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Evidence-Based Medicine 产品介绍说明书

Evidence-Based Medicine 产品介绍说明书

Purpose and procedure.......................................................T he purpose of Evidence-Based Medicine is to alert clinicians to important advances in internal medicine,general and family practice,surgery,psychiatry,paediatrics,and obstetrics and gynaecology by selecting from the biomedical literature those original and review articles whose results are most likely to be both true and useful.These articles are summar-ised in value-added abstracts and commented on by clinical experts.The author of the original article is given an opportu-nity to review the abstract and commentary before publication. The procedures we follow to achieve this purpose areN Detecting,using prestated criteria,the best original and review articles on the cause,course,diagnosis,prevention, treatment,quality of care,or economics of disorders in the foregoing fieldsN Introducing these articles with declarative titles and summarising them accurately in structured abstracts that describe their objectives,methods,results,and conclusions N Adding brief,highly expert commentaries to place each of these summaries in its proper clinical and healthcare context N Disseminating these summaries in a timely fashion.CRITERIA FOR REVIEW AND SELECTION FOR ABSTRACTINGGeneralAll English-language original and review articles in an issue of a candidate journal are considered for abstracting if they concern topics important to the clinical practice of internal medicine,general and family practice,surgery,psychiatry, paediatrics,or obstetrics and gynaecology.Access to foreign-language journals is provided through the systematic reviews we abstract,especially those in the Cochrane Library,which sum-marises articles from over800journals in several languages. Prevention or treatment;quality improvementN Random allocation of participants to interventionsN Outcome measures of known or probable clinical importance for>80%of the participants who entered the investigation.DiagnosisN Inclusion of a spectrum of participants,some(but not all)of whom have the disorder or derangement of interest N Each participant must receive the new test and thediagnostic standard testN Either an objective diagnostic standard or a contemporary clinical diagnostic standard with demonstrably reproduci-ble criteria for any subjectively interpreted component N Interpretation of the test without knowledge of the diagnostic standard resultN Interpretation of the diagnostic standard without knowl-edge of the test result.PrognosisN An inception cohort of persons,all initially free of theoutcome of interestN Follow up of>80%of patients until the occurrence of either a major study end point or the end of the study.CausationN Observations concerning the relation between exposuresand putative clinical outcomesN Prospective data collection with clearly identified compar-ison group(s)for those at risk for the outcome of interest (in descending order of preference from randomised controlled trials,quasi-randomised controlled trials,non-randomised controlled trials,cohort studies with case by case matching or statistical adjustment to create compar-able groups,to nested case control studies)N Masking of observers of outcomes to exposures(this criterion is assumed to be met if the outcome is objective).Economics of health care programmes or interventions N The economic question must compare alternative coursesof action in real or hypothetical patientsN The alternative diagnostic or therapeutic services or quality improvement strategies must be compared on the basis of both the outcomes they produce(effectiveness)and the resources they consume(costs)N Evidence of effectiveness must come from a study(or studies)that meets criteria for diagnosis,treatment,quality assurance,or review articlesN Results should be presented in terms of the incremental or additional costs and outcomes incurred and a sensitivity analysis should be done.Clinical prediction guidesN The guide must be generated in1set of patients(training set)and validated in an independent set of real not hypothetical patients(test set),and must pertain to treatment,diagnosis,prognosis,or causation. Differential diagnosisN A cohort of patients who present with a similar,initiallyundiagnosed but reproducibly defined clinical problem N Clinical setting is explicitly describedN Ascertainment of diagnosis for>80%of patients using a reproducible diagnostic workup strategy and follow up until patients are diagnosed or follow up of>1month for acute disorders or>1year for chronic or relapsing disorders. Systematic reviewsN The clinical topic being reviewed must be clearly stated;there must be a description of how the evidence on this topic was tracked down,from what sources,and with what inclusion and exclusion criteriaN>1article included in the review must meet the above-noted criteria for treatment,diagnosis,prognosis,causation,quality improvement,or the economics of healthcare programmes. Evidence-Based Medicine has a related journal,ACP Journal Club. It is generated using procedures identical to those used for Evidence-Based Medicine and is published by the American College of Physicians.Approximately one third of the abstracts in ACP Journal Club are published in Evidence-Based Medicine,and the abstracts not published are listed,by their declarative titles,in the section titled Additional Articles Abstracted in ACP Journal Club.33EBM on December 25, 2023 by guest. Protected by copyright./ Evid Based Med: first published as 10.1136/ebm.12.2.33 on 30 March 2007. Downloaded from。

第十四章现代数学概观二十世纪的数学第一节

第十四章现代数学概观二十世纪的数学第一节

第十四章:现代数学概观-二十世纪的数学第一节五大新兴学科的建立一、数理逻辑1.符号逻辑数理逻辑作为一门数学学科,来源于对数学和逻辑基础的探讨,它最早可追溯到莱布尼茨,他关于逻辑演算的观念预示着布尔代数,而英国数学家布尔(G.Boole 1815—1864)在1847年出版《逻辑的数学分析》一书,正式推出所谓布尔代数,在逻辑上相当于命题演算.其后由英国数学家杰方斯(W.S.Jevons,1835—1882)和小皮尔斯(C.S.Peirce,1839—1914)在1874年加入次序关系,德国数学卷中加以公理化.第一个完全形式化的语言是德国数学家弗瑞格(G.Frege,1848—1925)在1879年出版的《概念文字》中引进的.他首先定义了全称量词及存在量词.并引进一般的谓词逻辑.不过相应的逻辑代数一直到1950年才由波兰数学家塔斯基(A.Tarski,1902—1983)所发展,他引进所谓“圆柱代数”.1955年美国数学家哈尔莫斯(P.Halmos,1916—)又引进多进代数,形成一般的逻辑代数理论.1889年意大利数学家皮亚诺(G.Peano,1858—1932)提出自然数的公理系统,即后来所谓皮亚诺算术公理.而戴德金在前一年也提出类似的公理系统.弗雷格在1884年出版的《算术基础》中开始提到算术无非是扩展的逻辑.戴德金也提出类似的观点.弗雷格在1893年出版的《算术的基本规律》第一卷中,用五条逻辑公理来推导算术命题.1902年6月罗素给弗雷格一封信,提出著名的罗素悖论,并指出弗雷格的矛盾.弗雷格在1903年出版的《算术的基本规律》第二卷附录中承认这是对他的巨大打击,正是这个悖论,揭开了数理逻辑新的一章.2.罗素悖论罗素的悖论是关于集合论的,康托尔已经意识到不加限制地谈论“集合的集合”会导致矛盾.其他人也发现集合论中存在矛盾.而罗素在1903年出版的《数学的原理》(Principles of Mathematics)中,则十分清楚地表现出集合论的矛盾,从而动摇了整个数学的基础.罗素的悖论是说:可以把集合分成两类:凡不以自身为元素的集合称为第一类集合,凡以自身做为元素的集合称为第二类的集合,每个集合或为第一类集合或为第二类集合.设M表示第一类集合全体所成的集合.如果M是第一类集现了这个矛盾之后,导致第三次数学危机,在数学界出现了各种意见,从抛弃集合论到尽可能保持集合论在数学中的基础地位的都有.由于20世纪数学的发展主流是建立在集合论基础之上,这里只考虑数学家如何消除悖论.在20世纪初,大致有两种办法,一个办法是罗素的分支类型论,它在1908年发表,在这个基础上罗素与怀特海(A.N.Whitehead,1861—1947)写出三大卷《数学原理》(principia Mathematica,1910—1913),成为数理逻辑最早一部经典著作.还有一个办法是公理方法限制集合,由此产生公理集合论.3.集合论的公理化康托尔本人没有对集合论进行公理化.集合论公理化是策梅罗(E.Zermelo,1871—1953)在1908年发表的.富兰克尔(A.Fraenkel,1891—1965)等人曾加以改进,形成著名的ZF系统,这是最常用的一个系统,因此大家都希望从中推出常用的选择公理(1904年策梅罗引进它来设与ZF系统是相容的.1963年,柯亨(P.Cohen,1934—)发明“力迫法”证明这两条“公理”的否定也不能在ZF系统中证明,从而推出其独立性.4.希尔伯特纲领为了使数学奠定在严格公理化基础上,1922年希尔伯特提出希尔伯特纲领,首先将数学形式化,构成形式系统,然后通过有限主义方法证明其无矛盾性.1928年希尔伯特提出四个问题作为实现其纲领的具体步骤:(1)分析的无矛盾性.1924年阿克曼(W.Ackermann,896—1962)和1927年冯·诺伊曼(J.Von Neumann,1903—1957)的工作使希尔伯特相信只要一些纯算术的初等引理即可证明分析的无矛盾性.1930年夏天,哥德尔开始研究这个问题,他不理解希尔伯特为什么要直接证明分析的无矛盾性.哥德尔认为应该把困难分解:用有限主义的算术证明算术的无矛盾性,再用算术的无矛盾性证明分析的无矛盾性.哥德尔由此出发去证明算术的无矛盾性而得出不完全性定理.(2)更高级数学的无矛盾性.特别是选择公理的无矛盾性.这个问题后来被哥德尔在1938年以相对的方式解决.(3)算术及分析形式系统的完全性.这个问题在1930年秋天哥尼斯堡的会议上,哥德尔已经提出了一个否定的解决.这个问题的否定成为数理逻辑发展的转折点.(4)一阶谓词逻辑的完全性,这个问题已被哥德尔在1930年完全解决.这样一来哥德尔把希尔伯特的方向扭转,使数理逻辑走上全新的发展道路.5.哥德尔的三项重大贡献除了连续统假设的无矛盾性之外,哥德尔在1929—1930年证明下面两大定理:(1)完全性定理:哥德尔的学位论文《逻辑函数演算的公理的完全性》解决了一阶谓词演算的完全性问题.罗素与怀特海建立了逻辑演算的公理系统及推演规则之后,数学家最关心的事就是公理系统的无矛盾性及完全性.所谓完全性就是,每一个真的逻辑数学命题都可以由这个公理系统导出,也就是可证明.命题演算的完全性已由美国数学家波斯特(E.Post,1897—1954)在1921年给出证明.而一阶谓词演算的完全性一直到1929年才由哥德尔给出证明.(2)不完全性定理:这是数理逻辑最重大的成就之一,是数理逻辑发展的一个里程碑和转折点.哥德尔证明不完全性定理是从考虑数学分析的无矛盾性问题开始的.1930年秋在哥尼斯堡会议上他宣布了第一不完全性定理:一个包括初等数论的形式系统,如果是无矛盾的,那就是不完全的.不久之后他又宣布:如果初等算术系统是无矛盾的,则无矛盾性在算术系统内不可证明.哥德尔的不完全定理造的是一个不自然的数论问题,数学家一直希望在一阶皮亚诺算术中找到一个数学表述既简单又有趣的数论问题,就像哥德巴赫猜想或费马大定理来说明算术的不完全性.这一直到1977年才由巴黎斯(J.Paris)等人造出,这更加证明希尔伯特纲领是不可能实现的.6.哥德尔以后的数理逻辑.哥德尔的不完全性定理从根本上动摇了数学的基础,它指出绝对的无矛盾性的证明是不可能实现的,数学家只能限制自己的领域及要求.数理逻辑也成为一个专门的学科,它分成四大分支:证明论、递归论、公理集合论及模型论,它们都在30年代发展起来.证明论仍然继续希尔伯特纲领,但不得不放宽有限主义的条件.其中最主要的成就是根岑(G.Gentzen,1909—1945)在1934年用超穷归纳法证明自然数算术的无矛盾性.递归论也奠定基础,1935年克林尼(S.Kleene,1909—1994)定义一般递归函数,1936年图林(A.Tuˉring,1912—)提出图林机概念.同年车尔赤(A.Church1903—)提出车尔赤论点:任何有效可计算函数均等价于一般递归函数.递归论与数学关系至为密切,它不仅为计算机科学奠定基础,同时一系列判定问题则直接涉及数学基本问题:如群的基本问题是问什么时侯两个群同构,对于有限表出群是1908年提出的,到50年后,苏联数学家阿其扬(C.И.Aдьян,)在1957年及以色列数学家拉宾(M.O.Rabin,)在1958年独立证明这问题是不可解的.在这个基础上,小马尔科夫(A.A.MapkoB,1903—1979)证明拓扑学的基本问题——同胚问题也是不可解的,1970年最终证明希尔伯特第十问题是不可解的.模型论首先是处理真假问题,它指出一系列命题在某些模型下为真,而在另外模型下非真.其次它构造一批非标准模型.1934年斯科仑(T.Skolem,1887—1968)给出整数的非标准模型,1961年鲁宾逊(A.Robinson,1918—1974)提出非标准分析,使莱布尼茨的无穷小合法化,创立了非标准数学.二、抽象代数学代数学与拓扑学是现代数学的两大部门.它们构成现代数学的基础与核心.没有代数学和拓扑学,现代数学(除了那些较为孤立的、相对地讲不太重要的学科)可以说寸步难行.抽象代数学或近世代数学是在20世纪初发展起来的.1930—1931年范·德·瓦尔登(B.L.vander Waerden,1903—)的《近世代数学》(Moderne Algebra)一书问世,在数学界引起轰动,由此之后,抽象代数学或近世代数学成为代数学的主流,不久之后也就理所当然地把“抽象”及“近世”的帽子甩掉,堂尔皇之成为代数的正统.范·德·瓦尔登的书至今仍然是代数学的模式.它是根据德国女数学家E.诺特(E.Noether,1882—1935)和德国数学家阿廷(E.Artin,1898—1962)的讲义编写而成,在精神上基本来源于他们两位,特别是诺特,被公认为“近世代数学之母”.在诺特之前,不少大数学家都对近世代数学有过这样或那样的贡献,但是这种与经典代数学迥然不同的思想主要来源于戴德金和希尔伯特,戴德金不仅引进大多数抽象代数观念——如理想、模、环、格等,而且初步研究它们的结构及分类,而希尔伯特的抽象思维方式及公理方法则对现代整个数学都有举足轻重的影响.抽象代数学的研究对象与研究目标与经典代数学有着根本的不同:经典代数学的主要目标是求解代数方程和代数方程组,而抽象代数学的目标则是研究具有代数结构的集合的性质,刻划它们并加以分类,这些对象是用公理定义的.1.域论从古代起,人们就已经熟悉有理数和它们的运算——加法和乘法.这些运算满足加法交换律和加法结合律,乘法交换律和乘法结合律,以及分配律,而且对于加法存在零元素(0)及逆元素(倒数).所有有理数的集合是人们最早认识的具体的域,后来也知道实数集合、复数集合同样满足上述公理,它们也是城.除了这些最熟悉的域之以,在19世纪研究得最多的域是代数数域,这些都是含有无穷多元素的数域.有没有有限多个元素的域呢?1830年伽罗瓦已知有有限多个元素的域(后来被称为伽罗瓦域),其元素被称为伽罗瓦虚数,它们满足pa=0,其中p是一个素数,p称为域的特征.伽罗瓦曾具体证明,在一个特征为p的伽罗瓦域中,元素个数是p的一个幂.如在当时的情况一样,伽罗瓦所作的一切都是有具体表示的.到19世纪末,人们知道其他域的例子还有有理函数域及代数函数域.从整体结构上对域进行考察始自戴德金及克罗内克对代数数域的研究(从1855年起).但抽象域的观念则来自德国数学家韦伯(H.Weber,1842—1913),他的思想来自抽象群的观念.后来美国数学家狄克逊(L.E.Dickson,1874—1954)及亨廷顿(E.V.Huntington,1874—1952)给出域的独立的公理系统.在韦伯的影响下,德国数学家施泰尼茨(E.Steinitz,1871—1928)在1910年发表《域的代数理论》一文,为抽象域论奠定了基础.他把域分为两种类型:一种是特征为p的域,也即对所有元素a满足pa=0的域,它们一定包含最小的城(称为素域),最小的域一定是只含p个元素的伽罗瓦域.另一种是不存在这种p的域,称为特征0,其素域一定是有理数域.不管域属于哪一种类型,任何域均可由素域添加一些新元素“扩张”而成.所以域的根本问题是研究域的扩张.他对扩张进行了分类,其中主要的一类是添加系数在原域中的多项式的根后所得的扩张(代数扩张).当一个域通过代数扩张不能再扩大时称为代数封闭域.施泰尼茨证明,每个域均有唯一的代数封闭域.特别他还对特征p一般域胁许多特殊性质如不可分性、不完全性进行研究.关于抽象有限域,已经有了相当完整的结果:1893年美国数学家莫尔(E.H.Moore,1862—1932)证明,任何一有限域必定与某一个伽罗瓦域同构.反过来,对于任意素数p和正整数a,必定存在唯一一个伽罗瓦域,具有p a个元素.有限域理论在数论、编码理论、组合理论及数理统计等方面有着许多应用.在域论中引进p进域是一个重大成就.德国数学家亨泽尔(K.Hensel,1861—1941)在1908年出版的《代数数论》(Theorie der algebraischen Zahlen)中系统阐述了p进数,他对这种数规定了加、减、乘、除四种基本运算,构成一个域称p进域,而它是有理数域的一个完备化,如同实数域一样.但是与实数域性质的一个很大的不同是实数域具有阿基米德性质,也就是对任何两个实数a,b总存在一个正整数n,使na>b.p 进域虽然也有一个自然的顺序,但却没有阿基米德性质.pˉ进数域是一种“局部”域,在它里面也可定义整数及代数数,它的建立大大有助于数论的发展.亨泽尔之后,抽象赋值论得到发展,在代数数论及代数几何学上有着重要应用.抽象理论的建立不仅使已有的零散知识系统化,而且有助于许多问题的解决,1927年阿廷解决希尔伯特第17问题就是靠他引进抽象的实域(他称为形式实域).实域k是把实数域的一个特性抽象化:即-1不能表示为k中元素的平方和.通过这个概念,他证明“任何正定有理函数都可表示为有理函数平方和”.2.环论环的概念原始雏型是整数集合.它与域不同之处在于对于乘法不一定有逆元素.抽象环论的概念来源一方面是数论,整数的推广——代数整数具有整数的许多性质,也有许多不足之处,比如唯一素因子分解定理不一定成立,这导致理想数概念的产生.戴德金在1871年将理想数抽象化成“理想”概念,它是代数整数环中的一些特殊的子环.这开始了理想理论的研究,在诺特把环公理化之后,理想理论被纳入环论中去.环的概念的另一来源是19世纪对数系的各种推广.这最初可追溯到1843年哈密顿关于四元数的发现.他的目的是为了扩张用处很大的复数.它是第一个“超复数系”也是第一个乘法不交换的线性结合代数.它可以看成是实数域上的四元代数.不久之后凯莱得到八元数,它的乘法不仅不交换,而且连结合律也不满足,它可以看成是第一个线性非结合代数.其后各种“超复数”相继出现.1861年,魏尔斯特拉斯证明,有限维的实数域或复数域上的可除代数,如满足乘法交换律,则只有实数及复数的代数(1884年发表).1870年戴德金也得出同样结果(1888年发表).1878年弗洛宾尼乌斯(F.G.Frobenius,1849—1917)证明实数域上有限维可除代数只有实数、复数及实四元数的代数.1881年小皮尔斯也独立得到证明.1958年用代数拓扑学方法证明,实数域上有限维可除代数,连非结合可除代数也算在内,只有1,2,4,8这四种已知维数.可见实数域及复数域具有独特的性质.关于域上线性结合代数的研究在19世纪末处于枚举阶段,1870年老皮尔斯(B.Peirce,1809—1880)发表《线性结合代数》,列举6维以下的线性结合代数162个.他还引进幂零元与幂等元等重要概念为后来的结构理论奠定基础.1898年、嘉当(E.Cartan)在研究李代数的结构基础上,对于结合代数进行类似的研究,1900年,德国数学家摩林(T.Molien,1861—1941)征明,复数域上维数≥2的单结合代数都与复数域上适当阶数的矩阵代数同构.线性结合代数的结构定理是1907年由美国数学家魏德本(J.HM.Wedderburn,1882—1948)得出的:线性结合代数可以分解为幂零代数及半单代数,而半单代数又可以表示为单代数的直和.单代数可表为域上可除代数的矩阵代数.这样结合代数就归结为可除代数的研究.可除代数有着以下的结果.1905年魏德本证明:有限除环都是(交换)域,也即伽罗瓦域.当时除了伽罗瓦域及四元数之外,不知道有别的除环.20世纪虽然发现了一些新的除环,但除环的整个理论至今仍不完善.从线性结合代数到结合环的过渡是阿廷完成的.1928年,阿廷首先引进极小条件环(即左、右理想满足降键条件的环,后称阿廷环),证明相应的结构定理.对于半单环的分类,雅可布孙(N.Jacobson,1910—)创立了他的结构理论.他认为对任意环均可引进根基的概念,而对阿廷环来说,根基就是一组真幂零元.对于非半单的阿廷环(主要出现于有限群的模表示中),如福洛宾尼乌斯代数及其推广也有许多独立的研究.而与阿廷环对应的是诺特环,对于有么无的环,秋月康夫(1902—1984)及霍普金斯(C.H opkins)证明阿廷环都是诺特环.对于诺特环,却长期没有相应的结构理论.一直到1958年英国数学家戈尔迪(A.W.Gold-ie)才取得突破,他证明任何诺特半素环都有一个阿廷半单的分式环,这才促进了新研究.与诺特环平行发展的是满足多项式等式的环.近来环表示论及同调方法的应用对结合环理论有极大促进.环论的另一来源是代数数论及代数几何学及它们导致的交换环理论.1871年戴德金引进理想概念,开创了理想理论.环这个词首先见于希尔伯特的数论报告.代数几何学的研究促使希尔伯特证明多项式环的基定理.在本世纪初英国数学家腊斯克(E.Lasker,1868—1941)及麦考莱(F.S.Macaulay,1862—1937)对于多项式环得出分解定理.对于交换环的一般研究来源于E.诺特.她对一般诺特环进行公理化,证明准素分解定理从而奠定交换环论乃至抽象代数学基础,其后克鲁尔(W.Krull,1899—1971)给出系统的研究,他还引进了最值得注意的局部环.四十年代,薛华荔、柯恩(I.S.Cohen,1917—1955)及查瑞斯基(O.Zariski,1899—1986)对局部环论进行了系统的研究.3.群论19世纪末抽象群开始成为独立研究的对象,当时主要问题仍是以置换群为模式的有限群,问题涉及列举给定阶数的所有群以及群的可解性的判据.当时主要的定理是由挪威数学家西洛(L.Sylow,1832—1918)在的.而19世纪90年代群论最主要成就是群表示论的出现,它是由德国数学家福洛宾尼乌斯奠定的.后由他的学生舒尔(I.Schur,1875—1941)所发展,成为研究群论不可缺少的工具.所谓群表示即是把群具体实现为某种结构的自同构群,例如域F上的有限维线性空间的线性变换群,通常是把群的元素与F上的n×n 可逆矩阵相对应.在英国数学家伯恩塞德(W.Burnside,1852—1927)的经典著作《有限阶群论》(Theory of Groups of Finite Order)第二版(1911)已经进行综述并给出应用.20世纪有限群论的中心问题是有限单群的分类.很久以来,就已经知道一个相当长的有限单群的表,除了素数阶循环群之外,对于每一个整数n≥5存在一个n!/2阶单群,它由n个事物的所有偶置换构成,这就是所谓交错群.当n=5时,它就是二十面体群.另外还知道许多射影特殊线性变换群PSL(n,q),它们通过行列式为1的n×n矩阵群(元素取在有限域GL(q)中)的商群构造出来.另外对于正交矩阵、辛矩阵、酉矩阵也可以造出一批单群来.这些“典型群”,从若尔当时候起就已知道,后来经过美国数学家狄克逊、荷兰数学家范·德·瓦尔登、法国数学家丢东涅(J.Dieudonné,1906—1992)进行系统研究.真正重大的突破是1955年薛华荔在日本《东北数学杂志》上发表的“论某些单群”的论文,这篇论文的重要性不仅展示一些新单群,而且更重要的是对于以前知道的绝大部分通过李代数换基的办法进行统一的处理,从而得出九个系列的薛华荔群.其后,这些薛华荔群经过美国数学家斯坦伯格(R.Steinberg,1922—)、韩国数学家李林学、比利时数学家梯茨(J.Tits,1930—)、日本数学家铃木通夫(1926—)等人加以扩充,得出全部李型单群的16系列.除了上述这18个序列中的有限单群之外,还有几个不属于它们的所谓“散在单群”,其中头一个是7920阶的群M11是法国数学家马丢(E.L.Mathieu,1835—1890)在1861年发现的,他不久又发现另外4个单群M12,M22,M23,M24.一直到1965年之前再没有发现新的散在单群了.突然1965年南斯拉夫数学家严科(Z.Janko,1932—)发现了一个175560阶的新单群,其后10年间,陆续发现另外20个敬在单群,其中最大的称为费舍尔(B.Fischer,1936—)“魔群”,其阶大约为8.1053,到这时候是否所有单群均已找到,也就是有限单群的分类已经完成了呢?在这条漫长的路上,首先的突破是一系列群论性质及表示论的成果,其中包括1955年布劳尔(R.Brauer 1901—1977)的工作.第二个突破是1963年美国数学家费特(W.Feit,1930—)和汤姆逊(J.G.Thompson,1932—)证明除循环群之外,奇阶群都是可解群,这个长达250页的论文包括了极其丰富的信息.70年代,在群的结构研究上有了新的突破,最终导致1981年,有限单群的分类彻底完成,不过全文需要1万页以上,这是各国上百位群论专家通力合作的结果.对于无穷阶的离散群,也有一些重要的研究,其中重要的是与数理逻辑有关的“字的问题”,即两个符号序列何时相等,对于有限生成的具有有限个关系式的群,1955年左右苏联数学家诺维科夫(Π·C·H овиков,1901—1975)、美国数学家布里顿(J.L.Britton)和布恩(W.Boone,1920—1983)证明一般的字的问题是不可解的,也就是不存在一个普遍的算法来判定两个字是否相等,但是另一方面德国数学家马格努斯(W.Magnus,1907—)在1932年解决一个关系式的有限生成群的字的问题.另一个重要的问题是伯恩赛德问题,他问一个有限生成的群如果其所有元素都是有限阶的,该群是否有限,这个问题一直到1964年由前苏联数学家考斯特利金(А.И.Кострикин,1929—)举出例子而得出否定的回答.另外还有一个狭义的伯恩赛德猜想,即有限生成群当所有元素x满足x n=0是有限群,现在知道当n=2,3,4,6时,狭义伯恩赛德猜想成立,但如果n相当大,诺维科夫和布里顿等人也举出反例.三、测度与积分理论测度是长度、面积和体积概念的精密化及推广.各民族数学发展一开始均致力于测量长度和面积,得出相应的公式及方法,而统一的求积方法一直到牛顿和莱布尼茨建立微积分之后才得到.这时求积问题变成一个特殊的积分问题.但积分是一个相当复杂的概念,19世纪由于分析的严格化才导致由柯西、黎曼及达布相继改进的黎曼积分的概念,最后确定下来.随着康托尔点集论的建立,要求对更一般的点集的“大小”进行比较及量度,这要求定义测度.先是对黎曼可积性条件中函数的不连续点集的“测度”给出定义.最早是哈那克(A.Harnack,1851—1888)、杜布瓦—瑞芒(P.du Bois Rey-mond,1831—1889)、史托尔茨(O.Stolz,1842—1905)及康托尔在1881到1885试着做出定义,他们均采用覆盖区间长度的下确界,但是这样定义有毛病.例如,两个无公共点集的并集的“测度”有时能够小于两集的“测度”之和,除了上述定义的“外”测度之外,最先定义“内”测度的是皮亚诺,他在1887年定义“可测”集为内、外测度相等,这样虽然克服上述困难,但有界开集并不一定可测.若尔当在他的《分析教程》第一卷第二版(1893)中也做了类似的定义,同样也有类似的毛病.对这些毛病的补救来自波莱尔(E.Borel,1871—1956),他在《函数论教程》中大大改进了以前的测度观念,利用可数可加性对任一有界开集构造地定义测度.他还考虑零测度集(实际上这个观念可以追溯到黎曼).而真正把波莱尔的方法同皮亚诺—若尔当的办法结合而形成系统测度论的则是波莱尔的学生勒贝格,这些发表在他的博士论文《积分、长度、面积》当中.勒贝格的功绩不仅在于建立系统的测度理论,更主要的是建立系统的积分理论.在勒贝格之前,除了黎曼积分之外,还有斯蒂尔吉斯(T.J.Stieltjes,1856—1894)积分.斯蒂尔吉斯在1894年发表的“连分式的研究”中证明:如连分式数F(Z),F(Z)可表为曼积分对于一般的数学分析已经足够,但是还有一系列不理想的地方.微积分的基本定理是微分和积分互为逆运算,也就是说如果则导数F′(x)存在,而且等于f(x),至少在f光滑的点是如此.但是1881年沃尔泰拉(V.Volterra,1860—1940)还在比萨大学做学生时,发现一个例子:一个函数F在(0,1)区间上定义有界,其导数f=F′处处存在,但是在当时流行的积分——黎曼可积的意义是不可积的.因此,需要定义一种积分,它可以在更广的一类函数上定义,而且使微分和积分成为互逆的运算.另外对这种积分还希望收敛级数可以逐项积分.勒贝格在他的1902年学位论文中迈出新的一步,他定义勒贝格积分与以前定义积分的方式不同,以前是先定义积分,然后由积分得到“测度”,勒贝格与此相反,他先定义测度,然后定义积分.他定义积分时,不去把自变量的区间加以区分,而把因变量y的区间(对于实函数来说是R的子集)加以重分(成有限个区间),再仿照通常的办法定义积分,这样就可以使一些很坏的函数也成为勒贝格可积的,最明显的例子就是狄利克雷函数.这样,大大扩充了可积函数的范围.另外如果勒贝格可积函数同时也黎曼可积,则两个积分相等.并且与一些极限运算可以交换,而且可以推广到高维.勒贝格积分虽然能解决沃尔泰拉原来的问题,但并不足够一般以致能够使所有具有有限导数f(x)=F′(x)的函数F(x)的导数f(x)=F′(x)都可积.为此,法国数学家当日瓦(A.Denjoy,1884—1974)在1912年和德国数学家佩隆(O.Per-ron,1880—1975)在1914年分别设计了以他们各自的姓定义的积分.其后鲁金(H.H.Лузин,1883—1950)给出描述性定义,这三者是等价的.1915年法国数学家弗雷歇把积分扩张到抽象集合的泛函上.他的模式取自1913年奥地利数学家拉东(J.Radon,1887—1956)的工作,其中引进集函数.他实际上综合了斯蒂尔吉斯积分与勒贝格在1910年把勒贝格测度论推广到高维(三维及三维以上)欧氏空间的研究.勒贝格通过可测函数的积分定义一个集函数,证明它是完全可加的而且绝对连续的.不过他只有点函数观念,而拉东则利用集函数定义拉东测度.1930年波兰数学家尼古丁(O.Nikodyn,1887—1974)对抽象测度论完成了1910年勒贝格定理在抽象测度论的推广,最终完成抽象测度论的建立.它不仅构成概率论的基础,同时也是抽象调和分析、谱理论等分支不可少的前提.四、泛函分析泛函分析是一门新兴学科,1932年才被正式列入德国《数学文摘》.“泛函分析”这个词首先出现于列维(P.Lévy,1886—1971)的1922年出版的《泛函分析教程》中.它是一门分析学科,但与传统的分析学科不太一样,后者强调演算,而前者强调概念.它们的对象也有所不同,后者主要讨论个别函数(类)的。

2007年英语一真题(附答案)

2007年英语一真题(附答案)
mark A , B , C , or D on ANSWER SHEET 1. ( 10 points )
By 1830 the former Spanish and Portuguese colonies had become
independent nations. The roughly 20 million 1 of these nations looked 2 to the future. Bom in the crisis of the old regime and Iberian colonialism , many
of the leaders of independence 3 the ideals of representative government , careers 4_ to talent , freedom of commerce and trade , the 5 to private
property , and a belief in the individual as the basis of society. 6 there was a belief that the new nations should be sovereign and independent states , large enough to be economically viable and integrated by a 7 set of laws.
more of a cognitive exercise than an intuitive one. In other words , whatever
inborn differences two people may exhibit in their abilities to memorize , those

抗血友病因子纯化方法[发明专利]

抗血友病因子纯化方法[发明专利]

专利名称:抗血友病因子纯化方法
专利类型:发明专利
发明人:里塔·怀特·马修斯,阿兰·J·约翰森申请号:CN86102829
申请日:19860424
公开号:CN86102829A
公开日:
19871104
专利内容由知识产权出版社提供
摘要:本发明提供了一种纯化蛋白质的方法,该方法是在选自糖,多羟基醇,氨基酸和盐的水合作用添加剂存在下,并且在添加剂的浓度足以使从柱上回收的上述蛋白质的回收率,纯度和分辨率中至少一项有显著增加的条件下,用柱层析使蛋白质纯化。

申请人:纽约大学
地址:美国纽约州10012
国籍:US
代理机构:中国国际贸易促进委员会专利代理部
更多信息请下载全文后查看。

英语科技论文写作Unit 4

英语科技论文写作Unit 4
• Drafting the Abstract
– Use your own words wherever possible. – Avoid including opinions, examples, details and explanations. Do not use such phrases as “as noted in …”, “as shown by …” or “for example, …”. – Eliminate references to tables, figures, or sources found in the references list of the original paper. – Write concise, straightforward English; count every word. – Your abstract must be completely independent of the paper.
– It is an effective practice in preparing your abstract. This is especially important for a descriptive (or
indicative) abstract.
“5 Steps” for Abstract Writing
Likely Mistakes/Common Errors
• Mixed Writing Style
– In this paper, we have given a reason that is why the competitive ability of the national firms is weak. Because the non-national firms can get very cheap labor, under the same technical and economical conditions and the same cost, a non-national firm can produce more output than a national firm does, so it can get much more profit. In this way, the competitive ability of the non-national firm is stronger than the national firms.

URLhttpwww.cs.bham.ac.uk A Resolution Calculus for

URLhttpwww.cs.bham.ac.uk A Resolution Calculus for

T H E U N I V E R S I T Y O F B I R M I N G H A MS c h o o l o f C o m p u t e r S c i e n c eE d g b a s t o n ,B i r m i n g h a m B 152T T ,E n g l a n dU R L :h t t p ://w w w .c s .b h a m .a c .u k /A Resolution Calculus forPresuppositionsManfred Kerber and Michael KohlhasePublished as:ECAI-96,Proceedings of the 12th European Confer-ence on Artificial Intelligence,p.375–379,John Wiley &SonsA Resolution Calculus for PresuppositionsManfred Kerber1and Michael Kohlhase2Abstract.The semantics of everyday language and the semanticsof its naive translation into classicalfirst-order language consider-ably differ.An important discrepancy that is addressed in this paperis about the implicit assumption what exists.For instance,in thecase of universal quantification natural language uses restrictions andpresupposes that these restrictions are non-empty,while in classi-cal logic it is only assumed that the whole universe is non-empty.On the other hand,all constants mentioned in classical logic arepresupposed to exist,while it makes no problems to speak about hy-pothetical objects in everyday language.These problems have beendiscussed in philosophical logic and some adequate many-valuedlogics were developed to model these phenomena much better than classicalfirst-order logic can do.An adequate calculus,however,has not yet been given.Recent years have seen a thorough investigation of the framework of many-valued truth-functional logics.Unfortu-nately,restricted quantifications are not truth-functional,hence they do notfit the framework directly.We solve this problem by applying recent methods from sorted logics.1IntroductionFrom thefirst attempts of modelling everyday reasoning within the framework of classical logic,it has been known that many relevant aspects cannot be adequately expressed in classicalfirst-order logic. The attempts to cope with these have lead to a variety of logics.In this paper we address one of these problems,namely that of so-called presuppositions,where natural language allows to draw conclusions that classical logic does not warrant(for instance im-plicit consensus that universally quantified statements range over non-empty domains).These phenomena have been widely studied in the philosophy of language from a semantic point of view,but lack an efficient mechanisation,which is a primary concern of artificial intelligence.One of the more logic-oriented ways to cope with this phenomenon is to use a four-valued logic[3].We take this logic as a starting point of a mechanisation by a resolution calculus.There are two different kinds of presuppositions:the quantifica-tional ones presuppose that the domain of quantifications is non-empty and the existential ones assume the existence of constants.In natural language,thefirst ones are mandatory,whereas the second kind is defeasible(it is possible to talk about non-existing entities in natural language).Surprisingly enough,the standard semantics of classical logic treats the two kinds almost the opposite way:con-stants always must have denotations,that is,just speaking about an object means that is must exist(for instance,speaking about a dragon, means that there is one),while quantifications are unrestricted andwould be evaluated to and not to true at all.In[3]Bergmann proposes a four-valued logic to cope with pre-suppositions.She essentially argues that the semantical status of a formula has two independent dimensions,first a classical truth value,i.e.,or,and second a value,which tells whether the for-mula is secure(i.e.talks about existing objects)or not.In the caseIn this paper,we further formalise Bergmann’s logic and in par-ticular present a resolution calculus for this logic.Starting from an approach like that in[6]where we have presented a mechanisation of three-valued Kleene logic,the main problem of this work is to give a proper treatment of restricted quantification and their presupposi-tions.The range of the quantifiers is restricted and assumed to be non-empty.In the following we present the logic system,which is a variant of Bergmann’s ideas from[3].The treatment of the restriction part of a quantification is very similar to the sort techniques developed in[8].Definition2.1(Signature)A signatureΣ:consists of the following disjoint sets:is a countably infinite set of variable symbols,is a set of function symbols,and is a set of predicate symbols that contains a special predicate,called security predicate. The sets and are subdivided into the sets of function symbols of arity and of predicate symbols of arity.Note that individualconstants are just nullary functions.Definition2.2(Terms and Formulae)We define the set of terms to be the set of variables together with compound terms1for terms1and.The set of formulae consists of atoms(1,where)and of compound formulae ,,,,!,T,,where ,,and are formulae.The intended meaning of the restricted quantificationis equivalent to the sorted quantificationt f t ftf f f ftf f f ft t t tft t t tftttft f t fft f t fftftf!tfffto bet,if t for all andf,if there is an with ft,if t t for all,but t for some.f,if there is an with fNote that with this definition,the condition thatis conserved.We call this condition well-sortedness of assignments. Consequently,all assignments in the construction of the semantics of a sentence are well-sorted,if we start from the empty assignment (which we can always do,since like in classical logic the value of a formula only depends on those for it’s free variables).Thus we will restrict ourselves to well-sorted assignments.With the specification of the behaviours of the connectives and quantifiers we have completed the definition of the semantics of formulae.We say that a labelled formula is satisfied by,iff and valid,iff it is satisfied by all well-sorted assignments. Remark2.8Now we can further study the relation of restricted quantification to sorted logics.Those usually define the carrierfor any sort(unary predicate)as:t and use that to define sorted quantification asusually assume that the are non-empty3and therefore lead to the same presuppositions as on the sorted fragment.We exploit this similarity in this paper by generalising sort tech-niques for the mechanisation of.Definition2.9(Σ-Model)Let be a formula,then we call aΣ-algebra:aΣ-model for(written),ifft for allΣ-assignments.With this notion we can define the no-tions of validity,(un)-satisfiability,and entailment in the usual way. For a set of term declarations,we say that is a-Model,iff all labelled formulae in are valid(cf.2.7).In the following we will only consider-models.From a purely theoretical point of view,term declarations do not yield more ex-pressivity,since they can be axiomatised(any intended truth value can be characterised by combinations of the connectives!and). However,from a practical point of view,the term declarations pro-vide a convenient means of specifying the belief about existence and sortality in the world.Furthermore,the term declarations can be used for optimisations of the calculus by sorted unification as in[7]. Remark2.10The“tertium non datur”principle of classical logic is no longer valid,since formulae can be insecure,in which case they are neither true nor false.We do however have a“quintum non datur”principle,that is,formulae are either true or false,but independently they can be secure or not,which allows us to derive the validity(i.e. that it is true and secure in all models)of a formula by refuting that it is false or insecure or both.We will use this observation in our resolution calculus below.3Resolution Calculus()In this section we present a resolution calculus that is a gen-eralisation of the resolution calculus for partial functions[6],which in turn is a joint generalisation of Weidenbach’s logics with dynamic sorts[8]with ideas from[1,5].There are two variants of the sorted calculus,we have generalised both for our purposes,but in this paper we only present thefirst(simpler)version due to the lack of space. Definition3.1We will call a labelled atom a literal and a set ofliterals11a clause.We say that aΣ-model satisfies aclause,iff it satisfies one of its literals,that is,.satisfies a set of clauses iff it satisfies each clause.In order to conserve space,we employ the“,”as the operator for the disjoint union of sets,so that means and is not a member of.Furthermore we adopt H¨a hnle’s notion of multi-labels in the form to mean.Now we are in the position to give a set of transformations that take a set of labelled formulae to a refutationally equivalent set of clauses.Definition3.2(Transformations to Clause Normal Form)tf ft t t t t ttttt ft1t1f1t t1f1t t !tt f!tT tf fT twhere1Free and is a new function symbol of arity.Here Free denotes the set of free variables of.The transformations can be directly derived from the semantics of the connectives and quantifiers.Due to space restrictions we have not presented all of them above.Note that the transformations for the uni-versal quantifier have to associate the restriction with the variable ,that is,in the resolution setting,we assume variables to be pairs, consisting of a symbol and a restriction.Furthermore Skolem func-tions have to conserve security and insecurity.In particular Skolem constants are always secure.Note that this set of transformations is confluent,therefore any total reduction of a setΦof labelled sentences results in a unique set of clauses.We will denote this set with CNFΦ.Assumption3.3The clause normal form transformations as pre-sented above are not complete,that is,they do not transform every given labelled formula into clause form,since the rules for quantified formulae insist that the bound variable occurs in the scope.In fact the handling of degenerate quantifications poses some problems in the presence of possibly empty restrictions,as quantification over empty sets are vacuously true.In this situation we have three possibilities,ei-ther to forbid degenerate quantifications,or empty restrictions,or treat degenerate quantifications in the clause normal form transformations. For this paper we chose thefirst,since degenerate quantifications do not make much sense and do not appear in everyday language.See[7] for the other possibilities.Thus we will assume that in all formulae in this paper the bound variables of quantifications occur in the scopes. As usual the reduction to clause normal form conserves satisfiability. Theorem3.4LetΦbe a set of labelled sentences,then the clause normal form CNFΦis satisfiable,iffΦis.Proof sketch:The assertion critically depends on the fact that the notion of satisfiability employed there takes the restrictions into ac-count:A clause is valid in aΣ-model,iff for one literalfor all well-sorted assignments into.With this notion,the assertion can be reduced to the standard argumentation about Skolemisation and a tedious calculation with the truth tables from2.7.Now we proceed to give a simple resolution calculus,which utilises standard(unsorted)unification.In[7],we have further improved a similar calculus by using a sorted unification algorithm,which dele-gates parts of the search into the unification algorithm.For unsorted substitutions a naive resolution rule is unsound.Therefore we have to add a residual(the restriction constraint)that ensures the soundness (with respect to the restrictions on the variables)of the unifier.Definition3.5(Restriction Constraints)Let111be a substitution,then we define therestriction constraint for to be the clause:111f f f f These labelled formulae are residuated in the rules and have to be refuted in order to guarantee that holds(cf.defi-nition2.7)for every instance instantiated for a variable with restriction.Definition3.6(Resolution Inference Rules())Reswhere and is the most general unifier of and.Here we have assumed and to be single truth values,naturally the rules can be easily extended to sets of truth values.Remark3.7Note that clauses containing t f t f are tautolog-ical and can therefore be deleted in the generation of the clause normal form as well as in the deduction process.The calculus can be extended by the usual subsumption rule,allowing to delete clauses that are subsumed(super-sets).Definition3.8Let be a sentence andΦbe the clause normal form of the set f t f then we say that can be proven in (),iff there is a derivation of the empty clause fromΦwith the inference rules above.Theorem3.9(Soundness)is sound.Proof sketch:The soundness of the resolution and factoring rules is established in the usual way taking into account that the restriction constraints make the substitutions“well-sorted”and thus compati-ble with the semantics:The restriction constraints add two literalsper component of the substitution,which only can be refuted if indeed or are valid.Definition3.10Let:11be a clause,then the con-ditional instantiation of to is defined by:11Free The following result from[8]is independent of the number of truth values.Lemma3.11Conditional instantiation is sound:for any clause, substitution andΣ-model we have that,whenever .Definition3.12Let be a sentence and CNF be the clause nor-mal form of,then we define the Herbrand set of clauses CNFfor as CNF ground Dom FreeDefinition3.13We will call two literals and complementary, if.Definition3.14(Herbrand Model)LetΦbe a set of clauses,then the Herbrand baseΦofΦis defined to be the set of all ground atoms containing only function symbols that appear in the clauses ofΦ.If there is no individual constant inΦ,we add a new constant .A valuation is a functionΦt f t f.Note that these literals are not complementary since is a function.The Σ-Herbrand model forΦand is the set:Φ.We say that aΣ-Herbrand model satisfies a clause setΦiff for all ground substitutions and clausesΦwe have.A clause set is calledΣ-Herbrand-unsatisfiable iff there is noΣ-Herbrand-model forΦ.Theorem3.15(Herbrand Theorem)Let be a formula,then the clause normal form CNF has aΣ-model iff CNF has a Σ-Herbrand-model.Proof:Let be aΣ-model forΦ:CNF.The set:Φis aΣ-Herbrand model forΨ:CNF if is an arbitraryΣ-assignment,since obviously is a valuation.To show that indeed is aΣ-Herbrand model forΨ,we assume the opposite,that is, there is a clauseΨ,such that.SinceΨthere is a substitution and a clauseΦ,such that.Without loss of generality we can assume that,since otherwise,and thereforefor,which contradicts the assump-tion.Thus the mapping:is aΣ-assignment.Note that since is a model ofΦ,we have thatand therefore there is a literal,such that,hence,which contradicts the assumption. For the converse direction let be aΣ-Herbrand model forΨand the Herbrand base for.Furthermore let and be partial functions,such that1:1iff11:iff1We proceed by convincing ourselves thatΦ.LetΦand :be an arbitrary well-sortedΣ-assignment.Since is a set of ground terms is also a ground substitution and moreoveror by construction of and the fact that is well-sorted.is aΣ-Herbrand model forΨand thus.Because cannot contain complementary literals we must already have a literal.Now let be the valuation associated with.Since we have,which implies.We have taken and arbitrary,so we get the assertion.Corollary3.16A setΦof ground unit clauses is unsatisfiable iff it contains two complementary literals.Theorem3.17(Ground Completeness)LetΦbe an unsatisfiable set of ground clauses,then there exists a derivation of the empty clause fromΦ.Theorem3.18(Completeness)is complete.Proof sketch:For the proof of this assertion we combine the com-pleteness result from the ground case with a lifting argument.It turns out that the lifting property can be established by methods from[8], since they are independent of the number of truth values.4ExampleAtfirst we want to give an example for quantificational presupposi-tions and then shortly discuss existential presuppositions.Let us assume the following information.There is a company TheCompany which wants tofire people,but they have a social touch and don’tfire any persons which have children.We are worried whether John will befired,but then we hear that his children are sleeping.Implicitly we can conclude from this information that John has children and hence will not befired.This can be encoded in by the following statements:4ATwith the term declarations and. In order to prove the theorem T,the following generalised clause set has to be refuted:ATBy the rules for forming a clause normal form we get the clauses:A1A21B1B22B33C1C24C34TBy resolution we get from Res(B1,C2):R144Two-times resolving with C3results in:R2which in turn can be resolved with A1:。

寒地‘贝达’葡萄清汁的研制及理化指标分析

朱磊,吕珊珊,史文雅,等. 寒地‘贝达’葡萄清汁的研制及理化指标分析[J]. 食品工业科技,2024,45(7):177−183. doi: 10.13386/j.issn1002-0306.2023050223ZHU Lei, LÜ Shanshan, SHI Wenya, et al. Development and Physicochemical Index Analysis of Clear Grape Juice Made from 'Beta' in Cold Regions[J]. Science and Technology of Food Industry, 2024, 45(7): 177−183. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023050223· 工艺技术 ·寒地‘贝达’葡萄清汁的研制及理化指标分析朱 磊1,2,3,吕珊珊1,史文雅1,于昕楚1,宋晨龙1(1.黑龙江八一农垦大学食品学院,黑龙江大庆 163319;2.黑龙江省农产品加工工程技术研究中心,黑龙江大庆 163319;3.国家杂粮工程技术研究中心,黑龙江大庆 163319)摘 要:以寒地栽培的抗性砧木品种‘贝达’果实为原料,为了克服原汁‘糖低酸高’的缺陷,突出其美洲种特有的风味特征,并使果实中的营养活性成分得以充分保留,研制了一款葡萄清汁产品,实现了榨汁后葡萄皮渣的二次利用。

利用单因素实验,确定了葡萄皮渣酚类提取的最佳工艺条件:乙醇浓度为60%、料液比为1:25、浸提时间为1.5 h 、浸提次数为3次。

通过单因素实验和正交试验确定了寒地‘贝达’葡萄清汁的最优配方:原汁添加量为45%、白砂糖添加量为8.2%、柠檬酸添加量为0.035%、葡萄皮酚类提取物添加量为0.4%、葡萄籽酚类提取物添加量为0.5%。

胶原凝胶收缩试验英语

胶原凝胶收缩试验英语Here's a draft of the text in English, following the given requirements:Okay, let's talk about the collagen gel contraction test. It's pretty interesting, actually. It's a way to study how cells react to their environment by measuring how much a gel shrinks over time. You just set up the gel, add the cells, and watch what happens.The gel itself is made from collagen, which is a protein found in our bodies. It gives skin its elasticity and strength. In this test, the gel acts as a sort of scaffold for the cells to grow on. As the cells interact with the gel, they cause it to contract, kind of like a sponge shrinking after you squeeze it.Measuring this contraction can tell us a lot about how cells behave. For example, if the gel contracts a lot, that might mean the cells are really active and healthy. Or, ifit doesn't contract much, it could indicate something's wrong with the cells or their environment.The test is pretty simple to do, but it can provide valuable insights into cell biology and disease processes. So, whether you're a researcher studying wound healing or a drug developer looking for new therapies, the collagen gel contraction test could be a useful tool in your toolbox.All in all, it's just a cool way to see.。

Journal of the Association for Computing Machinery, 21(4)622--642, 1974.

Akademie van Wetenschappen, Afd. Letterkunde, Nieuwe Reeks, 18(13), 1955. Bet 58] E.W. Beth. On machines which prove theorems. In J. Siekmann and G. Wrightson, editors,
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环境设计英文参考文献(精选文献)

伴随人类社会不断的进步,人与自然,建筑与环境之间的关系密不可分.从当代人们所生活的环境中,我们可以看出环境艺术也在经历着自身的发展,而人们只有从尊重自然环境,尊重人类自身,才能够真正将环境艺术更好地融入建筑设计中去。

下面是环境设计英文参考文献的分享,供大家参考阅读。

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Introduction to Kleene Algebra Lecture12 CS786Spring2004March8,2004 Kleene Algebra with TestsIn semantics and logics of programs,Kleene algebra forms an essential component of Propo-sitional Dynamic Logic(PDL)[6],in which it is mixed with Boolean algebra and modal logic to give a simple yet powerful system for modeling and reasoning about computation at the propositional level.Syntactically,PDL is a two-sorted logic consisting of programs and propositions defined by mutual induction.A testϕ?can be formed from any propositionϕ;intuitively,ϕ?acts as a guard that succeeds with no side effects in states satisfyingϕand fails or aborts in states not satisfyingϕ.Semantically,programs are modeled as binary relations on a set of states, andϕ?is interpreted as the subset of the identity relation consisting of all pairs(s,s)such thatϕis true in state s.From a practical point of view,many simple program manipulations,such as loop un-winding and basic safety analysis,do not require the full power of PDL,but can be carried out in a purely equational subsystem using the axioms of Kleene algebra.However,tests are an essential ingredient,since they are needed to model conventional programming constructs such as conditionals and while loops.We define here a variant of Kleene algebra,called Kleene algebra with tests(KAT),for reasoning equationally with these constructs.KAT was introduced in[9,10].KAT has been applied successfully in a number of low-level verification tasks involving communication protocols,basic safety analysis,concurrency control,and local compiler op-timizations[3,5,11,1].A useful feature of KAT in this regard is its ability to accommodate certain basic equational assumptions regarding the interaction of atomic instructions and tests.This feature makes KAT ideal for reasoning about the correctness of low-level code transformations.In this lecture we introduce the system and illustrate its use by giving a complete equa-tional proof of a classical folk theorem[7,12]which states that every while program can be simulated by another while program with at most one while loop.The approach we take is that of[12],who gives a set of local transformations that allow every while pro-gram to be transformed systematically to one with at most one while loop.For each such transformation,we can give a purely equational proof of correctness.Definition of Kleene Algebra with TestsA Kleene algebra with tests is a two-sorted algebra(K,B,+,·,∗,0,1,)where is a unary operator defined only on B,such that•B⊆K,•(K,+,·,∗,0,1)is a Kleene algebra,and•(B,+,·,,0,1)is a Boolean algebra.The elements of B are called tests.We reserve the letters p,q,r,...for arbitrary elements of K and a,b,c,...for tests.In PDL,a test would be written b?,but since we are using different symbols for tests we can omit the?.This deceptively simple definition actually carries a lot of information in a concise pack-age.Note the overloading of the operators+,·,0,1,each of which plays two roles:applied to arbitrary elements of K,they refer to nondeterministic choice,composition,fail,and skip,respectively;and applied to tests,they take on the additional meaning of Boolean dis-junction,conjunction,falsity,and truth,respectively.These two usages do not conflict—for example,sequential testing of b and c is the same as testing their conjunction—and their coexistence admits considerable economy of expression.It follows immediately from the definition that b≤1for all b∈B(this is an axiom of Boolean algebra).It is tempting to define tests in an arbitrary Kleene algebra to be the set{p∈K|p≤1},and this is the approach taken by[4].This approach makes some sense in algebras of binary relations[13,14],but it does not work in all Kleene algebras.For example,it rules out the tropical Kleene algebra described in Lecture??.In this algebra, p≤1for all p,but the idempotence law pp=p fails,so the set{p∈K|p≤1}does not form a Boolean algebra.In our approach,every Kleene algebra extends trivially to a Kleene algebra with tests by taking the two-element Boolean algebra{0,1}.Of course,there are more interesting models as well.However,there is a more serious issue.Even in algebras of binary relations,this ap-proach forces us to consider all elements p≤1as tests,including conditions that in practice would not normally be considered testable.For example,there may be programs p whose input/output relations have no side effects—that is,p≤1—but the associated test succeeds iffp halts,which in general is undecidable.We intend tests to be viewed as simple predicates that are easily recognizable as such and that are immediately decidable in a given state(and whose complements are therefore also immediately decidable).Having an explicit Boolean subalgebra allows this.While ProgramsWe will work with a Pascal-like programming language with sequential composition p;q,a conditional test if b then p else q,and a looping construct while b do p.Programs built inductively from atomic programs and tests using these constructs are called while programs.We occasionally omit the else clause of a conditional test.This can be considered an abbreviation for a conditional test with the dummy else clause1(true).These constructs are modeled in Kleene algebra with tests as follows:p;q=pqif b then p else q=bp+bqif b then p=bp+bwhile b do p=(bp)∗b.ConditionsWe will also be reasoning in the presence of extra assumptions.Recall that Kleene algebra and KAT are Horn theories,and these extra assumptions take the form of equational premises to the left of the implication symbol in a Horn formala.There are several common forms of premises that arise in applications.The most common form is a commutativity condition pq=qp or pb=bp.A commutativity condition between two atomic programs p and q expresses the fact that the two operations represented by p and q do not interfere with each other and may be done in either order.For example,if p and q are the assignments x:=3and y:=4respectively,then they do not affect each other.A commutativity condition pb=bp,where p is a program and b is a test,indicates that the execution of p does not affect the truth value of b.For example,if p is the assignment x:=3 and b is the test y=4,then execution of p has no effect on the truth value of b.Another common assumption comes in the form of a pair of equations p=pb and bp=b. Thefirst equation indicates that the execution of p causes b to become true,thus testing b after executing p is always redundant.The second equation indicates that if the sole purpose of p is to make b true,then there is no need to execute p if b is already true.For example, if p is the assignment x:=3and b is the test x=3,then these conditions hold.This is useful for example when we want to eliminate a redundant assignment.We can use thefirst equation p=pb to generate the condition b in a KAT expression,then use commutativity conditions to move b around until it comes up against another p,then use the second equation bp=b to eliminate the second occurrence of p,then move the b back again and eliminate it by applying p=pb in the opposite direction.It stands to reason that if p does not affect b,then neither should it affect b.This isindeed the case.Thus pb=bp should be equivalent to pb=bp.More generally,Lemma12.1In any Kleene algebra with tests,the following are equivalent:(1)bp=pc(2)bp=pc(3)bpc+bpc=0.Proof.By symmetry,it suffices to show the equivalence of(1)and(3).Assuming(1),we havebpc+bpc=pcc+bbp=p0+0p=0.Conversely,assuming(3),we have bpc=bpc=0.Thenbp=bp(c+c)=bpc+bpc=bpc+0=bpc+bpc=(b+b)pc=pc.2 Of course,any pair of tests commute;that is,bc=cb.This is an axiom of Boolean algebra.A Folk TheoremOne can give a purely equational proof,using KAT and commutativity conditions,of a classical result:every while program can be simulated by a while program with at most one while loop.This theorem is the subject of a treatise on folk theorems by Harel[7],who notes that it is commonly but erroneously attributed to B¨o hm and Jacopini[2]and who argues with some justification that it was known to Kleene.The version as stated here is originally due to Mirkowska[12],who gives a set of local transformations that allow every while program to be transformed systematically to one with at most one while loop.We consider a similar set of local transformations and give a purely equational proof of correctness for each.This result illustrates the use of Kleene algebra with tests and commutativity conditions in program equivalence proofs.It is a commonly held belief that this result has no purely schematic(that is,propositional, uninterpreted)proof[7].The proofs of[8,12],as reported in[7],use extra variables to remember certain values at certain points in the program,either program counter values or the values of tests.Since having to remember these values seems unavoidable,one might infer that the only recourse is to introduce extra variables,along with an explicit assignment mechanism for assigning values to them.Thus,as the argument goes,proofs of this theorem cannot be purely propositional.However,in KAT,if we need to preserve the value of a test b across an action p with which b is not guaranteed to commute,we can introduce a new test c and commutativity condition cp=pc,which intuitively says that the computation of p does not affect the value of c.Then we insert in an appropriate place the program s;bc+bc,where s is a new atomic program. Intuitively,we regard s as assigning the value of b to some new Boolean variable that is tested in c,although there is no explicit mechanism for doing this;s is just an uninterpreted atomic program symbol.However,the guard bc+bc(equivalently,b↔c;in the language of while programs,if b then c else c)ensures that b and c have the same Boolean value just after execution of s.To illustrate this technique,consider the simple programif b then{p;q}(12.1)else{p;r}If the value of b were preserved by p,then we could rewrite this program more simply as p;if b then q else r(12.2) Formally,the assumption that the value of b is preserved by p takes the form of the commu-tativity condition bp=pb.By Lemma12.1,we also have bp=pb.Expressed in the language of Kleene algebra,the equivalence of(12.1)and(12.2)becomes the equationbpq+bpr=p(bq+br).This identity can be established by simple equational reasoning:p(bq+br)=pbq+pbr by distributivity=bpq+bpr by the commutativity assumptions.But what if b is not preserved by p?Here we can introduce a new atomic test c and atomic program s along with the commutativity condition pc=cp,intuitively modeling the idea that c tests a variable that is not modified by p,and insert the program s;bc+bc.We can now give a purely equational proof of the equivalence of the two programss;bc+bc;if b then{p;q}else{p;r}ands;bc+bc;p;if c then q else rusing the axioms of Kleene algebra with tests and the commutativity condition pc=cp.In fact,we can even do away with the atomic program s:if the two programs are equivalent without the precomputation s,then they are certainly equivalent with it.Removing the leading s and expressing the two programs in the language of Kleene algebra,the equivalence problem becomes(bc+bc)(bpq+bpr)=(bc+bc)p(cq+cr).(12.3) Using the distributive laws and the laws of Boolean algebra,we can simplify the left-hand side of(12.3)as follows:(bc+bc)(bpq+bpr)=bcbpq+bcbpq+bcbpr+bcbpr=bcpq+bcpr.The right-hand side of(12.3)simplifies in a similar fashion to the same expression:(bc+bc)p(cq+cr)=bcpcq+bcpcq+bcpcr+bcpcr=bccpq+bccpq+bccpr+bccpr=bcpq+bcpr.Here the commutativity assumption is used in the second step.Normal FormA program is in normal form if it is of the formp;while b do q(12.4) where p and q are while free.The subprogram p is called the precomputation of the normal form.Now we can show that every while program,suitably augmented withfinitely many new subprograms of the form s;bc+bc,is equivalent to a while program in normal form, reasoning in Kleene algebra with tests under certain commutativity assumptions cp=pc.This can be proved by induction on the structure of the program.Each programming construct accounts for one case in the inductive proof.For each case,we can give a trans-formation that moves an inner while loop to the outside and an equational proof of its correctness.The inductive construction is performed from the inside out;that is,smaller subprogramsfirst.Wefirst show how to deal with a conditional test containing programs in normal form in its then and else clauses.Consider the programif b then{p1;while d1do q1}else{p2;while d2do q2}.We introduce a new atomic program s and test c and assume that c commutes with p1,p2, q1,and q2.Under these assumptions,we show that the programss;bc+bc;(12.5)if b then{p1;while d1do q1}else{p2;while d2do q2}ands;bc+bc;if c then p1else p2;(12.6)while cd1+cd2doif c then q1else q2are equivalent.Note that if the two programs in the then and else clauses of(12.5)are in normal form,then(12.6)is in normal form.As previously mentioned,we can do away with the precomputation s.Removing s and rewriting(12.5)in the language of Kleene algebra,we obtain(bc+bc)(bp1(d1q1)∗d1+bp2(d2q2)∗d2)which reduces by distributivity and Boolean algebra tobcp1(d1q1)∗d1+bcp2(d2q2)∗d2.(12.7) Similarly,(12.6)becomes(bc+bc)(cp1+cp2)((cd1+cd2)(cq1+cq2))∗cd1+cd2.(12.8) The subexpression cd1+cd2of(12.8)is equivalent by propositional reasoning to cd1+cd2. Here we have used the familiar propositional equivalencecd1+cd2=(c+d1)(c+d2)and a De Morgan law.The other subexpressions of(12.8)can be simplified using distribu-tivity and Boolean algebra to obtain(bcp1+bcp2)(cd1q1+cd2q2)∗(cd1+cd2).(12.9) Using distributivity,this can be broken up into the sum of four terms:bcp1(cd1q1+cd2q2)∗cd1(12.10)+bcp1(cd1q1+cd2q2)∗cd2(12.11)+bcp2(cd1q1+cd2q2)∗cd1(12.12)+bcp2(cd1q1+cd2q2)∗cd2.(12.13)Under the commutativity assumptions,(12.11)and(12.12)vanish;and for the remaining two terms(12.10)and(12.13),we havebcp1(cd1q1+cd2q2)∗cd1=bcp1(ccd1q1+ccd2q2)∗d1=bcp1(d1q1)∗d1bcp2(cd1q1+cd2q2)∗cd2=bcp2(ccd1q1+ccd2q2)∗d2=bcp2(d2q2)∗d2.The sum of these two terms is exactly(12.7).Nested LoopsWe next consider two nested while loops.This construction is particularly interesting in that no commutativity conditions(thus no extra variables)are needed,in contrast to the corresponding transformations of[8,12],as reported in[7].It can be shown that the programwhile b do{p;while c do q}is equivalent to the programif b then{p;while b+c doif c then q else p}or in the language of Kleene algebra,(bp(cq)∗c)∗b=bp((b+c)(cq+cp))∗b+c+b.(12.14) The b on the right-hand side of(12.14)is for the nonexistent else clause of the outermost conditional of the second program.This construction transforms a pair of nested while loops to a single while loop inside a conditional test.After this transformation,the while loop can be taken outside the condi-tional using the previous transformation(this part does require a commutativity condition).A dummy normal form such as1;while0do1can be supplied for the missing else clause.We leave the proof of this equivalence as an exercise.Not surprisingly,the key property used in the proof is the denesting property(p∗q)∗p∗=(p+q)∗,which equates a regular expression of∗-depth two with another of∗-depth one.Eliminating PostcomputationsWe wish to show that a postcomputation occurring after a while loop can be absorbed into the while loop.Consider a program of the form{while b do p};q.(12.15)We can assume without loss of generality that b,the test of the while loop,commutes with the postcomputation q.If not,introduce a new test c that commutes with q along with an atomic program s that intuitively sets the value of c to b,and insert s;bc+bc before the loop and in the loop after the body.We then claim that the two programss;bc+bc;while b do{p;s;bc+bc};q(12.16)s;bc+bc;while c do{p;s;bc+bc};q(12.17)are equivalent.This allows us to replace(12.16)with(12.17),for which the commutativity assumption holds.For purposes of arguing that(12.16)and(12.17)are equivalent,we can omit all occur-rences of s.The leading occurrences can be omitted as argued above,and the occurrences inside the while loops can be assumed to be part of p.The two trailing occurrences of q can be omitted as well.After making these modifications and writing the programs in the language of KAT,we need to show(bc+bc)(bp(bc+bc))∗b=(bc+bc)(cp(bc+bc))∗c.Using the sliding rule p(qp)∗=(pq)∗p on both sides,this becomes((bc+bc)bp)∗(bc+bc)b=((bc+bc)cp)∗(bc+bc)c.By distributivity and Boolean algebra,both sides reduce easily to(bcp)∗bc.Under the assumption that b and q commute,we can show that(12.15)is equivalent to the programif bthen qelse while b do{(12.18)p;if b then q}Note that if p and q are while free,then(12.18)consists of a program in normal form inside a conditional,which can be transformed to normal form using the transformation above.We leave this equivalence as an exercise.CompositionThe composition of two programs in normal formp1;while b1do q1;(12.19)p2;while b2do q2can be transformed to a single program in normal form.First,we use the result of the previous section to absorb the while-free program p2into thefirst while loop.We can also ignore p1,since it can be absorbed into the precomputation of the resulting normal form when we are done.It therefore suffices to show how to transform a programwhile b do p;(12.20)while c do qto normal form,where p and q are while free.As already argued,we can assume without loss of generality that the test b commutes with the program q by introducing a new test if necessary.Since b also commutes with c by Boolean algebra,by a homework exercise we have that b commutes with the entire second while loop.This allows us to use the construction of the previous section to absorb the second while loop into thefirst.The resulting program looks likeif bthen while c do qelse{while b do{(12.21)p;if b then while c do q}}Here we have just substituted while c do q for q in(12.18).At this point we can apply the conditional test transformation to the inner subprogramif b then while c do qusing a dummy normal form for the omitted else clause,giving two nested loops in the else clause of(12.21);then denest the loops in the else clause of(12.21);finally,apply the conditional test transformation to the entire resulting program,yielding a program in normal form.The transformations described above give a systematic method for moving while loops outside of any other programming construct.By applying these transformations inductivelyfrom the innermost loops outward,we can transform any program into a program in normal form.None of these arguments needed an explicit assignment mechanism to Boolean variables, but only a dummy program s which does something unspecified(and which more often than not can be omitted in the actual proof)and a guard of the form bc+bc that says that b and c somehow obtained the same Boolean value.Of course,in a real implementation, s might assign the value of the test b to some new Boolean variable that is tested in c, but this does not play a role in equational proofs.The point is that it is not significant exactly how Boolean values are preserved across computations,but rather that they can be preserved;and for the purposes of formal verification,this fact is completely captured by a commutativity assumption.References[1]Allegra Angus and Dexter Kozen.Kleene algebra with 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