their more participative and motivated partners. Instead, they interpreted theSuch explicit recasts seem toadvantages for those students under treatment. A positive effect for another way of making recasts more salient was obtained by Muranoi (2000) with Japanese EFL learners. In this study, recasts were always preceded by a request for repetition from the learner after errors with the indefinitereceived explicit instruction (or 'debriefing' in the author's terminology) after the recast sessions and this group outperformed the other treatment group which just received explicit recasts andServicio de Publicaciones. Universidad de Murcia. 2004, pp. 197-219915.85'S2004, pp. 197-2192004, pp. 197-219vol. 42004, pp. 197-2192pp. 1972194. texts are manipulated (via6. Recasts are corrective reformulations of a student'sL. Q. (2000). Form-meaning c onnections and the French causative. Studies in Second Language Acquisition, 22, 69-84.(2nd ed.). New York: Holt,instruction andM. Shanvood-Smith (Eds.),7,Quarterly, 32:Swain, M. (1993). Explicit andStudies in Second Language Acquisition, 15,357-386. Celce-Murcia, M. (1991).rights reserved. 2004, pp. 197-219Seconds ystem. Studies in Second Language AcquisitionStudies in Second Language Acquisition,Second Language Acquisition (pp. 3 13-348). Oxford:Harrington, M. (2002). Whatinstruction? A commentary on VanPatten's "Processing instruction: An update". LanguageLearning.second language instruction (pp. 206-257). Cambridge: Cambridge University Press.Doughty, C. Varela, E. (1998). Communicative focus on form. In C. DoughtyWilliams, J. (Eds.) (1998). Focus on form in classroom second language acquisition.Cambridge: Cambridge University Press.N. C.and laboratory experiments. Language Awareness, 4, 123- 146.Ellis, R. Research and Language Teaching. Oxford: Oxford University Press.Language Learning and Teaching. Oxford: Oxford University Press.LanguageLearning, 5 :2,28 1-3 18.Fortune, A. Thorp, D. (2001).collaborative output-1 60.Fotos, S. (2002). Structure-Based Interactive S. Fotos Servicio de Publicaciones. Universidad de Murcia.2004, pp. 197-219216 Trogonr(Eds.), N ew Teaching i n SecondLanguageclassroom (pp. 88-1 15). Cambridge:P. Wilee,J.a ges. Studies in SecondAcquisition. 25,a nd the noticing hypothesis: A n experimental s tudy on ESLJensen, E. D.Learning.tasks toS. (1 985). The input hypothesis:development. Studies in Second382.Long, M. H. (1 990). The least a second language acquisitionlanguage teaching methodology.R. Ginsbergrights reserved. IJES, vol. 4 113371.287.4218 Traganit ype of instruction make a difference? Language Learning, 5 :Sup.1, 157-213.Ohta, A. (2000). Rethinking recasts: A(Eds.), The47-71). Mahwah, NJ: Lawrence Erlbaum. Paradis, M. (1994). Neurolinguistic aspects of implicit and explicit memory: Implications for bilingualism and SLA. In N. C. (pp.sensitiviw forConcordiaUniversity, Montreal.Robinson, P. (1 995). Attention, memory and the 'noticing' hypothesis. L anguage Learning,language rules under implicit, incidental, enhanced, and instructed conditions.Savignon, S. (1972).Philadelphia: Centre for Curriculum Development.applied(pp.3-32). Cambridge: Cambridge University Press.behaviour. Second Language Research, 2, 120-1 59.Sheen, R. (2002). AL anguage Teaching.rights 2004, pp. 197-21921983203.301.243.161.852583625.3253404。

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刊名简称刊名全称ATMOS CHEM PHYS ATMOSPHERIC CHEMISTRY AND PHYSICSB AM METEOROL SOC BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY CLIM DYNAM CLIMATE DYNAMICSCONTRIB MINERAL PETR CONTRIBUTIONS TO MINERALOGY AND PETROLOGY EARTH PLANET SC LETT EARTH AND PLANETARY SCIENCE LETTERSEARTH-SCI REV EARTH-SCIENCE REVIEWSGEOCHIM COSMOCHIM AC GEOCHIMICA ET COSMOCHIMICA ACTAGEOLOGY GEOLOGYGEOTEXT GEOMEMBRANES GEOTEXTILES AND GEOMEMBRANESJ CLIMATE JOURNAL OF CLIMATEJ PETROL JOURNAL OF PETROLOGYLIMNOL OCEANOGR LIMNOLOGY AND OCEANOGRAPHYNAT GEOSCI Nature GeosciencePALEOCEANOGRAPHY PALEOCEANOGRAPHYPRECAMBRIAN RES PRECAMBRIAN RESEARCHQUATERNARY SCI REV QUATERNARY SCIENCE REVIEWSREV GEOPHYS REVIEWS OF GEOPHYSICSGEOPHYS RES LETT GEOPHYSICAL RESEARCH LETTERSJ ATMOS SCI JOURNAL OF THE ATMOSPHERIC SCIENCESJ GEOPHYS RES JOURNAL OF GEOPHYSICAL RESEARCHJ HYDROL JOURNAL OF HYDROLOGYMON WEATHER REV MONTHLY WEATHER REVIEWANNU REV ASTRON ASTR ANNUAL REVIEW OF ASTRONOMY AND ASTROPHYSICS ASTRON ASTROPHYS REV ASTRONOMY AND ASTROPHYSICS REVIEWASTROPHYS J SUPPL S ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES ASTROPHYS J ASTROPHYSICAL JOURNALACM COMPUT SURV ACM COMPUTING SURVEYSACM T GRAPHIC ACM TRANSACTIONS ON GRAPHICSACS NANO ACS NanoACTA BIOMATER Acta BiomaterialiaACTA MATER ACTA MATERIALIAADV APPL MECH ADVANCES IN APPLIED MECHANICSADV BIOCHEM ENG BIOT ADVANCES IN BIOCHEMICAL ENGINEERING / BIOTECHNOL ADV FUNCT MATER ADVANCED FUNCTIONAL MATERIALSADV MATER ADVANCED MATERIALSANNU REV BIOMED ENG ANNUAL REVIEW OF BIOMEDICAL ENGINEERINGANNU REV MATER RES ANNUAL REVIEW OF MATERIALS RESEARCHAPPL SPECTROSC REV APPLIED SPECTROSCOPY REVIEWSARTIF INTELL ARTIFICIAL INTELLIGENCEBIOMATERIALS BIOMATERIALSBIORESOURCE TECHNOL BIORESOURCE TECHNOLOGYBIOSENS BIOELECTRON BIOSENSORS & BIOELECTRONICSBIOTECHNOL ADV BIOTECHNOLOGY ADVANCESBIOTECHNOL BIOENG BIOTECHNOLOGY AND BIOENGINEERINGBIOTECHNOL BIOFUELS Biotechnology for BiofuelsCARBON CARBONCHEM MATER CHEMISTRY OF MATERIALSCOMPUT INTELL COMPUTATIONAL INTELLIGENCECRIT REV BIOTECHNOL CRITICAL REVIEWS IN BIOTECHNOLOGYCRIT REV FOOD SCI CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION CURR OPIN BIOTECH CURRENT OPINION IN BIOTECHNOLOGY ELECTROCHEM COMMUN ELECTROCHEMISTRY COMMUNICATIONSHUM-COMPUT INTERACT HUMAN-COMPUTER INTERACTIONIEEE J SEL AREA COMM IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS IEEE SIGNAL PROC MAG IEEE SIGNAL PROCESSING MAGAZINEIEEE T EVOLUT COMPUT IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION IEEE T IND ELECTRON IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS IEEE T NEURAL NETWOR IEEE TRANSACTIONS ON NEURAL NETWORKSIEEE T PATTERN ANAL IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHIN IEEE T SOFTWARE ENG IEEE TRANSACTIONS ON SOFTWARE ENGINEERINGINT J COMPUT VISION INTERNATIONAL JOURNAL OF COMPUTER VISIONINT J HYDROGEN ENERG INTERNATIONAL JOURNAL OF HYDROGEN ENERGYINT J NONLIN SCI NUM INTERNATIONAL JOURNAL OF NONLINEAR SCIENCES AND INT J PLASTICITY INTERNATIONAL JOURNAL OF PLASTICITYINT MATER REV INTERNATIONAL MATERIALS REVIEWSJ CATAL JOURNAL OF CATALYSISJ HAZARD MATER JOURNAL OF HAZARDOUS MATERIALSJ MATER CHEM JOURNAL OF MATERIALS CHEMISTRYJ MECH BEHAV BIOMED Journal of the Mechanical Behavior of Biomedical J NEURAL ENG Journal of Neural EngineeringJ POWER SOURCES JOURNAL OF POWER SOURCESJ WEB SEMANT Journal of Web SemanticsLAB CHIP LAB ON A CHIPMACROMOL RAPID COMM MACROMOLECULAR RAPID COMMUNICATIONS MACROMOLECULES MACROMOLECULESMAT SCI ENG R MATERIALS SCIENCE & ENGINEERING R-REPORTS MATER TODAY Materials TodayMED IMAGE ANAL MEDICAL IMAGE ANALYSISMETAB ENG METABOLIC ENGINEERINGMIS QUART MIS QUARTERLYMOL NUTR FOOD RES MOLECULAR NUTRITION & FOOD RESEARCHMRS BULL MRS BULLETINNANO LETT NANO LETTERSNANO TODAY Nano TodayNANOMED-NANOTECHNOL Nanomedicine-Nanotechnology Biology and Medicine NANOTECHNOLOGY NANOTECHNOLOGYNAT BIOTECHNOL NATURE BIOTECHNOLOGYNAT MATER NATURE MATERIALSNAT NANOTECHNOL Nature NanotechnologyORG ELECTRON ORGANIC ELECTRONICSP IEEE PROCEEDINGS OF THE IEEEPLASMONICS PlasmonicsPOLYM REV Polymer ReviewsPROG CRYST 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PROCESSINGIND ENG CHEM RES INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCHINT J HEAT MASS TRAN INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER J AM CERAM SOC JOURNAL OF THE AMERICAN CERAMIC SOCIETYJ ELECTROCHEM SOC JOURNAL OF THE ELECTROCHEMICAL SOCIETYJ MEMBRANE SCI JOURNAL OF MEMBRANE SCIENCEMATER LETT MATERIALS LETTERSSCRIPTA MATER SCRIPTA MATERIALIASENSOR ACTUAT B-CHEM SENSORS AND ACTUATORS B-CHEMICALSURF COAT TECH SURFACE & COATINGS TECHNOLOGYSYNTHETIC MET SYNTHETIC METALSTHIN SOLID FILMS THIN SOLID FILMSJ OPER MANAG JOURNAL OF OPERATIONS MANAGEMENTMANAGE SCI MANAGEMENT SCIENCEOMEGA-INT J MANAGE S OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENC PROD OPER MANAG PRODUCTION AND OPERATIONS MANAGEMENTEUR J OPER RES EUROPEAN JOURNAL OF OPERATIONAL RESEARCH ACCOUNTS CHEM RES ACCOUNTS OF CHEMICAL RESEARCHACTA CRYSTALLOGR A ACTA CRYSTALLOGRAPHICA SECTION AALDRICHIM ACTA ALDRICHIMICA ACTAANGEW CHEM INT EDIT ANGEWANDTE CHEMIE-INTERNATIONAL EDITIONANNU REV PHYS CHEM ANNUAL REVIEW OF PHYSICAL 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ENVIRONMENTAL HEALTH PERSPECTIVESENVIRON MICROBIOL ENVIRONMENTAL MICROBIOLOGYEVOLUTION EVOLUTIONFRONT ECOL ENVIRON FRONTIERS IN ECOLOGY AND THE ENVIRONMENT GLOBAL CHANGE BIOL GLOBAL CHANGE BIOLOGYGLOBAL ECOL BIOGEOGR GLOBAL ECOLOGY AND BIOGEOGRAPHYISME J ISME JournalATMOS ENVIRON ATMOSPHERIC ENVIRONMENTCHEMOSPHERE CHEMOSPHEREENVIRON SCI TECHNOL ENVIRONMENTAL SCIENCE & TECHNOLOGYWATER RES WATER RESEARCHADV AGRON ADVANCES IN AGRONOMYAGR FOREST METEOROL AGRICULTURAL AND FOREST METEOROLOGYATLA-ALTERN LAB ANIM ATLA-ALTERNATIVES TO LABORATORY ANIMALSEUR J SOIL SCI EUROPEAN JOURNAL OF SOIL SCIENCEFISH FISH FISH AND FISHERIESFISH OCEANOGR FISHERIES OCEANOGRAPHYFISH SHELLFISH IMMUN FISH & SHELLFISH IMMUNOLOGYFOOD BIOPROCESS TECH Food and Bioprocess TechnologyGEODERMA GEODERMAILAR J ILAR JOURNALJ AGR FOOD CHEM JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRYJ ANIM SCI JOURNAL OF ANIMAL SCIENCEJ DAIRY SCI JOURNAL OF DAIRY SCIENCEMOL BREEDING MOLECULAR BREEDINGREV FISH BIOL FISHER REVIEWS IN FISH BIOLOGY AND FISHERIESSOIL BIOL BIOCHEM SOIL BIOLOGY & BIOCHEMISTRYSOIL SCI SOC AM J SOIL SCIENCE SOCIETY OF AMERICA JOURNALTREE PHYSIOL TREE PHYSIOLOGYVET MICROBIOL VETERINARY MICROBIOLOGYVET RES VETERINARY RESEARCHAQUACULTURE AQUACULTURECAN J FISH AQUAT SCI CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENC FOREST ECOL MANAG FOREST ECOLOGY AND MANAGEMENTJAVMA-J AM VET MED A JAVMA-JOURNAL OF THE AMERICAN VETERINARY MEDICAL PLANT SOIL PLANT AND SOILAM J BIOETHICS AMERICAN JOURNAL OF BIOETHICSECONOMETRICA ECONOMETRICAJ ECONOMETRICS JOURNAL OF ECONOMETRICSAM J HUM GENET AMERICAN JOURNAL OF HUMAN GENETICSANNU REV BIOCHEM ANNUAL REVIEW OF BIOCHEMISTRYANNU REV BIOPH BIOM ANNUAL REVIEW OF BIOPHYSICS AND BIOMOLECULAR STR ANNU REV BIOPHYS Annual Review of BiophysicsANNU REV CELL DEV BI ANNUAL REVIEW OF CELL AND DEVELOPMENTAL BIOLOGY ANNU REV ECOL EVOL S ANNUAL REVIEW OF ECOLOGY EVOLUTION AND SYSTEMATI ANNU REV ENTOMOL ANNUAL REVIEW OF ENTOMOLOGYANNU REV GENET ANNUAL REVIEW OF GENETICSANNU REV 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0163-8998物理1Y11.964 1040-8436物理1Y 5.167 1126-6708物理1Y 6.019 1863-8880物理1Y 5.814 1433-8351物理1Y10.600 0277-7037物理1Y10.623 1749-4885物理1Y22.869 1745-2473物理1Y15.491 0370-1573物理1Y17.752 0031-9007物理1Y7.328 0079-6565物理1Y 6.742 0034-4885物理1Y11.444 0034-6861物理1Y33.145 0003-6951物理2Y 3.554 0021-9606物理2Y 3.093 1098-0121物理2Y 3.475 1550-7998物理2Y 4.922 0169-409X医学1Y11.957 0065-2776医学1Y7.725 0002-9165医学1Y 6.307 0002-9270医学1Y 6.012 0002-953X医学1Y12.522 1073-449X医学1Y10.689 1600-6135医学1Y 6.433 0003-4819医学1Y16.225 0364-5134医学1Y9.317 0003-4967医学1Y8.111 0003-4932医学1Y7.900 0732-0582医学1Y37.902 0066-4219医学1Y9.940 0147-006X医学1Y24.822 0199-9885医学1Y8.783 1553-4006医学1Y13.500 0362-1642医学1Y22.468 0066-4278医学1Y18.170 0066-4308医学1Y22.750 0163-7525医学1Y7.915 0003-990X医学1Y12.257 0003-9926医学1Y9.813 1079-5642医学1Y7.235 0004-3591医学1Y7.332。

项目管理英文术语

职能经理
Functional Organization
职能型组织
Funds
资金
Gantt Chart
甘特图
Goods
货物、物品、商品
Grade
等级
Ground Rules[Tool]
基本规则、条例
Hammock Activity
集合活动
Historical Information
历史信息
Human Resource Planning[Process]
异常报告
Execute
执行
Executing
执行
Executing Processes[Process Group]
执行过程
Execution
执行
Expected Monetary Value（EMV）Analysis
期望货币值分析
Expert Judgment[Technique]
专家判断
Failure Mode and Effect Analysis（FMEA）[Technique]
类比估算
Application Area
应用领域
Apportioned Effort（AE）
分配的工作量
Approval
批准
Approve
批准
Approved Change Request
已批准的变更请求
Arrow
箭线
Arrow Diagramming Method（ADM）
箭线图
As-of Date
变更控制委员会
Change Control System[Tool]
变更控制系统
Change Request

METHOD, COMPUTER-PROGRAM PRODUCT AND SYSTEM FOR DY

专利名称：METHOD, COMPUTER-PROGRAM PRODUCT AND SYSTEM FOR DYNAMICALLYCONTROLLING A FLUIDIC NETWORK发明人：SCHOORENS, Jérôme,SCHOORENS,Jérôme,PERARNAUD, Jean-Jacques,PERARNAUD, Jean-Jacques申请号：EP2017/064215申请日：20170612公开号：WO2017/216080A1公开日：20171221专利内容由知识产权出版社提供专利附图：摘要：The invention relates to a method for dynamically controlling a fluidic network with a supervising module, said method comprising: - an operation-forecasting step that generates a forecast datum relating to operation of said fluidic network; - a step of selecting a control strategy for the fluidic network on the basis of a metrological datum and/or a meteorological datum and/or the forecast datum; - a step of generating setpoints intended for an actuator of a unit for regulating said fluidic network, on the basis of the selected control strategy, the metrological datum or the meteorological datum or the forecast datum; and - transmitting the regulation setpoint to said actuator.申请人：SUEZ GROUPE,SUEZ GROUPE地址：Tour CB 21 - 16, place de l'Iris 92040 PARIS LA DEFENSE CEDEX FR国籍：FR代理人：ARMENGAUD AINE更多信息请下载全文后查看。

eubacterium分类 -回复

eubacterium分类-回复Eubacteria Classification: Exploring the Diversity of the Eubacteria KingdomIntroduction:The classification of living organisms helps scientists understand and organize the vast diversity of species on our planet. One such classification is the categorization of bacteria into different kingdoms. The Eubacteria kingdom, also known as true bacteria, encompasses a wide range of organisms, each with unique characteristics and ecological roles. In this article, we will delve into the classification of Eubacteria, exploring the various groups and their distinguishing features.Historical Background:The study of bacteria classification dates back to the early 17th century when the Dutch scientist Antonie van Leeuwenhoek observed bacteria under a microscope for the first time. However, it was not until the groundbreaking work of the German microbiologist Carl Woese in the 1970s that a better understandingof bacteria classification emerged. Woese proposed a system based on the sequencing of ribosomal RNA (rRNA) genes, which allowed for a more accurate classification of microorganisms.Classification of Eubacteria:The Eubacteria kingdom is divided into multiple phyla, each containing different classes, orders, families, genera, and species. While the exact number of phyla is subject to ongoing research and debate, some of the most well-known and extensively studied phyla include Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes.1. Proteobacteria:The Proteobacteria phylum comprises a diverse group of bacteria with varying shapes and metabolic capabilities. This phylum is subdivided into several classes, including Alpha-, Beta-, Gamma-, Delta-, and Epsilonproteobacteria. Alpha-proteobacteria include several symbiotic and pathogenic species like Rhizobium and Agrobacterium. Beta-proteobacteria often inhabit aquatic environments and include nitrifying bacteria such as Nitrosomonas.Gamma-proteobacteria include many clinically significant bacteria like Escherichia coli and Pseudomonas aeruginosa. Delta- and Epsilonproteobacteria encompass species capable of inhabiting extreme environments, such as deep-sea hydrothermal vents.2. Firmicutes:The Firmicutes phylum consists of bacteria with a Gram-positive cell wall structure. This phylum is further divided into several classes, including Bacilli and Clostridia. Bacilli include well-known pathogenic species like Staphylococcus and Streptococcus. Moreover, Bacillus subtilis, a species in this class, serves as a model organism for studying bacterial biofilms. Clostridia include notable species such as Clostridium botulinum, responsible for botulism, and Clostridium tetani, the causative agent of tetanus.3. Actinobacteria:The Actinobacteria phylum is known for its filamentous structure and includes many different classes, such as Actinobacteria, Acidimicrobiia, and Thermoleophilia. Actinobacteria, often referred to as Actinomycetes, include numerous species involved in theproduction of antibiotics, such as Streptomyces and Mycobacterium tuberculosis, the bacterium responsible for tuberculosis. Acidimicrobiia and Thermoleophilia comprise thermophilic or acidophilic species found in extreme environments.4. Bacteroidetes:The Bacteroidetes phylum consists of Gram-negative bacteria found in diverse habitats, including soil, water, and the guts of animals. This phylum is characterized by its ability to degrade complex carbohydrates. Notable genera within Bacteroidetes include Bacteroides and Prevotella, which play essential roles in the digestion process within the intestines of humans and animals.Conclusion:The classification of bacteria provides scientists with a systematic approach to identify and study the diverse array of species within the Eubacteria kingdom. This classification allows researchers to understand the ecological significance, evolutionary relationships, and potential applications of different bacterial groups. While the classifications discussed in this article are just a glimpse into thevast diversity present in the Eubacteria kingdom, they provide an important foundation for further exploration and understanding of these microscopic organisms.By delving into the classification of Eubacteria, we can gain a deeper appreciation for the intricate and diverse nature of these microorganisms. Advances in molecular techniques and ongoing research will undoubtedly contribute to future refinements in the classification system, providing us with an even more precise understanding of the bacterial world.。

微生物屏障试验 DIN 58953-6_2010 Test report

Interlaboratory T est …Microbial barrier testing of packa ging materials for medical devices which are tobe ster ili ze d“according to DIN 58953-6:2010Test re portJanuary 2013Author: Daniel ZahnISEGA Forschungs- und Untersuchungsgesellschaft mbHTest report Page 2 / 15Table of contentsSeite1.General information on the Interlaboratory Test (3)1.1 Organization (3)1.2 Occasion and Objective (3)1.3 Time Schedule (3)1.4 Participants (4)2.Sample material (4)2.1 Sample Description and Execution of the Test (4)2.1.1 Materials for the Analysis of the Germ Proofness under Humidityaccording to DIN 58953-6, section 3 (5)2.1.2 Materials for the Analysis of the Germ Proofness with Air Permeanceaccording to DIN 58953-6, section 4 (5)2.2 Sample Preparation and Despatch (5)2.3 Additional Sample and Re-examination (6)3.Results (6)3.1 Preliminary Remark (6)3.2 Note on the Record of Test Results (6)3.3 Comment on the Statistical Evaluation (6)3.4 Outlier tests (7)3.5 Record of Test Results (7)3.5.1 Record of Test Results Sample F1 (8)3.5.2 Record of Test Results Sample F2 (9)3.5.3 Record of Test Results Sample F3 (10)3.5.4 Record of Test Results Sample L1 (11)3.5.5 Record of Test Results Sample L2 (12)3.5.6 Record of Test Results Sample L3 (13)3.5.7 Record of Test Results Sample L4 (14)4.Overview and Summary (15)Test report Page 3 / 15 1. General Information on the Interlaboratory Test1.1 OrganizationOrganizer of the Interlaboratory Test:Sterile Barrier Association (SBA)Mr. David Harding (director.general@)Pennygate House, St WeonardsHerfordshire HR2 8PT / Great BritainRealization of the Interlaboratory Test:Verein zur Förderung der Forschung und Ausbildung fürFaserstoff- und Verpackungschemie e. V. (VFV)vfv@isega.dePostfach 10 11 0963707 Aschaffenburg / GermanyTechnical support:ISEGA Forschungs- u. Untersuchungsgesellschaft mbHDr. Julia Riedlinger / Mr. Daniel Zahn (info@isega.de)Zeppelinstraße 3 – 563741 Aschaffenburg / Germany1.2 Occasion and ObjectiveIn order to demonstrate compliance with the requirements of the ISO 11607-1:2006 …Packaging for terminally sterilized medical devices -- Part 1: Requirements for materials, sterile barrier systems and packaging systems“ validated test methods are to be preferably utilized.For the confirmation of the microbial barrier properties of porous materials demanded in the ISO 11607-1, the DIN 58953-6:2010 …Sterilization – Sterile supply – Part 6: Microbial barrier testing of packaging materials for medical devices which are to be sterilized“ represents a conclusive method which can be performed without the need for extensive equipment.However, since momentarily no validation data on DIN 58953-6 is at hand concerns emerged that the method may lose importance against validated methods in a revision of the ISO 11607-1 or may even not be considered at all.Within the framework of this interlaboratory test, data on the reproducibility of the results obtained by means of the analysis according to DIN 58953-6 shall be gathered.1.3 Time ScheduleSeptember 2010:The Sterile Barrier Association queried ISEGA Forschungs- und Unter-suchungsgesellschaft about the technical support for the interlaboratory test.For the realization, the Verein zur Förderung der Forschung und Ausbildungfür Faserstoff- und Verpackungschemie e. V. (VFV) was won over.November 2010: Preliminary announcement of the interlaboratory test / Seach for interested laboratoriesTest report Page 4 / 15 January toDecember 2011: Search for suitable sample material / Carrying out of numerous pre-trials on various materialsJanuary 2012:Renewed contact or search for additional interested laboratories, respectively February 2012: Sending out of registration forms / preparation of sample materialMarch 2012: Registration deadline / sample despatchMay / June 2012: Results come in / statistical evaluationJuly 2012: Despatch of samples for the re-examinationSeptember 2012: Results of the re-examination come in / statistical evaluationNovember 2012: Results are sent to the participantsDecember 2012/January 2013: Compilation of the test report1.4 ParticipantsFive different German laboratories participated in the interlaboratory test. In one laboratory, the analyses were performed by two testers working independently so that six valid results overall were received which can be taken into consideration in the evaluation.To ensure an anonymous evaluation of the results, each participant was assigned a laboratory number (laboratory 1 to laboratory 6) in random order, which was disclosed only to the laboratory in question. The complete laboratory number breakdown was known solely by the ISEGA staff supporting the proficiency test.2. Sample Material2.1 Sample Description and Execution of the TestUtmost care in the selection of suitable sample material was taken to include different materials used in the manufacture of packaging for terminally sterilized medical devices.With the help of numerous pre-trials the materials were chosen covering a wide range of results from mostly germ-proof samples to germ permeable materials.Test report Page 5 / 15 2.1.1 Materials for the Analysis of Germ Proofness under Humidity according to DIN 58953-6, section 3:The participants were advised to perform the analysis on the samples according to DIN 58953-6, section 3, and to protocol their findings on the provided result sheets.The only deviation from the norm was that in case of the growth of 1 -5 colony-forming units (in the following abbreviated as CFU) per sample, no re-examination 20 test pieces was performed.2.1.2 Materials for the Analysis of Germ Proofness with Air Permeance according to DIN 58953-6, section 4:The participants were advised to perform the analysis on the samples according to DIN 58953-6, section 4, and to protocol their findings on the provided result sheets.2.2 Sample Preparation and DespatchFor the analysis of the germ proofness under humidity, 10 test pieces in the size of 50 x 50 mm were cut out of each sample and heat-sealed into a sterilization pouch with the side to be tested up.Out of the 10 test pieces, 5 were intended for the testing and one each for the two controls according to DIN 58953-6, sections 3.6.2 and 3.6.3. The rest should remain as replacements (e.g. in case of the dropping of a test piece on the floor etc.).For the analysis of the germ proofness with air permeance, 15 circular test pieces with a diameter of 40 mm were punched out of each sample and heat-sealed into a sterilization pouch with the side to be tested up.Test report Page 6 / 15 Out of the 15 test pieces, 10 were intended for the testing and one each for the two controls according to DIN 58953-6, section 4.9. The rest should remain as replacements (e.g. in case of the dropping of a test piece on the floor etc.).The sterilization pouches with the test pieces were steam-sterilized in an autoclave for 15 minutes at 121 °C and stored in an climatic room at 23 °C and 50 % relative humidity until despatch.2.3 Additional Sample and Re-examinationFor the analysis of the germ proofness under humidity another test round was performed in July / August 2012. For this, an additional sample (sample L4) was sent to the laboratories and analysed (see 2.1.2). The results were considered in the evaluation.For validation or confirmation of non-plausible results, occasional samples for re-examination were sent out to the laboratories. The results of these re-examinations (July / August 2012) were not taken into consideration in the evaluation.3. Results3.1 Preliminary RemarkSince the analysis of germ proofness is designed to be a pass / fail – test, the statistical values and precision data were meant only to serve informative purposes.The evaluation of the materials according to DIN58953-6,sections 3.7and 4.7.6by the laboratories should be the most decisive criterion for the evaluation of reproducibility of the interlaboratory test results. Based on this, the classification of a sample as “sufficiently germ-proof” or “not sufficiently germ-proof” is carried out.3.2 Note on the Record of Test Results:The exact counting of individual CFUs is not possible with the required precision if the values turn out to be very high. Thus, an upper limit of 100 CFU per agar plate or per test pieces, respectively, was defined. Individual values above this limit and values which were stated with “> 100” by the laboratories, are listed as 100 CFU per agar plate or per test piece, respectively, in the evaluation.Test report Page 7 / 153.3 Comment on the Statistical EvaluationThe statistical evaluation was done based on the series of standards DIN ISO 5725-1ff.The arithmetic laboratory mean X i and the laboratory standard deviation s i were calculated from the individual measurement values obtained by the laboratories.The overall mean X of the laboratory means as well as the precision data of the method (reproducibility and repeatability) were determined for each sample3.4 Outlier testsThe Mandel's h-statistics test was utilised as outlier test for differences between the laboratory means of the participants.A laboratory was identified as a “statistical outlier” as soon as an exceedance of Mandel's h test statistic at the 1 % significance level was detected.The respective results of the laboratories identified as outliers were not considered in the statistical evaluation.3.5 Record of Test ResultsOn the following pages, the records of the test results for each interlaboratory test sample with the statistical evaluation and the evaluation according to DIN 58953-6 are compiled.Test report Page 8 / 153.5.1 Record of Test Results Sample F1Individual Measurement values:Statistical Evaluation:Comment:Laboratory 4, as an outlier, has not been taken into consideration in the statistical Evaluation.Outlier criterion: Mandel's h-statistics (1 % level of significance)Overall mean X:91.0CFU / agar plateRepeatability standard deviation s r:17.9CFU / agar plateReproducibility standard deviation s R:19.8CFU / agar plateRepeatability r:50.0CFU / agar plateRepeatability coefficient of variation:19.6%Reproducibility R:55.5CFU / agar plateReproducibility coefficient of variation:21.8%Evaluation according to DIN 58953-6, Section 3.7:Lab. 1 - 6:Number of CFU > 5, i.e. the material is classified as not sufficiently germ-proof.Conclusion:All of the participants, even the Laboratory 4 which was identified as an outlier, came to the same results and would classify the sample material as “not sufficiently germ-proof”Test report Page 9 / 153.5.2 Record of Test Results Sample F2Individual Measurement values:Statistical Evaluation:Comment:Laboratory 4, as an outlier, has not been taken into consideration in the statistical Evaluation.Outlier criterion: Mandel's h-statistics (1 % level of significance)Overall mean X:0CFU / agar plateRepeatability standard deviation s r:0CFU / agar plateReproducibility standard deviation s R:0CFU / agar plateRepeatability r:0CFU / agar plateRepeatability coefficient of variation:0%Reproducibility R:0CFU / agar plateReproducibility coefficient of variation:0%Evaluation according to DIN 58953-6, Section 3.7:Lab. 1 – 3:Number of CFU = 0, i.e. the material is classified as sufficiently germ-proofLab. 4:Number of CFU ≤ 5, i.e. a re-examination on 20 test pieces would have to be done Lab. 5 – 6:Number of CFU = 0, i.e. the material is classified as sufficiently germ-proofConclusion:All of the participants, except for the Laboratory 4 which was identified as an outlier, came to the same results and would classify the sample material as “sufficiently germ-proof”.Test report Page 10 / 153.5.3 Record of Test Results Sample F3Individual Measurement values:Statistical Evaluation:Overall mean X:30.1CFU / agar plateRepeatability standard deviation s r:17.2CFU / agar plateReproducibility standard deviation s R:30.9CFU / agar plateRepeatability r:48.2CFU / agar plateRepeatability coefficient of variation:57.1%Reproducibility R:86.5CFU / agar plateReproducibility coefficient of variation:103%Evaluation according to DIN 58953-6, Section 3.7:Lab. 1 - 4:Number of CFU > 5, i.e. the material is classified as not sufficiently germ-proof. Lab. 5:Number of CFU = 0, i.e. the material is classified as sufficiently germ-proof. Lab. 6:Number of CFU > 5, i.e. the material is classified as not sufficiently germ-proof.Conclusion:Five of the six participants came to the same result and would classify the sample as “not sufficiently germ-proof”. Only laboratory 5 would classify the sample material as “sufficiently germ-proof”.Test report Page 11 / 153.5.4 Record of Test Results Sample L1Individual Measurement values:Statistical Evaluation:Overall mean X:0.09CFU / test pieceRepeatability standard deviation s r:0.32CFU / test pieceReproducibility standard deviation s R:0.33CFU / test pieceRepeatability r:0.91CFU / test pieceRepeatability coefficient of variation:357%Reproducibility R:0.93CFU / test pieceReproducibility coefficient of variation:366%Evaluation according to DIN 58953-6, Section 4.7:Lab. 1 - 6:Number of CFU < 15, i.e. the material is classified as sufficiently germ-proof.Conclusion:All participants came to the same result and would classify the sample as “sufficiently germ-proof”.Test report Page 12 / 153.5.5 Record of Test Results Sample L2Individual Measurement values:Statistical Evaluation:Overall mean X:0.73CFU / test pieceRepeatability standard deviation s r: 1.10CFU / test pieceReproducibility standard deviation s R: 1.18CFU / test pieceRepeatability r: 3.07CFU / test pieceRepeatability coefficient of variation:151%Reproducibility R: 3.32CFU / test pieceReproducibility coefficient of variation:163%Evaluation according to DIN 58953-6, Section 4.7:Lab. 1:Number of CFU > 15, i.e. the material is classified as not sufficiently germ-proof. Lab. 2 - 6:Number of CFU < 15, i.e. the material is classified as sufficiently germ-proof.Conclusion:Five of the six participants came to the same result and would classify the sample as “sufficiently germ-proof”. Only laboratory 1 exceeds the limit value slightly by 1 CFU, so that the sample would be classified as “not sufficiently germ-proof”.Test report Page 13 / 153.5.6 Record of Test Results Sample L3Individual Measurement values:Statistical Evaluation:Overall mean X:0.36CFU / test pieceRepeatability standard deviation s r: 1.00CFU / test pieceReproducibility standard deviation s R: 1.06CFU / test pieceRepeatability r: 2.79CFU / test pieceRepeatability coefficient of variation:274%Reproducibility R: 2.98CFU / test pieceReproducibility coefficient of variation:293%Evaluation according to DIN 58953-6, Section 4.7:Lab. 1 - 6:Number of CFU < 15, i.e. the material is classified as sufficiently germ-proof.Conclusion:All participants came to the same result and would classify the sample as “sufficiently germ-proof”.Test report Page 14 / 153.5.7 Record of Test Results Sample L4Individual Measurement values:Statistical Evaluation:Overall mean X:35.1CFU / test pieceRepeatability standard deviation s r:18.8CFU / test pieceReproducibility standard deviation s R:42.6CFU / test pieceRepeatability r:52.7CFU / test pieceRepeatability coefficient of variation:53.7%Reproducibility R:119CFU / test pieceReproducibility coefficient of variation:122%Evaluation according to DIN 58953-6, Section 4.7:Lab. 1 - 3:Number of CFU > 15, i.e. the material is classified as not sufficiently germ-proof. Lab. 4:Number of CFU < 15, i.e. the material is classified as sufficiently germ-proof. Lab. 5 - 6:Number of CFU > 15, i.e. the material is classified as not sufficiently germ-proof.Conclusion:Five of the six participants came to the same result and would classify the sample as“not sufficiently germ-proof”.Test report Page 15 / 15 4. Overview and SummarySummary:In case of four of the overall seven tested materials, a 100 % consensus was reached regarding the evaluation as“sufficiently germ-proof”and“not sufficiently germ-proof”according to DIN 58 953-6.As for the other three tested materials, there were always 5 concurrent participants out of 6 (83 %). In each case, only one laboratory would have evaluated the sample differently.It is noteworthy that the materials about the evaluation of which a 100 % consensus was reached were the smooth sterilization papers. The differences with one deviating laboratory each occurred with the slightly less homogeneous materials, such as with the creped paper and the nonwoven materials.。

Understanding individual human mobility patterns

a r X i v :0806.1256v 1 [p h y s i c s .s o c -p h ] 7 J u n 2008Understanding individual human mobility patternsMarta C.Gonz´a lez,1,2C´e sar A.Hidalgo,1and Albert-L´a szl´o Barab´a si 1,2,31Center for Complex Network Research and Department of Physics and Computer Science,University of Notre Dame,Notre Dame IN 46556.2Center for Complex Network Research and Department of Physics,Biology and Computer Science,Northeastern University,Boston MA 02115.3Center for Cancer Systems Biology,Dana Farber Cancer Institute,Boston,MA 02115.(Dated:June 7,2008)Despite their importance for urban planning [1],trafﬁc forecasting [2],and the spread of biological [3,4,5]and mobile viruses [6],our understanding of the basic laws govern-ing human motion remains limited thanks to the lack of tools to monitor the time resolved location of individuals.Here we study the trajectory of 100,000anonymized mobile phone users whose position is tracked for a six month period.We ﬁnd that in contrast with the random trajectories predicted by the prevailing L´e vy ﬂight and random walk models [7],human trajectories show a high degree of temporal and spatial regularity,each individual being characterized by a time independent characteristic length scale and a signiﬁcant prob-ability to return to a few highly frequented locations.After correcting for differences in travel distances and the inherent anisotropy of each trajectory,the individual travel patterns collapse into a single spatial probability distribution,indicating that despite the diversity of their travel history,humans follow simple reproducible patterns.This inherent similarity in travel patterns could impact all phenomena driven by human mobility,from epidemic prevention to emergency response,urban planning and agent based modeling.Given the many unknown factors that inﬂuence a population’s mobility patterns,ranging from means of transportation to job and family imposed restrictions and priorities,human trajectories are often approximated with various random walk or diffusion models [7,8].Indeed,early mea-surements on albatrosses,bumblebees,deer and monkeys [9,10]and more recent ones on marine predators [11]suggested that animal trajectory is approximated by a L´e vy ﬂight [12,13],a random walk whose step size ∆r follows a power-law distribution P (∆r )∼∆r −(1+β)with β<2.While the L´e vy statistics for some animals require further study [14],Brockmann et al.[7]generalized this ﬁnding to humans,documenting that the distribution of distances between consecutive sight-ings of nearly half-million bank notes is fat tailed.Given that money is carried by individuals, bank note dispersal is a proxy for human movement,suggesting that human trajectories are best modeled as a continuous time random walk with fat tailed displacements and waiting time dis-tributions[7].A particle following a L´e vyﬂight has a signiﬁcant probability to travel very long distances in a single step[12,13],which appears to be consistent with human travel patterns:most of the time we travel only over short distances,between home and work,while occasionally we take longer trips.Each consecutive sightings of a bank note reﬂects the composite motion of two or more indi-viduals,who owned the bill between two reported sightings.Thus it is not clear if the observed distribution reﬂects the motion of individual users,or some hitero unknown convolution between population based heterogeneities and individual human trajectories.Contrary to bank notes,mo-bile phones are carried by the same individual during his/her daily routine,offering the best proxy to capture individual human trajectories[15,16,17,18,19].We used two data sets to explore the mobility pattern of individuals.Theﬁrst(D1)consists of the mobility patterns recorded over a six month period for100,000individuals selected randomly from a sample of over6million anonymized mobile phone users.Each time a user initiates or receives a call or SMS,the location of the tower routing the communication is recorded,allowing us to reconstruct the user’s time resolved trajectory(Figs.1a and b).The time between consecutive calls follows a bursty pattern[20](see Fig.S1in the SM),indicating that while most consecutive calls are placed soon after a previous call,occasionally there are long periods without any call activity.To make sure that the obtained results are not affected by the irregular call pattern,we also study a data set(D2)that captures the location of206mobile phone users,recorded every two hours for an entire week.In both datasets the spatial resolution is determined by the local density of the more than104mobile towers,registering movement only when the user moves between areas serviced by different towers.The average service area of each tower is approximately3km2 and over30%of the towers cover an area of1km2or less.To explore the statistical properties of the population’s mobility patterns we measured the dis-tance between user’s positions at consecutive calls,capturing16,264,308displacements for the D1and10,407displacements for the D2datasets.Weﬁnd that the distribution of displacements over all users is well approximated by a truncated power-lawP(∆r)=(∆r+∆r0)−βexp(−∆r/κ),(1)withβ=1.75±0.15,∆r0=1.5km and cutoff valuesκ|D1=400km,andκ|D2=80km(Fig.1c,see the SM for statistical validation).Note that the observed scaling exponent is not far fromβB=1.59observed in Ref.[7]for bank note dispersal,suggesting that the two distributions may capture the same fundamental mechanism driving human mobility patterns.Equation(1)suggests that human motion follows a truncated L´e vyﬂight[7].Yet,the observed shape of P(∆r)could be explained by three distinct hypotheses:A.Each individual follows a L´e vy trajectory with jump size distribution given by(1).B.The observed distribution captures a population based heterogeneity,corresponding to the inherent differences between individuals.C.A population based heterogeneity coexists with individual L´e vy trajectories,hence(1)represents a convolution of hypothesis A and B.To distinguish between hypotheses A,B and C we calculated the radius of gyration for each user(see Methods),interpreted as the typical distance traveled by user a when observed up to time t(Fig.1b).Next,we determined the radius of gyration distribution P(r g)by calculating r g for all users in samples D1and D2,ﬁnding that they also can be approximated with a truncated power-lawP(r g)=(r g+r0g)−βr exp(−r g/κ),(2) with r0g=5.8km,βr=1.65±0.15andκ=350km(Fig.1d,see SM for statistical validation). L´e vyﬂights are characterized by a high degree of intrinsic heterogeneity,raising the possibility that(2)could emerge from an ensemble of identical agents,each following a L´e vy trajectory. Therefore,we determined P(r g)for an ensemble of agents following a Random Walk(RW), L´e vy-Flight(LF)or Truncated L´e vy-Flight(T LF)(Figure1d)[8,12,13].Weﬁnd that an en-semble of L´e vy agents display a signiﬁcant degree of heterogeneity in r g,yet is not sufﬁcient to explain the truncated power law distribution P(r g)exhibited by the mobile phone users.Taken together,Figs.1c and d suggest that the difference in the range of typical mobility patterns of indi-viduals(r g)has a strong impact on the truncated L´e vy behavior seen in(1),ruling out hypothesis A.If individual trajectories are described by a LF or T LF,then the radius of gyration should increase in time as r g(t)∼t3/(2+β)[21,22]while for a RW r g(t)∼t1/2.That is,the longer we observe a user,the higher the chances that she/he will travel to areas not visited before.To check the validity of these predictions we measured the time dependence of the radius of gyration for users whose gyration radius would be considered small(r g(T)≤3km),medium(20<r g(T)≤30km)or large(r g(T)>100km)at the end of our observation period(T=6months).Theresults indicate that the time dependence of the average radius of gyration of mobile phone users is better approximated by a logarithmic increase,not only a manifestly slower dependence than the one predicted by a power law,but one that may appear similar to a saturation process(Fig.2a and Fig.S4).In Fig.2b,we have chosen users with similar asymptotic r g(T)after T=6months,and measured the jump size distribution P(∆r|r g)for each group.As the inset of Fig.2b shows,users with small r g travel mostly over small distances,whereas those with large r g tend to display a combination of many small and a few larger jump sizes.Once we rescale the distributions with r g(Fig.2b),weﬁnd that the data collapses into a single curve,suggesting that a single jump size distribution characterizes all users,independent of their r g.This indicates that P(∆r|r g)∼r−αg F(∆r/r g),whereα≈1.2±0.1and F(x)is an r g independent function with asymptotic behavior F(x<1)∼x−αand rapidly decreasing for x≫1.Therefore the travel patterns of individual users may be approximated by a L´e vyﬂight up to a distance characterized by r g. Most important,however,is the fact that the individual trajectories are bounded beyond r g,thus large displacements which are the source of the distinct and anomalous nature of L´e vyﬂights, are statistically absent.To understand the relationship between the different exponents,we note that the measured probability distributions are related by P(∆r)= ∞0P(∆r|r g)P(r g)dr g,whichsuggests(see SM)that up to the leading order we haveβ=βr+α−1,consistent,within error bars, with the measured exponents.This indicates that the observed jump size distribution P(∆r)is in fact the convolution between the statistics of individual trajectories P(∆r g|r g)and the population heterogeneity P(r g),consistent with hypothesis C.To uncover the mechanism stabilizing r g we measured the return probability for each indi-vidual F pt(t)[22],deﬁned as the probability that a user returns to the position where it was ﬁrst observed after t hours(Fig.2c).For a two dimensional random walk F pt(t)should follow ∼1/(t ln(t)2)[22].In contrast,weﬁnd that the return probability is characterized by several peaks at24h,48h,and72h,capturing a strong tendency of humans to return to locations they visited before,describing the recurrence and temporal periodicity inherent to human mobility[23,24].To explore if individuals return to the same location over and over,we ranked each location based on the number of times an individual was recorded in its vicinity,such that a location with L=3represents the third most visited location for the selected individual.Weﬁnd that the probability ofﬁnding a user at a location with a given rank L is well approximated by P(L)∼1/L, independent of the number of locations visited by the user(Fig.2d).Therefore people devote mostof their time to a few locations,while spending their remaining time in5to50places,visited with diminished regularity.Therefore,the observed logarithmic saturation of r g(t)is rooted in the high degree of regularity in their daily travel patterns,captured by the high return probabilities(Fig.2b) to a few highly frequented locations(Fig.2d).An important quantity for modeling human mobility patterns is the probabilityΦa(x,y)toﬁnd an individual a in a given position(x,y).As it is evident from Fig.1b,individuals live and travel in different regions,yet each user can be assigned to a well deﬁned area,deﬁned by home and workplace,where she or he can be found most of the time.We can compare the trajectories of different users by diagonalizing each trajectory’s inertia tensor,providing the probability ofﬁnding a user in a given position(see Fig.3a)in the user’s intrinsic reference frame(see SM for the details).A striking feature ofΦ(x,y)is its prominent spatial anisotropy in this intrinsic reference frame(note the different scales in Fig3a),and weﬁnd that the larger an individual’s r g the more pronounced is this anisotropy.To quantify this effect we deﬁned the anisotropy ratio S≡σy/σx, whereσx andσy represent the standard deviation of the trajectory measured in the user’s intrinsic reference frame(see SM).Weﬁnd that S decreases monotonically with r g(Fig.3c),being well approximated with S∼r−ηg,forη≈0.12.Given the small value of the scaling exponent,other functional forms may offer an equally goodﬁt,thus mechanistic models are required to identify if this represents a true scaling law,or only a reasonable approximation to the data.To compare the trajectories of different users we remove the individual anisotropies,rescal-ing each user trajectory with its respectiveσx andσy.The rescaled˜Φ(x/σx,y/σy)distribution (Fig.3b)is similar for groups of users with considerably different r g,i.e.,after the anisotropy and the r g dependence is removed all individuals appear to follow the same universal˜Φ(˜x,˜y)prob-ability distribution.This is particularly evident in Fig.3d,where we show the cross section of ˜Φ(x/σ,0)for the three groups of users,ﬁnding that apart from the noise in the data the curves xare indistinguishable.Taken together,our results suggest that the L´e vy statistics observed in bank note measurements capture a convolution of the population heterogeneity(2)and the motion of individual users.Indi-viduals display signiﬁcant regularity,as they return to a few highly frequented locations,like home or work.This regularity does not apply to the bank notes:a bill always follows the trajectory of its current owner,i.e.dollar bills diffuse,but humans do not.The fact that individual trajectories are characterized by the same r g-independent two dimen-sional probability distribution˜Φ(x/σx,y/σy)suggests that key statistical characteristics of indi-vidual trajectories are largely indistinguishable after rescaling.Therefore,our results establish the basic ingredients of realistic agent based models,requiring us to place users in number propor-tional with the population density of a given region and assign each user an r g taken from the observed P(r g)ing the predicted anisotropic rescaling,combined with the density function˜Φ(x,y),whose shape is provided as Table1in the SM,we can obtain the likelihood ofﬁnding a user in any location.Given the known correlations between spatial proximity and social links,our results could help quantify the role of space in network development and evolu-tion[25,26,27,28,29]and improve our understanding of diffusion processes[8,30].We thank D.Brockmann,T.Geisel,J.Park,S.Redner,Z.Toroczkai and P.Wang for discus-sions and comments on the manuscript.This work was supported by the James S.McDonnell Foundation21st Century Initiative in Studying Complex Systems,the National Science Founda-tion within the DDDAS(CNS-0540348),ITR(DMR-0426737)and IIS-0513650programs,and the U.S.Ofﬁce of Naval Research Award N00014-07-C.Data analysis was performed on the Notre Dame Biocomplexity Cluster supported in part by NSF MRI Grant No.DBI-0420980.C.A.Hi-dalgo acknowledges support from the Kellogg Institute at Notre Dame.Supplementary Information is linked to the online version of the paper at /nature.Author Information Correspondence and requests for materials should be addressed to A.-L.B.(e-mail:alb@)[1]Horner,M.W.&O’Kelly,M.E.S Embedding economies of scale concepts for hub networks design.Journal of Transportation Geography9,255-265(2001).[2]Kitamura,R.,Chen,C.,Pendyala,R.M.&Narayaran,R.Micro-simulation of daily activity-travelpatterns for travel demand forecasting.Transportation27,25-51(2000).[3]Colizza,V.,Barrat,A.,Barth´e l´e my,M.,Valleron,A.-J.&Vespignani,A.Modeling the WorldwideSpread of Pandemic Inﬂuenza:Baseline Case and Containment Interventions.PLoS Medicine4,095-0110(2007).[4]Eubank,S.,Guclu,H.,Kumar,V.S.A.,Marathe,M.V.,Srinivasan,A.,Toroczkai,Z.&Wang,N.Controlling Epidemics in Realistic Urban Social Networks.Nature429,180(2004).[5]Hufnagel,L.,Brockmann,D.&Geisel,T.Forecast and control of epidemics in a globalized world.Proceedings of the National Academy of Sciences of the United States of America101,15124-15129 (2004).[6]Kleinberg,J.The wireless epidemic.Nature449,287-288(2007).[7] D.Brockmann,D.,Hufnagel,L.&Geisel,T.The scaling laws of human travel.Nature439,462-465(2006).[8]Havlin,S.&ben-Avraham,D.Diffusion in Disordered Media.Advances in Physics51,187-292(2002).[9]Viswanathan,G.M.,Afanasyev,V.,Buldyrev,S.V.,Murphy,E.J.,Prince,P.A.&Stanley,H.E.L´e vyFlight Search Patterns of Wandering Albatrosses.Nature381,413-415(1996).[10]Ramos-Fernandez,G.,Mateos,J.L.,Miramontes,O.,Cocho,G.,Larralde,H.&Ayala-Orozco,B.,L´e vy walk patterns in the foraging movements of spider monkeys(Ateles geoffroyi).Behavioral ecol-ogy and Sociobiology55,223-230(2004).[11]Sims D.W.et al.Scaling laws of marine predator search behaviour.Nature451,1098-1102(2008).[12]Klafter,J.,Shlesinger,M.F.&Zumofen,G.Beyond Brownian Motion.Physics Today49,33-39(1996).[13]Mantegna,R.N.&Stanley,H.E.Stochastic Process with Ultraslow Convergence to a Gaussian:TheTruncated L´e vy Flight.Physical Review Letters73,2946-2949(1994).[14]Edwards,A.M.,Phillips,R.A.,Watkins,N.W.,Freeman,M.P.,Murphy,E.J.,Afanasyev,V.,Buldyrev,S.V.,da Luz,M.G.E.,Raposo,E.P.,Stanley,H.E.&Viswanathan,G.M.Revisiting L´e vyﬂightsearch patterns of wandering albatrosses,bumblebees and deer.Nature449,1044-1049(2007). [15]Sohn,T.,Varshavsky,A.,LaMarca,A.,Chen,M.Y.,Choudhury,T.,Smith,I.,Consolvo,S.,High-tower,J.,Griswold,W.G.&de Lara,E.Lecture Notes in Computer Sciences:Proc.8th International Conference UbiComp2006.(Springer,Berlin,2006).[16]Onnela,J.-P.,Saram¨a ki,J.,Hyv¨o nen,J.,Szab´o,G.,Lazer,D.,Kaski,K.,Kert´e sz,K.&Barab´a si A.L.Structure and tie strengths in mobile communication networks.Proceedings of the National Academy of Sciences of the United States of America104,7332-7336(2007).[17]Gonz´a lez,M.C.&Barab´a si,plex networks:From data to models.Nature Physics3,224-225(2007).[18]Palla,G.,Barab´a si,A.-L.&Vicsek,T.Quantifying social group evolution.Nature446,664-667(2007).[19]Hidalgo C.A.&Rodriguez-Sickert C.The dynamics of a mobile phone network.Physica A387,3017-30224.[20]Barab´a si,A.-L.The origin of bursts and heavy tails in human dynamics.Nature435,207-211(2005).[21]Hughes,B.D.Random Walks and Random Environments.(Oxford University Press,USA,1995).[22]Redner,S.A Guide to First-Passage Processes.(Cambridge University Press,UK,2001).[23]Schlich,R.&Axhausen,K.W.Habitual travel behaviour:Evidence from a six-week travel diary.Transportation30,13-36(2003).[24]Eagle,N.&Pentland,A.Eigenbehaviours:Identifying Structure in Routine.submitted to BehavioralEcology and Sociobiology(2007).[25]Yook,S.-H.,Jeong,H.&Barab´a si A.L.Modeling the Internet’s large-scale topology.Proceedings ofthe Nat’l Academy of Sciences99,13382-13386(2002).[26]Caldarelli,G.Scale-Free Networks:Complex Webs in Nature and Technology.(Oxford UniversityPress,USA,2007).[27]Dorogovtsev,S.N.&Mendes,J.F.F.Evolution of Networks:From Biological Nets to the Internet andWWW.(Oxford University Press,USA,2003).[28]Song C.M.,Havlin S.&Makse H.A.Self-similarity of complex networks.Nature433,392-395(2005).[29]Gonz´a lez,M.C.,Lind,P.G.&Herrmann,H.J.A system of mobile agents to model social networks.Physical Review Letters96,088702(2006).[30]Cecconi,F.,Marsili,M.,Banavar,J.R.&Maritan,A.Diffusion,peer pressure,and tailed distributions.Physical Review Letters89,088102(2002).FIG.1:Basic human mobility patterns.a,Week-long trajectory of40mobile phone users indicate that most individuals travel only over short distances,but a few regularly move over hundreds of kilometers. Panel b,displays the detailed trajectory of a single user.The different phone towers are shown as green dots,and the V oronoi lattice in grey marks the approximate reception area of each tower.The dataset studied by us records only the identity of the closest tower to a mobile user,thus we can not identify the position of a user within a V oronoi cell.The trajectory of the user shown in b is constructed from186 two hourly reports,during which the user visited a total of12different locations(tower vicinities).Among these,the user is found96and67occasions in the two most preferred locations,the frequency of visits for each location being shown as a vertical bar.The circle represents the radius of gyration centered in the trajectory’s center of mass.c,Probability density function P(∆r)of travel distances obtained for the two studied datasets D1and D2.The solid line indicates a truncated power law whose parameters are provided in the text(see Eq.1).d,The distribution P(r g)of the radius of gyration measured for the users, where r g(T)was measured after T=6months of observation.The solid line represent a similar truncated power lawﬁt(see Eq.2).The dotted,dashed and dot-dashed curves show P(r g)obtained from the standard null models(RW,LF and T LF),where for the T LF we used the same step size distribution as the onemeasured for the mobile phone users.FIG.2:The bounded nature of human trajectories.a,Radius of gyration, r g(t) vs time for mobile phone users separated in three groups according to theirﬁnal r g(T),where T=6months.The black curves correspond to the analytical predictions for the random walk models,increasing in time as r g(t) |LF,T LF∼t3/2+β(solid),and r g(t) |RW∼t0.5(dotted).The dashed curves corresponding to a logarithmicﬁt of the form A+B ln(t),where A and B depend on r g.b,Probability density function of individual travel distances P(∆r|r g)for users with r g=4,10,40,100and200km.As the inset shows,each group displays a quite different P(∆r|r g)distribution.After rescaling the distance and the distribution with r g(main panel),the different curves collapse.The solid line(power law)is shown as a guide to the eye.c,Return probability distribution,F pt(t).The prominent peaks capture the tendency of humans to regularly return to the locations they visited before,in contrast with the smooth asymptotic behavior∼1/(t ln(t)2)(solid line)predicted for random walks.d,A Zipf plot showing the frequency of visiting different locations.The symbols correspond to users that have been observed to visit n L=5,10,30,and50different locations.Denoting with(L)the rank of the location listed in the order of the visit frequency,the data is well approximated by R(L)∼L−1. The inset is the same plot in linear scale,illustrating that40%of the time individuals are found at theirﬁrsttwo preferred locations.FIG.3:The shape of human trajectories.a,The probability density functionΦ(x,y)ofﬁnding a mobile phone user in a location(x,y)in the user’s intrinsic reference frame(see SM for details).The three plots, from left to right,were generated for10,000users with:r g≤3,20<r g≤30and r g>100km.The trajectories become more anisotropic as r g increases.b,After scaling each position withσx andσy theresulting˜Φ(x/σx,y/σy)has approximately the same shape for each group.c,The change in the shape of Φ(x,y)can be quantiﬁed calculating the isotropy ratio S≡σy/σx as a function of r g,which decreases as S∼r−0.12(solid line).Error bars represent the standard error.d,˜Φ(x/σx,0)representing the x-axis cross gsection of the rescaled distribution˜Φ(x/σx,y/σy)shown in b.。

黑曲霉固体发酵工艺及有效活菌数

黑曲霉固体发酵工艺及有效活菌数检测作者：2006级生物工程专业刘强指导教师：杜志兵工程师摘要：本实验旨在利用微生物固体发酵技术，以廉价农产品副产物作为发酵培养基,大量制备黑曲霉菌体，用于有机物料腐熟剂的生产，并检测产品的有效活菌数。

首先以济宁三环化工生产用黑曲霉菌种作为原始菌种，采用平板划线技术，进行菌种的分离筛选；将获得的纯系菌株接入豆芽汁液体培养基中，开始摇瓶扩大培养；然后选择合适的摇瓶培养物作为固体发酵菌种，接入固体发酵基质中，进行曲盒发酵；发酵结束后，黑曲霉生产接种量为1‰。

最后对腐熟剂产品依据GB20287-2006农用微生物菌剂标准中有效活菌数的测定方法进行检测。

结果表明，发酵所产黑曲霉在质量和数量上符合腐熟剂生产标准，产品有效活菌数检测结果符合行业标准的规定，且操作规范、重复性高、结果准确可靠。

关键词：固体发酵；黑曲霉；有效活菌数；测定Abstract:This study was designed to use solid microbial fermentation technology to low-cost agricultural by-products as fermentation medium,large scale preparation of Aspergillus niger biomass, decomposition of organic materials used in the production of agents and the number of active bacteria detection products.Jining first to use three-ring chemical production as the original strain of Aspergillus niger strains,using flat crossed technology for Strains;strains will be of purely physical medium access bean sprout juice,began expanding culture flask;and then select the appropriate culture flask as a solid fermentation bacteria,access solid substrate fermentation,fermentation march boxes;fermentation after inoculation of Aspergillus niger producing1‰.Finally,the decomposition agent agricultural products according to GB20287-2006standard microbiological agents Determination of the number of active bacteria were detected.The results show that the fermentation produced by Aspergillus niger in the quality and quantity production standards consistent with decomposition agent,the product number of active bacteria test results meet industry standard requirements,and operating specifications,reproducible,accurate and reliable.Key words:solid state fermentation；Aspergillus niger；effective viable count；determination1前言秸秆、人畜粪便、生活垃圾、工业废渣等各种有机废弃物是数量巨大的可再生资源，绝大部分没被充分有效利用，不仅导致严重的环境污染，而且造成资源的巨大浪费。

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分子模拟教程PPT课件

近似求解E[g(X)]:
g(x)N l i mN 1 iN 1g(ix)
随机抽样
近似求解积分: I(b -a)g( x)
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说明：
当我们用简单Monte Carlo计算积分时，若该函数为常数函数，g(x)=constant，则取样数不管多少，准确度为100％。
如果在积分区间内， g(x) 为一平滑函数，则简单 Monte Carlo方法较为准确，反之，如果g(x)的变动很剧烈，则简单Monte Carlo方法的误差会变大。
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Monte Carlo方法基本思想
当所求的问题是某种事件出现的概率，或是某个随机变量的期望值时，它们可以通过某种“随机试验”的方法，得到这种事件出现的频率和概率，或者得到这个随机变量的统计平均值，并用它们作为问题的解。
Monte Carlo方法解决的问题
• 问题本身是确定性问题，要求我们去寻找一个随机过程，使该随机过程的统计平均就是所求问题的解。
Δx = (b-a)/N 可编辑课件
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② 简单的Monte Carlo积分方法求解：
Ibg(x d)x (b-ab)g(x1) dx
a
a b-a
I(b -a)g( x)其中 X为均匀分布，并且 X[a,b]
利用均匀分布的随机数发生器，从[a,b]区间产生一系列随机数xi，i=1, 2, ..., N
况均匀性与互不相关的特性是有联系的
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❖有效性（Efficiency):
模拟结果可靠模拟产生的样本容量大所需的随机数的数量大随机数的产生必须快速、有效，最好能够进行并行计算。

Atomic Decomposition by Basis pursuit

SIAM R EVIEWc2001Society for Industrial and Applied Mathematics Vol.43,No.1,pp.129–159Atomic Decomposition by BasisPursuit ∗Scott Shaobing Chen †David L.Donoho ‡Michael A.Saunders §Abstract.The time-frequency and time-scale communities have recently developed a large number ofovercomplete waveform dictionaries—stationary wavelets,wavelet packets,cosine packets,chirplets,and warplets,to name a few.Decomposition into overcomplete systems is not unique,and several methods for decomposition have been proposed,including the method of frames (MOF),matching pursuit (MP),and,for special dictionaries,the best orthogonal basis (BOB).Basis pursuit (BP)is a principle for decomposing a signal into an “optimal”superpo-sition of dictionary elements,where optimal means having the smallest l 1norm of coef-ﬁcients among all such decompositions.We give examples exhibiting several advantages over MOF,MP,and BOB,including better sparsity and superresolution.BP has interest-ing relations to ideas in areas as diverse as ill-posed problems,abstract harmonic analysis,total variation denoising,and multiscale edge denoising.BP in highly overcomplete dictionaries leads to large-scale optimization problems.With signals of length 8192and a wavelet packet dictionary,one gets an equivalent linear program of size 8192by 212,992.Such problems can be attacked successfully only because of recent advances in linear and quadratic programming by interior-point methods.We obtain reasonable success with a primal-dual logarithmic barrier method and conjugate-gradient solver.Key words.overcomplete signal representation,denoising,time-frequency analysis,time-scale anal-ysis, 1norm optimization,matching pursuit,wavelets,wavelet packets,cosine pack-ets,interior-point methods for linear programming,total variation denoising,multiscale edges,MATLAB code AMS subject classiﬁcations.94A12,65K05,65D15,41A45PII.S003614450037906X1.Introduction.Over the last several years,there has been an explosion of in-terest in alternatives to traditional signal representations.Instead of just represent-ing signals as superpositions of sinusoids (the traditional Fourier representation)we now have available alternate dictionaries—collections of parameterized waveforms—of which the wavelets dictionary is only the best known.Wavelets,steerable wavelets,segmented wavelets,Gabor dictionaries,multiscale Gabor dictionaries,wavelet pack-∗Publishedelectronically February 2,2001.This paper originally appeared in SIAM Journal onScientiﬁc Computing ,Volume 20,Number 1,1998,pages 33–61.This research was partially sup-ported by NSF grants DMS-92-09130,DMI-92-04208,and ECS-9707111,by the NASA Astrophysical Data Program,by ONR grant N00014-90-J1242,and by other sponsors./journals/sirev/43-1/37906.html†Renaissance Technologies,600Route 25A,East Setauket,NY 11733(schen@).‡Department of Statistics,Stanford University,Stanford,CA 94305(donoho@).§Department of Management Science and Engineering,Stanford University,Stanford,CA 94305(saunders@).129D o w n l o a d e d 08/09/14 t o 58.19.126.38. R e d i s t r i b u t i o n s u b j e c t t o S I A M l i c e n s e o r c o p y r i g h t ; s e e h t t p ://w w w .s i a m .o r g /j o u r n a l s /o j s a .p h p130S.S.CHEN,D.L.DONOHO,AND M.A.SAUNDERSets,cosine packets,chirplets,warplets,and a wide range of other dictionaries are now available.Each such dictionary D is a collection of waveforms (φγ)γ∈Γ,with γa parameter,and we envision a decomposition of a signal s ass =γ∈Γαγφγ,(1.1)or an approximate decomposition s =m i =1αγi φγi +R (m ),(1.2)where R (m )is a residual.Depending on the dictionary,such a representation de-composes the signal into pure tones (Fourier dictionary),bumps (wavelet dictionary),chirps (chirplet dictionary),etc.Most of the new dictionaries are overcomplete ,either because they start out that way or because we merge complete dictionaries,obtaining a new megadictionary con-sisting of several types of waveforms (e.g.,Fourier and wavelets dictionaries).The decomposition (1.1)is then nonunique,because some elements in the dictionary have representations in terms of other elements.1.1.Goals of Adaptive Representation.Nonuniqueness gives us the possibility of adaptation,i.e.,of choosing from among many representations one that is most suited to our purposes.We are motivated by the aim of achieving simultaneously the following goals .•Sparsity.We should obtain the sparsest possible representation of the object—the one with the fewest signiﬁcant coeﬃcients.•Superresolution.We should obtain a resolution of sparse objects that is much higher resolution than that possible with traditional nonadaptive approaches.An important constraint ,which is perhaps in conﬂict with both the goals,follows.•Speed.It should be possible to obtain a representation in order O (n )or O (n log(n ))time.1.2.Finding a Representation.Several methods have been proposed for obtain-ing signal representations in overcomplete dictionaries.These range from general approaches,like the method of frames (MOF)[9]and the method of matching pursuit (MP)[29],to clever schemes derived for specialized dictionaries,like the method of best orthogonal basis (BOB)[7].These methods are described brieﬂy in section 2.3.In our view,these methods have both advantages and shortcomings.The principal emphasis of the proposers of these methods is on achieving suﬃcient computational speed.While the resulting methods are practical to apply to real data,we show below by computational examples that the methods,either quite generally or in important special cases,lack qualities of sparsity preservation and of stable superresolution.1.3.Basis Pursuit.Basis pursuit (BP)ﬁnds signal representations in overcom-plete dictionaries by convex optimization:it obtains the decomposition that minimizes the 1normof the coeﬃcients occurring in the representation.Because of the nondif-ferentiability of the 1norm,this optimization principle leads to decompositions that can have very diﬀerent properties fromthe MOF—in particular,they can be m uch sparser.Because it is based on global optimization,it can stably superresolve in ways that MP cannot.D o w n l o a d e d 08/09/14 t o 58.19.126.38. R e d i s t r i b u t i o n s u b j e c t t o S I A M l i c e n s e o r c o p y r i g h t ; s e e h t t p ://w w w .s i a m .o r g /j o u r n a l s /o j s a .p h pATOMIC DECOMPOSITION BY BASIS PURSUIT131BP can be used with noisy data by solving an optimization problem trading oﬀa quadratic misﬁt measure with an 1normof coeﬃcients.Examples show that it can stably suppress noise while preserving structure that is well expressed in the dictionary under consideration.BP is closely connected with linear programming.Recent advances in large-scale linear programming—associated with interior-point methods—can be applied to BP and can make it possible,with certain dictionaries,to nearly solve the BP optimization problem in nearly linear time.We have implemented primal-dual log barrier interior-point methods as part of a MATLAB [31]computing environment called Atomizer,which accepts a wide range of dictionaries.Instructions for Internet access to Atomizer are given in section 7.3.Experiments with standard time-frequency dictionaries indicate some of the potential beneﬁts of BP.Experiments with some nonstandard dictionaries,like the stationary wavelet dictionary and the heaviside dictionary,indicate important connections between BP and methods like Mallat and Zhong’s [29]multiscale edge representation and Rudin,Osher,and Fatemi’s [35]total variation-based denoising methods.1.4.Contents.In section 2we establish vocabulary and notation for the rest of the article,describing a number of dictionaries and existing methods for overcomplete representation.In section 3we discuss the principle of BP and its relations to existing methods and to ideas in other ﬁelds.In section 4we discuss methodological issues associated with BP,in particular some of the interesting nonstandard ways it can be deployed.In section 5we describe BP denoising,a method for dealing with problem (1.2).In section 6we discuss recent advances in large-scale linear programming (LP)and resulting algorithms for BP.For reasons of space we refer the reader to [4]for a discussion of related work in statistics and analysis.2.Overcomplete Representations.Let s =(s t :0≤t <n )be a discrete-time signal of length n ;this may also be viewed as a vector in R n .We are interested in the reconstruction of this signal using superpositions of elementary waveforms.Traditional methods of analysis and reconstruction involve the use of orthogonal bases,such as the Fourier basis,various discrete cosine transformbases,and orthogonal wavelet bases.Such situations can be viewed as follows:given a list of n waveforms,one wishes to represent s as a linear combination of these waveforms.The waveforms in the list,viewed as vectors in R n ,are linearly independent,and so the representation is unique.2.1.Dictionaries and Atoms.A considerable focus of activity in the recent sig-nal processing literature has been the development of signal representations outside the basis setting.We use terminology introduced by Mallat and Zhang [29].A dic-tionary is a collection of parameterized waveforms D =(φγ:γ∈Γ).The waveforms φγare discrete-time signals of length n called atoms .Depending on the dictionary,the parameter γcan have the interpretation of indexing frequency,in which case the dictionary is a frequency or Fourier dictionary,of indexing time-scale jointly,in which case the dictionary is a time-scale dictionary,or of indexing time-frequency jointly,in which case the dictionary is a time-frequency ually dictionaries are complete or overcomplete,in which case they contain exactly n atoms or more than n atoms,but one could also have continuum dictionaries containing an inﬁnity of atoms and undercomplete dictionaries for special purposes,containing fewer than n atoms.Dozens of interesting dictionaries have been proposed over the last few years;we focusD o w n l o a d e d 08/09/14 t o 58.19.126.38. R e d i s t r i b u t i o n s u b j e c t t o S I A M l i c e n s e o r c o p y r i g h t ; s e e h t t p ://w w w .s i a m .o r g /j o u r n a l s /o j s a .p h p132S.S.CHEN,D.L.DONOHO,AND M.A.SAUNDERSin this paper on a half dozen or so;much of what we do applies in other cases as well.2.1.1.T rivial Dictionaries.We begin with some overly simple examples.The Dirac dictionary is simply the collection of waveforms that are zero except in one point:γ∈{0,1,...,n −1}and φγ(t )=1{t =γ}.This is of course also an orthogonal basis of R n —the standard basis.The heaviside dictionary is the collection of waveforms that jump at one particular point:γ∈{0,1,...,n −1};φγ(t )=1{t ≥γ}.Atoms in this dictionary are not orthogonal,but every signal has a representation s =s 0φ0+n −1 γ=1(s γ−s γ−1)φγ.(2.1)2.1.2.Frequency Dictionaries.A Fourier dictionary is a collection of sinusoidalwaveforms φγindexed by γ=(ω,ν),where ω∈[0,2π)is an angular frequency variable and ν∈{0,1}indicates phase type:sine or cosine.In detail,φ(ω,0)=cos(ωt ),φ(ω,1)=sin(ωt ).For the standard Fourier dictionary,we let γrun through the set of all cosines with Fourier frequencies ωk =2πk/n ,k =0,...,n/2,and all sines with Fourier frequencies ωk ,k =1,...,n/2−1.This dictionary consists of n waveforms;it is in fact a basis,and a very simple one:the atoms are all mutually orthogonal.An overcomplete Fourier dictionary is obtained by sampling the frequencies more ﬁnely.Let be a whole number >1and let Γ be the collection of all cosines with ωk =2πk/( n ),k =0,..., n/2,and all sines with frequencies ωk ,k =1,..., n/2−1.This is an -fold overcomplete system.We also use complete and overcomplete dictionaries based on discrete cosine transforms and sine transforms.2.1.3.Time-Scale Dictionaries.There are several types of wavelet dictionaries;to ﬁx ideas,we consider the Haar dictionary with “father wavelet”ϕ=1[0,1]and “mother wavelet”ψ=1(1/2,1]−1[0,1/2].The dictionary is a collection of transla-tions and dilations of the basic mother wavelet,together with translations of a father wavelet.It is indexed by γ=(a,b,ν),where a ∈(0,∞)is a scale variable,b ∈[0,n ]indicates location,and ν∈{0,1}indicates gender.In detail,φ(a,b,1)=ψ(a (t −b ))·√a,φ(a,b,0)=ϕ(a (t −b ))·√a.For the standard Haar dictionary,we let γrun through the discrete collection ofmother wavelets with dyadic scales a j =2j /n ,j =j 0,...,log 2(n )−1,and locations that are integer multiples of the scale b j,k =k ·a j ,k =0,...,2j −1,and the collection of father wavelets at the coarse scale j 0.This dictionary consists of n waveforms;it is an orthonormal basis.An overcomplete wavelet dictionary is obtained by sampling the locations more ﬁnely:one location per sample point.This gives the so-called sta-tionary Haar dictionary,consisting of O (n log 2(n ))waveforms.It is called stationary since the whole dictionary is invariant under circulant shift.A variety of other wavelet bases are possible.The most important variations are smooth wavelet bases,using splines or using wavelets deﬁned recursively fromtwo-scale ﬁltering relations [10].Although the rules of construction are more complicated (boundary conditions [33],orthogonality versus biorthogonality [10],etc.),these have the same indexing structure as the standard Haar dictionary.In this paper,we use symmlet -8smooth wavelets,i.e.,Daubechies nearly symmetric wavelets with eight vanishing moments;see [10]for examples.D o w n l o a d e d 08/09/14 t o 58.19.126.38. R e d i s t r i b u t i o n s u b j e c t t o S I A M l i c e n s e o r c o p y r i g h t ; s e e h t t p ://w w w .s i a m .o r g /j o u r n a l s /o j s a .p h pATOMIC DECOMPOSITION BY BASIS PURSUIT133Time 00.5100.20.40.60.81(c) Time DomainFig.2.1Time-frequency phase plot of a wavelet packet atom.2.1.4.Time-Frequency Dictionaries.Much recent activity in the wavelet com-munities has focused on the study of time-frequency phenomena.The standard ex-ample,the Gabor dictionary,is due to Gabor [19];in our notation,we take γ=(ω,τ,θ,δt ),where ω∈[0,π)is a frequency,τis a location,θis a phase,and δt is the duration,and we consider atoms φγ(t )=exp {−(t −τ)2/(δt )2}·cos(ω(t −τ)+θ).Such atoms indeed consist of frequencies near ωand essentially vanish far away from τ.For ﬁxed δt ,discrete dictionaries can be built fromtim e-frequency lattices,ωk =k ∆ωand τ = ∆τ,and θ∈{0,π/2};with ∆τand ∆ωchosen suﬃciently ﬁne these are complete.For further discussions see,e.g.,[9].Recently,Coifman and Meyer [6]developed the wavelet packet and cosine packet dictionaries especially to meet the computational demands of discrete-time signal pro-cessing.For one-dimensional discrete-time signals of length n ,these dictionaries each contain about n log 2(n )waveforms.A wavelet packet dictionary includes,as special cases,a standard orthogonal wavelets dictionary,the Dirac dictionary,and a collec-tion of oscillating waveforms spanning a range of frequencies and durations.A cosine packet dictionary contains,as special cases,the standard orthogonal Fourier dictio-nary and a variety of Gabor-like elements:sinusoids of various frequencies weighted by windows of various widths and locations.In this paper,we often use wavelet packet and cosine packet dictionaries as exam-ples of overcomplete systems,and we give a number of examples decomposing signals into these time-frequency dictionaries.A simple block diagram helps us visualize the atoms appearing in the decomposition.This diagram,adapted from Coifman and Wickerhauser [7],associates with each cosine packet or wavelet packet a rectangle in the time-frequency phase plane.The association is illustrated in Figure 2.1for a cer-tain wavelet packet.When a signal is a superposition of several such waveforms,we indicate which waveforms appear in the superposition by shading the corresponding rectangles in the time-frequency plane.D o w n l o a d e d 08/09/14 t o 58.19.126.38. R e d i s t r i b u t i o n s u b j e c t t o S I A M l i c e n s e o r c o p y r i g h t ; s e e h t t p ://w w w .s i a m .o r g /j o u r n a l s /o j s a .p h p134S.S.CHEN,D.L.DONOHO,AND M.A.SAUNDERS2.1.5.Further Dictionaries.We can always merge dictionaries to create mega-dictionaries;examples used below include mergers of wavelets with heavisides.2.2.Linear Algebra.Suppose we have a discrete dictionary of p waveforms and we collect all these waveforms as columns of an n -by-p matrix Φ,say.The decompo-sition problem(1.1)can be written Φα=s ,(2.2)where α=(αγ)is the vector of coeﬃcients in (1.1).When the dictionary furnishes a basis,then Φis an n -by-n nonsingular matrix and we have the unique representation α=Φ−1s .When the atoms are,in addition,mutually orthonormal,then Φ−1=ΦT and the decomposition formula is very simple.2.2.1.Analysis versus Synthesis.Given a dictionary of waveforms,one can dis-tinguish analysis from synthesis .Synthesis is the operation of building up a signal by superposing atoms;it involves a matrix that is n -by-p :s =Φα.Analysis involves the operation of associating with each signal a vector of coeﬃcients attached to atoms;it involves a matrix that is p -by-n :˜α=ΦT s .Synthesis and analysis are very diﬀer-ent linear operations,and we must take care to distinguish them.One should avoid assuming that the analysis operator ˜α=ΦT s gives us coeﬃcients that can be used as is to synthesize s .In the overcomplete case we are interested in,p n and Φis not invertible.There are then many solutions to (2.2),and a given approach selects a particular solution.One does not uniquely and automatically solve the synthesis problemby applying a sim ple,linear analysis operator.We now illustrate the diﬀerence between synthesis (s =Φα)and analysis (˜α=ΦTs ).Figure 2.2a shows the signal Carbon .Figure 2.2b shows the time-frequency structure of a sparse synthesis of Carbon ,a vector αyielding s =Φα,using a wavelet packet dictionary.To visualize the decomposition,we present a phase-plane display with shaded rectangles,as described above.Figure 2.2c gives an analysis of Carbon ,with the coeﬃcients ˜α=ΦT s ,again displayed in a phase plane.Once again,between analysis and synthesis there is a large diﬀerence in sparsity.In Figure 2.2d we compare the sorted coeﬃcients of the overcomplete representation (synthesis)with the analysis coeﬃcients.putational Complexity of Φand ΦT .Diﬀerent dictionaries can im-pose drastically diﬀerent computational burdens.In this paper we report compu-tational experiments on a variety of signals and dictionaries.We study primarily one-dimensional signals of length n ,where n is several thousand.Signals of this length occur naturally in the study of short segments of speech (a quarter-second to a half-second)and in the output of various scientiﬁc instruments (e.g.,FT-NMR spec-trometers).In our experiments,we study dictionaries overcomplete by substantial factors,say,10.Hence the typical matrix Φwe are interested in is of size “thousands”by “tens-of-thousands.”The nominal cost of storing and applying an arbitrary n -by-p matrix to a p -vector is a constant times np .Hence with an arbitrary dictionary of the sizes we are interested in,simply to verify whether (1.1)holds for given vectors αand s would require tens of millions of multiplications and tens of millions of words of memory.In contrast,most signal processing algorithms for signals of length 1000require only thousands of memory words and a few thousand multiplications.Fortunately,certain dictionaries have fast implicit algorithms .By this we mean that Φαand ΦT s can be computed,for arbitrary vectors αand s ,(a)without everD o w n l o a d e d 08/09/14 t o 58.19.126.38. R e d i s t r i b u t i o n s u b j e c t t o S I A M l i c e n s e o r c o p y r i g h t ; s e e h t t p ://w w w .s i a m .o r g /j o u r n a l s /o j s a .p h pATOMIC DECOMPOSITION BY BASIS PURSUIT135Time0.5100.20.40.60.81Time0.5100.20.40.60.81(d) Sorted CoefficientsSynthesis: SolidAnalysis: Dashed Fig.2.2Analysis versus synthesis of the signal Carbon .storing the matrices Φand ΦT ,and (b)using special properties of the matrices to accelerate computations.The most well-known example is the standard Fourier dictionary for which we have the fast Fourier transform algorithm.A typical implementation requires 2·n storage locations and 4·n ·J multiplications if n is dyadic:n =2J .Hence for very long signals we can apply Φand ΦT with much less storage and time than the matrices would nominally require.Simple adaptation of this idea leads to an algorithm for overcomplete Fourier dictionaries.Wavelets give a more recent example of a dictionary with a fast implicit algorithm;if the Haar or S8-symmlet is used,both Φand ΦT may be applied in O (n )time.For the stationary wavelet dictionary,O (n log(n ))time is required.Cosine packets and wavelet packets also have fast implicit algorithms.Here both Φand ΦT can be applied in order O (n log(n ))time and order O (n log(n ))space—much better than the nominal np =n 2log 2(n )one would expect fromnaive use of the m atrix deﬁnition.For the viewpoint of this paper,it only makes sense to consider dictionaries with fast implicit algorithms.Among dictionaries we have not discussed,such algorithms may or may not exist.2.3.Existing Decomposition Methods.There are several currently popular ap-proaches to obtaining solutions to (2.2).2.3.1.Frames.The MOF [9]picks out,among all solutions of (2.2),one whose coeﬃcients have minimum l 2norm:min α 2subject toΦα=s .(2.3)The solution of this problemis unique;label it α†.Geometrically,the collection of all solutions to (2.2)is an aﬃne subspace in R p ;MOF selects the element of this subspace closest to the origin.It is sometimes called a minimum-length solution.There is aD o w n l o a d e d 08/09/14 t o 58.19.126.38. R e d i s t r i b u t i o n s u b j e c t t o S I A M l i c e n s e o r c o p y r i g h t ; s e e h t t p ://w w w .s i a m .o r g /j o u r n a l s /o j s a .p h p136S.S.CHEN,D.L.DONOHO,AND M.A.SAUNDERSTime0.5100.20.40.60.81Time0.5100.20.40.60.81Fig.2.3MOF representation is not sparse.matrix Φ†,the generalized inverse of Φ,that calculates the minimum-length solution to a systemof linear equations:α†=Φ†s =ΦT (ΦΦT )−1s .(2.4)For so-called tight frame dictionaries MOF is available in closed form.A nice example is the standard wavelet packet dictionary.One can compute that for all vectors v ,ΦT v 2=L n · v 2,L n =log 2(n ).In short Φ†=L −1n ΦT .Notice that ΦTis simply the analysis operator.There are two key problems with the MOF.First,MOF is not sparsity preserving .If the underlying object has a very sparse representation in terms of the dictionary,then the coeﬃcients found by MOF are likely to be very much less sparse.Each atom in the dictionary that has nonzero inner product with the signal is,at least potentially and also usually,a member of the solution.Figure 2.3a shows the signal Hydrogen made of a single atom in a wavelet packet dictionary.The result of a frame decomposition in that dictionary is depicted in a phase-plane portrait;see Figure 2.3c.While the underlying signal can be synthesized from a single atom,the frame decomposition involves many atoms,and the phase-plane portrait exaggerates greatly the intrinsic complexity of the object.Second,MOF is intrinsically resolution limited .No object can be reconstructed with features sharper than those allowed by the underlying operator Φ†Φ.Suppose the underlying object is sharply localized:α=1{γ=γ0}.The reconstruction will not be α,but instead Φ†Φα,which,in the overcomplete case,will be spatially spread out.Figure 2.4presents a signal TwinSine consisting of the superposition of two sinusoids that are separated by less than the so-called Rayleigh distance 2π/n .We analyze these in a fourfold overcomplete discrete cosine dictionary.In this case,reconstruction by MOF (Figure 2.4b)is simply convolution with the Dirichlet kernel.The result is the synthesis fromcoeﬃcients with a broad oscillatory appearance,consisting not of twoD o w n l o a d e d 08/09/14 t o 58.19.126.38. R e d i s t r i b u t i o n s u b j e c t t o S I A M l i c e n s e o r c o p y r i g h t ; s e e h t t p ://w w w .s i a m .o r g /j o u r n a l s /o j s a .p h pATOMIC DECOMPOSITION BY BASIS PURSUIT137Fig.2.4Analyzing TwinSine with a fourfold overcomplete discrete cosine dictionary.but of many frequencies and giving no visual clue that the object may be synthesized fromtwo frequencies alone.2.3.2.Matching Pursuit.Mallat and Zhang [29]discussed a general method for approximate decomposition (1.2)that addresses the sparsity issue directly.Starting froman initial approxim ation s (0)=0and residual R (0)=s ,it builds up a sequence of sparse approximations stepwise.At stage k ,it identiﬁes the dictionary atomthat best correlates with the residual and then adds to the current approximation a scalar multiple of that atom,so that s (k )=s (k −1)+αk φγk ,where αk = R (k −1),φγk and R (k )=s −s (k ).After m steps,one has a representation of the form(1.2),with residual R =R (m ).Similar algorithms were proposed by Qian and Chen [39]for Gabor dictionaries and by Villemoes [48]for Walsh dictionaries.A similar algorithm was proposed for Gabor dictionaries by Qian and Chen [39].For an earlier instance of a related algorithm,see [5].An intrinsic feature of the algorithmis that when stopped after a few steps,it yields an approximation using only a few atoms.When the dictionary is orthogonal,the method works perfectly.If the object is made up of only m n atoms and the algorithmis run for m steps,it recovers the underlying sparse structure exactly.When the dictionary is not orthogonal,the situation is less clear.Because the algorithmis m yopic,one expects that,in certain cases,it m ight choose wrongly in the ﬁrst few iterations and end up spending most of its time correcting for any mistakes made in the ﬁrst few terms.In fact this does seem to happen.To see this,we consider an attempt at superresolution.Figure 2.4a portrays again the signal TwinSine consisting of sinusoids at two closely spaced frequencies.When MP is applied in this case (Figure 2.4c),using the fourfold overcomplete discrete cosine dictionary,the initial frequency selected is in between the two frequencies making up the signal.Because of this mistake,MP is forced to make a series of alternating corrections that suggest a highly complex and organized structure.MPD o w n l o a d e d 08/09/14 t o 58.19.126.38. R e d i s t r i b u t i o n s u b j e c t t o S I A M l i c e n s e o r c o p y r i g h t ; s e e h t t p ://w w w .s i a m .o r g /j o u r n a l s /o j s a .p h p138S.S.CHEN,D.L.DONOHO,AND M.A.SAUNDERSFig.2.5Counterexamples for MP.misses entirely the doublet structure.One can certainly say in this case that MP has failed to superresolve.Second,one can give examples of dictionaries and signals where MP is arbitrarily suboptimal in terms of sparsity.While these are somewhat artiﬁcial,they have a character not so diﬀerent fromthe superresolution exam ple.DeVore and Temlyakov’s Example.Vladimir Temlyakov,in a talk at the IEEE Confer-ence on Information Theory and Statistics in October 1994,described an example in which the straightforward greedy algorithmis not sparsity preserving.In our adapta-tion of this example,based on Temlyakov’s joint work with DeVore [12],one constructs a dictionary having n +1atoms.The ﬁrst n are the Dirac basis;the ﬁnal atomin-volves a linear combination of the ﬁrst n with decaying weights.The signal s has an exact decomposition in terms of A atoms,but the greedy algorithm goes on forever,with an error of size O (1/√m )after m steps.We illustrate this decay in Figure 2.5a.For this example we set A =10and choose the signal s t =10−1/2·1{1≤t ≤10}.The dictionary consists of Dirac elements φγ=δγfor 1≤γ≤n andφn +1(t )=c,1≤t ≤10,c/(t −10),10<t ≤n,with c chosen to normalize φn +1to unit norm.Shaobing Chen’s Example.The DeVore–Temlyakov example applies to the original MP algorithmas announced by Mallat and Zhang in 1992.A later reﬁnem ent of the algorithm(see Pati,Rezaiifar,and Krishnaprasad [38]and Davis,Mallat,and Zhang [11])involves an extra step of orthogonalization.One takes all m terms that have entered at stage m and solves the least-squares problemmin (αi )s −m i =1αi φγi2D o w n l o a d e d 08/09/14 t o 58.19.126.38. R e d i s t r i b u t i o n s u b j e c t t o S I A M l i c e n s e o r c o p y r i g h t ; s e e h t t p ://w w w .s i a m .o r g /j o u r n a l s /o j s a .p h p。

羟胺与氰基反应

1. Single Step100%OverviewSteps/Stages Notes1.1 R:NH2OH, S:H2O, S:EtOH, 48 h, reflux Reactants: 1, Reagents: 1, Solvents: 2, Steps:1, Stages: 1, Most stages in any one step: 1ReferencesNitrile and amidoxime compounds, theirpreparation and use in semiconductorprocessingBy Lee, Wai MunFrom U.S. Pat. Appl. Publ., 20090111965, 30Apr 2009Experimental ProcedureAB) Reaction of Benzonitrile. Benzonitrile (0.99 cm3, 1 g, 9.7 mmol) and hydroxylamine (50% in water,0.89 cm3, 0.96 g, 14.55 mmol, 1.5 eq) were stirred under reflux in EtOH (10 cm3) for 48 hours. Thesolvent was evaporated under reduced pressure and water (10 cm3) was added to the residue. Themixture was extracted with dichloromethane (100 cm3) and the organic extract was evaporated underreduced pressure. The residue was purified by column chromatography to give the product. N'-hydroxybenzimidamide, yield 1.32 g, 100%, as a white crystalline solid. mp 79-81° C. (lit 79-80° C.) CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.2. Single Step100%OverviewSteps/Stages Notes1.1 R:NH2OH, S:EtOH, 1 h, reflux; reflux → rt stereoselective, Reactants: 1, Reagents: 1,Solvents: 1, Steps: 1, Stages: 1, Most stagesin any one step: 1ReferencesPreparation of diaryl-substituted 5-memberedheterocycles as antibacterial agentsBy Mobashery, Shahriar et alFrom PCT Int. Appl., 2009082398, 02 Jul2009Experimental Procedure(Z)-N'-hydroxybenzamidine (compound 17-structure shown below): A solution of ethanol (5.0 mL),benzonitrile (203 mg, 1.97 mmol) and hydroxylamine (520 mg, 7.87 mmol) were refluxed for 1 hour.The reaction was then cooled to room temperature and concentrated in vacuo to give the a clear oilwhich was taken to the next step without further purification (268 mg, 100%). 1H NMR (500 MHz,CDCL3) δ(ppm): 4.92 (2H, bs), 7.38-7.44 (3H, m), 7.62-7.65 (2H, m). 13C NMR (125 MHz, CDCL3)δ(ppm): 126.1 (CH), 128.9 (CH), 130.2 (CH), 132.6, 152.8. MS (FAB+): 137 (MH+). HRMS forC7H8N2O (MH+): calculated: 137.0715; found 137.0718.CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.3. Single Step100%OverviewSteps/Stages Notes1.1 R:NH2OH, S:EtOH, 1 h, reflux; reflux → rt stereoselective, Reactants: 1, Reagents: 1,Solvents: 1, Steps: 1, Stages: 1, Most stagesin any one step: 1ReferencesPreparation of oxadiazole derivatives asantibacterial agentsBy Mobashery, Shahriar et alFrom PCT Int. Appl., 2009041972, 02 Apr2009Experimental Procedure(Z)-N'-hydroxybenzamidine (compound 17 - structure shown below): A solution of ethanol (5.0 mL),benzonitrile (203 mg, 1.97 mmol) and hydroxylamine (520 mg, 7.87 mmol) were refluxed for 1 hour.The reaction was then cooled to room temperature and concentrated in vacuo to give the a clear oilwhich was taken to the next step without further purification (268 mg, 100%). 1H NMR (500 MHz,CDCL3) δ(ppm): 4.92 (2H, bs), 7.38-7.44 (3H, m), 7.62-7.65 (2H, m). 13C NMR (125 MHz, CDCL3)δ(ppm): 126.1 (CH), 128.9 (CH), 130.2 (CH), 132.6, 152.8. MS (FAB+): 137 (MH+). HRMS forC7H8N2O (MH+): calculated: 137.0715; found 137.0718.CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.4. Single Step99%OverviewSteps/Stages Notes1.2 R:Disodium carbonate, S:H2OReferencesDiscovery and SAR exploration of N-aryl-N-(3-aryl-1,2,4-oxadiazol-5-yl)amines aspotential therapeutic agents for prostatecancerBy Krasavin, Mikhail et alFrom Chemistry Central Journal, 4, No pp.given; 2010CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.5. Single Step95%OverviewSteps/Stages Notes1.1 R:H2NOH-HCl, R:NaOH, S:H2O, 1 h, 30°C, pH 10; 2 h, reflux Reactants: 1, Reagents: 2, Solvents: 1, Steps:1, Stages: 1, Most stages in any one step: 1ReferencesTwo synthetic methods of 3,4-bis(3-nitrophenyl)furoxanBy Yang, Jian-ming et alFrom Hanneng Cailiao, 17(5), 527-530; 2009 CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.6. Single Step95%OverviewSteps/Stages NotesReferencesSynthesis of 3,4-bis(3',5'-dinitrophenyl-1'-yl)furoxanBy Huo, Huan et alFrom Hecheng Huaxue, 17(2), 208-210; 2009 CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.7. Single Step93%OverviewSteps/Stages Notes1.1 R:NH2OH, S:H2O, S:MeOH, > 1 min, 50°C; 3 h, reflux Reactants: 1, Reagents: 1, Solvents: 2, Steps:1, Stages: 1, Most stages in any one step: 1ReferencesQuinazoline derivatives as adrenergicreceptor antagonists and their preparation,pharmaceutical compositions and use in thetreatment of diseasesBy Sarma, Pakala Kumara Savithru et alFrom Indian Pat. Appl., 2005DE01706, 31Aug 2007CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.8. Single Step92%OverviewSteps/Stages Notes1.1 R:NH2OH, R:Et3N, S:EtOH, rt stereoselective, Reactants: 1, Reagents: 2,Solvents: 1, Steps: 1, Stages: 1, Most stagesin any one step: 1ReferencesPotent inhibitors of lipoprotein-associatedphospholipase A2: Benzaldehyde O-heterocycle-4-carbonyloximeBy Jeong, Hyung Jae et alFrom Bioorganic & Medicinal ChemistryLetters, 16(21), 5576-5579; 2006 CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.9. Single Step89%OverviewSteps/Stages Notes1.1 R:EtN(Pr-i)2, R:H2NOH-HCl, S:EtOH, 18 h, 80°C Reactants: 1, Reagents: 2, Solvents: 1, Steps:1, Stages: 1, Most stages in any one step: 1ReferencesTuned methods for conjugate addition to avinyl oxadiazole; synthesis ofpharmaceutically important motifsBy Burns, Alan R. et alFrom Organic & Biomolecular Chemistry,8(12), 2777-2783; 2010CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.10. Single Step91%OverviewSteps/Stages Notes1.1 R:NaOH, R:H2NOH-HCl, S:H2O, S:EtOH, 12 h, 80°C; cooled Reactants: 1, Reagents: 2, Solvents: 2, Steps:1, Stages: 1, Most stages in any one step: 1ReferencesPreparation of heteropolycyclic compoundsand their use as metabotropic glutamatereceptor antagonistsBy Edwards, Louise et alFrom U.S. Pat. Appl. Publ., 20050272779, 08Dec 2005Experimental ProcedureGeneral/Typical Procedure: Example 6 N-Hydroxy-3-methoxy-benzamidine. Using the generalprocedure of Shine et al., J. Heterocyclic Chem. (1989) 26:125-128, hydroxylamine hydrochloride (22ml, 5 M, 110 mmol) and sodium hydroxide (11 ml, 10 M, 110 mmol) were added to a solution of 3-methoxybenzonitrile (11.5 ml. 94 mmol) in ethanol (130 ml). The reaction mixture was then heated atreflux (80 °C.) for 12 h. After the mixture was cooled, most of the solvent was removed in vacuo. Thecrude product was partitioned between ethyl acetate and water, washed with saturated brine, driedover anhydrous sodium sulfate and the solvent was removed in vacuo. Flash chromatography on silicagel using 35-50% ethyl acetate in hexane yielded the title compound (8.05 g, 52%). Examples 7-9were prepared in an analogous method to the procedure given in Example 6. N-Hydroxy-benzamidine.N-hydroxy-benzamidine (4.83 g, 91%, white solid) was obtained from benzonitrile (4 g, 38.9 mmol),hydroxylamine hydrochloride (8.89 ml, 44.0 mmol) and sodium hydroxide (4.49 ml, 45.0 mmol) inethanol (30 ml). 1H NMR (CDCl3), δ (ppm): 8.81 (broad peak, 1H), 7.63 (m, 2H), 7.39(m, 3H), 4.91 (s,2H).CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.11. Single Step91%OverviewSteps/Stages Notes1.1 R:NaOH, R:H2NOH-HCl, S:H2O, S:EtOH, 12 h, 80°C literature preparation, Reactants: 1, Reagents:2, Solvents: 2, Steps: 1, Stages: 1, Moststages in any one step: 1ReferencesPreparation of five-membered heterocycliccompounds as mGluR5 receptor antagonistsBy Wensbo, David et alFrom PCT Int. Appl., 2004014881, 19 Feb2004CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.12. Single Step85%OverviewSteps/Stages Notes1.1 R:Et3N, R:H2NOH-HCl, S:EtOH, 18 h, reflux stereoselective (Z), Reactants: 1, Reagents: 2,Solvents: 1, Steps: 1, Stages: 1, Most stagesin any one step: 1ReferencesUnexpected C-C Bond Cleavage: Synthesisof 1,2,4-Oxadiazol-5-ones from Amidoximeswith Pentafluorophenyl or TrifluoromethylAnion Acting as Leaving GroupBy Gerfaud, Thibaud et alFrom Organic Letters, 13(23), 6172-6175;2011CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.13. Single Step85%OverviewSteps/Stages Notes1.1 R:Disodium carbonate, R:H2NOH-HCl, S:H2O, S:EtOH, 15 min,55°Cultrasound (40kHz), reaction withoutultrasound at room temperature decreasedyield and increased reaction time, Reactants:1, Reagents: 2, Solvents: 2, Steps: 1, Stages:1, Most stages in any one step: 1ReferencesSynthesis of amidoximes using an efficientand rapid ultrasound methodBy Barros, Carlos Jonnatan Pimentel et alFrom Journal of the Chilean ChemicalSociety, 56(2), 721-722; 2011CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.14. Single Step83%OverviewSteps/Stages Notes1.1 R:NaHCO3, R:H2NOH-HCl, S:H2O, S:EtOH, 4 h, 80°C Reactants: 1, Reagents: 2, Solvents: 2, Steps:1, Stages: 1, Most stages in any one step: 1ReferencesA novel bifunctional chelating agent based onbis(hydroxamamide) for 99mTc labeling ofpolypeptidesBy Ono, Masahiro et alFrom Journal of Labelled Compounds andRadiopharmaceuticals, 55(2), 71-79; 2012 CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.15. Single Step80%OverviewSteps/Stages Notes1.1 R:NaHCO3, R:H2NOH-HCl, S:H2O, 10 min, 25°C1.2 S:EtOH, 20 h, 25°C1.3 R:H2NOH-HCl, 50 h, 25°Cregioselective, other product also detected, in-situ generated reagent, Reactants: 1,Reagents: 2, Solvents: 2, Steps: 1, Stages: 3,Most stages in any one step: 3ReferencesSynthesis, mechanism of formation, andmolecular orbital calculations ofarylamidoximesBy Srivastava, Rajendra M. et alFrom Monatshefte fuer Chemie, 140(11),1319-1324; 2009CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.16. Single Step79%OverviewSteps/Stages Notes1.1 R:Disodium carbonate, R:H2NOH-HCl, S:H2O, S:EtOH Reactants: 1, Reagents: 2, Solvents: 2, Steps:1, Stages: 1, Most stages in any one step: 1ReferencesSynthesis of 1,2,4- and 1,3,4-oxadiazolesfrom 1-aryl-5-methyl-1H-1,2,3-triazole-4-carbonyl chloridesBy Obushak, N. D. et alFrom Russian Journal of Organic Chemistry,44(10), 1522-1527; 2008CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.17. Single Step85%OverviewSteps/Stages Notes1.1 R:K2CO3, R:H2NOH-HCl, S:EtOH1.2 R:HCl, S:Et2O, S:H2O1.3 R:NH3, R:NaCl1.4 S:Et2OReactants: 1, Reagents: 5, Solvents: 3, Steps:1, Stages: 4, Most stages in any one step: 4ReferencesModification of the Tiemann rearrangement:One-pot synthesis of N,N-disubstitutedcyanamides from amidoximesBy Bakunov, Stanislav A. et alFrom Synthesis, (8), 1148-1159; 2000 CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.18. Single Step76%OverviewSteps/Stages Notes1.1 R:EtN(Pr-i)2, R:H2NOH-HCl, S:EtOH, 6-12 h, 80°C Reactants: 1, Reagents: 2, Solvents: 1, Steps:1, Stages: 1, Most stages in any one step: 1ReferencesA versatile solid-phase synthesis of 3-aryl-1,2,4-oxadiazolones and analoguesBy Charton, Julie et alFrom Tetrahedron Letters, 48(8), 1479-1483;2007CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.19. Single Step70%OverviewSteps/Stages Notes1.1 R:Disodium carbonate, R:H2NOH-HCl, S:H2O, S:EtOH, 8 h, reflux Reactants: 1, Reagents: 2, Solvents: 2, Steps:1, Stages: 1, Most stages in any one step: 1ReferencesDesign, synthesis, characterization, andantibacterial activity of {5-chloro-2-[(3-substitutedphenyl-1,2,4-oxadiazol-5-yl)-methoxy]-phenyl}-(phenyl)-methanonesBy Rai, Neithnadka Premsai et alFrom European Journal of MedicinalChemistry, 45(6), 2677-2682; 2010 CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.20. Single Step70%OverviewSteps/Stages Notes1.1 R:H2NOH-HCl, R:NaHCO3, S:H2O, S:MeOH, 1 h, rt → 70°C; cooled stereoselective, Reactants: 1, Reagents: 2, Solvents: 2, Steps: 1, Stages: 1, Most stages in any one step: 1ReferencesDiscovery and Optimization of a Novel Series of N-Arylamide Oxadiazoles as Potent, Highly Selective and Orally Bioavailable Cannabinoid Receptor 2 (CB2) AgonistsBy Cheng, Yuan et alFrom Journal of Medicinal Chemistry, 51(16), 5019-5034; 2008Experimental ProcedureN-(9-Ethyl-9H-carbazol-3-yl)-3-(3-phenyl-1,2,4-oxadiazol-5-yl) propanamide (37). To a mixture ofsodium carbonate (1.0 g, 10 mmol) and hydroxylamine hydrochloride (1.0 g, 19 mmol) inmethanol/H2O was added benzonitrile (2 mL, 19 mmol). The mixture was heated to 70 °C for 1 h. Thecooled reaction mixture was concentrated, and the residue was taken up in dichloromethane. Theorganic layer was washed with water and concentrated to give (Z)-N'-hydroxybenzamidine (1.85 g,70% yield), which was used without further purification.CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.21. Single Step75%OverviewSteps/Stages Notes1.1 R:H2NOH-HCl, R:Disodium carbonate, S:MeOH Reactants: 1, Reagents: 2, Solvents: 1, Steps:1, Stages: 1, Most stages in any one step: 1ReferencesN-Aryl N'-Hydroxyguanidines, A New Class ofNO-Donors after Selective Oxidation by NitricOxide Synthases: Structure-ActivityRelationshipBy Renodon-Corniere, Axelle et alFrom Journal of Medicinal Chemistry, 45(4),944-954; 2002Experimental ProcedureBenzamidoximes 30-32 were prepared by refluxing anhydrous methanolic solutions of hydroxylaminehydrochloride with the corresponding nitrile in the presence of sodium carbonate as previouslydescribed.57Benzamidoxime (30). Compound 30 was obtained as a white solid in 75% yield frombenzonitrile mp 76 °C (literature: 76 °C).57CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.22. Single Step70%OverviewSteps/Stages Notes1.1 R:KOH, R:H2NOH-HCl, S:MeOH, 3-6 h, 6°C in-situ generated reagent, Reactants: 1,Reagents: 2, Solvents: 1, Steps: 1, Stages: 1,Most stages in any one step: 1ReferencesHCV NS5b RNA-Dependent RNAPolymerase Inhibitors: From α,γ-Diketoacidsto 4,5-Dihydroxypyrimidine- or 3-Methyl-5-hydroxypyrimidinonecarboxylic Acids. Designand SynthesisBy Summa, Vincenzo et alFrom Journal of Medicinal Chemistry, 47(22),5336-5339; 2004Experimental ProcedureN'-hydroxybenzenecarboximidamide (12), 3-(benzyloxy)-N'-hydroxybenzenecarboximidamide (13), N'-hydroxy-3-[(4-methoxybenzyl)oxy]benzenecarboximidamide were prepared from the correspondingnitriles by use of known procedures. Generally, one equiv of potassium hydroxide dissolved inmethanol was added to a solution of hydroxylamine hydrochloride (1 equiv) in methanol. Theprecipitated potassium chloride was removed by filtration and to the above solution the appropriate arylnitrile was added. Reaction mixture was stirred at 60°C for the appropriate time (3-6 h, TLCmonitoring). After cooling, the solvent was removed under vacuum, and the residue was triturated withdiethyl ether. The precipitate was collected and eventually recristallyzed from an appropriate solvent,furnishing the desired amidoxime in 60-70 % yield. N'-hydroxybenzenecarboximidamide (12): spectraldata matches literature data.3CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.23. Single Step65%OverviewSteps/Stages Notes1.1 R:K2CO3, R:H2NOH-HCl, S:EtOH, 1 h, rt; 6 h, reflux Reactants: 1, Reagents: 2, Solvents: 1, Steps:1, Stages: 1, Most stages in any one step: 1ReferencesAcetic acid aldose reductase inhibitorsbearing a five-membered heterocyclic corewith potent topical activity in a visualimpairment rat modelBy La Motta, Concettina et alFrom Journal of Medicinal Chemistry, 51(11),3182-3193; 2008Experimental ProcedureGeneral Procedure for the Synthesis of N-Hydroxybenzimidamides3a-i and N-Hydroxy-2-phenylacetimidamides 4a-i. A solution of the appropriate nitrile 1a-i or 2a-i (1.00 mmol), hydroxylaminehydrochloride (1.35 mmol), and potassium carbonate (1.00 mmol) in ethanol was left under stirring atroom temperature for 1 h, then heated under reflux until the disappearance of the starting materials (6h, TLC analysis). After cooling, the resulting mixture was filtered and the solvent was evaporated todryness under reduced pressure to give the target compound as a white solid, which was purified byrecrystallization (Supporting Information, Tables 1 and 2).CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.24. Single Step60%OverviewSteps/Stages Notes1.1 R:Et3N, R:H2NOH-HCl, S:EtOH, rt → reflux; 24 h, reflux Reactants: 1, Reagents: 2, Solvents: 1, Steps:1, Stages: 1, Most stages in any one step: 1ReferencesSynthesis and cannabinoid activity of 1-substituted-indole-3-oxadiazole derivatives:Novel agonists for the CB1 receptorBy Moloney, Gerard P. et alFrom European Journal of MedicinalChemistry, 43(3), 513-539; 2008 CASREACT ®: Copyright © 2012 American Chemical Society. All Rights Reserved. CASREACT contains reactions from CAS and from: ZIC/VINITI database (1974-1999) provided by InfoChem; INPI data prior to 1986; Biotransformations database compiled under the direction of Professor Dr. Klaus Kieslich; organic reactions, portions copyright 1996-2006 John Wiley & Sons, Ltd., John Wiley and Sons, Inc., Organic Reactions Inc., and Organic Syntheses Inc. Reproduced under license. All Rights Reserved.25. Single Step60%Overview。

新型双幅板压制滑轮及其制造技术

新型双幅板压制滑轮及其制造技术陈创业朱国和上海振华重工（集团）股份有限公司长兴分公司上海 201913摘要：文中针对原有技术存在的不足，通过理论分析和现场型式试验，自主研发开发了一种新型双幅板压制滑轮，并形成了独特的双幅板压制滑轮制造技术。

压制滑轮的轮缘采用冷加工方式成型,避免了热加工成型如铸造、锻造和热轧滑轮制造过程中不可避免的表面氧化和脱碳问题，而表面氧化和脱碳直接影响滑轮轮缘的表面硬度和服役寿命，且压制加工方式简单、制造成本低，具有独特的优势。

研究结果表明，该款新型双幅板压制滑轮具有结构设计合理、强度和刚度好、自重轻、轮槽耐磨使用寿命长的特点，能够完全替代常规的热轧滑轮。

使用该技术制造的滑轮，已在多个项目中得到应用和验证，创造了良好的经济效益和社会效益，新型双幅板压制滑轮发展前景良好，市场前景广阔。

关键词：起重机；滑轮；压制；双幅板中图分类号：TG457. 25 文献标识码：B 文章编号：1001-0785（2023）13-0077-04Abstract: Considering the shortcomings of the original technology, through theoretical analysis and field type test, a new type of double-plate pressed pulley was independently developed, and a unique manufacturing technology of double-plate pressed pulley was developed. The flange of pressed pulley is formed by cold working, which avoids the inevitable surface oxidation and decarbonization in hot working, such as casting, forging and hot rolling pulley manufacturing. Surface oxidation and decarbonization will directly affect the surface hardness and service life of pulley flange, and the pressed method is simple and the manufacturing cost is low, with unique advantages. The research results show that this new type of double-plate pressed pulley has the characteristics of reasonable structure and design, good strength and stiffness, light weight, long service life of wheel groove wear resistance and so on, and can completely replace the conventional hot rolling pulley. Pulleys manufactured with this technology have been applied and verified in many projects, which has brought good economic and social benefits. Therefore, this new double-plate pressed pulley has a good development prospect and a broad market prospect.Keywords:crane; pulley; suppress; double plate0 引言滑轮作为承载部件之一，广泛应用在各种起重运输机械中。

Biosci. Biotechnol. Biochem.杂志要求

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水玻璃-Na2CO3激发富镁镍渣-粉煤灰基地质聚合物的制备及性能

第41卷第2期2022年2月硅㊀酸㊀盐㊀通㊀报BULLETIN OF THE CHINESE CERAMIC SOCIETY Vol.41㊀No.2February,2022水玻璃-Na 2CO 3激发富镁镍渣-粉煤灰基地质聚合物的制备及性能刘㊀云1,封春甫1,刘㊀洋1,杨圣玮1,王觅堂1,2(1.内蒙古科技大学材料与冶金学院,包头㊀014010;2.上海理工大学材料科学与工程学院,上海㊀200093)摘要:本文使用正交试验法,研究了富镁镍渣与粉煤灰的质量比㊁复合碱激发剂(水玻璃-Na 2CO 3)掺量及水胶比对富镁镍渣-粉煤灰基地质聚合物力学性能的影响,通过XRD㊁SEM㊁EDS 及TG 等测试方法对水化产物进行表征㊂结果表明,最优试样28d 抗压强度可达37.50MPa㊂XRD 结果显示,7d 与28d 的水化产物中含有水化硅酸钙凝胶,结合SEM㊁EDS 分析可知,产物中还有菱沸石(N-A-S-H)与钠镁硅铝酸盐(N-M-A-S)无定形凝胶相,这些凝胶相是地质聚合物强度增加的主要原因㊂关键词:碱激发地质聚合物;复合碱激发剂;富镁镍渣;粉煤灰;力学性能中图分类号:TQ172.4+4㊀㊀文献标志码:A ㊀㊀文章编号:1001-1625(2022)02-0582-07Preparation and Properties of Sodium Silicate-Na 2CO 3Activated Magnesium-Rich Nickel Slag-Fly Ash Based GeopolymerLIU Yun 1,FENG Chunfu 1,LIU Yang 1,YANG Shengwei 1,WANG Mitang 1,2(1.College of Materials and Metallurgy,Inner Mongolia University of Science and Technology,Baotou 014010,China;2.College of Materials Science and Engineering,Shanghai University of Technology,Shanghai 200093,China)Abstract :In this paper,the effects of the mass ratio of magnesium-rich nickel slag and fly ash,the content of composite alkali activator (sodium silicate-Na 2CO 3)and water binder ratio on the mechanical properties of magnesium-rich nickel slag-fly ash based geopolymer were studied by orthogonal test.The products were characterized by XRD,SEM,EDS and TG.The results show that the 28d compressive strength of the optimal sample reaches 37.50MPa.XRD results shows that calcium silicate gel form in the products of 7d and 28d.SEM and EDS analysis show that there are chabazite (N-A-S-H)and sodium magnesium aluminum silicate gel (N-M-A-S)amorphous gel phases in the products.These gel phases are the main reasons for the increase of the strength of geopolymer.Key words :alkali activated geopolymer;composite alkali activator;magnesium-rich nickel slag;fly ash;mechanical property㊀收稿日期:2021-07-01;修订日期:2021-09-13基金项目:国家自然科学基金(51974168,51662033);硅酸盐建筑材料国家重点实验室(武汉理工大学)开放基金(SYSJJ2020-08);内蒙古自治区科技重大专项(2019ZD023)作者简介:刘㊀云(1997 ),男,硕士研究生㊂主要从事固废处理研究㊂E-mail:mbyliuyun@通信作者:王觅堂,博士,教授㊂E-mail:btwmt@ 0㊀引㊀言20世纪70年代,法国科学家Davidovits [1]提出了地质聚合物的概念,它是一种由[AlO 4]4-和[SiO 4]4-四面体结构单元组成的三维立体网状结构无机聚合物,无定形到半晶态,属于非金属材料㊂这种材料具有优良的机械性能,凝结硬化快[2]㊁强度高㊁耐高温[3]和耐酸腐蚀[4-5],在土木建筑㊁固核固废㊁高强㊁密封和高温环境等工程中有广大的应用前景㊂镍渣中含有的大量硅铝质活性材料具有制备地质聚合物的潜力,使用镍渣来制备地质聚合物不仅可以第2期刘㊀云等:水玻璃-Na 2CO 3激发富镁镍渣-粉煤灰基地质聚合物的制备及性能583㊀减少镍渣堆积对环境的污染,也可以为企业和地区带来巨大的经济效益,符合新时代可持续发展理念[6-8]㊂目前,国内外对矿渣类地质聚合物做了大量的研究,主要是以粉煤灰和偏高岭土为原料,并且取得了一些研究成果[9-12],但是使用镍渣与粉煤灰这两种工业固体废弃物来制备地质聚合物的研究相对较少㊂Yang 等[13-15]研究了富镁镍渣添加对粉煤灰基地质聚合物反应㊁力学性能和微观结构的影响㊂结果表明,粉煤灰-富镁镍渣基地质聚合物的主要相是一种具有无定形特征的钠镁硅铝酸盐凝胶㊂Wu 等[16]研究了富镁镍渣对硅酸盐水泥净浆水化特性的影响,结果表明,随着镍渣含量的增加,水泥浆体水化累积放热降低,表明镍渣的火山灰活性较低㊂刘洋等[17]以水玻璃和NaOH 作为碱激发剂,研究了富镁镍渣与粉煤灰混合制备地质聚合物的可行性,制得地质聚合物的抗压强度最高为22.15MPa㊂以上研究都以水玻璃或者水玻璃加强碱作为碱激发剂,制得的地质聚合物强度并不高,而以水玻璃加强碱弱酸盐为碱激发剂去激发富镁镍渣-粉煤灰基地质聚合物的研究还较少㊂本研究以水玻璃和Na 2CO 3作为复合激发剂,使用正交试验法,制备一系列碱激发富镁镍渣-粉煤灰基地质聚合物,以获得最优配合比㊂通过X 射线衍射(XRD)㊁扫描电子显微镜(SEM)㊁X 射线能谱(EDS)及热重(TG)等表征方法探究活性较低的富镁镍渣制备地质聚合物的可行性㊂1㊀实㊀验1.1㊀原材料水淬富镁镍渣,比表面积为1096.30m 2/kg,任何一种污染物的浓度未超过GB 8978 2002‘污水综合排放标准“最高允许排放浓度,pH 值在6~9,为第Ⅰ类工业固体废弃物㊂高钙类C 级粉煤灰,比表面积为4900.70m 2/kg㊂富镁镍渣和粉煤灰的化学成分见表1,图1㊁图2分别为富镁镍渣和粉煤灰的XRD 谱和SEM 照片㊂其中富镁镍渣主要含有镁铁橄榄石等矿物相,活性极低,难激发,粉煤灰主要由无定形的石英和游离的生石灰等物质组成,具有一定的活性㊂碱激发剂是由水玻璃和Na 2CO 3复配获得,其中水玻璃原始模数为2.90,SiO 2㊁Na 2O 的质量百分含量分别为59.60%㊁21.20%,NaOH 为分析纯粒状,纯度ȡ96%(质量分数),用于调节水玻璃模数为1.20,Na 2CO 3为纯度ȡ99.5%(质量分数)的无水碳酸钠㊂表1㊀富镁镍渣和粉煤灰的化学成分Table 1㊀Chemical composition of magnesium-rich nickel slag and fly ashOxide Mass fraction /%SiO 2MgO Fe 2O 3Al 2O 3CaO MnO K 2O Other LOI Nickel slag (NS)42.9626.5212.5212.09 4.880.890.110.03 Fly ash (FA)53.33 1.978.4319.6411.720.09 1.172.63 1.02图1㊀富镁镍渣和粉煤灰的XRD 谱Fig.1㊀XRD patterns of magnesium-rich nickel slag and fly ash584㊀胶凝材料硅酸盐通报㊀㊀㊀㊀㊀㊀第41卷图2㊀富镁镍渣和粉煤灰的SEM照片Fig.2㊀SEM images of magnesium-rich nickel slag and fly ash1.2㊀试样制备本试验使用正交试验法,研究了富镁镍渣与粉煤灰的质量比㊁复合碱激发剂(水玻璃-Na2CO3)掺量及水胶比对富镁镍渣-粉煤灰基地质聚合物力学性能及组织结构的影响㊂正交试验因素水平如表2所示,正交试验配合比如表3所示㊂表2㊀正交试验因素水平Table2㊀Factor level of orthogonal testLevel NS/FA(A)Na2CO3(B)/%Water-binder ratio(C)17ʒ340.2825ʒ560.3033ʒ780.32㊀㊀注:%为质量分数㊂表3㊀正交试验配合比Table3㊀Mix proportion of orthogonal testSample number FactorNS/FA Na2CO3mass fraction/%Water-binder ratio Sodium silicatemass fraction/%Sodium silicatemodulus17ʒ340.2827ʒ360.3237ʒ380.3045ʒ540.3255ʒ560.3015 1.2065ʒ580.2873ʒ740.3083ʒ760.2893ʒ780.32地质聚合物净浆的制备:将水玻璃㊁Na2CO3㊁NaOH和水按照一定质量比例配制成碱溶液,搅拌均匀并静置,冷却至室温,然后按原料配合比称取经球磨机球磨过的富镁镍渣和粉煤灰至规定质量(精确到0.01g),随后将配置好的碱溶液以及富镁镍渣和粉煤灰倒入JJ5型ISO-679行星式水泥净浆搅拌机中搅拌均匀,待浆体表面无明显气泡析出时,迅速倒入40mmˑ40mmˑ160mm三联模具中,放到ZT-96胶砂成型振实台上振实1min,室温下养护24h后脱模,再将脱模后的成品放入YH-20B标准水泥恒温恒湿养护箱中养护至规定龄期㊂1.3㊀测试方法用万能压力试验机(TES-10000型)测定富镁镍渣-粉煤灰基地质聚合物3d㊁7d㊁28d的抗压强度,测试方法依据GB/T17671 1999‘水泥胶砂强度检验方法(ISO法)“;用X射线衍射仪(D/max-RB型,Rigaku公司)分析富镁镍渣-粉煤灰基地质聚合物的物相组成变化;用场发射扫描电镜(TESCAN-MIRA3型)观察富第2期刘㊀云等:水玻璃-Na 2CO 3激发富镁镍渣-粉煤灰基地质聚合物的制备及性能585㊀镁镍渣-粉煤灰基地质聚合物的微观形貌,并配合X 射线能谱仪分析微区元素成分;用同步热分析仪(TGA /DSC3+型,METTLER 公司)对地质聚合物进行热分析㊂2㊀结果与讨论2.1㊀正交试验结果正交试验结果如表4所示,以3d㊁7d㊁28d 的抗压强度作为地质聚合物力学性能的优劣指标,由极差(R )分析结果可知,影响富镁镍渣-粉煤灰基地质聚合物抗压强度的因素主次顺序为:Na 2CO 3掺量(B)>NS /FA(A)>水胶比(C),说明Na 2CO 3掺量这一因素对富镁镍渣-粉煤灰基地质聚合物的抗压强度影响最大㊂表4㊀正交试验结果Table 4㊀Results of orthogonal testSample number A B C 3d compressive strength /MPa 7d compressive strength /MPa 28d compressive strength /MPa 111114.1023.3024.60212314.8017.7021.303132 6.307.908.70421318.3025.8022.10522220.8026.1022.406231 5.109.607.30731219.8025.6037.50832111.2024.8015.80933313.6013.3014.40图3㊀各因素对富镁镍渣-粉煤灰基地质聚合物抗压强度的影响Fig.3㊀Influence of various factors on compressive strength of magnesium-rich nickel slag fly ash geopolymer 图3为各因素对富镁镍渣-粉煤灰基地质聚合物抗压强度的影响,由图可知,使用水玻璃-Na 2CO 3复合碱激发剂制备富镁镍渣-粉煤灰基地质聚合物的最佳方案为A 3B 1C 2,即NS /FA 为3ʒ7㊁Na 2CO 3掺量为4%㊁水胶比为0.30㊂2.2㊀XRD 分析图4是最优试样3d㊁7d㊁28d 的XRD 谱,从图中可以看出,10ʎ~70ʎ的衍射区域中存在着不同衍射强度的尖锐峰,与标准PDF 卡片对比之后发现,7d 和28d 的产物中新生成了少量的水化硅酸钙(C-S-H),且28d C-S-H 衍射峰的强度更高,3d 的产物中则未检测到有C-S-H 的生成,说明随着养护时间的增加,试样中的物质在不断发生水化反应,XRD 结果也表明,反应后的试样中还存在着大量的石英(quartz),这是由于最优试样中粉煤灰的含量达到了70%(质量分数),而粉煤灰中本身就含有大量的石英,碱激发剂不足以让这么多的粉煤灰都参与水化反应,所以试样中会检测出大量石英㊂试样中未检测出富镁镍渣的主要晶相镁橄榄石相,但是在28d 的产物中检测出了少量的透镁铝石(meixnerite),可能是镁橄榄石相与铝氧化物在激发剂的激发下发生水化反应而生成,这也是地质聚合物强度提升的原因之一㊂此外,碱激发地质聚合物的反应产物大多是无定形的,常规养护的样品很难形成沸石等结晶材料,因此,在试样的XRD 谱中新出现的峰很少㊂2.3㊀微观形貌及能谱分析图5为最优试样3d㊁7d㊁28d 的截面微观形貌与对应区域EDS 谱㊂从图中可以看出,随着养护时间的增加,试样的微观结构变得越来越致密,并且可以看到反应后试样中仍存在部分未反应的粉煤灰颗粒,这表明在碱激发剂的作用下,粉煤灰并没有完全参与反应,这一点从2.2节中的XRD 谱中也可以得到佐证㊂从586㊀胶凝材料硅酸盐通报㊀㊀㊀㊀㊀㊀第41卷图4㊀最优试样3d㊁7d㊁28d XRD 谱Fig.4㊀3d,7d,28d XRD patterns of the best samples 图5(a)中可以看到a 区有团聚凝胶生成,从能谱分析结果表明,a 区的主要元素有Na㊁Al㊁O㊁Si,可以判定为菱沸石(N-A-S-H)相㊂从图5(b)中可以观察到b 区有大量絮状凝胶生成,且看上去结构致密,能谱分析结果表明,b 区的主要元素有Na㊁Al㊁Mg㊁O㊁Si,可以判定此凝胶相为钠镁硅铝酸盐凝胶(N-M-A-S),是一种无定形凝胶㊂从28d 试样中的c 区可以看到有长条状致密凝胶生成,能谱分析结果表明,c 区的主要元素有Ca㊁O㊁Si,并且钙含量达到了20%(质量分数),结合XRD 谱中检测出的硅酸钙,可以判定为C-S-H 凝胶团聚体㊂可以看到地质聚合物基体中有少量的微裂纹和凹坑,微裂纹是由压力引起的,而凹坑是由粉煤灰微球脱落形成的[18]㊂图5㊀最优试样3d㊁7d㊁28d SEM 照片及对应区域a㊁b㊁c 的EDS 谱Fig.5㊀3d,7d,28d SEM images of the best samples and EDS spectra of corresponding regions a,b,c第2期刘㊀云等:水玻璃-Na 2CO 3激发富镁镍渣-粉煤灰基地质聚合物的制备及性能587㊀2.4㊀热稳定性分析图6㊀最优试样养护28d TG-DSC 曲线Fig.6㊀Optimal sample curing 28d TG-DSC curves 图6是最优试样养护28d 的TG-DSC 曲线㊂由图可知,DSC 曲线上120ħ附近出现一个吸热峰,这主要是C-S-H 中的自由水和吸附水的蒸发引起的[19]㊂在0~350ħ这一阶段质量急速下降,失重率达到了8.66%,这是化学结合水遭到破坏而失重,在地质聚合物浆体中,水只有两种存在形式,一是存在于地质聚合物孔洞中的物理结合水,二是作为水化产物组成的化学结合水,0~350ħ这一阶段化学结合水的急速减少说明地质聚合物的水化程度增加㊂在630ħ附近出现的吸热峰为CaCO 3的分解峰㊂500~700ħ期间,质量下降速率降低并趋于平稳,在700ħ左右失重率达到1.25%,总失重率大约有10%,研究[20]表明,这是材料中的硅铝酸盐相分解造成的㊂在700ħ以后没有出现任何吸热峰和放热峰,地质聚合物的质量基本趋于稳定㊂2.5㊀Na 2CO 3掺量对胶凝材料力学性能的影响综合正交试验结果分析可知,Na 2CO 3掺量对地质聚合物的强度影响较大,地质聚合物养护28d 最大抗压强度为37.50MPa,比刘洋等[17]以水玻璃和NaOH 作为碱激发剂制得的地质聚合物养护28d 最高强度为22.15MPa 有了明显的提高,通过XRD 及SEM 的分析知,本试验中的地质聚合物主要水化产物为C-S-H㊁N-A-S-H 与N-M-A-S 无定形凝胶相,而刘洋等以水玻璃和NaOH 作为碱激发剂制得的地质聚合物主要水化产物只有N-M-A-S 无定形凝胶相,所以Na 2CO 3的加入促使了更多的水化产物生成,这就使得地质聚合物的强度更高,另外不同的实验操作也可能会引起最后强度的不同,比如搅拌㊁振实是否充分,这些因素都决定着地质聚合物的致密度以及最终的强度㊂3㊀结㊀论本研究以富镁镍渣㊁粉煤灰为主要原料,采用水玻璃-Na 2CO 3作为复合碱激发剂制备富镁镍渣-粉煤灰基地质聚合物,得出以下结论:(1)NS /FA 与Na 2CO 3掺量是影响地质聚合物强度的主要因素,水胶比对于地质聚合物强度的影响较小㊂使用水玻璃-Na 2CO 3作为复合碱激发剂激发的富镁镍渣-粉煤灰基地质聚合物具有良好的力学性能,当富镁镍渣与粉煤灰质量比为3ʒ7,水玻璃掺量为15%,模数为1.20,Na 2CO 3掺量为4%,水胶比为0.30时,所制备的地质聚合物净浆具有最优的力学性能,其28d 抗压强度可达37.50MPa㊂(2)从XRD㊁SEM㊁EDS 及TG 的表征结果得知,致使碱激发富镁镍渣-粉煤灰基地质聚合物强度提高的主要水化产物为水化硅酸钙(C-S-H)㊁菱沸石(N-A-S-H)与钠镁硅铝酸盐(N-M-A-S)无定形凝胶相,粉煤灰的反应并不完全,结构中仍有大量未反应的粉煤灰颗粒㊂参考文献[1]㊀DAVIDOVITS J.Geopolymers and geopolymeric materials[J].Journal of Thermal Analysis,1989,35(2):429-441.[2]㊀SOFI M,VAN DEVENTER J S J,MENDIS P A,et al.Engineering properties of inorganic polymer concretes (IPCs)[J].Cement and ConcreteResearch,2007,37(2):251-257.[3]㊀RASHAD A M,ZEEDAN S R,HASSAN A A.Influence of the activator concentration of sodium silicate on the thermal properties of alkali-activated slag pastes[J].Construction and Building Materials,2016,102:811-820.[4]㊀BAKHAREV T.Resistance of geopolymer materials to acid attack[J].Cement and Concrete Research,2005,35(4):658-670.[5]㊀BAKHAREV T.Durability of geopolymer materials in sodium and magnesium sulfate solutions[J].Cement and Concrete Research,2005,35(6):1233-1246.[6]㊀葛利杰,杨鼎宜,李㊀浩,等.镍渣综合利用技术综述[J].江苏建材,2015(4):6-9.588㊀胶凝材料硅酸盐通报㊀㊀㊀㊀㊀㊀第41卷GE L J,YANG D Y,LI H,et al.The technical summary of comprehensive utilization of nickel slag[J].Jiangsu Building Materials,2015(4): 6-9(in Chinese).[7]㊀李国洲,张燕云,马泳波,等.镍冶金渣综合利用现状[J].中国冶金,2017,27(8):1-5.LI G Z,ZHANG Y Y,MA Y B,et prehensive utilization of nickel metallurgical residue[J].China Metallurgy,2017,27(8):1-5(in Chinese).[8]㊀张祥成,孟永彪.浅析中国粉煤灰的综合利用现状[J].无机盐工业,2020,52(2):1-5.ZHANG X C,MENG Y B.Brief analysis on present situation of comprehensive utilization of fly ash in China[J].Inorganic Chemicals Industry, 2020,52(2):1-5(in Chinese).[9]㊀管柏伦,郭荣鑫,齐荣庆,等.偏高岭土-粉煤灰基地聚物砂浆力学性能研究[J].硅酸盐通报,2021,40(4):1250-1257.GUAN B L,GUO R X,QI R Q,et al.Mechanical properties of geopolymer mortar based on metakaolin and fly ash[J].Bulletin of the Chinese Ceramic Society,2021,40(4):1250-1257(in Chinese).[10]㊀DUXSON P,PROVIS J L,LUKEY G C,et al.Understanding the relationship between geopolymer composition,microstructure and mechanicalproperties[J].Colloids and Surfaces A:Physicochemical and Engineering Aspects,2005,269(1/2/3):47-58.[11]㊀陶㊀涛,杨建明,李㊀涛,等.偏高岭土和粉煤灰对大流动性磷酸钾镁水泥抗盐冻性能的影响[J].混凝土,2021(4):87-90+95.TAO T,YANG J M,LI T,et al.Effect of fly ash and metakaolin on salt-frost resistance of high fluidity magnesium potassium phosphate cement[J].Concrete,2021(4):87-90+95(in Chinese).[12]㊀PALOMO A,GRUTZECK M W,BLANCO M T.Alkali-activated fly ashes:a cement for the future[J].Cement and Concrete Research,1999,29(8):1323-1329.[13]㊀ZHANG Z,ZHU Y C,YANG T,et al.Conversion of local industrial wastes into greener cement through geopolymer technology:a case study ofhigh-magnesium nickel slag[J].Journal of Cleaner Production,2017,141:463-471.[14]㊀YANG T,ZHANG Z H,ZHU H J,et al.Re-examining the suitability of high magnesium nickel slag as precursors for alkali-activated materials[J].Construction and Building Materials,2019,213:109-120.[15]㊀YANG T,WU Q S,ZHU H J,et al.Geopolymer with improved thermal stability by incorporating high-magnesium nickel slag[J].Constructionand Building Materials,2017,155:475-484.[16]㊀WU Q S,WANG S X,YANG T,et al.Effect of high-magnesium nickel slag on hydration characteristics of Portland cement[J].Journal ofMaterials in Civil Engineering,2019,31(5):04019051.[17]㊀刘㊀洋,吴锦绣,封春甫,等.富镁镍渣-粉煤灰基地质聚合物的制备与性能表征[J].硅酸盐通报,2021,40(3):921-928.LIU Y,WU J X,FENG C F,et al.Preparation and performance characterization of magnesium-rich nickel slag-fly ash-based geopolymer[J].Bulletin of the Chinese Ceramic Society,2021,40(3):921-928(in Chinese).[18]㊀LV Q F,WANG Z S,GU L Y,et al.Effect of sodium sulfate on strength and microstructure of alkali-activated fly ash based geopolymer[J].Journal of Central South University,2020,27(6):1691-1702.[19]㊀王灿强.碱激发镍渣-粉煤灰炉渣胶凝材料的制备研究[D].福州:福州大学,2017.WANG C Q.Study on preparation of alkali-activated nickel slag-fly ash-incineration slag cementitious material[D].Fuzhou:Fuzhou University, 2017(in Chinese).[20]㊀刘㊀云.粉煤灰-镍铁渣地质聚合物的制备及其性能研究[D].济南:济南大学,2017.LIU Y.Preparation and properties of fly ash-ferronickel slag geopolymer[D].Jinan:University of Jinan,2017(in Chinese).。

爱普生产品指南说明书

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事件史分析操作及说明A_08

事件史分析的Stata操作及说明目录离散时间模型示例：职位晋升分析 (1)Cox模型 (2)Cox模型示例：癌症数据分析 (3)分层的(stratified) Cox模型的背景 (11)示例：癌症生存的分层分析 (12)最大似然估计的连续时间存活分析 (18)Exponential分布模型 (18)Gompertz模型 (19)Weibull模型 (19)用Stata拟合exponential模型、Weibull模型和Gompertz模型：癌症生存 (19)本章参考文献：1.* Lawrence C. Hamilton. Statistics with STATA, Updated for Version 9. Brooks/Cole, a division of Thomson Learning,Inc.,-2006. （第11章）// 中译本：郭志刚等，应用STATA做统计分析，重庆大学出版社，2008.2.* Rabe-Hesketh and Everitt. A Handbook of Statistical Analyses Using Stata. Chapman & Hall/CRC, 20043.* Kleinbaum. Survival Analysis. 1996;4.* Yamaguchi, Kazuo. Event History Analysis. Sage Publications. Inc. 19915.* Allison, Paul D.. Event History Analysis: Regression for Longitudinal Event Data.Sage Publications, Inc. 19846.* Blossfeld, Hamerle and Mayer. Event History wrence Erlbaum Associates, Inc. 19897.* Blossfeld and Rohwer. Techniques of Event History Modeling: New Approaches to Causal Analysis (Second Edition).Lawrence Erlbaum Associates, Publishers, 2002.8.* Cleves, Gould and Gutierrez. An Introduction to Survival Analysis Using Stata (reviced edition). Stata PressPublication, 2004.9.* Janet M. Box-Steffensmeier and Bradford S. Jones. Event History Modeling : A Guide for Social Scientists.Cambridge University Press, 200410.梁在，事件史分析，载郭志刚主编《社会统计分析方法----SPSS软件应用》，中国人民大学出版社，1999年。

信息管理与信息系统学科基础课程

信息管理与信息系统学科基础课程学科基础课程：高级语言程序设计、高等数学（B）、管理信息系统、数据库原理与应用、管理学原理。

专业主干课程：信息管理学基础、经济学原理、管理学原理、高级语言程序设计、计算机原理、数据结构、信息分析与预测、数据库原理与应用、计算机网络、信息组织、信息检索、信息服务与用户、信息计量学、信息系统分析与设计、管理信息系统、网站设计与开发、操作系统原理、信息需求分析、市场营销、运筹学、标准化与质量管理、智能信息系统、信息经济学等。

信息管理与信息系统专业人才培养方案Undergraduate Program for Information Management &Information System Major 学科门类：管理学代码：11Discipline Type: Administration Code: 11类别：管理科学与工程类代码：1101Type:Management Science and Engineering Code: 1101专业名称：信息管理与信息系统代码：110102Title of the Major: Information Management &Information System Code: 110102一、学制与学位Length of Schooling and Degree学制：四年Duration：4 years学位：管理学学士学位Degree：Bachelor of Administration二、培养目标Educational Objectives本专业培养具有扎实的管理学理论基础、熟练掌握计算机技术知识，有较强的计算机和网络应用能力、有较强的信息系统分析和设计方法以及信息管理等方面的知识和能力的高级管理人才。

能在电力系统、企事业单位、金融机构、科研院所和国家各级管理部门从事信息系统分析、设计、开发、实施、维护和评价等方面的工作。

Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease trans

Reproduction numbers and sub-threshold endemicequilibria for compartmental models of disease transmissionP.van den Driesschea,1,James Watmough b,*,2aDepartment of Mathematics and Statistics,University of Victoria,Victoria,BC,Canada V8W 3P4b Department of Mathematics and Statistics,University of New Brunswick,Fredericton,NB,Canada E3B 5A3Received 26April 2001;received in revised form 27June 2001;accepted 27June 2001Dedicated to the memory of John JacquezAbstractA precise deﬁnition of the basic reproduction number,R 0,is presented for a general compartmental disease transmission model based on a system of ordinary diﬀerential equations.It is shown that,if R 0<1,then the disease free equilibrium is locally asymptotically stable;whereas if R 0>1,then it is unstable.Thus,R 0is a threshold parameter for the model.An analysis of the local centre manifold yields a simple criterion for the existence and stability of super-and sub-threshold endemic equilibria for R 0near one.This criterion,together with the deﬁnition of R 0,is illustrated by treatment,multigroup,staged progression,multistrain and vector–host models and can be applied to more complex models.The results are signiﬁcant for disease control.Ó2002Elsevier Science Inc.All rights reserved.Keywords:Basic reproduction number;Sub-threshold equilibrium;Disease transmission model;Disease control1.IntroductionOne of the most important concerns about any infectious disease is its ability to invade a population.Many epidemiological models have a disease free equilibrium (DFE)at whichtheMathematical Biosciences 180(2002)29–48/locate/mbs*Corresponding author.Tel.:+1-5064587323;fax:+1-5064534705.E-mail addresses:pvdd@math.uvic.ca (P.van den Driessche),watmough@unb.ca (J.Watmough).URL:http://www.math.unb.ca/$watmough.1Research supported in part by an NSERC Research Grant,the University of Victoria Committee on faculty research and travel and MITACS.2Research supported by an NSERC Postdoctoral Fellowship tenured at the University of Victoria.0025-5564/02/$-see front matter Ó2002Elsevier Science Inc.All rights reserved.PII:S0025-5564(02)00108-630P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–48population remains in the absence of disease.These models usually have a threshold parameter, known as the basic reproduction number,R0,such that if R0<1,then the DFE is locally as-ymptotically stable,and the disease cannot invade the population,but if R0>1,then the DFE is unstable and invasion is always possible(see the survey paper by Hethcote[1]).Diekmann et al.[2]deﬁne R0as the spectral radius of the next generation matrix.We write down in detail a general compartmental disease transmission model suited to heterogeneous populations that can be modelled by a system of ordinary diﬀerential equations.We derive an expression for the next generation matrix for this model and examine the threshold R0¼1in detail.The model is suited to a heterogeneous population in which the vital and epidemiological parameters for an individual may depend on such factors as the stage of the disease,spatial position,age or behaviour.However,we assume that the population can be broken into homo-geneous subpopulations,or compartments,such that individuals in a given compartment are indistinguishable from one another.That is,the parameters may vary from compartment to compartment,but are identical for all individuals within a given compartment.We also assume that the parameters do not depend on the length of time an individual has spent in a compart-ment.The model is based on a system of ordinary equations describing the evolution of the number of individuals in each compartment.In addition to showing that R0is a threshold parameter for the local stability of the DFE, we apply centre manifold theory to determine the existence and stability of endemic equilib-ria near the threshold.We show that some models may have unstable endemic equilibria near the DFE for R0<1.This suggests that even though the DFE is locally stable,the disease may persist.The model is developed in Section2.The basic reproduction number is deﬁned and shown to bea threshold parameter in Section3,and the deﬁnition is illustrated by several examples in Section4.The analysis of the centre manifold is presented in Section5.The epidemiological ramiﬁcations of the results are presented in Section6.2.A general compartmental epidemic model for a heterogeneous populationConsider a heterogeneous population whose individuals are distinguishable by age,behaviour, spatial position and/or stage of disease,but can be grouped into n homogeneous compartments.A general epidemic model for such a population is developed in this section.Let x¼ðx1;...;x nÞt, with each x i P0,be the number of individuals in each compartment.For clarity we sort the compartments so that theﬁrst m compartments correspond to infected individuals.The distinc-tion between infected and uninfected compartments must be determined from the epidemiological interpretation of the model and cannot be deduced from the structure of the equations alone,as we shall discuss below.It is plausible that more than one interpretation is possible for some models.A simple epidemic model illustrating this is given in Section4.1.The basic reproduction number can not be determined from the structure of the mathematical model alone,but depends on the deﬁnition of infected and uninfected compartments.We deﬁne X s to be the set of all disease free states.That isX s¼f x P0j x i¼0;i¼1;...;m g:In order to compute R0,it is important to distinguish new infections from all other changes inpopulation.Let F iðxÞbe the rate of appearance of new infections in compartment i,Vþi ðxÞbe therate of transfer of individuals into compartment i by all other means,and VÀi ðxÞbe the rate oftransfer of individuals out of compartment i.It is assumed that each function is continuously diﬀerentiable at least twice in each variable.The disease transmission model consists of non-negative initial conditions together with the following system of equations:_x i¼f iðxÞ¼F iðxÞÀV iðxÞ;i¼1;...;n;ð1Þwhere V i¼VÀi ÀVþiand the functions satisfy assumptions(A1)–(A5)described below.Sinceeach function represents a directed transfer of individuals,they are all non-negative.Thus,(A1)if x P0,then F i;Vþi ;VÀiP0for i¼1;...;n.If a compartment is empty,then there can be no transfer of individuals out of the compartment by death,infection,nor any other means.Thus,(A2)if x i¼0then VÀi ¼0.In particular,if x2X s then VÀi¼0for i¼1;...;m.Consider the disease transmission model given by(1)with f iðxÞ,i¼1;...;n,satisfying con-ditions(A1)and(A2).If x i¼0,then f iðxÞP0and hence,the non-negative cone(x i P0, i¼1;...;n)is forward invariant.By Theorems1.1.8and1.1.9of Wiggins[3,p.37]for each non-negative initial condition there is a unique,non-negative solution.The next condition arises from the simple fact that the incidence of infection for uninfected compartments is zero.(A3)F i¼0if i>m.To ensure that the disease free subspace is invariant,we assume that if the population is free of disease then the population will remain free of disease.That is,there is no(density independent) immigration of infectives.This condition is stated as follows:(A4)if x2X s then F iðxÞ¼0and VþiðxÞ¼0for i¼1;...;m.The remaining condition is based on the derivatives of f near a DFE.For our purposes,we deﬁne a DFE of(1)to be a(locally asymptotically)stable equilibrium solution of the disease free model,i.e.,(1)restricted to X s.Note that we need not assume that the model has a unique DFE. Consider a population near the DFE x0.If the population remains near the DFE(i.e.,if the introduction of a few infective individuals does not result in an epidemic)then the population will return to the DFE according to the linearized system_x¼Dfðx0ÞðxÀx0Þ;ð2Þwhere Dfðx0Þis the derivative½o f i=o x j evaluated at the DFE,x0(i.e.,the Jacobian matrix).Here, and in what follows,some derivatives are one sided,since x0is on the domain boundary.We restrict our attention to systems in which the DFE is stable in the absence of new infection.That is, (A5)If FðxÞis set to zero,then all eigenvalues of Dfðx0Þhave negative real parts.P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–4831The conditions listed above allow us to partition the matrix Df ðx 0Þas shown by the following lemma.Lemma 1.If x 0is a DFE of (1)and f i ðx Þsatisﬁes (A1)–(A5),then the derivatives D F ðx 0Þand D V ðx 0Þare partitioned asD F ðx 0Þ¼F 000 ;D V ðx 0Þ¼V 0J 3J 4;where F and V are the m Âm matrices deﬁned byF ¼o F i o x j ðx 0Þ !and V ¼o V i o x jðx 0Þ !with 16i ;j 6m :Further ,F is non-negative ,V is a non-singular M-matrix and all eigenvalues of J 4have positive real part .Proof.Let x 02X s be a DFE.By (A3)and (A4),ðo F i =o x j Þðx 0Þ¼0if either i >m or j >m .Similarly,by (A2)and (A4),if x 2X s then V i ðx Þ¼0for i 6m .Hence,ðo V i =o x j Þðx 0Þ¼0for i 6m and j >m .This shows the stated partition and zero blocks.The non-negativity of F follows from (A1)and (A4).Let f e j g be the Euclidean basis vectors.That is,e j is the j th column of the n Ân identity matrix.Then,for j ¼1;...;m ,o V i o x jðx 0Þ¼lim h !0þV i ðx 0þhe j ÞÀV i ðx 0Þh :To show that V is a non-singular M-matrix,note that if x 0is a DFE,then by (A2)and (A4),V i ðx 0Þ¼0for i ¼1;...;m ,and if i ¼j ,then the i th component of x 0þhe j ¼0and V i ðx 0þhe j Þ60,by (A1)and (A2).Hence,o V i =o x j 0for i m and j ¼i and V has the Z sign pattern (see Appendix A).Additionally,by (A5),all eigenvalues of V have positive real parts.These two conditions imply that V is a non-singular M-matrix [4,p.135(G 20)].Condition (A5)also implies that the eigenvalues of J 4have positive real part.Ã3.The basic reproduction numberThe basic reproduction number,denoted R 0,is ‘the expected number of secondary cases produced,in a completely susceptible population,by a typical infective individual’[2];see also [5,p.17].If R 0<1,then on average an infected individual produces less than one new infected individual over the course of its infectious period,and the infection cannot grow.Conversely,if R 0>1,then each infected individual produces,on average,more than one new infection,and the disease can invade the population.For the case of a single infected compartment,R 0is simply the product of the infection rate and the mean duration of the infection.However,for more complicated models with several infected compartments this simple heuristic deﬁnition of R 0is32P.van den Driessche,J.Watmough /Mathematical Biosciences 180(2002)29–48insuﬃcient.A more general basic reproduction number can be deﬁned as the number of new infections produced by a typical infective individual in a population at a DFE.To determine the fate of a‘typical’infective individual introduced into the population,we consider the dynamics of the linearized system(2)with reinfection turned oﬀ.That is,the system _x¼ÀD Vðx0ÞðxÀx0Þ:ð3ÞBy(A5),the DFE is locally asymptotically stable in this system.Thus,(3)can be used to de-termine the fate of a small number of infected individuals introduced to a disease free population.Let wi ð0Þbe the number of infected individuals initially in compartment i and letwðtÞ¼w1ðtÞ;...;w mðtÞðÞt be the number of these initially infected individuals remaining in the infected compartments after t time units.That is the vector w is theﬁrst m components of x.The partitioning of D Vðx0Þimplies that wðtÞsatisﬁes w0ðtÞ¼ÀV wðtÞ,which has the unique solution wðtÞ¼eÀVt wð0Þ.By Lemma1,V is a non-singular M-matrix and is,therefore,invertible and all of its eigenvalues have positive real parts.Thus,integrating F wðtÞfrom zero to inﬁnity gives the expected number of new infections produced by the initially infected individuals as the vector FVÀ1wð0Þ.Since F is non-negative and V is a non-singular M-matrix,VÀ1is non-negative[4,p.137 (N38)],as is FVÀ1.To interpret the entries of FVÀ1and develop a meaningful deﬁnition of R0,consider the fate of an infected individual introduced into compartment k of a disease free population.The(j;k)entry of VÀ1is the average length of time this individual spends in compartment j during its lifetime, assuming that the population remains near the DFE and barring reinfection.The(i;j)entry of F is the rate at which infected individuals in compartment j produce new infections in compartment i. Hence,the(i;k)entry of the product FVÀ1is the expected number of new infections in com-partment i produced by the infected individual originally introduced into compartment k.Fol-lowing Diekmann et al.[2],we call FVÀ1the next generation matrix for the model and set R0¼qðFVÀ1Þ;ð4Þwhere qðAÞdenotes the spectral radius of a matrix A.The DFE,x0,is locally asymptotically stable if all the eigenvalues of the matrix Dfðx0Þhave negative real parts and unstable if any eigenvalue of Dfðx0Þhas a positive real part.By Lemma1, the eigenvalues of Dfðx0Þcan be partitioned into two sets corresponding to the infected and uninfected compartments.These two sets are the eigenvalues of FÀV and those ofÀJ4.Again by Lemma1,the eigenvalues ofÀJ4all have negative real part,thus the stability of the DFE is determined by the eigenvalues of FÀV.The following theorem states that R0is a threshold parameter for the stability of the DFE.Theorem2.Consider the disease transmission model given by(1)with fðxÞsatisfying conditions (A1)–(A5).If x0is a DFE of the model,then x0is locally asymptotically stable if R0<1,but un-stable if R0>1,where R0is deﬁned by(4).Proof.Let J1¼FÀV.Since V is a non-singular M-matrix and F is non-negative,ÀJ1¼VÀF has the Z sign pattern(see Appendix A).Thus,sðJ1Þ<0()ÀJ1is a non-singular M-matrix;P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–483334P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–48where sðJ1Þdenotes the maximum real part of all the eigenvalues of the matrix J1(the spectral abscissa of J1).Since FVÀ1is non-negative,ÀJ1VÀ1¼IÀFVÀ1also has the Z sign pattern.Ap-plying Lemma5of Appendix A,with H¼V and B¼ÀJ1¼VÀF,we have ÀJ1is a non-singular M-matrix()IÀFVÀ1is a non-singular M-matrix:Finally,since FVÀ1is non-negative,all eigenvalues of FVÀ1have magnitude less than or equal to qðFVÀ1Þ.Thus,IÀFVÀ1is a non-singular M-matrix;()qðFVÀ1Þ<1:Hence,sðJ1Þ<0if and only if R0<1.Similarly,it follows thatsðJ1Þ¼0()ÀJ1is a singular M-matrix;()IÀFVÀ1is a singular M-matrix;()qðFVÀ1Þ¼1:The second equivalence follows from Lemma6of Appendix A,with H¼V and K¼F.The remainder of the equivalences follow as with the non-singular case.Hence,sðJ1Þ¼0if and only if R0¼1.It follows that sðJ1Þ>0if and only if R0>1.ÃA similar result can be found in the recent book by Diekmann and Heesterbeek[6,Theorem6.13].This result is known for the special case in which J1is irreducible and V is a positive di-agonal matrix[7–10].The special case in which V has positive diagonal and negative subdiagonal elements is proven in Hyman et al.[11,Appendix B];however,our approach is much simpler(see Section4.3).4.Examples4.1.Treatment modelThe decomposition of fðxÞinto the components F and V is illustrated using a simple treat-ment model.The model is based on the tuberculosis model of Castillo-Chavez and Feng[12,Eq.(1.1)],but also includes treatment failure used in their more elaborate two-strain model[12,Eq.(2.1)].A similar tuberculosis model with two treated compartments is proposed by Blower et al.[13].The population is divided into four compartments,namely,individuals susceptible to tu-berculosis(S),exposed individuals(E),infectious individuals(I)and treated individuals(T).The dynamics are illustrated in Fig.1.Susceptible and treated individuals enter the exposed com-partment at rates b1I=N and b2I=N,respectively,where N¼EþIþSþT.Exposed individuals progress to the infectious compartment at the rate m.All newborns are susceptible,and all indi-viduals die at the rate d>0.Thus,the core of the model is an SEI model using standard inci-dence.The treatment rates are r1for exposed individuals and r2for infectious individuals. However,only a fraction q of the treatments of infectious individuals are successful.Unsuc-cessfully treated infectious individuals re-enter the exposed compartment(p¼1Àq).The diseasetransmission model consists of the following diﬀerential equations together with non-negative initial conditions:_E¼b1SI=Nþb2TI=NÀðdþmþr1ÞEþpr2I;ð5aÞ_I¼m EÀðdþr2ÞI;ð5bÞ_S¼bðNÞÀdSÀb1SI=N;ð5cÞ_T¼ÀdTþr1Eþqr2IÀb2TI=N:ð5dÞProgression from E to I and failure of treatment are not considered to be new infections,but rather the progression of an infected individual through the various compartments.Hence,F¼b1SI=Nþb2TI=NB B@1C CA and V¼ðdþmþr1ÞEÀpr2IÀm Eþðdþr2ÞIÀbðNÞþdSþb1SI=NdTÀr1EÀqr2Iþb2TI=NB B@1C CA:ð6ÞThe infected compartments are E and I,giving m¼2.An equilibrium solution with E¼I¼0has the form x0¼ð0;0;S0;0Þt,where S0is any positive solution of bðS0Þ¼dS0.This will be a DFE if and only if b0ðS0Þ<d.Without loss of generality,assume S0¼1is a DFE.Then,F¼0b100;V¼dþmþr1Àpr2Àm dþr2;givingVÀ1¼1ðdþmþr1Þðdþr2ÞÀm pr2dþr2pr2m dþmþr1and R0¼b1m=ððdþmþr1Þðdþr2ÞÀm pr2Þ.A heuristic derivation of the(2;1)entry of VÀ1and R0are as follows:a fraction h1¼m=ðdþmþr1Þof exposed individuals progress to compartment I,a fraction h2¼pr2=ðdþr2Þof infectious individuals re-enter compartment E.Hence,a fractionh1of exposed individuals pass through compartment I at least once,a fraction h21h2passthroughat least twice,and a fraction h k 1h k À12pass through at least k times,spending an average of s ¼1=ðd þr 2Þtime units in compartment I on each pass.Thus,an individual introduced into com-partment E spends,on average,s ðh 1þh 21h 2þÁÁÁÞ¼s h 1=ð1Àh 1h 2Þ¼m =ððd þm þr 1Þðd þr 2ÞÀm pr 2Þtime units in compartment I over its expected lifetime.Multiplying this by b 1gives R 0.The model without treatment (r 1¼r 2¼0)is an SEI model with R 0¼b 1m =ðd ðd þm ÞÞ.The interpretation of R 0for this case is simpler.Only a fraction m =ðd þm Þof exposed individuals progress from compartment E to compartment I ,and individuals entering compartment I spend,on average,1=d time units there.Although conditions (A1)–(A5)do not restrict the decomposition of f i ðx Þto a single choice for F i ,only one such choice is epidemiologically correct.Diﬀerent choices for the function F lead to diﬀerent values for the spectral radius of FV À1,as shown in Table 1.In column (a),treatment failure is considered to be a new infection and in column (b),both treatment failure and pro-gression to infectiousness are considered new infections.In each case the condition q ðFV À1Þ<1yields the same portion of parameter space.Thus,q ðFV À1Þis a threshold parameter in both cases.The diﬀerence between the numbers lies in the epidemiological interpretation rather than the mathematical analysis.For example,in column (a),the infection rate is b 1þpr 2and an exposed individual is expected to spend m =ððd þm þr 1Þðd þr 2ÞÞtime units in compartment I .However,this reasoning is biologically ﬂawed since treatment failure does not give rise to a newly infected individual.Table 1Decomposition of f leading to alternative thresholds(a)(b)Fb 1SI =N þb 2TI =N þpr 2I 0000B B @1C C A b 1SI =N þb 2TI =N þpr 2I m E 000B B @1C C A Vðd þm þr 1ÞE Àm E þðd þr 2ÞI Àb ðN ÞþdS þb 1SI =N dT Àr 1E Àqr 2I þb 2TI =N 0B B @1C C A ðd þm þr 1ÞE ðd þr 2ÞI Àb ðN ÞþdS þb 1SI =N dT Àr 1E Àqr 2I þb 2TI =N 0B B @1C C A F0b 1þpr 200 0b 1þpr 2m 0 V d þm þr 10Àm d þr 2d þm þr 100d þr 2 q (FV À1)b 1m þpr 2mðd þm þr 1Þðd þr 2Þﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃb 1m þpr 2mðd þm þr 1Þðd þr 2Þs 36P.van den Driessche,J.Watmough /Mathematical Biosciences 180(2002)29–484.2.Multigroup modelIn the epidemiological literature,the term‘multigroup’usually refers to the division of a het-erogeneous population into several homogeneous groups based on individual behaviour(e.g., [14]).Each group is then subdivided into epidemiological compartments.The majority of mul-tigroup models in the literature are used for sexually transmitted diseases,such as HIV/AIDS or gonorrhea,where behaviour is an important factor in the probability of contracting the disease [7,8,14,15].As an example,we use an m-group SIRS-vaccination model of Hethcote[7,14]with a generalized incidence term.The sample model includes several SI multigroup models of HIV/ AIDS as special cases[8,15].The model equations are as follows:_I i ¼X mj¼1b ijðxÞS i I jÀðd iþc iþ iÞI i;ð7aÞ_S i ¼ð1Àp iÞb iÀðd iþh iÞS iþr i R iÀX mj¼1b ijðxÞS i I j;ð7bÞ_Ri¼p i b iþc i I iþh i S iÀðd iþr iÞR i;ð7cÞfor i¼1;...;m,where x¼ðI1;...;I m;S1;...;S m;R1;...;R mÞt.Susceptible and removed individu-als die at the rate d i>0,whereas infected individuals die at the faster rate d iþ i.Infected in-dividuals recover with temporary immunity from re-infection at the rate c i,and immunity lasts an expected1=r i time units.All newborns are susceptible,and a constant fraction b i are born into each group.A fraction p i of newborns are vaccinated at birth.Thereafter,susceptible individuals are vaccinated at the rate h i.The incidence,b ijðxÞdepends on individual behaviour,which determines the amount of mixing between the diﬀerent groups(see,e.g.,Jacquez et al.[16]). The DFE for this model isx0¼ð0;...;0;S01;...;S0m;R01;...;R0mÞt;whereS0 i ¼b i d ið1Àp iÞþr iðÞd iðd iþh iþr iÞ;R0 i ¼b iðh iþd i p iÞd iðd iþh iþr iÞ:Linearizing(7a)about x¼x0givesF¼S0i b ijðx0ÞÂÃandV¼½ðd iþc iþ iÞd ij ;where d ij is one if i¼j,but zero otherwise.Thus,FVÀ1¼S0i b ijðx0Þ=ðd iÂþc iþ iÞÃ:P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–4837For the special case with b ij separable,that is,b ijðxÞ¼a iðxÞk jðxÞ,F has rank one,and the basic reproduction number isR0¼X mi¼1S0ia iðx0Þk iðx0Þd iþc iþ i:ð8ÞThat is,the basic reproduction number of the disease is the sum of the‘reproduction numbers’for each group.4.3.Staged progression modelThe staged progression model[11,Section3and Appendix B]has a single uninfected com-partment,and infected individuals progress through several stages of the disease with changing infectivity.The model is applicable to many diseases,particularly HIV/AIDS,where transmission probabilities vary as the viral load in an infected individual changes.The model equations are as follows(see Fig.2):_I 1¼X mÀ1k¼1b k SI k=NÀðm1þd1ÞI1;ð9aÞ_Ii¼m iÀ1I iÀ1Àðm iþd iÞI i;i¼2;...;mÀ1;ð9bÞ_Im¼m mÀ1I mÀ1Àd m I m;ð9cÞ_S¼bÀbSÀX mÀ1k¼1b k SI k=N:ð9dÞThe model assumes standard incidence,death rates d i>0in each infectious stage,and theﬁnal stage has a zero infectivity due to morbidity.Infected individuals spend,on average,1=m i time units in stage i.The unique DFE has I i¼0,i¼1;...;m and S¼1.For simplicity,deﬁne m m¼0. Then F¼½F ij and V¼½V ij ,whereF ij¼b j i¼1;j6mÀ1;0otherwise;&ð10ÞV ij¼m iþd i j¼i;Àm j i¼1þj;0otherwise:8<:ð11ÞLet a ij be the(i;j)entry of VÀ1.Thena ij¼0i<j;1=ðm iþd iÞi¼j;Q iÀ1k¼jm kQ ik¼jðm kþd kÞj<i:8>>><>>>:ð12ÞThus,R0¼b1m1þd1þb2m1ðm1þd1Þðm2þd2Þþb3m1m2ðm1þd1Þðm2þd2Þðm3þd3ÞþÁÁÁþb mÀ1m1...m mÀ2ðm1þd1Þ...ðm mÀ1þd mÀ1Þ:ð13ÞThe i th term in R0represents the number of new infections produced by a typical individual during the time it spends in the i th infectious stage.More speciﬁcally,m iÀ1=ðm iÀ1þd iÀ1Þis the fraction of individuals reaching stage iÀ1that progress to stage i,and1=ðm iþd iÞis the average time an individual entering stage i spends in stage i.Hence,the i th term in R0is the product of the infectivity of individuals in stage i,the fraction of initially infected individuals surviving at least to stage i,and the average infectious period of an individual in stage i.4.4.Multistrain modelThe recent emergence of resistant viral and bacterial strains,and the eﬀect of treatment on their proliferation is becoming increasingly important[12,13].One framework for studying such sys-tems is the multistrain model shown in Fig.3,which is a caricature of the more detailed treatment model of Castillo-Chavez and Feng[12,Section2]for tuberculosis and the coupled two-strain vector–host model of Feng and Velasco-Hern a ndez[17]for Dengue fever.The model has only a single susceptible compartment,but has two infectious compartments corresponding to the two infectious agents.Each strain is modelled as a simple SIS system.However,strain one may ‘super-infect’an individual infected with strain two,giving rise to a new infection incompartment。