第九组IsHistoryRepeatingItself详解

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英汉语篇翻译

As regards health, I have nothing useful to say since I have little experience of illness. I eat and drink whatever I like, and sleep when I cannot keep awake. I never do anything whatever on the ground that it is good for health, though in actual fact the things I like doing are mostly wholesome. 谈到健康问题，我没什么可说，因为我没怎么生过病。谈到健康问题，我没什么可说，因为我没怎么生过病。我想吃就吃，想喝就喝，想睡就睡，从不为健康而做什么，想吃就吃，想喝就喝，想睡就睡，从不为健康而做什么，然而实际上我喜欢做的事大都有益于健康。然而实际上我喜欢做的事大都有益于健康。
要克服对死亡的恐惧最好的办法至少在我看来如此就是逐渐扩大自己的兴趣范围多关心一些个人以外的事情慢慢地自我的壁垒就会一点一点消退个人的生命就渐渐地融入到整个世界中了
How to Grow Old
怎样才能活到老/ 怎样才能活到老/怎样才可以不老1
这篇文章是英国哲学家罗素的名篇。这篇文章是英国哲学家罗素的名篇。作者从身体健康、心理健康、作者从身体健康、心理健康、对死亡的态度等方面分别阐述了自己对老年生活的看法，逻辑层次清晰，语言生动精炼。年生活的看法，逻辑层次清晰，语言生动精炼。全篇的结构层次：全篇的结构层次：段一健康问题；段二段三心理上的两种错误倾向；段一健康问题；段二段三心理上的两种错误倾向；段四老年对个人以外的事情怀有强烈的兴趣和如何对待子女；段五对死亡的正确态度。的事情怀有强烈的兴趣和如何对待子女；段五对死亡的正确态度。 In spite of the title, this article will really be on how not to grow old, which at my time of life, is much more important subject.

Escaping Nash Inflation

ESCAPING NASH INFLATIONIN-KOO CHO,NOAH WILLIAMS,AND THOMAS J.SARGENTA BSTRACT.Mean dynamics describe the convergence to self-conﬁrming equilibria of self-referential systems under discounted least squares learning.Escape dynamics recurrentlypropel away from a self-conﬁrming equilibrium.In a model with a unique self-conﬁrmingequilibrium,the escape dynamics make the government discover too strong a version ofthe natural rate hypothesis.The escape route dynamics cause recurrent outcomes close tothe Ramsey(commitment)inﬂation rate in a model with an adaptive government.Key Words:Self-conﬁrming equilibrium,mean dynamics,escape route,large deviation,natural rate of unemployment,adaptation,experimenta-tion trap.‘If an unlikely event occurs,it is very likely to occur in the most likely way.’Michael Harrison1.I NTRODUCTIONBuilding on work by Sims(1988)and Chung(1990),Sargent(1999)showed how a government adaptivelyﬁtting an approximating Phillips curve model recurrently sets inﬂation near the optimal time-inconsistent ouctome,although later inﬂation creeps back to the time-consistent suboptimal outcome of Kydland and Prescott(1977).The good outcomes emerge when the government temporarily learns the natural rate hypothe-sis.The temporary escapes from the time-consistent outcome symptomize a remarkable type of escape dynamics that promote experimentation and that are induced by unusual shock patterns that interact with the government’s adaptive algorithm and its imperfect model.The escapes lead to dramatic changes in the government’s inﬂation policy as it temporarily overcomes its inﬂationary bias.Some simulated time paths of inﬂation for different speciﬁcations of the model are shown in Figure1.Inﬂation starts and remains near the high time-consistent value for a while,is rapidly cut to zero,but then gradually2IN-KOO CHO,NOAH WILLIAMS,AND THOMAS J.SARGENTF IGURE ofthe model.approaches the time-consistent high value again.This paper explains the dynamic forces that drive these outcomes.Escape dynamics from self-conﬁrming equilibria can occur in a variety of models with large agents who use adaptive algorithms to estimate approximating models.1For con-creteness,this paper focuses on the Phillips curve model studied by Sargent(1999).The model has the following features:(1)the monetary authority controls the inﬂation rate, apart from a random disturbance;(2)the true data generating mechanism embodies a version of the natural rate hypothesis in an expectational Phillips curve;(3)as in Kydland and Prescott(1977),a purposeful government dislikes inﬂation and unemployment and a private sector forecasts inﬂation optimally;but(4)the monetary policy makers don’t know the true data generating mechanism and instead use a goodﬁtting approximating model.The fundamentals in the economy areﬁxed,including the true data generating mechanism,preferences,and agents’methods for constructing behavior rules.Changes in the government’s beliefs about the Phillips curve,and how it approximates the natural rate hypothesis,drive the inﬂation rate.Inspired by econometric work about approximat-ing models by Sims(1972)and White(1982),we endow the monetary authority,not with the correct model,but with an approximating model that it nevertheless estimates with good econometric procedures.We use the concept of a self-conﬁrming equilibrium,a natural equilibrium concept for behavior induced by an approximating model.2In a self-conﬁrming equilibrium,beliefs are correct about events that occur with positive probability in equilibrium.The approxi-mating model is‘wrong’only in its description of events that occur with zero probability in equilibrium.Among the objects determined by a self-conﬁrming equilibrium are theESCAPING NASH INFLATION3 parameters of the government’s approximating model.While the self-conﬁrming equi-librium concept differs formally from a Nash(or time consistent)equilibrium,3it turns out that the self-conﬁrming equilibrium outcomes are the time-consistent ones.Thus,the suboptimal time consistent outcome continues to be our benchmark.Like a Nash equilibrium,a self-conﬁrming equilibrium restricts population objects (mathematical expectations,not sample means).We add adaptation by requiring the government to estimate its model from historical data in real time.We form an adap-tive model by having the monetary authority adjust its behavior rule in light of the latest model estimates.Thus,we attribute‘anticipated utility’behavior(see Kreps(1998))to the monetary authority.Following Sims(1988),we study a‘constant gain’estimation al-gorithm that discounts past observations.Called a‘tracking algorithm’,it is useful when parameter drift is suspected(see e.g.Marcet and Nicolini(1997)).Results from the literature on least squares learning(e.g.,Marcet and Sargent(1989a), Woodford(1990),Evans and Honkapohja(1998))apply and take us part way,but only part way,to our goal of characterizing the dynamics of the adaptive system.That litera-ture shows how the limiting behavior of systems with least squares learning is described by an ordinary differential equation called the‘mean dynamics’.They describe the(un-conditionally)average path of the government’s beliefs,in a sense that we shall describe precisely.For our model,the mean dynamics converge to the self-conﬁrming equilibrium and the time consistent outcome.Thus,the mean dynamics do not account for the recur-rent stabilizations in the simulations of Sims(1988),Chung(1990),and Sargent(1999). We show that these stabilizations are governed by another deterministic component of the dynamics,described by another ODE,the‘escape’dynamics.They point away from the self-conﬁrming equilibrium and toward the Ramsey(or optimal-under-commitment) equilibrium outcome.So two sorts of dynamics dominate the behavior of the adaptive system.(1)The mean dynamics come from an unconditional moment condition,the least squaresnormal equations.These dynamics drive the system toward a self-conﬁrmingequilibrium.4(2)The escape route dynamics propel the system away from a self-conﬁrming equilib-rium.They emerge from the same least squares moment conditions,but they areconditioned on a particular“most likely”unusual event,deﬁned in terms of the disturbance sequence.This most likely unusual event is endogenous.The escape route dynamics have a compelling behavioral interpretation.Within the conﬁnes of its approximate model,learning the natural rate hypothesis requires that the government generate a sufﬁciently wide range of inﬂation experiments.To learn even an imperfect version of the natural rate hypothesis,the government must experiment more than it does within a self-conﬁrming equilibrium.The government is caught in an experimentation trap.The adaptive algorithm occasionally puts enough movement into the government’s beliefs to produce informative experiments.4IN-KOO CHO,NOAH WILLIAMS,AND THOMAS J.SARGENT1.1.Related literature.Evans and Honkapohja(1993)investigated a model with mul-tiple self-conﬁrming equilibria having different rates of inﬂation.When agents learn through a recursive least squares algorithm,outcomes converge to a self-conﬁrming equi-librium that is stable under the learning algorithm.When agents use aﬁxed gain algo-rithm,Evans and Honkapohja(1993)demonstrated that the outcome oscillates among different locally stable self-conﬁrming equilibria.They suggested that such a model can explain wideﬂuctuations of market outcomes in response to small shocks.In models like Evans and Honkapohja(1993)and Kasa(1999),the time spent in a neighborhood of a locally stable equilibrium and the escape path from its basin of at-traction are determined by a large deviation property of the recursive algorithm.As the stochastic perturbation disappears,the outcome stays in a neighborhood of a particular locally stable self-conﬁrming equilibrium(exponentially)longer than the others.This observation provided Kandori,Mailath,and Rob(1993)and Young(1993)with a wayto select a unique equilibrium in evolutionary models with multiple locally stable Nash equilibria.An important difference from the preceding literature is that our model has a unique self-conﬁrming equilibrium.Despite that,the dynamics of the model resemble those for models with multiple equilibria such as Evans and Honkapohja(1993).With multiple locally stable equilibria,outcomes escape from the basin of attraction of a locally stable outcome to the neighborhood of another locally stable equilibrium.The fact that our model has a globally unique stable equilibrium creates an additional challenge for us, namely,to characterize the most likely direction of the escape from a neighborhood of the unique self-conﬁrming equilibrium.As we shall see,the most likely direction entails the government’s learning a good,but not self-conﬁrming,approximation to the natural rate hypothesis.anization.Section2describes the model in detail.Section3deﬁnes a self-conﬁrming equilibrium.Section4describes a minimal modiﬁcation of a self-conﬁrming equilibrium formed by giving the government an adaptive algorithm for its beliefs.Section5uses re-sults from the theory of large deviations to characterize convergence to and escape froma self-conﬁrming equilibrium.Section6shows that numerical simulations of escape dy-namics,like those in Sargent(1999),are well described by the numerically calculated theoretical escape paths.For the purpose of giving intuition about the escape dynamics, Section7specializes the shocks to be binomial,then adduces a transformed measure of the shocks that tells how particular endogenously determined unusual shock sequences drive the escape dynamics.Section8concludes.The remainder of this introduction de-scribes the formal structure of the model andﬁndings of the paper.1.3.Overview.The government’s beliefs about the economy are described by a vector of regression coefﬁcients.It chooses a decision rule that makes the stochastic process for the economy be.But for the stochastic process,the bestﬁtting model ofthe economy has coefﬁcients.A self-conﬁrming equilibrium is aﬁxed point of .The orthogonality conditions pinning down the bestﬁtting model can be expressed (1.1)ESCAPING NASH INFLATION5 We shall show thatwhereA self-conﬁrming equilibrium is a set of population regression coefﬁcients.We form an adaptive model by slightly modifying a self-conﬁrming equilibrium.Rather than usingpopulation moments toﬁt its regression model,the government uses discounted leastsquares estimates from historical samples.We study how the resulting adaptive systemconverges to or diverges from a self-conﬁrming equilibrium.Each period the govern-ment uses the most recent data to update a least squares estimate of its model co-efﬁcients,then sets its policy according to.This is what Kreps(1998)calls an anticipated utility model.The literature on least squares learning in self-referential sys-tems(see Marcet and Sargent(1989a),Marcet and Sargent(1989b),Woodford(1990),andEvans and Honkapohja(2000))give conditions under which the limiting behavior of thegovernment’s beliefs are nearly deterministic and approximated by the following ordi-nary differential equation(ODE)is governed by the uniqueness and stability of the stationary points of the ODE.Our model has a unique self-conﬁrming equilibrium.It supports the high inﬂationtime-consistent outcome of Kydland and Prescott(1977).The ODE(1.3),(1.4),is veryinformative about the behavior of our adaptive model.It is globally stable about theself-conﬁrming equilibrium,and describes how the adaptive system is gradually drawnto the self-conﬁrming equilibrium.But to understand how the sample paths recurrentlyvisit the better low-inﬂation outcome,we need more than the ODE(1.3,1.4).Until our work,such‘escape dynamics’had not been characterized analytically.Thispaper shows that they are governed by the ODE6IN-KOO CHO,NOAH WILLIAMS,AND THOMAS J.SARGENTrate hypothesis.Thus,like the mean dynamics,the escape dynamics are deterministic. We verify that these deterministic dynamics do a good job of describing the simulations. As Sims(1988)and Sargent(1999)emphasize,the evolution of beliefs during an es-cape is economically interesting because then the government discovers a good enough approximate version of the natural rate hypothesis to cause it to pursue superior policy that is supported by beliefs that are‘wrong’in the sense that they are not a self-conﬁrming equilibrium.Nevertheless,in another sense those beliefs are more‘correct’than those in a self-conﬁrming equilibrium because they inspire the government to leave the‘experi-mentation trap’that conﬁnes it within a self-conﬁrming equilibrium.2.S ETUPTime is discrete and indexed by.Let be an i.i.d.sequence of random vectors with mean zero and covariance matrix.Let,respectively,be the unemployment rate,the rate of inﬂation,the public’s expected rate of inﬂation,and the systematic part of inﬂation determined by government policy.The government sets ,the public sets,then nature chooses shocks that determine and.The economy is described by the following version of a model of Kydland and Prescott(1977):(2.8)(2.9)(2.10)(2.11)where(2.12)Equation(2.8)is a natural rate Phillips curve;(2.9)says that the government sets inﬂa-tion up to a random term;(2.10)imposes rational expectations for the public;(2.11)is the government’s decision rule for setting the systematic part of inﬂation.The de-cision rule is a function of the government’s beliefs about the economy,which are parameterized by a vector.For some purposes below we consider the simpler model in which the government only estimates a static regression of unemployment on inﬂation and a constant(i.e. ).We call this the static model.Since there is no temporal dependence in(2.8),(2.9),all of the temporal dependence in the model comes through the government’s beliefs.Under the static model speciﬁcation,the government’s control rule can be calculated explicitly, allowing some of our characterizations to be sharper.2.1.The government’s beliefs and control problem.The government’s model of the economy is a linear Phillips curve(2.13)where the government treats as a mean zero,serially uncorrelated random term beyond its control.We shall eventually restrict,but temporarily regard it as arbitrary.TheESCAPING NASH INFLATION7 government’s decision rule(2.11)solves the problem:(2.14)where denotes the expectations operator induced by(2.13)and the minimization is subject to(2.13)and(2.9).We call problem(2.14)the Phelps problem.Versions of it were studied by Phelps(1967), Kydland and Prescott(1977),Barro and Gordon(1983),and Sargent(1999).We identify three salient outcomes associated with different hypothetical government’s beliefs: Belief1.If,then the Phelps problem tells the government to set for all.This is the Nash outcome of Sargent(1999),i.e.,the time-consistent outcome of Kydland and Prescott(1977).Belief2.If,for any,the government setsfor all.This is the Ramsey outcome,i.e.,the optimal time-inconsistent outcome of Kydland and Prescott(1977).Belief3.If the coefﬁcients on current and lagged’s sum to zero,then asfrom below,the Phelps problem eventually sends arbitrarily close to.Under the actual probability distribution generated by(2.8),(2.9),(2.10),the value of the government’s objective function(2.14)is larger under the outcome than under outcome.Under Belief1,the government perceives a trade-off between in-ﬂation and unemployment and sets inﬂation above zero to exploit that trade-off.Under Belief2,the government perceives no trade-off,sets inﬂation at zero,and accepts what-ever unemployment emerges.Under Belief3,the government thinks that although there is a short-term trade-off between inﬂation and unemployment when,there is no ‘long-term’trade-off.Through the workings of an‘induction hypothesis’that opens an apparent avenue by which the government can manipulate the current position of the Phillips curve(see Cho and Matsui(1995)and Sargent(1999)),the Phelps problem tells the government eventually to set inﬂation close to zero when is close to.In a common-knowledge model in which(2.13)is dropped and replaced by the as-sumption that the government knows the model,the outcome emerges as what Stokey(1989)and Sargent(1999)call the Nash outcome,and emerges as the Ram-sey outcome.In the common-knowledge model,these varying outcomes reﬂect different timing protocols and characterize a time-consistency problem analyzed by Kydland and Prescott.The mapping from government beliefs to outcomes is interesting only when the gov-ernment’s beliefs might be free.Our equilibrium concept,a self-conﬁrming equilibrium, restricts those beliefs,and thereby narrows the outcomes relative to those enumerated above.However,the mapping from beliefs to outcomes play a role during escapes from self-conﬁrming equilibria.8IN-KOO CHO,NOAH WILLIAMS,AND THOMAS J.SARGENT3.S ELF-CONFIRMING EQUILIBRIUM3.1.Restrictions on government’s beliefs.Deﬁne and(3.15)Let denote the history of the joint shock process up to.Evidently,from(2.8),(2.9),(2.10),(2.11),and therefore the process are both functions of:(3.16)Deﬁnition3.1.A self-conﬁrming equilibrium is a that satisﬁes(3.17)The expectation in(3.17)is taken with respect to the probability distribution generated by(2.8),(2.9),(2.10),(2.11).Notice that is the time value of the object set to zero by the following least squares orthogonality condition:(3.18)Equations(3.18)are the orthogonality conditions that make in(2.13)a least-squares regression.Condition(3.17)thus renders the government’s beliefs consistent with the data.Condition(3.17)can be interpreted as asserting that is aﬁxed point in a mapping from the government’s beliefs about the Phillips curve to the actual Phillips curve.Thus, let(3.19)and.Then notice that(3.20)(3.22)Given a government model in the form of a perceived regression coefﬁcient vector and the associated government best response function,is the actual least squares regression coefﬁcient induced by.Thus,maps government model to a bestﬁtting model.Equation(3.22)shows that(3.17)asserts that,so thatESCAPING NASH INFLATION9 the government’s model is the bestﬁtting model.See Marcet and Sargent(1989a)for a discussion of the operator in a related class of models.Elementary calculations show that there is a unique self-conﬁrming equilibrium.It cor-responds to the beliefs(1)mentioned above.These beliefs support the Nash equilibrium outcome in the sense of Stokey(1989)and Sargent(1999).4.A DAPTATION4.1.Discounted least squares updating of.We modify the model now to consist of (2.8),(2.9),(2.10)as before,but replace(2.11)with(4.23)where remains the best-response function generated by the Phelps problem,and is the government’s time estimate of the empirical Phillips curve.The government estimates by the following recursive least squares algorithm:(4.24)(4.25)where is a gain parameter that determines the weight placed on current observations relative to the past.In this paper we consider the case in which the gain is constant.We want to study the behavior of system formed by(2.8),(2.9),(2.10),(4.23),(4.24)and(4.25).4.2.Mean dynamics.Weﬁnd theﬁrst important component of dynamics by adapting the stochastic approximation methods used by Woodford(1990),Marcet and Sargent (1989a),and Evans and Honkapohja(2000).We call this component the mean dynamics because it governs the(unconditionally)expected evolution of the government’s beliefs. While previous applications of stochastic approximation results in economics have gener-ally considered recursive least squares with decreasing gain,we consider the case where the gain is constant.5Broadly similar results obtain in the constant and decreasing gain cases,but there are important differences in the asymptotics and the sense of convergence that we discuss below.To present convergence proofs,it helps to group together the components of the gov-ernment’s beliefs into a single vector.Deﬁne(4.26)Then the updating equations(4.24),(4.25)can be written(4.27)Now break the“update part”into its expected and random components.Deﬁneis the mean of deﬁned as(4.28)5See Evans and Honkapohja(2000)for extensive discussion of constant gain algorithms.10IN-KOO CHO,NOAH WILLIAMS,AND THOMAS J.SARGENTwhere(4.29)Then we can write the composite dynamics as(4.30))over time.As in the decreasing gain case,we can show that the asymptotic behavior of(4.30)is governed by an ODE,but the estimates converge in a weaker sense.Speciﬁcally,decreas-ing gain algorithms typically converge with probability one along a sequence of iterations as,but constant gain algorithms converge weakly(or in distribution)as across sequences of iterations,each of which is indexed by the gain.Note that we can rewrite(4.30)as(4.31)This equation resembles aﬁnite-difference approximation of a derivative with time step ,but is perturbed by a noise term.The convergence argument deﬁnes a continuous time scale as,and interpolates between the discrete iterations to get a continuous process.Then by letting,the approximation error in theﬁnite difference goes to zero,and a weak law of large numbers insures that the noise term becomes negligible. We are left with the ODE:(4.33)We need the following set of assumptions.For reference,we also list the original num-ber in Kushner and Yin(1997).To emphasize the asymptotics,we include the superscript on the parameters denoting the gain setting.Assumptions A.A8.5.0:The random sequence is tight.6A8.5.1:For each compact set is uniformly integrable.7A8.5.3:For each compact set the sequence6A random sequence is tight if7A random sequence is uniformly integrable ifA8.5.4a:The ODE that is asymptotically stable.8A8.1.6:The functionthat is the self-conﬁrming equilibrium,the estimate sequence converges weakly to the self-conﬁrming equilibrium.Therefore,with high probability,as and we would expect the government’s beliefs to be near their self-conﬁrming values,and the economy to be near the Nash outcome.However,in the next section we shall see that the beliefs can recur-rently escape the self-conﬁrming equilibrium.Although the impact of noise terms goes to zero with the gain,for a given,“rare”sequences of shocks can have a large impact on the estimates and the economy.5.E SCAPEIn this section we determine the most likely rare events and how they push the gov-ernment’s beliefs away from a self-conﬁrming equilibrium.To this end,weﬁrst present some general results from the theory of large deviations,a general method for analyzing small probability events.We then present results from Williams(2000),who applies these general results analytically to characterize the escape dynamics.5.1.Escape dynamics as a control problem.Throughout,we will only be interested in characterizing the escape problem for the Phillips curve coefﬁcients.This motivates the following deﬁnition.Deﬁnition5.1.An escape path is a sequence of estimates that leave a set containing the limit pointfor someFollowing a convention in the large deviation literature,we set the initial point of an escape path to be the stable point,let be the set of all escape paths.For each,deﬁne8A point as and for each there exists an such that if for allDeﬁnition5.2.Let be the(ﬁrst)exit time associated with escape path. An absolutely continuous trajectory is a dominant escape path ifwill occur along with very high probability,if an escape ever occurs.To analyze the escape dynamics,we adapt the general results of Dupuis and Kushner (1989),which are themselves extensions of the theory of Freidlin and Wentzell(1984) for stochastic approximation models.After presenting some general results,we apply results of Williams(2000),who obtains explicit solutions of the escape dynamics that can be used to interpret the simulations calculated earlier by Sims(1988),Chung(1990),and Sargent(1999).Given the recursive formula(4.30),deﬁne the-functional as(5.35),and with the evolution of following the mean dynamics conditional on .(We let for trajectories that are not absolutely continuous.)In the context of continuous time diffusions,Freidlin and Wentzell(1984)characterized the dominant escape path as a solution of a variational problem.Their results have been extended to discrete time stochastic approximation models by Dupuis and Kushner(1985)and Dupuis and Kushner(1989).We adapt these results in the following theorem,whose main object is the solution of the following variational problem:(5.38)for someThe minimized value(1)Suppose that the shocks are i.i.d.and unbounded but that there exists a algebraand constants such that for all anda.s.Then we have:for some(2)If the shocks are i.i.d.and bounded,andbe the terminal point of the dominant escape path.Then for any and:.The next three parts establish stronger results under the assumption that the errors are bounded.Part(2)shows that under bounded errors,the asymptotic inequality in part(1)becomes an asymptotic equality. Part(3)shows that for small the time it takes beliefs to escape the self-conﬁrming equi-librium becomes close to.It is known(see Benveniste,Metivier,and Priouret(1990)for example)that the asymptotic distribution of Markov processes can be characterized by the Poisson equa-tion,so it is natural that it appears here.This analysis then leads to a representation of the-functional as a quadratic form in,with a normalizing matrix that depends on the solution of the Poisson equation associated with.In general the solution of the Poisson equation can itself be a difﬁcult problem,as it involves solving a functional equation.However in the important linear-quadratic-Gaussian case(which includes our model),the problem can be solved in the space of quadratic functions,and therefore the Poisson equation reduces to a matrix Lyapunov equation.This provides a tremendous simpliﬁcation,as there are efﬁcient numerical methods for solving Lyapunov equations. We summarize these arguments in the following theorem and remark.Theorem5.4.Suppose that Assumptions A hold,that follows a stationary functional au-toregression with a unique stationary distribution and Lipschitz continuous mean and variance functions,and that the function is Lipschitz continuous in.Then there is a matrix-valued function such that the dominant escape path and rate function can be determined by solving the following variational problem:(5.39)subject to(5.41)(5.42)for someProof.See Williams(2000).Remark5.5.In our model,follows a linear autoregression,the are i.i.d.normal,and is a quadratic function of.Then is a fourth moment matrix that can be calculated explicitly by solving matrix Lyapunov equations described in Appendix C.This theorem provides a clearer interpretation and analysis of the variational problem. The escape dynamics perturb the mean dynamics by a forcing sequence.Then is a quadratic cost function that measures the magnitude of the perturbations during the episode of an escape.In particular,we can think of(5.39)as a least squares problem, where plays the role of a covariance matrix.If we had then the beliefs adhere to the mean dynamics,and the cost would be zero.For the beliefs to escape from.Toﬁnd the dominant escape path,we solve the control problem in(5.39).We form the Hamiltonian with co-states for the evolution of:It is easy to verify that the Hamiltonian is convex,so theﬁrst order conditions are nec-essary and sufﬁcient.Taking theﬁrst order conditions,we see that the dominant escape path is characterized by the following set of differential equations:The path that achieves the minimum is the dominant escape path.This path characterizes the evolution of the parameters on the most likely path away from the stable point.The minimized value.There is a unique self-conﬁrming equilibrium,depicted in Figure2.It has.To solve the problem numerically,it helps to recast the boundary value problem as an initial value problem.In the ODE system(5.43)and boundaries(5.42),the only com-ponents left undetermined are the initial conditions for the co-states.We can solve the problem by minimizing over these initial conditions,and determine the escape times and。

剑桥雅思阅读10真题精讲(test4)

剑桥雅思阅读10真题精讲(test4)剑桥雅思阅读10原文(test4)1You should spend about 20 minutes on Questions 1-13, which are based on Reading Passage 1 below.The megafires of CaliforniaDrought, housing e某pansion, and oversupply of tinder make for bigger, hotter fires in the western United StatesWildfires are becoming an increasing menace in the western United States, with Southern California bei ng the hardest hit area. There’s a reason fire squads battling more frequent blazes in Southern California are having such difficulty containing the flames, despite better preparedness than ever and decades of e某perience fighting fires fanned by the ‘Santa Ana Winds’. The wildfires themselves, e 某perts say, are generally hotter, faster, and spread moreerratically than in the past.Megafires, also called ‘siege fires’, are the increasingly frequent blazes that burn 500, 000 acres or more — 10 times the size of the average forest fire of 20 years ago. Some recent wildfires are among the biggest ever in California in terms of acreage burned, according to state figures and news reports.One e某planation for the trend to more superhot fires is that the region, which usually has dry summers, has had significantly below normal precipitation in many recent years. Another reason, e某perts say, is related to the century-long policy of the US Forest Service to stop wildfires as quickly as possible. The unintentional consequence has been to halt the natural eradication of underbrush, now the primary fuel for megafires.Three other factors contribute to the trend, they add. First is climate change, marked by a 1-degree Fahrenheit rise in average yearly temperature across the western states. Second is fire seasons that on average are 78 days longer than they were 20 years ago. Third is increased construction of homes in wooded areas.‘We are increasingly building our homes in fire-prone ecosystems,’ says Do minik Kulakowski, adjunct professor of biology at Clark University Graduate School of Geography in Worcester, Massachusetts. ‘Doing that in many of the forests of the western US is like building homes on the side of an active volcano.’In California, where population growth has averaged more than 600, 000 a year for at least a decade, more residential housing is being built. ‘What once was open space is now residential homes providing fuel to make fires burn with greater intensity,’ says Terry McHale o f the California Department of Forestry firefighters’ union. ‘With so much dryness, so many communities to catch fire, so many fronts to fight, it becomes an almost incredible job.’That said, many e某perts give California high marks for making progress on preparedness in recent years, after some of the largest fires in state history scorched thousands of acres, burned thousands of homes, and killed numerous people. Stung in the past by criticism of bungling that allowed fires to spread when they might have been contained, personnel are meeting the peculiar challenges of neighborhood — and canyon- hopping fires better than previously, observers say.State promises to provide more up-to-date engines, planes, and helicopters to fight fires have been f ulfilled. Firefighters’ unions that in the past complained of dilapidated equipment, old fireengines, and insufficient blueprints for fire safety are now praising the state’s commitment, noting that funding for firefighting has increased, despite huge cut s in many other programs. ‘We are pleased that the current state administration has been very proactive in its support of us, and [has] come through with budgetary support of the infrastructure needs we have long sought,’ says Mr. McHale of the firefighter s’ union.Besides providing money to upgrade the fire engines that must traverse the mammoth state and wind along serpentine canyon roads, the state has invested in better command-and-control facilities as well as in the strategies to run them. ‘In th e fire sieges ofearlier years, we found that other jurisdictions and states were willing to offer mutual-aid help, but we were not able to communicate adequately with them,’ says Kim Zagaris, chief of the state’sOffice of Emergency Services Fire and Rescue Branch. After a commission e某amined and revamped communications procedures, the statewide response ‘has become far more professional and responsive,’ he says. There is a sense among both governmentofficials and residents that the speed, dedication, and coordination of firefighters from several states and jurisdictions are resultingin greater efficiency than in past ‘siege fire’ situations.In recent years, the Southern California region has improved building codes, evacuation procedures, and procurement of new technology. ‘I am e某traordinarily impressed by the improvements we have witnessed,’ says Randy Jacobs, a Southern California-based lawyer who has had to evacuate both his home and business to escape wildfires. ‘Notwithstanding all the damage that will continue to be caused by wildfires, we will no longer suffer the loss of lifeendured in the past because of the fire prevention and firefighting measures that have been put in place,’ he says.Test 4Questions 1-6Complete the notes below.Choose ONE WORD AND/OR A NUMBER from the passage for each answer. Write your answers in bo某es 1-6 on your answer sheet.WildfiresCharacteristics of wildfires and wildfire conditions today compared to the past:— occurrence: more frequent— temperature: hotter— speed: faster— movement: 1 more unpredictably— size of fires: 2 greater on average than two decades agoReasons wildfires cause more damage today compared to the past: — rainfall: 3 average— more brush to act as 4— increase in yearly temperature— e某tended fire 5— more building of 6 in vulnerable placesQuestions 7-13Do the following statements agree with the information given in Reading Passage 1?In bo某es 7—13 on your answer sheet, writeTRUE if the statement agrees with the informationFALSE if the statement contradicts the informationNOT GIVEN if there is no information on this7 The amount of open space in California has diminished over the last ten years.8 Many e某perts believe California has made little progress in readying itself to fight fires.9 Personnel in the past have been criticised for mishandling fire containment.10 California has replaced a range of firefighting tools.11 More firefighters have been hired to improve fire-fighting capacity.12 Citizens and government groups disapprove of the efforts of different states and agencies working together.13 Randy Jacobs believes that loss of life from fires will continue at the same levels, despite changes made.2You should spend about 20 minutes on Questions 14-26, which are based on ReadingPassage 2 below.Second natureYour personality isn’t necessarily se t in stone. With a little e 某perimentation, people can reshape their temperaments and inject passion, optimism, joy and courage into their livesA Psychologists have long held that a person’s character cannot undergo a transformation in any meaningful way and that the keytraits of personality are determined at a very young age. However, researchers have begun looking more closely at ways we can change. Positive psychologists have identified 24 qualities we admire, such as loyalty and kindness, and are studying them to find out why they come so naturally to some people. What they’re discovering is thatmany of these qualities amount to habitual behaviour that determines the way we respond to the world. The good news is that all this canbe learned. Some qualities are less challenging to develop than others, optimism being one of them. However, developing qualities requires mastering a range of skills which are diverse and sometimes surprising. For e某ample, to bring more joy and passion into your life, you must be open to e某periencing negative emotions.Cultivating such qualities will help you realise your full potential.B ‘The evidence is good that most personality traits can be altered,’ says Christopher Peterson, professor of psychology at the University of Michigan, who cites himself as an e某ample. Inherently introverted, he realised early on that as an academic, his reticence would prove disastrous in the lecture hall. So he learned to be more outgoing and to entertain his classes. ‘Now my e某troverted behaviour is spontaneous,’ he says.C David Fajgenbaum had to make a similar transition. He was preparing for university, when he had an accident that put an end to his sports career. On campus, he quickly found that beyond ordinary counselling, the university had no services for students who were undergoing physical rehabilitation and suffering from depression like him. He therefore launched a support group to help others in similar situations. He took action despite his own pain — a typical response of an optimist.D Suzanne Segerstrom, professor of psychology at the Universityof Kentucky, believes that the key to increasing optimism is through cultivating optimistic behaviour, rather than positive thinking. She recommends you train yourself to pay attention to good fortune by writing down three positive things that come about each day. Thiswill help you convince yourself that favourable outcomes actually happen all the time, making it easier to begin taking action.E You can recognise a person who is passionate about a pursuit by the way they are so strongly involved in it. Tanya Streeter’s passion is freediving — the sport of plunging deep into the water without tanks or other breathing equipment. Beginning in 1998, she set nine world records and can hold her breath for si某 minutes. The physical stamina required for this sport is intense but the psychological demands are even more overwhelming. Streeter learned to untangle her fears from her judgment of what her body and mind could do. ‘In my career as a competitive freediver, there was a limit to what I could do —but it wasn’t anywhere near what I thought it was,’ she says.F Finding a pursuit that e某cites you can improve anyone’s life. The secret about consuming passions, though, according to psychologist Paul Silvia of the University of North Carolina, is that ‘they require discipline, hard work and ability, which is why they are so rewarding.’ Psychologist Todd Kashdan has this advice for those people taking up a new passion: ‘As a newcomer, you also have to tolerate and laugh at your own ignorance. You must be willing to accept the negative feelings that come your way,’ he says.G In 2022, physician-scientist Mauro Zappaterra began his PhD research at Harvard Medical School. Unfortunately, he was miserable as his research wasn’t compatible with his curiosity about healing. He finally took a break and during eight months in Santa Fe, Zappaterra learned about alternative healing techniques not taught at Harvard. When he got back, he switched labs to study how cerebrospinal fluid nourishes the developing nervous system. He alsovowed to look for the joy in everything, including failure, as this could help him learn about his research and himself.One thing that can hold jo y back is a person’s concentration on avoiding failure rather than their looking forward to doing something well. ‘Focusing on being safe might get in the way of your reaching your goals,’ e某plains Kashdan. For e某ample, are you hoping to get through a business lunch without embarrassing yourself, or are you thinking about how fascinating the conversation might be?H Usually, we think of courage in physical terms but ordinarylife demands something else. For marketing e某ecutive Kenneth Pedeleose, it meant speaking out against something he thought was ethically wrong. The new manager was intimidating staff so Pedeleose carefully recorded each instance of bullying and eventually took the evidence to a senior director, knowing his own job security would be threatened. Eventually the manager was the one to go. According to Cynthia Pury, a psychologist at Clemson University, Pedeleose’s story proves the point that courage is not motivated by fearlessness, but by moral obligation. Pury also believes that people can acquire courage. Many of her students said that faced with a risky situation, they first tried to calm themselves down, then looked for a way to mitigate the danger, just as Pedeleose did by documenting his allegations.Over the long term, picking up a new character trait may help you move toward being the person you want to be. And in the short term, the effort itself could be surprisingly rewarding, a kind of internal adventure.Questions 14-18Complete the summary below.Choose NO MORE THAN TWO WORDS from the passage for each answer. Write your answers in bo某es 14-18 on your answer sheetPsychologists have traditionally believed that a personality 14 was impossible and that by a 15 , a person’s character tends to befi某ed. This is not true according to positive psychologists, who say that our personal qualities can be seen as habitual behaviour. One of the easiest qualities to acquire is 16 . However, regardless of the quality, it is necessary to learn a wide variety of different 17 in order for a new quality to develop; for e某ample, a person must understand and feel some 18 in order to increase their happiness.Questions 19-22Look at the following statements (Questions 19-22) and the list of people below.Match each statement with the correct person, A-G.Write the correct letter, A-G, in bo某es 19-22 on your answer sheet19 People must accept that they do not know much when firsttrying something new.20 It is important for people to actively notice when good things happen.21 Courage can be learned once its origins in a sense of responsibility are understood.22 It is possible to overcome shyness when faced with the need to speak in public.List of PeopleA Christopher PetersonB David FajgenbaumC Suzanne SegerstromD Tanya StreeterE Todd KashdanF Kenneth PedeleoseG Cynthia PuryQuestions 23-26Reading Passage 2 has eight sections, A-H.Which section contains the following information?Write the correct letter, A-H, in bo某es 23-26 on your answer sheet23 a mention of how rational thinking enabled someone to achieve physical goals24 an account of how someone overcame a sad e某perience25 a description of how someone decided to rethink their academic career path26 an e某ample of how someone risked his career out of a sense of duty3You should spend about 20 minutes on Questions 27-40, which are based on Reading Passage 3 below.When evolution runs backwardsEvolution isn’t supposed to run backwards — yet an increasing number of e某amples show that it does and that it can sometimes represent the future of a speciesThe description of any animal as an ‘evolutionary throwback’ is controversial. For the better part of a century, most biologists have been reluctant to use those words, mindful of a principle of evolution that says ‘evolution cannot run backwards’. But as moreand more e某amples come to light and modern genetics enters the scene, that principle is having to be rewritten. Not only are evolutionary throwbacks possible, they sometimes play an important role in the forward march of evolution.The technical term for an evolutionary throwback is an‘atavism’, from the Latin atavus, meaning forefather. The word has ugly connotations thanks largely to Cesare Lombroso, a 19th-century Italian medic who argued that criminals were born not made and could be identified by certain physical features that were throwbacks to a primitive, sub-human state.While Lombroso was measuring criminals, a Belgian palaeontologist called Louis Dollo was studying fossil records and coming to the opposite conclusion. In 1890 he proposed that evolution was irreversible: that ‘an organism is unabl e to return, even partially, to a previous stage already realised in the ranks of its ancestors’. Early 20th-century biologists came to a similar conclusion, though they qualified it in terms of probability, stating that there is no reason why evolution cannot run backwards — it is just very unlikely. And so the idea of irreversibility in evolution stuck and came to be known as ‘Dollo’s law’.If Dollo’s law is right, atavisms should occur only very rarely, if at all. Yet almost since the idea took root, e某ceptions have been cropping up. In 1919, for e某ample, a humpback whale with apair of leg-like appendages over a metre long, complete with a full set of limb bones, was caught off Vancouver Island in Canada. E某plorer Roy Chapman Andrews argued at the time that the whale must be a throwback to a land-living ancestor. ‘I can see no other e某planation,’ he wrote in 1921.Since then, so many other e某amples have been discovered that it no longer makes sense to say that evolution is as good as irreversible. And this poses a puzzle: how can characteristics that disappeared millions of years ago suddenly reappear? In 1994, Rudolf Raff and colleagues at Indiana University in the USA decided to use genetics to put a number on the probability of evolution going into reverse. They reasoned that while some evolutionary changes involve the loss of genes and are therefore irreversible, others may be the result of genes being switched off. If these silent genes are somehow switched back on, they argued, long-lost traits could reappear.Raff’s team went on to calculate the likelihood of it happening. Silent genes accumulate random mutations, they reasoned, eventually rendering them useless. So how long can a gene survive in a speciesif it is no longer used? The team calculated that there is a good chance of silent genes surviving for up to 6 million years in atleast a few individuals in a population, and that some might survive as long as 10 million years. In other words, throwbacks are possible, but only to the relatively recent evolutionary past.As a possible e某ample, the team pointed to the mole salamanders of Me某ico and California. Like most amphibians these begin life in a juvenile ‘tadpole’ state, then metamorphose into the adult form — e某cept for one species, the a某olotl, which famously lives its entire life as a juvenile. The simplest e某planation for this isthat the a某olotl lineage alone lost the ability to metamorphose, while others retained it. From a detailed analysis of the salamanders’ family tr ee, however, it is clear that the other lineages evolved from an ancestor that itself had lost the ability to metamorphose. In other words, metamorphosis in mole salamanders is anatavism. The salamander e某ample fits with Raff’s 10-million-year time frame.More recently, however, e某amples have been reported that break the time limit, suggesting that silent genes may not be the whole story. In a paper published last year, biologist Gunter Wagner of Yale University reported some work on the evolutionary history of a group of South American lizards called Bachia. Many of these have minuscule limbs; some look more like snakes than lizards and a few have completely lost the toes on their hind limbs. Other species, however, sport up to four toes on their hind legs. The simplest e某planation is that the toed lineages never lost their toes, but Wagner begs to differ. According to his analysis of the Bachia family tree, the toed species re-evolved toes from toeless ancestors and, what is more, digit loss and gain has occurred on more than one occasion over tens of millions of years.So what’s going on? One possibility is that these traits arelost and then simply reappear, in much the same way that similar structures can independently arise in unrelated species, such as the dorsal fins of sharks and killer whales. Another more intriguing possibility is that the genetic information needed to make toes somehow survived for tens or perhaps hundreds of millions of years in the lizards and was reactivated. These atavistic traits provided an advantage and spread through the population, effectively reversing evolution.But if silent genes degrade within 6 to 10 million years, how can long-lost traits be reactivated over longer timescales? The answer may lie in the womb. Early embryos of many species develop ancestral features. Snake embryos, for e某ample, sprout hind limb buds. Laterin development these features disappear thanks to developmental programs that say ‘lose the leg’. If for any reason this does not happen, the ancestral feature may not disappear, leading to an atavism.Questions 27-31Choose the correct letter, A, B, C or D.Write the correct letter in bo某es 27-31 on your answer sheet.27 When discussing the theory developed by Louis Dollo, thewriter says thatA it was immediately referred to as Dollo’s law.B it supported the possibility of evolutionary throwbacks.C it was modified by biologists in the early twentieth century.D it was based on many years of research.28 The humpback whale caught off Vancouver Island is mentioned because ofA the e某ceptional size of its body.B the way it e某emplifies Dollo’s law.C the amount of local controversy it caused.D the reason given for its unusual features.29 What is said about ‘silent genes’?A Their numbers vary according to species.B Raff disagreed with the use of the term.C They could lead to the re-emergence of certain characteristics.D They can have an unlimited life span.30 The writer mentions the mole salamander becauseA it e某emplifies what happens in the development of most amphibians.B it suggests that Raff’s theory is correct.C it has lost and regained more than one ability.D its ancestors have become the subject of e某tensive research.31 Which of the following does Wagner claim?A Members of the Bachia lizard family have lost and regained certain features several times.B Evidence shows that the evolution of the Bachia lizard is due to the environment.C His research into South American lizards supports Raff’s assertions.D His findings will apply to other species of South American lizards.Questions 32-36Complete each sentence with the correct ending, A-G, below.Write the correct letter, A-G, in bo某es 32-36 on your answer sheet.32 For a long time biologists rejected33 Opposing views on evolutionary throwbacks are represented by34 E某amples of evolutionary throwbacks have led to35 The shark and killer whale are mentioned to e某emplify36 One e某planation for the findings of Wagner’s research isA the question of how certain long-lost traits could reappear.B the occurrence of a particular feature in different species.C parallels drawn between behaviour and appearance.D the continued e某istence of certain genetic information.E the doubts felt about evolutionary throwbacks.F the possibility of evolution being reversible.G Dollo’s findings and the convictions held by Lombroso.Questions 37-40Do the following statements agree with the claims of the writer in Reading Passage 3?In bo某es 37-40 on your answer sheet, writeYES if the statement agrees with the claims of the writerNO if the statement contradicts the claims of the writerNOT GIVEN if it is impossible to say what the writer thinks about this37 Wagner was the first person to do research on South American lizards.38 Wagner believes that Bachia lizards with toes had toeless ancestors.39 The temporary occurrence of long-lost traits in embryos is rare.40 Evolutionary throwbacks might be caused by developmental problems in the womb.剑桥雅思阅读10原文参考译文(test4)Passage 1参考译文：加利福尼亚州的特大火灾干旱，房屋的大量扩建，易燃物的过度供给导致美国西部发生更大更热的火灾。

Reflets走遍法国--上--笔记

Reflets走遍法国--上--笔记Rｅflets走遍法国上／1【第0课】学会使用数字：0 zéro、１un/uｎｅ、2 deux、3tro ｉs、4 quatｒｅ、5cinq、6 six、7 ｓｅpｔ、8 huit、9 neｕf、10 diｘ、11 onze、12 douzｅ、１3 treize、1４qｕatorze、１5 quinze、1６seize、17dix-sｅｐt、１8 dix-huit、19 dix-ｎｅuｆ、２0 vingｔ西班牙人:eｓpagｎｏl / eｓｐagnole、希腊人：gｒｅc/ grecque、德国人:aｌleｍａnd / aｌlｅmande、法国人：fran?ａiｓ/ fran?aiｓe、中国人:chinｏis / ｃhinｏise、加拿大人:canadien /ｃanadienｎｅ、意大利人：itａlien/ italｉennｅ、日本人:ｊaponais/ japｏnaiseＳaluｔ：你好。

与ｂoｎjｏｕr不同,sａlut用于熟悉的朋友或年轻人之间,而且既可以表示“你好”，也可以表示“再见”。

动词êｔre(是）的变位：jeｓuiｓ、tu eｓ、il /ｅlｌｅeｓt、nou ｓsoｍｍes、vousêteｓ、iｌs / elｌｅs sｏnｔ词汇：à在（某个地方）、ａcｔeur,trice 演员、adressｅ地址、age年龄、agent 代理人,经纪人、ａmi,e 朋友、an 年,岁,年龄、animateur,tricｅ组织者，主持人、aｒｔiｓtｅ艺术家,艺术工作者、bonjｏur 你好,早上好【第1课】主语人称代词:一般放在谓语动词前作主语,用来指代已知的或上文已提及的人或物。

ｊe、tｕ、iｌ、eｌle、ｖous（我、你、他、她、您)都是单数主语人称代词。

一般疑问句：对整个句子提问，用oｕi和noｎ回答，提问时一般句末语调上升。

汉英段落翻译分析解析

（1） The Yu Yuan Garden in the south of Shanghai is a famous classical garden. It was originally the private garden of a man named Pan, who was once the governor of Sichuan Province during the Ming Dynasty. （2） The construction of the garden started in 1858, but it was not completed until twenty years later (because it went on and off) for lack of money.
解放以后，在人民政府的关怀下，豫园经历了多次修复。最近一次在1987年，恢复了其东西部分。 Under the care of the people’s government since liberation, Yu Yuan Garden has gone through many renovations, with the recent one carried out in 1987 to restore its eastern part. Since 1949, under the care of …, Yu Yuan Garden has gone through many renovations, the most recent of which was done in 1987 when its eastern part and western part were restored.
解放以后，在人民政府的关怀下，豫园经历了多次修复。最近一次在1987年，恢复了其东西部分。豫园在1982年被列为国务院重点保护单位，是中国南方最优秀的园林之一。园内有亭台楼阁，有池塘和假山，景点超过 40个，每天至少有一万人在园内游览。难怪人们说：“到上海不去豫园和城隍庙商场不算来过大上海。”

考研英语阅读、翻译长难句结构分析

考研英语阅读、翻译长难句结构分析一、了解句子主要成分:1. 主语、表语、宾语(1) What is harder to establish is whether the productivity revolution that businessmen assume they are presiding over is for real. (从句-----1998)商人们自认为他们领导了一场生产力革命，这场革命是否确有其事，这一点更加难以确定。

(2)The trouble is that part of the recent acceleration is due to the usual rebound that occurs at this point in a business cycle, and so is not conclusive evidence of a revival in the underlying trend. (从句-----1998)问题在于，近年发生的生产力快速增长部分是由于商业周期通常到了这时候就会出现的反弹造成的，因而它不是经济复苏潜在趋势的结论性证据。

(3) Strengthening economic growth, at the same time as winter grips the northern hemisphere, could push the price higher still in the short term. （动名词-----2002）强劲的经济增长势头，随着北半球冬季的到来，有可能在短期内使石油价格涨得更高。

(4) When a new movement in art attains a certain fashion, it is advisable to find out what its advocates are aiming at, for, however farfetched and unreasonable their principles may seem today, it is possible that in years to come they may be regarded as normal. (不定式-----2000)当一场新的艺术运动形成某种时尚时，理应弄清其倡导者的目标所在，因为无论他们的准则在今天看来是多么牵强附会、不可思议，将来都有可能被视为正常的。

lesson 9 royal espionage

Lesson 9 Royal espionage第九课王室谍报活动by BERNARD NEWMANfrom Spies in Britain9-1. Alfred the Great acted as his own spy, visiting Danish camps disguised as a minstrel.【译文】阿尔弗雷德大帝曾亲自充当间谍。

他乔装吟游歌手进入丹麦军队营地侦察。

【讲解】Alfred the Great，阿尔弗雷德大帝，古英国国王，22岁登基，为抵抗入侵的丹麦人，先后与丹麦军交战6年未能取胜，后潜匿于阿森尔尼岛，终于打败丹麦军。

visiting Danish camps disguised as a minstrel作方式状语，修饰acted。

disguised as a minstrel作方式状语，修饰visiting。

【单词和短语】disguise:假扮，化装（to change someone’s appearance so that people cannot recognize them），例如：She disguised herself as a man with a false beard.她戴上假须女扮男装。

9-2. In those days wandering minstrels were welcome everywhere.【译文】当时，浪迹四方的吟游歌手到处受欢迎。

【讲解】wandering minstrels，浪迹四方的吟游歌手。

中世纪时期，欧洲云游四方的歌手一般都身带竖琴，自弹自唱，传颂古代的历史传说。

【单词和短语】wandering：漫游的；闲逛的；流浪的（one uses wandering to describe a person who moves from place to place and has no permanent home）。

09_Flip_Flops

Module 9: Latches and Flip FlopsTo successfully complete this module you need to:•Read through all of the notes.•Do all of the problem sets.•Complete all of the labs.•Do the practice module test.•Pass the module test with a mark of at least 80%.Flip FlopsThe combinational circuits we have been dealing with so far respond only to the current inputs, they have no knowledge of previous states of the circuit. Circuits which have a memory of past states are called sequential circuits and these will be considered now. We will deal first with the SR latch and then the SR flip flop (FF).While these circuits don't look simple, they are in fact the simplest flip flips since more complex flip flips are built upon the basic SR design.SR LatchWe will consider two implementations of the SR latch, one which uses NOR gates and the other which uses NAND gates.The NOR LatchThis is the simplest of sequential logic circuits and consists of two cross-coupled NOR gates as shown in the circuit below.Notice firstly that the outputs are and which are the complement of each other, so the only two possible output states are and or and . Notice also that the outputsand are fed back to two of the inputs to the NOR gates and it is in this way that the previous output state of the circuit has an influence on the next state, that is, gives the circuit a “memory”. We will develop the truth table for this circuit by studying all possible input cases and for each of these cases looking to see whether the two possible outputs yield a stable or an unstable circuit. So all possible input cases are shown in the truth table below, and for each of these cases we will consider the two possible output states to see whether a stable circuit arises.Consider the first case, when the inputs S and R are both zero, and for this case consider the two possible output states. The circuits are as follows:Case A: ( and )The output states have been shown fed back to the NOR gate inputs and we now need to see whether this is a stable state. The NOR gate truth table is:and from this we can see that both the NOR gates are satisfying their truth table (the top gate has inputs 0 and 1 and an output of 0 which is the case of either the second or third rows of the truth table, while the lower gate has inputs both zero and an output 1 which agrees with the top row of the truth table). So as long as the inputs are and and the output is , the state ofthe circuit will remain stable. Consider now the other possible output state, with and .Case B: ( and )We have just reversed the roles of the two NOR gates and so this circuit is also stable. So as long as the inputs are and and the output is , the state of the circuit will also remainstable. This means that when , whatever the previous output state was (;or ; ), it remains the same. We indicate this in the truth table as follows:What this entry means is that the next (n+1th state) is the same as the previous state, or in other words the output does not change. So if the input states were not 0,0 but were changed to 0,0 then the output state does not change as a result of this change in the input state.Consider now the case when and (second row of inputs in truth table) for our twopossible output states.Case C: ( and )Is this circuit stable, in other words are the input and output states of the NOR gates consistent with their truth table? The top NOR gate has both inputs 1 and an output of 0 and this agrees with the bottom row of the truth table. The lower NOR gate has both inputs 0 and an output 1 and this is also consistent, agreeing with the top row of the truth table. The circuit is therefore stable in this state. Consider now the same inputs, but with the other output state.Case D: ( and )Is this circuit stable, in other words are the input and output states of the NOR gates consistent with their truth table? The top NOR gate has inputs of 0 and 1 and an output of 1 and this does not agree with the truth table. However the lower NOR gate has inputs of 0 and 1 and an output of 0 and this is consistent with the truth table. Because one of the gates is not consistent with the NOR gate truth table the circuit is un-stable in this state. The top NOR gate will therefore force its output to 0 which will change one of the inputs to the lower gate and it will be forced to have an output of 1. The circuit will then be in the stable state of the circuit of Case C. So we can conclude that whenthe inputs to the circuit are and , the outputs are forced to and and thisoperation is called a RESET.Consider now the situation when the inputs are and (Case E). Because the circuit issymmetrical (both gates are wired within the circuit the same) it is as if we have just turned the circuit upside down. In this case the stable outputs will also be swapped and will be andand this operation is called a SET. Including the Cases D and E in our truth table for the SR latch, it now looks like:The last possible input combination to consider is when , and we will consider this forthe two possible output states.Case F: ( and )Is this circuit stable, in other words are the input and output states of the NOR gates consistent with their truth table? The top NOR gate has inputs of 0 and 1 and an output of 1 and this does not agree with the truth table. The lower NOR gate has both inputs 1 and an output 0 and this is consistent with the truth table. However the circuit is therefore un-stable in this state. The top NOR gate will therefore force its output to 0 and this will change one of the inputs to the lower NOR gate with the result that its inputs are 0 and 1 and its output should be a 0 to agree with the NOR gate truth table, but a 1 to be the complement of the Q output.The circuit is therefore unstable and is not used in practice. The last case is Case G for which the inputs are the same as for case F but the outputs are reversed. Because the circuit is symmetrical (both gates are wired within the circuit the same) and the inputs are both 1, it is as if we have just turned the circuit upside down. In this case the outputs will also be unstable and is not used in practice. Including the Cases F and G in our truth table for the SR latch, it now looks like:To summarise, when the inputs are different (0 and 1) the outputs are forced to a particular state, SET () when and RESET () when . This is why the circuit is called a SR (SetReset) latch. When both inputs are 0 there is no change at the outputs, and the combination of both inputs = 1 is not used.Instead of drawing the complete SR latch circuit we have a symbolic representation as shown below:EXAMPLE 1:The timing diagram below shows the inputs to the S and R terminals of an SR latch. Also is shown the starting state of the circuit ( and ). The timing diagram, showing the outputs states, is shown below.EXAMPLE 2:The timing diagram below shows the inputs to the S and R terminals of an SR latch. Also is shown the starting state of the circuit ( and ). The timing diagram, showing the outputs states,is also shown below.The NAND LatchThis is a latch with active-low inputs so that the SET operation puts a LOW on S and the RESET operation puts a low on . There is no change when (for the NOR latch there was nochange when) and the case of inputs is not used. This sequential logiccircuit consists of two cross-coupled NAND gates as shown in the circuit below.The truth table is similar, but the inputs are active-low as mentioned earlier.The circuit symbol is the same as for the NOR latch.EXAMPLE 3:The timing diagram below shows the inputs to the S and R terminals of a NAND latch. Also is shown the starting state of the circuit ( and ). The timing diagram, showing the outputs states, is also shown.The Gated LatchWe can control when a NAND latch circuit is operating by adding a pair of extra NAND gates at the inputs. These have the effect of “turning on” the circuit and allowing the S and R inputs to take effect. The circuit is as shown below with an ENABLE (E) line:The truth table for the input circuit is shown below:Recall that the inputs to the NAND latch are active LOW, and that the input circuit keeps andhigh when the enable line E is 0 (LOW). When the enable line is HIGH, the R and S inputsare effectively transmitted to the NAND latch. So the input circuit has the following effects:•The and inputs are inverted so they become active HIGH and•The inputs are only allowed to pass through when E is high.Flip FlopsFlip flops (FF) are sequential logic circuits which are similar to the gated latch. However whereas the gated latch requires the enable line E to be SET (to 1) FFs have a clock input and there must be a transition on this input (LOW to HIGH or HIGH to LOW) for the outputs to change. Digital systems can be asynchronous or synchronous. Asynchronous circuits can change their outputs at any time whereas synchronous circuits change their outputs at specific times, set by the regular pulses of the system clock. Clocked FFs change their states only on the edge of a clock transition and this is called “edge triggering”. For the logic symbol below, the clock input is labelled CLK, the fact that the device is edge triggered is indicated by the small triangle and the bubble on this input signifies that the device triggers on a falling clock edge.If there were no bubble on the CLK input the device would be triggered by the rising edge of a clock pulse and this is called positive edge triggering.A circuit which would "enable" an RS flip flop on the rising edge of a clock pulse is as shown below.To understand how this circuit functions we must appreciate that all gates, including inverters, have a propagation delay between a change at the input(s) and any change at the output that is caused as a result. We can therefore show a timing diagram for the circuit above, as shown below:As can be seen, the enable line is only momentarily high, starting at the rising edge of the clock pulse and finishing after a time equal to the propagation delay of the inverter.There are a number of FF devices we will now consider in some detail.Clocked SR Flip Flop (SR FF)The device’s logic symbol and truth table are shown below.The S and R inputs control the state of the FF however nothing happens until there is a falling clock edge. As an example of the operation of this device, look at the timing diagram below.JK Flip Flop (JK FF)The device’s logic symbol and truth table are shown below.The J and K inputs control the state of the FF however nothing happens until there is a falling clock edge. Whereas in the SR FF the last combination of control inputs () is not allowed however in the case of the JK FF this causes the output to toggle. As an example of the operation of this device, look at the timing diagram below.D Flip Flop (D FF)The device’s logic symbol and truth table are shown below. Notice the absence of a bubble on the clock input, indicating that the FF responds to a rising clock edge.As can be seen, on the rising clock edge the signal on the data line is clocked through to the Q output. As an example of the operation of this device, look at the timing diagram below.T Flip Flop (T FF)The device’s logic symbol and truth table are shown below. Notice the absence of a bubble on the clock input, indicating that the FF responds to a rising clock edge.As can be seen, on the rising clock edge if there is no change at the output. If the output toggles (changes either from a 0 to a 1 or from a 1 to a 0). As an example of the operation of this device, look at the timing diagram below.Schmitt Trigger DevicesThis is a device with hysteresis and can be particularly useful in giving clean LOW to HIGH and HIGH to LOW transitions. For a standard inverter, as the input makes a transition the output may show some oscillations as the circuitry changes its mind about whether the input is a LOW or aHIGH. This is illustrated by the timing diagram below.A AStandard InverterA Schmitt trigger inverter is suited to slowly changing signals and as the timing diagram below illustrates, the output only goes LOW when the input exceeds the upper threshold (V T+) and only goes HIGH when the input falls below the lower threshold (V T-).A AInverting Schmitt Trigger0V 5V 0V5VAsynchronous InputsThese are high priority inputs which operate on the outputs independent of the clock. They can SET or CLEAR the FF at any time. The asynchronous set is usually called or while the asynchronous clear input is usually called or . For these asynchronous inputs to be ACTIVE LOW, there is either a bar over the name or a bubble on the line, BUT NOT BOTH. Examples of such asynchronous inputs are shown below.The truth table for the asynchronous inputs CLEAR and PRESET shown above is:VVAATimeORTiming ConsiderationsBefore proceeding to look at some circuits which use FFs we need to consider some of the timing issues associated with these devices.Setup and Hold TimesFor clocked circuits to operate satisfactorily the control inputs (S and R or J and K etc) must be held stable for a minimum period of time before and after a clock edge. The time required before the clock edge is called the setup time (t s) and the time after the clock edge is called the hold time (t h). These times are illustrated in the timing diagram below.Propagation DelaysWhen the inputs to a digital circuit change the outputs can change, however there is always a delay between the inputs changing and the outputs changing and this is known as the propagation delay t PD. Some circuits depend on these delays for their correct operation and we need to be mindful of them when analysing clocked digital circuits. Two delays are specified, one for a LOW to HIGH transition (t PDLH) and one for the HIGH to LOW transition (t PDHL). These delays are illustrated in the timing diagram below.Maximum Clock FrequencyA circuit will not continue to operate satisfactorily if the clock speed is increased too much. A maximum clock frequency is specified, below which the device should operate satisfactorily.Flip Flop ApplicationsSerial Shift RegisterThe circuit below shows how data can be loaded into a serial shift register one bit at a time. This is a 4 bit register and so it would take four clock cycles to load a 4-bit number into the register.The timing diagram for this circuit (loading four 1s) is as follows:Notice how each JK flip flop transfers the“old”output from the previous FF because the propagation delay prevents them from seeing the “new” output because all FFs are clocked at the same time, or synchronously.EXAMPLE 4:For the serial shift register circuit above, draw the timing diagram as the 4-bit binary word 1011 is loaded.Parallel Shift RegisterThe circuit below shows how all data bits can be loaded from the parallel B inputs into the parallel Q register. This is a 4 bit register but it only takes one clock cycle to load the 4-bit number into the register.If the signal is inactive, the previously loaded data on Q3 – Q0 is always available no matter what is happening on the input lines B3 – B0. The advantage of this circuit is that while new inputs may present themselves at different times, they can be loaded synchronously to the output lines when the LOAD line is pulled LOW.Flip Flops Used in CountersIt will be seen in the following circuit that a FF operating in toggle mode is acting as a divide by two circuit and so frequency dividers and counters can be constructed from FFs in this mode.A 3-bit binary UP counterNotice that the JK control inputs are all tied to 5 V olts, which puts each of the FFs into toggle mode.EXAMPLE 5:For the 3-bit binary UP counter circuit above, draw the timing diagram for 10 clock cycles.EXAMPLE 6:For the 3-bit binary DOWN counter circuit below, draw the timing diagram for 10 clock cycles.DIGITAL ARITHMETICBinary Addition and SubtractionComputers use modified addition to perform subtraction and mulitiplication.Binary addition proceeds in the same manner as does decimal addition as is shown by the example below. The carries are shown is boxes.+1101100011 001000001011 1111100100EXAMPLE 7:Perform the binary addition below.+1100100111 00011101111101111 1110000010Signed NumbersIt is not easy to represent a + or – sign with a digital circuit and so an alternative is to use the MSBof a number to indicate whether it is positive or negative. The MSB is then the sign bit and the remainder of the number represents the magnitude. So for example, using a 0 to represent a positive number and a 1 to represent a negative number we could have the following:0 1001101 represents a positive number (MSB 0) of magnitude 10011012 = + 7710. Similarly:1 1001101 represents a negative number (MSB 1) of magnitude 10011012 = - 7710.The problem with using a system such as this is that the digital electronic circuits required to implement such a scheme are more complex than they need to be. For this reason we represent negative numbers using the 2’s-complement system.2’s-complement formFirstly, look at the 1’s complement of a binary number, which is formed by toggling all the bits in the number. For the 6-bit binary number 0001102(decimal 6) the 1’s complement is found by toggling all the bits:0001101's complement111001(all 1s to 0, all 0s to 1)So we say that the 1’s complement of 0001102 is 1110012. Then the 2’s complement of a binary number is found by adding 1 to the 1’s complement of that number. So for the example we used above, the 2’s complement of 0001102 is given by:000110 21's complement11100 1 2plus 1+ 1 1 22's complement111010 2The leading 1 means that the 6-bit number is negative and this bit contributes -25 = -3210 to the final result. The remaining bits sum to 2610, so the 2’s complement representation represents:-3210+2610 = -610.So taking the 2’s complement of the binary number representing + 610has yielded -610in 2’s complement notation.It is very important to note that we must be clear about how many bits we are working with. For example, if we are working with 6 bits, then 710 in binary is 0001112 which we would complement to form 1110002, however if we are working with 8 bits, then 710 would be represented as 000001112 which has a 1s complement of 111110002!So what are the limits to the numbers which can be represented in2’s complement form? Considering an n-bit number, the largest positive number we can represent will have a leading 0 followed by all 1’s. For example for 6 bits this number would look like:0111112 = 20 + 21 + 22 + 23 + 24 = 1 + 2 + 4 + 8 + 16 = 31 = 25-1.The largest negative number we can represent would have a leading 1 (to indicate it is negative) followed by all 0s. Again for a 6 bit number this would be:1000002 = - 25.More generally, the largest positive number which can be represented in n-bit 2’s complement notation is given by:2n-1 -1and the largest negative number which can be represented in n-bit 2’s complement notation is given by - 2n-1.As an example, represent the decimal number -2310in 2’s complement form using the minimum number of bits. The table below shows the minimum and maximum numbers (in decimal form) which can be represented in n-bit 2’s complement notation for n between 2 and 10.So to represent -2310 we need at least 6 bits.+2310 in 6-bit binary is:0101112and so the2’s complement of this binary number will represent - 2310.Taking the 2’s complement of 010111:01011 1 2101000 2+ 1 2101001 2Therefore our answer is:101001.Check: In 2’s complement notation:1010012 = -2510 + 10012 = -3210 + 910 = - 2310 as required.Would there have been any problem had we done all calculations using 8 bits instead of 6? Check this, and the 8-bit representation of +2310 is:000101112 and so the 2’s complement of this binary number should represent -2310.Taking the 2’s complement of 00010111:0001011 1 211101000 2+ 1 211101001 2Therefore our answer is:11101001.Check: In 2’s complement notation:111010012 = -2710 + 11010012 = -12810 + 10510 = - 2310 as required.EXAMPLE 8:Represent the number -7910 in 2’s complement notation using an 8-bit representation. + 7910 in 8-bit binary is given by 010011112.Taking the 2’s complement of 01001111:0100111 1 210110000 2+ 1 210110001 2Therefore our answer is:10110001.Check: In 2’s complement notation:101100012 = -2710 + 01100012= -12810 + 4910 = - 7910 as required.Addition and Subtraction Using Signed Binary NotationAdditionEach number must have the same number of bits and any carry in the result is discarded. The result will then be either:1. Correct2. Incorrect and +25610 larger than it should be or3. Incorrect and +25610 smaller than it should be.EXAMPLE 9:Add the two 8-bit signed binary numbers 011011112 (11110) and 001000002 (3210) together.+01101111 2 010******* 2 10001111 2This answer should be 11110 + 3210 = 14310. However the answer (remembering that it is in 8-bit signed binary form) is:.This is exactly 25610 less than it should be.Binary SubtractionIf we wish to calculate A – B we first find the 2’s complement of B (which is the negative of B) and then add it to A. We discard any carry which results from these operations.EXAMPLE 10:Using 8-bit signed binary notation, subtract 001000002 (3210) from 011011112 (11110). Confirm that the answer is 7910.Taking the 2’s complement of 001000002:00100000 2+1101111 1 2111111 211100000 2Add to 011011112 to give:+11100000 20111101111 2111111 2Discarding the carry we can see that this is the correct result.Binary MultiplicationThis proceeds in a way which is very similar to decimal multiplication. As an example, multiply 111001002 ( 22810) by 00001010 (1010). Confirm that the result is correct (228010).11100100 200001010 2+0000000111001000000000011111001001111100 2This binary number is in fact 228010.Arithmetic Circuits Half AdderThe 2-bit half adder circuit looks like:The truth table for this circuit is:CarryFull AdderWhile the half-adder can only add two bits together the full-adder can add together two words. Addition of the LSBs can result in a carry in, and addition of the next two bits (with the carry in) can lead to a carry out. The full-adder can manage these operations. A circuit which is capable of this operation is shown below.Counters and RegistersAsynchronous Ripple CountersAsynchronous DOWN and UP counters were introduced earlier. The figure below shows a 3-bit binary UP counter implemented using T FFs. The left most FF is changing its state most frequently and so the output is the LSB of the counter.We can draw the timing diagram for this circuit as follows.Notice that each flip flop divides the frequency by a factor of two.A state transition diagram shows us how the counter goes from state to state and an example from the circuit above is shown below.This counter has 8 possible states and it uses all of them. For such a simple counter when all states are being used we say the MODULUS of the counter is 2n where n is the number of FFs. In this case there are 3 FFs and so 8 states, as we have observed. However if we wish to design a counter with less states we will need some additional circuitry. One way to reduce the number of states is to detect a particular state and reset the counter.The NAND gate detects the two MSBs going high (as the circuit starts to enter the 110 state) and clears all FFs to 0. There will actually be a glitch in the timing diagram since the FFs have to start entering the 110 state momentarily before the conditions have been established to fire the NAND gate a clear all FFs. Our state diagram for this circuit is shown below. Notice that all possible states of the circuit are still shown, even though they are now not part of the normal count sequence.Notice also that the FFs do not change state at the same time, because there are propagation delays at each stage. Returning to the asynchronous ripple counter on page 28 and its timing diagram on page 29, if we look carefully at the transition from 111 to 000 we would see:If we look carefully at the transitions taking place as we go from 111 to 000 we see the following sequence:111110100000Including this set of transitions in a state diagram we have:If we wish to avoid these unwanted intermediate states we may need to add additional circuitry.Decoding Counter OutputsCounters can be used as timers and as such we need a means of detecting when a certain count has been reached. A decoding circuit does just this, generating an output when a certain count is detected. For a 4-bit counter there are 16 states, each one of which is different to the others. It is possible to therefore detect any one of the 16 states.EXAMPLE 11:Develop a circuit to decode the 5th count of a MOD 16 UP counter.The 5th state is 01012 and so a suitable circuit could look like:Decoding AddressesWe may wish to select a particular address on a 16 bit address bus from all the possible addresses.A similar circuit as that shown above can be used for this task.EXAMPLE 12:Develop a circuit to decode the address 4590510 from a 16-bit address bus.First we need to convert 4590510 to binary. We can use repeated division as follows:22952 remainder of122952 ÷ 2 11476 remainder of011476 ÷ 2 5738 remainder of05738 ÷ 2 2869 remainder of02869 ÷ 2 1434 remainder of11434 ÷ 2 717 remainder of0717 ÷ 2 358 remainder of 1358 ÷ 2 179 remainder of0179 ÷ 2 89 remainder of189 ÷ 2 44 remainder of144 ÷ 2 22 remainder of022 ÷ 2 11 remainder of011 ÷ 2 5 remainder of15 ÷ 2 2 remainder of12 ÷ 2 1 remainder of01 ÷2 0 remainder of1The binary equivalent of 4590510is therefore 10110011010100012. A circuit which decodes this address is therefore as shown below. Notice that all 16 inputs to the NAND gate are set to one, the only condition which will create a zero at the NAND gate output.Some Medium Scale Integrated Circuit DevicesEncodersThis device takes any one of a number of possible inputs and outputs a code to represent that input.A generalised structure for an encoder is:Note that:.DecodersInputs N-bits of coded data and activates one of M outputs. A generalised decoder is shown below.MultiplexersThese devices select one of a number of input lines and put the data on that line through to the output. These are also called MUXs and can be thought of as a digital multi-position switch. A generalised MUX is shown below.The control inputs , and determine which input will be passed to the output.DemultiplexerA demultiplexer (DEMUX) takes a single input and distributes is to one of several outputs. A generalised DEMUX is shown below. The control inputs , and determine to which outputthe input is passed.MODULE 9 PRACTICE TEST1.The timing diagram below shows the inputs to the and terminals of an SR latch. Alsoshown is the starting state of the circuit ( and ). Complete the and outputsfor the timing diagram.plete the truth table for the circuit below, showing all possible combinations of and, and and the role of each combination.。

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• 这两种形式的城市再发展都是以改善旧城居住条件的名义，运用政府职权和公共补贴去帮助大规模的私人或准私人投资项目。
• It finds that both programs use government authority and subsidies to make large-scale private or quasi-private investment attractive in the name of ameliorating living conditions．
• 将Logan与Molotch的“成长联盟”理论谨慎地应用于中国，作者认为在中国经济的疏散化进程中“成长机器”就已经形成。
• Cautiously applying Logan and Molotch’s “growth coalition” concept to China, the authors assert that a “growth machine” has formed during China’s economic decentralization processes.
Introduction 引言
引用新颖观点，补充论点
Growthing Meachine in the Making in achina
“成长机器”在中国的使用
呼应文章开头，体现整体性，概括全文，突出中心
Conclusion 结论
摘要
Abstract
对论文内容的简短陈述，提示论文的主要观点、见解、论据或概括地简单介绍论文的主要内容
2、引言：鲜明地提出观点，提出所研究的问题的背景.概述研究的动机、目的、意义与方法。文字要简洁、明确、具体,使人看到引言就知道本文的意义所在。
论证：详细阐述问题,证明作者所提出的论点。这部分要主次分明,段落衔接自如,结构上较多地采用总分并列法、层次法和对比法。
结论：归纳论点，清晰强调研究结果。措词严谨，文字简洁。
相似性 Similarities
采用对比法，利用分论点支撑文章主题
差异性 Difference
采用对比法，利用分论点支撑文章主题
优点(Advantages)：
1、基本结构清晰：按照提出问题（引论）、分析问题（本论）和解决问题（结论）来论证全文，再采用并列展开的模式进行阐述，丛不同角度分析问题后进行归纳总结。
Is History Repeating Itself ?
From Urban Renewal in the United States to Inner-City Redevelopment in China
Group 9:肖月3150400 方雪雯 3150406 席梦涵3150399 尹小萌3150401
• 尽管两者很类似，但是美国的城市更新是由地方政府和商业开发投资者共同合作去振兴衰败的城市中心地带，相比较而言，中国的旧城改造是由新兴的地方精英所推动的，他们通过旧城改造项目在蓬勃发展的房地产市场中追逐经济的快速增长。
• Despite the similarities，America’s urban renewal was an program in which the local government and downtown business interests cooperated to boost declining inner—cities that were competing with burgeoning suburbs．In contrast，China’S redevelopment has been propelled by emer ginglocal elitesusingdecentralized statepowerto pursue fast growth in rising real estate markets．
早期的城市更新，主要针对贫民窟和颓废区进行住宅改造行动，但多为清除式的手法
波士顿芬纽市政厅周围集市
摘要
• 本文主要对美国1950--1960年的“城市更新”与中国20世纪80年代后期开始的“旧城改造”进行了比较研究。
• This study compares urban renewal in the United states in the 1950s and 1960s with inner-city redevelopment in China since the late 1980s.
目录
• 文章大意 • 摘要 • 背景 • 研究方法 • 文章结构评价 • 文章内容评价 • 创新点
肖月 3150400
方雪雯3150406 席梦涵3150399 尹小萌3150401
文章大意
• 本文提出了美国“城市更新”和中国 “旧城改造”的本质，表现了该运动只存在于表面，没有真正实质上提高全体居民的生活水平，形成了政府与企业之间的“政治联盟”。同时作者分析了两国的相似点以及不同所在。美国的城市更新是不成功的，中国正在重蹈覆辙。该文章分析情况的现状，作者提出了自己的看法，提出了改善情况的可能性。
背景ห้องสมุดไป่ตู้
• 从1978年开始，中国大胆地踏上了由计划经济到市场经济转变的旅程。从那时起，大规模的城市内部改造项目开始于改造旧城区居民住宅条件和启动旧城区的现代化进程。
• 这种涉及大规模清除活动的政府运作项目，与之相似的还有美国1950-1960 年通过清除贫民窟来提供更多更好的住房，来振兴日趋枯萎的城市中心地区的“城市更新计划”。本文通过比较这两者的异同来分析出两国的收益效果和社会反响。
研究方法
对比研究
作者从各个方面比较了美国城市更新与当代中国的“旧城改造”之间的相似点与不同之处。
举例论证
结合美国50年代城市更新的实例分析中国当代旧城改造的利弊。
引用资料
通过引用罗奇 (Molotch)的理论来解释土地和建筑物被作为商品处理的原因。
文章结构
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