Probabilistic and fractal aspects of Levy trees
a r X i v :m a t h /0501079v 1 [m a t h .P R ] 6 J a n 2005PROBABILISTIC AND FRACTAL ASPECTS OF LEVY TREES by Thomas Duquesne,Universit′e Paris 11,Math′e matiques,91405Orsay Cedex,France and Jean-Fran?c ois Le Gall D.M.A.,Ecole normale sup′e rieure,45rue d’Ulm,75005Paris,France February 1,2008Abstract We investigate the random continuous trees called L′e vy trees,which are obtained as scaling limits of discrete Galton-Watson trees.We give a mathematically precise de?nition of these random trees as random variables taking values in the set of equivalence classes of compact rooted R -trees,which is equipped with the Gromov-Hausdor?distance.To construct L′e vy trees,we make use of the coding by the height process which was studied in detail in previous work.We then investigate various probabilistic properties of L′e vy trees.In particular we establish a branching property analogous to the well-known property for Galton-Watson trees:Conditionally given the tree below level a ,the subtrees originating from that level are distributed as the atoms of a Poisson point measure whose intensity involves a local time measure supported on the vertices at distance a from the root.We study regularity properties of local times in the space variable,and prove that the support of local time is the full level set,except for certain exceptional values of a corresponding to local extinctions.We also compute several fractal dimensions of L′e vy trees,including Hausdor?and packing dimensions,in terms of lower and upper indices for the branching mechanism function ψwhich characterizes the distribution of the tree.We ?nally discuss
some applications to super-Brownian motion with a general branching mechanism.1Introduction.
This work is devoted to the study of various properties of the so-called L′e vy trees,which are continuous analogues of the discrete Galton-Watson trees.Our main contributions to the probabilistic analysis of L′e vy trees include the construction of local time measures supported on level sets of the tree,the use of these local times to formulate and establish a branching property analogous to a well-known result in the discrete setting,and the proof of a “subtree”decomposition along the ancestral line of a typical vertex in the tree.Additionally,we study the fractal properties of L′e vy trees and compute their Hausdor?and packing dimensions as well as that of particular subsets such as level sets,under broad assumptions on the branching mechanism characterizing the tree.
One major originality of the present article compared to our previous work [9],[20],[21]is to view L′e vy trees as random variables taking values in the space of compact rooted R -trees.
The precise de?nition of an R-tree is recalled in https://www.wendangku.net/doc/ae13115340.html,rmally an R-tree is a metric space(T,d)such that for any two pointsσandσ′in T there is a unique arc with endpointsσandσ′and furthermore this arc is isometric to a compact interval of the real line.A rooted R-tree is an R-tree with a distinguished vertex called the root.We write h(T) for the height of T,that is the maximal distance from the root to a vertex in T.Say that two rooted R-trees are equivalent if there is a root-preserving isometry that maps one onto the other.It was noted in[13]that the set of equivalence classes of compact rooted R-trees, equipped with the Gromov-Hausdor?distance[15]is a Polish space.
The study of R-trees has been motivated by algebraic and geometric purposes.See in particular[26]and the survey[6].One of our goals is to initiate a probabilistic theory of R-trees,by starting with the fundamental case of L′e vy trees.See[13]for another probabilistic application of R-trees.We also mention the recent article[3],which discusses a di?erent class of continuum random trees obtained as weak limits of birthday trees(instead of the Galton-Watson trees considered here),using ideas related to the present work.
To motivate our de?nition of L′e vy trees,let us describe a simple approximation result, which is a special case of Theorem4.1below.Letμbe a probability measure on Z+,with μ(1)<1.Assume thatμhas mean one and is in the domain of attraction of a stable distribution with indexγ∈(1,2].Whenγ=2,this holds as soon asμhas?nite variance, and whenγ∈(1,2),it is enough to assume thatμ(k)～c k?1?γas k→∞.Denote byθa Galton-Watson tree with o?spring distributionμ,which describes the genealogy of a(discrete-time)Galton-Watson branching process with o?spring distributionμstarted initially with one ancestor.We can viewθas a(random)?nite graph and equip it with the natural graph distance.If r>0,the scaled tree rθis obviously de?ned by requiring the distance between two neighboring vertices to be r instead of1.Also let h(θ)stand for the maximal generation inθ.Then there is aσ-?nite measureΘ(d T)on the space of(equivalence classes of)rooted compact R-trees such that for every a>0,the conditional law of the scaled tree n?1θknowing that h(θ)≥an converges as n→∞to the probability measureΘ(d T|h(T)≥a),in the sense of weak convergence for the Gromov-Hausdor?distance on pointed metric spaces.
In a sense,the preceding result is not really new:See[2],[8]and especially Chapter2of [9]for related limit theorems with a di?erent formalism.Still we believe that the formalism of R-trees is useful both to formulate such results and to analyse the limiting objects as we do in the present work.
Let us turn to a more precise description of the class of random trees that will be con-sidered here.A L′e vy tree can be interpreted as the genealogical tree of a continuous-state branching process,whose law is characterized by a real functionψde?ned on[0,∞),which is called the branching mechanism.Here we restrict our attention to the critical or subcritical case whereψis nonnegative and of the form
ψ(λ)=αλ+βλ2+ (0,∞)π(dr)(e?λr?1+λr),λ≥0,
whereα,β≥0andπis aσ-?nite measure on(0,∞)such that (0,∞)π(dr)(r∧r2)<∞.We assume throughout this work the condition
∞1du
are the quadratic branching caseψ(λ)=cλ2and the stable caseψ(λ)=cλγ,1<γ<2, which both arise in the discrete approximation described above.
The precise de?nition of theψ-L′e vy tree then depends on the height process introduced by Le Gall and Le Jan[20](see also Chapter1of[9])in view of coding the genealogy of general continuous-state branching processes.The height process is obtained as a functional of the spectrally positive L′e vy process X with Laplace exponentψ.An important role is played by the excursion measure N of X above its minimum process.In the quadratic branching caseψ(u)=c u2,X is a(scaled)Brownian motion,the height process H is a re?ected Brownian motion and the“law”of H under N is just the It?o measure of positive excursions of linear Brownian motion:This is related to the fact that the contour process of Aldous’Continuum Random Tree is given by a normalized Brownian excursion(see[1]and[2]),or to the Brownian snake construction of superprocesses with quadratic branching mechanism (see e.g.[19]).In our more general setting,the height process can be de?ned informally as follows.For every t≥0,H t measures the size of the set{s≤t:X s=inf[s,t]X r}.A precise de?nition of H t is recalled in Section3below.Under our assumptions,the process H has a continuous modi?cation.
The claim is now that the sample path of H under N codes a random continuous tree called theψ-L′e vy tree.The precise meaning of the coding is explained in Section2in a deterministic setting,but let us immediately outline the construction of the tree.We write ζfor the duration of the excursion under N and de?ne a random function d H on[0,ζ]2by setting
d H(s,t)=H s+H t?2m H(s,t),
where we have set m H(s,t)=inf s∧t≤r≤s∨t H r.We introduce an associated equivalence rela-tion by setting s～H t if and only if d H(s,t)=0.In particular,0～Hζ.The function d H obviously extends to the quotient set T H:=[0,ζ]/～H and de?nes a distance on this set. It is not hard to verify that(T H,d H)is a compact R-tree,and its root is by de?nition the equivalence class https://www.wendangku.net/doc/ae13115340.html,rmally,each real number s∈[0,ζ]corresponds to a vertex at level H s in the tree,and d H(s,t)is the distance between vertices corresponding to s and t(in particular s and t correspond to the same vertex if and only if d H(s,t)=0).The quantity m H(s,t)can be interpreted as the generation of the most recent common ancestor to s and t.
The law of the L′e vy tree is by de?nition the distributionΘ(d T)of the compact rooted R-tree(T H,d H)under the measure N.Notice that N is an in?nite measure,and so isΘ. However,for every a>0,v(a):=Θ(h(T)>a)<∞,and more precisely v(a)is determined by the equation ∞v(a)du
on?a,the point measure i∈Iδ(σi,T(i))
is Poisson with intensity?a(dσ)Θ(d T)(see Theorem4.2for a slightly more precise result
stating that this point measure is also independent of the part of the tree“below level a”).
Up to some point,the branching property follows from a result of[9](Proposition1.3.1or
Proposition4.2.3)showing that excursions of the height process above level a are distributed
as the atoms of a Poisson point measure whose intensity is(a random multiple of)the law of
H under N.In this form,the branching property has been recently used by Miermont[25]
to investigate self-similar fragmentations of the stable tree.
Using the branching property,we investigate the regularity properties of local times.We
show that the mapping a?→?a has a c`a dl`a g modi?cation and that,except for a countable set of values of a(corresponding to local extinctions of the tree)the support of?a is the full
level set T(a).This is used in Section6to extend to superprocesses with a general branching
mechanism a continuity property of the support process that had been derived by Perkins
[28]in the quadratic case.
In the?nal part of Section4we prove a Palm-like decomposition of the tree along the
ancestor line of a typical vertex at level a(Theorem4.5).This decomposition plays an
important role in Section5.We use it in Section4to analyse the multiplicity of vertices of the
tree.By de?nition,the multiplicity n(σ)ofσ∈T is the number of connected components of
T\{σ}.We prove thatΘa.e.n(σ)takes values in the set{1,2,3,∞}.We also characterize
the branching mechanism functionsψfor which there exist binary(n(σ)=3)or in?nite
(n(σ)=∞)branching points.We then observe that in?nite branching points are related to discontinuities of local times:Precisely,for any level b such that the mapping a?→?a is
discontinuous at b,there is a(unique)in?nite branching pointσb such that?b=?b?+λbδσ
b for someλb>0.As a last application of our Palm decomposition,we prove an invariance
property of the measureΘunder uniform re-rooting(Proposition4.8).
Section5is mostly devoted to the computation of the Hausdor?and packing dimensions of
various subsets of T.For any subset A of T,we denote by dim h(A)the Hausdor?dimension
of A and by dim p(A)its packing dimension.Following[14],Section3.1,we also consider the
lower and upper box counting dimensions of A:
dim
log(1/δ),
log(1/δ)
,
where N(A,δ)is the minimal number of open balls with radiusδthat are necessary to cover A.In order to state our main results,we need to introduce the lower and upper indices ofψat in?nity:
γ=sup{a≥0:lim
λ→∞λ?aψ(λ)=+∞},η=inf{a≥0:lim
λ→∞
λ?aψ(λ)=0}.
Note that1≤γ≤ηand thatη=γifψis regularly varying at in?nity.Let E be a nonempty compact subset of the interval(0,∞)and assume that E is regular in the sense that its Hausdor?and upper box counting dimensions coincide:dim h(E)=
dim obviously refer to the usual metric on the real line).Set a=sup E and
T(E)= l∈E T(l).
Theorem5.5asserts that under the assumptionγ>1,we haveΘ-a.e.on{h(T)>a},
dim
η?1and
γ?1
.
In particular,we haveΘ-a.e.
dim h(T)=η
γ?1
and,Θ-a.e.on{h(T)>a},
dim h(T(a))=1
γ?1
.
Note that in the stable branching caseψ(u)=uγ,the Hausdor?dimension of T has been computed by Haas and Miermont[16]independently of the present work.
The proofs rely on the classical results linking upper and lower densities of a measure with the Hausdor?and packing dimensions of its support.Another useful ingredient is the following estimate for covering numbers of T(Proposition5.2).We haveΘ-a.e.for all su?ciently smallδ,
v(2δ)
δ
ζ.
In Section6,we give an application of Theorem5.5to the range of a superprocess Z= (Z l,l≥0)with branching mechanismψ,whose spatial motion is standard Brownian motion in R k.To this end,we introduce the notion of a spatial tree,which allows us to combine the genealogical structure of T with independent spatial Brownian motions.Of course, this is more or less equivalent to the L′e vy snake approach of[21]and Chapter4of[9]. Still the formalism of R-trees makes this construction more tractable and more e?cient for applications.Roughly speaking,spatial trees allow us to express the superprocess Z in terms of the occupation measure of a Gaussian process indexed by T.It is therefore possible to use soft arguments to lift fractal properties of the index set T to the range of Z.We prove the following result(Theorem6.3).Let E?(0,∞)and a=sup E be as above.Denote by R E the range of Z over the time set E,de?ned by
R E=
η?1 ∧k.(1) In the quadratic branching case,this result was obtained earlier by Tribe[30](see also Serlet [29]).For more general superprocesses,closely related results can be found in Theorem 2.1of Delmas[7],whose proof depends on a subordination method which requires certain restrictions on the branching mechanism functionψ.See Dawson[4]for more references and results in the stable branching case.
This paper is intended to be as self-contained as possible.However,it is clear that many of our results depend on properties of the height process H that were derived in the monograph
[9].For the reader’s convenience,we have recalled most of the needed results in Section3 below.
The paper is organized as follows.Section2explains the coding of trees by continuous functions in a deterministic setting,and also includes a brief discussion of the convergence of trees in the Gromov-Hausdor?metric.Section3recalls the basic facts about the height process and establishes an important preliminary result that is needed for the ancestral line decomposition of subsection4.3.Section4is the core of this paper.It?rst contains the precise de?nition of the L′e vy tree as the tree coded by the excursion of H under N,in the framework of Section2.This de?nition is justi?ed by limit theorems relating discrete and continuous trees.Section4then presents the basic probabilitic properties of L′e vy trees, in particular the branching property,the existence and regularity of local times and the decomposition along an ancestral line.Fractal properties of L′e vy trees are studied in Section 5.Finally,Section6discusses applications to superprocesses.
2Deterministic trees
2.1The R-tree coded by a continuous function
We start with a basic de?nition(see e.g.[6]).
De?nition2.1A metric space(T,d)is an R-tree if the following two properties hold for everyσ1,σ2∈T.
(i)There is a unique isometric map fσ
1,σ2from[0,d(σ1,σ2)]into T such that fσ
1,σ2
(0)=σ1
and fσ
1,σ2
(d(σ1,σ2))=σ2.
(ii)If q is a continuous injective map from[0,1]into T,such that q(0)=σ1and q(1)=σ2, we have
q([0,1])=fσ
1,σ2
([0,d(σ1,σ2)]).
A rooted R-tree is an R-tree(T,d)with a distinguished vertexρ=ρ(T)called the root.
In what follows,R-trees will always be rooted,even if this is not mentioned explicitly.
Let us consider a rooted R-tree(T,d).The range of the mapping fσ
1,σ2in(i)is denoted
by[[σ1,σ2]](this is the line segment betweenσ1andσ2in the tree).In particular,for every σ∈T,[[ρ,σ]]is the path going from the root toσ,which we will interpret as the ancestral line of vertexσ.More precisely we de?ne a partial order on the tree by settingσ σ′(σis an ancestor ofσ′)if and only ifσ∈[[ρ,σ′]].
Ifσ,σ′∈T,there is a uniqueη∈T such that[[ρ,σ]]∩[[ρ,σ′]]=[[ρ,η]].We writeη=σ∧σ′and callηthe most recent common ancestor toσandσ′.
By de?nition,the multiplicity of a vertexσ∈T is the number of connected components of T\{σ}.Vertices of T\{ρ}which have multiplicity1are called leaves.
Our main goal in this section is to describe a method for constructing R-trees,which is particularly well-suited to our forthcoming applications to random trees.We consider a (deterministic)continuous function g:[0,∞)?→[0,∞)with compact support and such that
g(0)=0.To avoid trivialities,we will also assume that g is not identically zero.For every s,t≥0,we set
g(r),
m g(s,t)=inf
r∈[s∧t,s∨t]
and
d g(s,t)=g(s)+g(t)?2m g(s,t).
Clearly d g(s,t)=d g(t,s)and it is also easy to verify the triangle inequality
d g(s,u)≤d g(s,t)+d g(t,u)
for every s,t,u≥0.We then introduce the equivalence relation s～t i?d g(s,t)=0(or equivalently i?g(s)=g(t)=m g(s,t)).Let T g be the quotient space
T g=[0,∞)/～.
Obviously the function d g induces a distance on T g,and we keep the notation d g for this distance.We denote by p g:[0,∞)?→T g the canonical projection.Clearly p g is continuous (when[0,∞)is equipped with the Euclidean metric and T g with the metric d g).
Theorem2.1The metric space(T g,d g)is an R-tree.
We will view(T g,d g)as a rooted R-tree with rootρ=p g(0).Ifζ>0is the supremum of the support of g,we have p g(t)=ρfor every t≥ζ.In particular,T g=p g([0,ζ])is compact. We will call T g the R-tree coded by g.
Before proceeding to the proof of the theorem,we state and prove the following root change lemma.
Lemma2.2Let s0∈[0,ζ).For any real r≥0,denote by
r is an integer multiple ofζ.Set
g′(s)=g(s0)+g(s0+s),
for every s∈[0,ζ],and g′(s)=0for s>ζ.Then,the function g′is continuous with compact support and satis?es g′(0)=0,so that we can de?ne the metric space(T g′,d g′).Furthermore, for every s,t∈[0,ζ],we have
d g′(s,t)=d g(s0+t)(2) and ther
e exists a unique isometry R from T g′onto T g such that,for every s∈[0,ζ],
R(p g′(s))=p g(
It follows that
d g′(s,t)=g′(s)+g′(t)?2m g′(s,t)
=g(s0+s)?2m g(s0,s0+s)+g(s0+t)?2m g(s0,s0+t)
?2(m g(s0+s,s0+t)?2m g(s0,s0+s))
=g(s0+s)+g(s0+t)?2m g(s0+s,s0+t)
=d g(s0+s,s0+t).
If m g(s0+s,s0+t) m g′(s,t)=g(s0)?m g(s0,s0+s), and d g′(s,t)=g(s0+s)?2m g(s0,s0+s)+g(s0+t)?2m g(s0,s0+t)+2m g(s0,s0+s) =d g(s0+s,s0+t). The other cases are treated in a similar way and are left to the reader. By(2),if s,t∈[0,ζ]are such that d g′(s,t)=0,we have d g(s0+t)=0so that p g(s0+t).Noting that T g′=p g′([0,ζ])(the supremum of the support of g′is less than or equal toζ),we can de?ne R in a unique way by the relation(3).From(2),R is an isometry,and it is also immediate that R takes T g′onto T g. Proof of Theorem2.1.Let us start with some preliminaries.Forσ,σ′∈T g,we setσ σ′if and only if d g(σ,σ′)=d g(ρ,σ′)?d g(ρ,σ).Ifσ=p g(s)andσ′=p g(t),it follows from our de?nitions thatσ σ′i?m g(s,t)=g(s).It is immediate to verify that this de?nes a partial order on T g. For anyσ0,σ∈T g,we set [[σ0,σ]]={σ′∈T g:d g(σ0,σ)=d g(σ0,σ′)+d g(σ′,σ)}. Ifσ=p g(s)andσ′=p g(t),then it is easy to verify that[[ρ,σ]]∩[[ρ,σ′]]=[[ρ,γ]],where γ=p g(r),if r is any time which achieves the minimum of g between s and t.We then put γ=σ∧σ′. We set T g[σ]:={σ′∈T g:σ σ′}.If T g[σ]={σ}andσ=ρ,then T g\T g[σ]and T g[σ]\{σ} are two nonempty disjoint open sets.To see that T g\T g[σ]is open,let s be such that p g(s)=σand note that T g[σ]is the image under p g of the compact set{u∈[0,ζ]:m g(s,u)=g(s)}. The set T g[σ]\{σ}is open because ifσ′∈T g[σ]andσ′=σ,it easily follows from our de?nitions that the open ball centered atσ′with radius d g(σ,σ′)is contained in T g[σ]\{σ}. We now prove property(i)of the de?nition of an R-tree.By using Lemma2.2with s0 such that p g(s0)=σ1,we may assume thatσ1=ρ=p g(0).Ifσ∈T g is?xed,we have to prove that there exists a unique isometry f from[0,d g(ρ,σ)]into T g such that f(0)=ρand f(d g(ρ,σ))=σ.Let s∈p?1g({σ}),so that g(s)=d g(ρ,σ).Then,for every a∈[0,d g(ρ,σ)], we set w(a)=inf{r∈[0,s]:m g(r,s)=a}. Note that g(w(a))=a.We put f(a)=p g(w(a)).We have f(0)=ρand f(d g(ρ,σ))=σ, the latter because m g(w(g(s)),s)=g(s)implies p g(w(g(s)))=p g(s)=σ.It is also easy to verify that f is an isometry:If a,b∈[0,d g(ρ,σ)]with a≤b,it is immediate that m g(w(a),w(b))=a,and so d g(f(a),f(b))=g(w(a))+g(w(b))?2a=b?a. To get uniqueness,suppose that?f is an isometry satisfying the property in(i).Then,if a∈[0,d g(ρ,σ)], d g(?f(a),σ)=d g(ρ,σ)?a=d g(ρ,σ)?d g(ρ,?f(a)). Therefore,?f(a) σ.Recall thatσ=p g(s),and choose t such that p g(t)=?f(a).Note that g(t)=d g(ρ,p g(t))=a.Since?f(a) σwe have g(t)=m g(t,s).On the other hand,we also know that a=g(w(a))=m g(w(a),s).It follows that we have a=g(t)=g(w(a))= m g(w(a),t)and thus d g(t,w(a))=0,so that?f(a)=p g(t)=p g(w(a))=f(a).This completes the proof of(i). As a by-product of the preceding argument,we see that f([0,d g(ρ,σ)])=[[ρ,σ]]:Indeed, we have seen that for every a∈[0,d g(ρ,σ)],we have f(a) σand,on the other hand,if η σ,the end of the proof of(i)just shows thatη=f(d g(ρ,η)). We turn to the proof of(ii).We let q be a continuous injective mapping from[0,1] into T g,and we aim at proving that q([0,1])=f q(0),q(1)([0,d g(q(0),q(1))]).From Lemma2.2 again,we may assume that q(0)=ρ,and we setσ=q(1).Then we have just noticed that f0,σ([0,d g(ρ,σ)])=[[ρ,σ]]. We?rst argue by contradiction to prove that[[ρ,σ]]?q([0,1]).Suppose thatη∈[[ρ,σ]]\q([0,1]),and in particular,η=ρ,σ.Then q([0,1])is contained in the union of the two disjoint open sets T g\T g[η]and T g[η]\{η},with q(0)=ρ∈T g\T g[η]and q(1)=σ∈T g[η]\{η}. This contradicts the fact that q([0,1])is connected. Conversely,suppose that there exists a∈(0,1)such that q(a)/∈[[ρ,σ]].Setη=q(a)and letγ=σ∧η.Note thatγ∈[[ρ,η]]∩[[η,σ]](from the de?nition ofσ∧η,it is immediate to verify that d g(η,σ)=d g(η,γ)+d g(γ,σ)).From the?rst part of the proof of(ii),γ∈q([0,a]) and,via a root change argument,γ∈q([a,1]).Since q is injective,this is only possible if γ=q(a)=η,which contradicts the fact thatη/∈[[ρ,σ]]. Once we know that(T g,d g)is an R-tree,it is straightforward to verify that the notation σ σ′,[[σ,σ′]],σ∧σ′introduced in the preceding proof is consistent with the de?nitions stated for a general R-tree at the beginning of this section. Let us brie?y discuss multiplicities of vertices in the tree T g.Ifσ∈T g is not a leaf then we must have?(σ) ?(σ):=sup p?1g({σ}),r(σ):=inf p?1g({σ}) are respectively the smallest and the largest element in the equivalence class ofσin[0,ζ]. Note that m g(?(σ),r(σ))=g(?(σ))=g(r(σ))=d g(ρ,σ).Denote by(a i,b i),i∈I the connected components of the open set(?(σ),r(σ))∩{t∈[0,∞):g(t)>d g(ρ,σ)}(the index set I is empty ifσis a leaf).Then we claim that the connected components of the open set T g\{σ}are the sets p g((a i,b i)),i∈I and T g\T g[σ](the latter only ifσis not the root).We have already noticed that T g\T g[σ]is open,and the argument used above for T g[σ]\{σ}also shows that the sets p g((a i,b i)),i∈I are open.Finally the sets p g((a i,b i))are connected as continuous images of intervals,and T g\T g[σ]is also connected because ifσ′,σ′′∈T g\T g[σ], [[ρ,σ′]]∪[[ρ,σ′′]]is a connected closed set contained in T g\T g[σ]. 2.2Convergence of trees Two rooted R-trees T(1)and T(2)are called equivalent if there is a root-preserving isometry that maps T(1)onto T(2).We denote by T the set of all equivalence classes of rooted compact R-trees.The set T can be equipped with the(pointed)Gromov-Hausdor?distance,which is de?ned as follows. If(E,δ)is a metric space,we use the notationδHaus(K,K′)for the usual Hausdor?metric between compact subsets of E.Then,if T and T′are two rooted compact R-trees with respective rootsρandρ′,we de?ne the distance d GH(T,T′)as d GH(T,T′)=inf δHaus(?(T),?′(T′))∨δ(?(ρ),?′(ρ′)) , where the in?mum is over all isometric embeddings?:T?→E and?′:T′?→E of T and T′into a common metric space(E,δ).Obviously d GH(T,T′)only depends on the equivalence classes of T and T′.Furthermore d GH de?nes a metric on T(cf[15]and[13]). According to Theorem2of[13],the metric space(T,d GH)is complete and separable. Furthermore,the distance d GH can often be evaluated in the following way.First recall that if(E1,d1)and(E2,d2)are two compact metric spaces,a correspondence between E1and E2 is a subset R of E1×E2such that for every x1∈E1there exists at least one x2∈E2such that(x1,x2)∈R and conversely for every y2∈E2there exists at least one y1∈E1such that (y1,y2)∈R.The distorsion of the correspondence R is de?ned by dis(R)=sup{|d1(x1,y1)?d2(x2,y2)|:(x1,x2),(y1,y2)∈R}. Then,if T and T′are two rooted R-trees with respective rootsρandρ′,we have 1 d GH(T,T′)= d g′(σ′,η′)=g′(s)+g′(t)?2m g′(s,t), so that |d g(σ,η)?d g′(σ′,η′)|≤4 g?g′ . Thus we have dis(R)≤4 g?g′ and the desired result follows from(4). 3The height process 3.1The de?nition of the height process We will now introduce the random process which codes,in the sense of subsection2.1,the genealogical structure of a continuous-state branching process.Recall that a continuous-state branching process is a Markov process(Y t,t≥0)with values in the positive half-line[0,∞), with a Feller semigroup(Q t,t≥0)satisfying the following additivity(or branching)property: For every t≥0and x,x′≥0, Q t(x,·)?Q t(x′,·)=Q t(x+x′,·). Informally,this is just saying that the union of two independent populations started respec-tively at x and x′will evolve like a single population started at x+x′. We will consider only the critical or subcritical case,meaning that [0,∞)y Q t(x,dy)≤x for every t≥0and x≥0.Then the Laplace functional of the semigroup can be written in the following form: [0,∞)e?λy Q t(x,dy)=exp(?x u t(λ)),(5) where the function(u t(λ),t≥0,λ≥0)is determined by the di?erential equation du t(λ) <∞.(7) ψ(u) Note that this implies that at least one of the following two conditions holds: β>0or (0,1)rπ(dr)=∞.(8) (8)is necessary and su?cient for the paths of Y to be of in?nite variation a.s.The coding of the genealogy that is presented below remains valid under(8)even if(7)fails to hold, but the resulting tree is no longer compact(see Theorem4.7in[20]).On the other hand,if (8)is not satis?ed(that is in the?nite variation case),the underlying branching structure is basically discrete:See Section3of[20]and also[23]for a discussion with applications to queuing processes). Special cases that satisfy our assumptions are the quadratic branching caseψ(u)=c u2 and the stable branching caseψ(u)=c uγ,for some1<γ<2. It has been argued in[20]and[9]that the genealogy of theψ-CSBP is coded by the so-called height process,which is itself a functional of the L′e vy process with Laplace exponent ψ.We denote by X a(spectrally positive)L′e vy process with Laplace exponentψ,de?ned under the probability measure P: E[exp(?λX t)]=exp(tψ(λ)),t,λ≥0. The subcriticality assumption on Y and condition(8)are equivalent to saying respectively that X does no drift to+∞and has paths of in?nite variation. The height process H=(H t;t≥0)associated with X is de?ned in such a way that,for every t≥0,H t measures the size of the set X r}.(9) {s∈[0,t]:X s?≤inf s≤r≤t This is motivated by a discrete analogue for Galton-Watson trees(see Section0.2in[9]).To make the preceding de?nition precise,we use a time-reversal argument:For any t>0,we de?ne the L′e vy process reversed at time t by X t s=X t?X(t?s)?,0≤s S s=sup X r and S t s=sup r≤s X t r. r≤s The set(9)is the image of {s∈[0,t]: S t s= X t s}. under the time reversal operation s→t?s.Recall that S?X is a strong Markov process for which0is a regular point.So,we can consider its local time process at0,which is denoted byΓ(X)=(Γt(X),t≥0).We de?ne the height process by H t=Γt( X t),t≥0.(10) To complete the de?nition,we still need to specify the normalization of the local time Γ(X).This can be done through the following approximation: 1 H t=lim ε↓0 where I s t=inf s≤r≤t X r and the convergence holds in probability(this approximation follows from Lemma1.1.3in[9]).Thanks to condition(7),we know that the process H has a modi?cation with continuous sample paths(Theorem4.7in[9]).From now on we consider only this modi?cation.Whenβ>0,it is not hard to see that,for any t≥0, H t= 1 ε s0dr1{a (see Section1.3of[9]).It is then easy to see that the support of the measure dL a s is contained in the closed set{s≥0:H s=a}.When a>0,we have also lim ε→0 E sup0≤s≤t 1 Let us recall the“Ray-Knight theorem”for H([9]Theorem 1.4.1,see also [20],Theorem 4.2),which can be viewed as a generalization of famous results about linear Brownian motion. For any r≥0,set:T r=inf{s≥0:X s=?r}.Then,the process(L a T r ;a≥0)is a ψ-CSBP started at r.In particular,this process has a c`a dl`a g modi?cation. The local time at level a can also be used to describe the distribution of excursions of the height process above level a,and this will be very important for our applications.Let us?x a>0and denote by(αj,βj),j∈J the connected components of the open set {s≥0:H s>a}.For any j∈J,denote by H j the corresponding excursion of H de?ned by: H j s=H(α j+s)∧βj ?a,s≥0. Also set H a s=H?τa s,where for every s≥0, τa s=inf{t≥0: t0dr1{H r≤a}>s}. Informally, H a corresponds to the evolution of H“below level a”. The next result is a straightforward consequence of Proposition1.3.1in[9]. Proposition3.1Under the probability P,the point measure j∈Jδ(L aαj,H j)(d?dω) is independent of H a and is a Poisson point measure on R+×C+([0,∞))with intensity d??(dω). It will be important to de?ne local times under the excursion measure N.This creates no additional di?culty thanks to the following simple remark.If r>0,then for anyδ>0,there is a positive probability under P that exactly one excursion of H away from zero hits levelδbefore time T r.It easily follows that we can de?ne for every a>0a continuous increasing process(Λa s,s≥0),such that,for everyδ∈(0,a)and t≥0, lim ε→0 N 1{sup H>δ}sup0≤s≤t∧ζ 1 ψ(u) . Moreover,for every a>0,we have v(a)=N Λaζ>0 =N sup s≤ζH s>a .(14) The?rst equality follows from the de?nition of v.The second one can be deduced from Proposition3.1,which implies that inf{s≥0:L a s>0}=inf{s≥0:H s>a},P a.s. We will need an analogue of Proposition3.1under the excursion measure N.To state it,?x a>0and denote by(αj,βj),j∈J the excursion intervals of H above level a(just as before,but we are now arguing under N)and for every j∈J let H j be the corresponding excursion.Let the process H a be de?ned as previously and let H a be theσ-?eld generated by H a and the class of N-negligible measurable sets.From our approximation(12)it follows thatΛaζis measurable with respect to H a. Corollary3.2Under the probability measure N(·|sup H>a)and conditionally on H a,the point measure j∈Jδ(Λaαj,H j)(d?dω) is distributed as a Poisson point measure on R+×C+([0,∞))with intensity1[0,Λa ζ] (?)d??(dω). This is really an immediate consequence of Proposition3.1if we notice that the law under P of the?rst excursion of H that hits level a is N(·|sup H>a).Alternatively,the statement of Corollary3.2also appears as an intermediate result in the proof of Proposition4.2.3in[9]. We will need one additional property related to Corollary3.2.First denote by( Λa s,s≥0) the local time of H a at level a,which may be de?ned either by an approximation similar to (12)or directly by the formula Λa s=Λa?τa s.Then we have N a.e.on{sup H>a} inf{s≥0: Λa s>Λaαj}= αj0ds1{H s≤a},for every j∈J.(15) For a proof,see pages108-109of[9]. We conclude this section with an important regularity property of local times.Recall that a c`a dl`a g process Y is said to have no?xed discontinuities if for every?xed t>0,the sample path of Y is continuous at t outside a set of zero probability. Lemma3.3SetΛ0s=0for every s≥0.Then the process(Λaζ,a≥0)has a c`a dl`a g modi?-cation under N,and this modi?cation has no?xed discontinuities. Proof.Let r>0.Since the process(L a T r ,a≥0)is aψ-CSBP and thus a Feller process, it has a c`a dl`a g modi?cation with no?xed discontinuities under P.Let H i,i∈I be the excursions of H away from0,as in(11),and for every i∈I letζi be the duration of H i. From our approximation of local times,it is easy to see that,for every a>0, L a T r = i∈I,I g i>?rΛaζi(H i),N a.e.(16) Using a previous remark about the existence of exactly one excursion of H hitting level δbefore time T r,we easily deduce from the previous formula and the c`a dl`a g property of (L a T r ,a≥0)that the process(Λaζ,a>0)must have a c`a dl`a g modi?cation with no?xed discontinuities under N.Furthermore,if we use this modi?cation in the right side of(16), for every a>0,we will obviously obtain the c`a dl`a g modi?cation of the process(L a T r ,a>0). It remains to verify thatΛaζconverges to0,N a.e.as a↓0(we now consider the modi?cation that has just been introduced).For this,we need a di?erent argument.Let δ>0and let H i 0be the?rst excursion of H that reaches levelδ.From properties of Poisson measures,the law under P of the point measure i∈I\{i0},I g i>?rδ(?I g i,H i)(drdω) is absolutely continuous with respect to that of i∈I,I g i>?rδ(?I g i,H i)(drdω). In particular,the function a?→ i∈I\{i0},I g i>?rΛaζi(H i) must converge P a.s.to r as a↓0.Now note that,on the event{?I g i0>?r}={sup[0,T r] H> δ},we have for every a>0 Λaζ i0(H i )= i∈I,I g i>?rΛaζi(H i)? i∈I\{i0},I g i>?rΛaζi(H i) and use the fact that the distribution of H i 0under P(·|sup[0,T r] H>δ)coincides with the law of H under N(·|sup H>δ)to complete the proof. From now on,we assume that have chosen a modi?cation of the collection(Λa,a≥0)in such a way that the process(Λaζ,a≥0)is c`a dl`a g.This will be important in the applications developed in Section4below. Let us?nally brie?y comment on the use of the measures P and N for our purposes.As will be made precise in the next section,the height process under N codes a single(compact rooted)R-tree,whereas under P it codes a Poissonnian collection of such trees,each excursion of H away from0corresponding to one tree. 3.3A key lemma In this subsection,we prove a basic preliminary lemma,which is a consequence of the results in[9].We need to introduce some notation.Denote by M f the space of all?nite measures on[0,∞).Ifμ∈M f,we denote by H(μ)∈[0,∞]the supremum of the(topological)support ofμ.We also introduce a“killing operator”on measures de?ned as follows.For every x≥0, k xμis the element of M f such that k xμ([0,t])=μ([0,t])∧(μ([0,∞))?x)+for every t≥0. Let M?f stand for the set of all measuresμ∈M f such that H(μ)<∞and the topological support ofμis[0,H(μ)].Ifμ∈M?f,we denote by Qμthe law under P of the process Hμde?ned by Hμt=H(k?I t μ)+H t,if t≤T μ,1 , Hμt=0,if t>T μ,1 , where T μ,1 =inf {t ≥0:X t =? μ,1 }.Our assumption μ∈M ?f guarantees that H μhas continuous sample paths,and we can therefore view Q μas a probability measure on the space C +([0,∞))of nonnegative continuous functions on [0,∞). Finally,let ψ?(u )=ψ(u )?αu ,and let (U 1,U 2)be a two-dimensional subordinator with Laplace functional E [exp(?λU 1t ?λ′U 2t )]=exp ? ψ?(λ)?ψ?(λ′) λ?λ′should obviously be interpreted as ψ′(λ)?α,so that we see that U 1+U 2is a subordinator with Laplace exponent ψ′?α.For every a ≥0,we let M a be the probability measure on (M ?f )2which is the distribution of (1[0,a ](t )dU 1t ,1[0,a ](t )dU 2t ).Lemma 3.4For any nonnegative measurable function F on C +([0,∞))2,N ζ0ds F (H (s ?t )+,t ≥0),(H (s +t )∧ζ,t ≥0) = ∞0da e ?αa M a (dμdν) Q μ(dh )Q ν(dh ′)F (h,h ′).Remark.In the Brownian case ψ(u )=u 2,this lemma reduces to the well-known Bismut decomposition of the Brownian excursion. Proof.We start by recalling some results from [9](see Chapter 1and Section 3.1in [9]). We can de?ne both under P and under N a c`a dl`a g process (ρt ,ηt )t ≥0taking values in (M ?f )2such that the following properties hold: (i)We have H (ρt )=H t =H (ηt )for every t ≥0,N a.e.and P a.e. (ii)The process (ρt ,ηt )is adapted with respect to the ?ltration (F t )t ≥0generated by the L′e vy process X .Furthermore,if G is any nonnegative measurable functional on C +([0,∞)),we have for every s >0,N a.e.on the event {s <ζ},N G (H (ρ(s +t )∧ζ),t ≥0) F s =Q ρs (G ). (17)(iii)The process (η(ζ?s )?,ρ(ζ?s )?)0≤s<ζhas the same distribution as (ρs ,ηs )0≤s<ζunder N .(iv)For any nonnegative measurable function Φon (M ?f )2,N ζ0ds Φ(ρs ,ηs ) = ∞ 0da e ?αa M a (G ).(18) To make sense of the conditional expectation in (17),note that the event {s <ζ}has ?nite N -measure.We refer to [9]for a proof of properties (i)–(iv)above:See in particular Propositions 1.2.3and 1.2.6for (17),Corollary 3.1.6for (iii)and Proposition 3.1.3for (iv). We now proceed to the proof of the lemma.We may and will assume that F is of the form F (h,h ′)=F 1(h )F 2(h ′).Using (i)and then (ii),we have N ζ ds F 1 H (s ?t )+,t ≥0 F 2 H (s +t )∧ζ,t ≥0 =N ζ0ds F1 H(ρ(s?t)+),t≥0 F2 H(ρ(s+t)∧ζ),t≥0 =N ζ0ds F1 H(ρ(s?t)+),t≥0 Qρs(F2) . From the time-reversal property(iii)we see that the last quantity is equal to N ζ0ds Qηs(F2)F1 H(ρ(s+t)∧ζ),t≥0 =N ζ0ds Qηs(F2)Qρs(F1) , using(17)once again.The formula of the lemma now follows from(18). Corollary3.5Let a>0.Then,for any nonnegative measurable function F on C+([0,∞))2, N ζ0dΛa s F (H(s?t)+,t≥0),(H(s+t)∧ζ,t≥0) =e?αa M a(dμdν) Qμ(dh)Qν(dh′)F(h,h′). Proof.This is a straightforward consequence of Lemma3.4and the approximation of local time given in(12). Remark.The case F=1of Corollary3.5gives N(Λa ζ )=e?αa,for every a>0. 4The L′e vy tree We have seen that N a.e.the function s→H s satis?es the properties stated at the beginning of subsection2.1,namely it is continuous with compact support and such that H0=0. De?nition4.1Theψ-L′e vy tree is the tree(T H,d H)coded by the function s→H s under the measure N. We will say the L′e vy tree rather than theψ-L′e vy tree if there is no risk of confusion. We denote byΘ(d T)theσ-?nite measure on T which is the law of the L′e vy tree,that is the law of the tree T H under N.Note that the measurability of the random variable T H follows from Lemma2.3. 4.1From discrete to continuous trees In this subsection,we will state a result which justi?es the de?nition of theψ-L′e vy tree by showing that it arises as the limit in the Gromov-Hausdor?distance of suitably rescaled discrete Galton-Watson trees. We start by introducing some formalism for discrete trees.Let U=∞ n=0N n where N ={1,2,...}and by convention N 0={?}.If u =(u 1,...u m )and v =(v 1,...,v n )belong to U ,we write uv =(u 1,...u m ,v 1,...,v n )for the concatenation of u and v .In particular u ?=?u =u . A (?nite)rooted ordered tree θis a ?nite subset of U such that: (i)?∈θ. (ii)If v ∈θand v =uj for some u ∈U and j ∈N ,then u ∈θ. (iii)For every u ∈θ,there exists a number k u (θ)≥0such that uj ∈θif and only if 1≤j ≤k u (θ). We denote by T the set of all rooted ordered trees.In what follows,we see each vertex of the tree θas an individual of a population whose θis the family tree. If θis a tree and u ∈θ,we de?ne the shift of θat u by τu θ={v ∈U :uv ∈θ}.Note that τu θ∈T .We also denote by h (θ)the height of T ,that is the maximal generation of a vertex in θ. e e e e e ????? Now let us turn to Galton-Watson trees.Letμbe a critical or subcritical o?spring distribution.This means thatμis a probability measure on Z+such that ∞k=0kμ(k)≤1. We exclude the trivial case whereμ(1)=1.Then,there is a unique probability distribution Πμon T such that (i)Πμ(k?=j)=μ(j),j∈Z+. (ii)For every j≥1withμ(j)>0,the shifted treesτ1θ,...,τjθare independent under the conditional probabilityΠμ(·|k?=j)and their conditional distribution isΠμ. A random tree with distributionΠμis called a Galton-Watson tree with o?spring distri-butionμ,or in short aμ-Galton-Watson tree.Obviously it describes the genealogy of the Galton-Watson process with o?spring distributionμstarted initially with one individual. We can now state our result relating discrete and continuous trees.If T is a(compact rooted)R-tree with metric d,and if r>0,we slightly abuse notation by writing r T for the “same”tree equipped with the distance r d.Recall that the height of T is h(T)=sup{d(ρ(T),σ):σ∈T}, whereρ(T)denotes the root of T.For every real number x,[x]denotes the integer part of x. Theorem4.1Let(μp)p≥1be a sequence of critical or subcritical o?spring distributions.For every p≥1denote by Y p a Galton-Watson branching process with o?spring distributionμp, started at Y p0=p.Assume that there exists a nondecreasing sequence(m p)p≥1of positive integers converging to+∞such that p?1Y p[m p t],t≥0 (d)?→p→∞(Y t,t≥0)(19) where the limiting process Y is aψ-CSBP.Assume furthermore that for everyδ>0, lim inf p→∞P[Y p [m pδ] =0]>0.(20) Then,for every a>0,the law of the R-tree m?1p TθunderΠμ p (dθ|h(θ)≥[a m p])converges as p→∞to the probability measureΘ(d T|h(T)>a),in the sense of weak convergence of measures in the space T. Proof.We noted that the tree Tθis the tree coded by the function Cθ,in the sense of Section2.Lemma2.3then shows that the convergence of the theorem follows from the weak convergence of the scaled contour function(m?1p Cθ(pm p t),t≥0)underΠμ p (dθ|h(θ)≥[a m p])towards the height process H under N(·|sup H>a).But this is precisely the contents of Proposition2.5.2in[9],which is itself a consequence of Theorem2.3.1in the same work. The technical assumption(20)guarantees that the Galton-Watson process Y p dies out at a time of order m p,as one expects from the convergence(19)(recall that Y dies out in?nite time).See Chapter2of[9]for a discussion of this assumption,and note that it is always true in the case whenμp=μfor every p(Theorem2.3.2in[9]).In particular,the approximation result stated in the introduction above is easily seen to be a consequence of Theorem4.1. 脐带间充质干细胞的研究进展 间充质干细胞（mesenchymal stem cells,MSC S ）是来源于发育早期中胚层 的一类多能干细胞[1-5]，MSC S 由于它的自我更新和多项分化潜能，而具有巨大的 治疗价值 ,日益受到关注。MSC S 有以下特点：(1)多向分化潜能，在适当的诱导条件下可分化为肌细胞[2]、成骨细胞[3、4]、脂肪细胞、神经细胞[9]、肝细胞[6]、心肌细胞[10]和表皮细胞[11, 12]；(2)通过分泌可溶性因子和转分化促进创面愈合；(3) 免疫调控功能，骨髓源（bone marrow ）MSC S 表达MHC-I类分子，不表达MHC-II 类分子，不表达CD80、CD86、CD40等协同刺激分子，体外抑制混合淋巴细胞反应，体内诱导免疫耐受[11, 15]，在预防和治疗移植物抗宿主病、诱导器官移植免疫耐受等领域有较好的应用前景；(4)连续传代培养和冷冻保存后仍具有多向分化潜能，可作为理想的种子细胞用于组织工程和细胞替代治疗。1974年Friedenstein [16] 首先证明了骨髓中存在MSC S ，以后的研究证明MSC S 不仅存在于骨髓中，也存在 于其他一些组织与器官的间质中：如外周血[17]，脐血[5]，松质骨[1, 18]，脂肪组织[1]，滑膜[18]和脐带。在所有这些来源中，脐血(umbilical cord blood)和脐带(umbilical cord)是MSC S 最理想的来源，因为它们可以通过非侵入性手段容易获 得，并且病毒污染的风险低，还可冷冻保存后行自体移植。然而，脐血MSC的培养成功率不高[19, 23-24]，Shetty 的研究认为只有6%，而脐带MSC的培养成功率可 达100%[25]。另外从脐血中分离MSC S ，就浪费了其中的造血干/祖细胞(hematopoietic stem cells/hematopoietic progenitor cells,HSCs/HPCs) [26, 27]，因此，脐带MSC S (umbilical cord mesenchymal stem cells, UC-MSC S )就成 为重要来源。 一．概述 人脐带约40 g, 它的长度约60–65 cm, 足月脐带的平均直径约1.5 cm[28, 29]。脐带被覆着鳞状上皮，叫脐带上皮，是单层或复层结构，这层上皮由羊膜延续过来[30, 31]。脐带的内部是两根动脉和一根静脉，血管之间是粘液样的结缔组织，叫做沃顿胶质，充当血管外膜的功能。脐带中无毛细血管和淋巴系统。沃顿胶质的网状系统是糖蛋白微纤维和胶原纤维。沃顿胶质中最多的葡萄糖胺聚糖是透明质酸，它是包绕在成纤维样细胞和胶原纤维周围的并维持脐带形状的水合凝胶，使脐带免受挤压。沃顿胶质的基质细胞是成纤维样细胞[32]，这种中间丝蛋白表达于间充质来源的细胞如成纤维细胞的，而不表达于平滑肌细胞。共表达波形蛋白和索蛋白提示这些细胞本质上肌纤维母细胞。 脐带基质细胞也是一种具有多能干细胞特点的细胞，具有多项分化潜能，其 形态和生物学特点与骨髓源性MSC S 相似[5, 20, 21, 38, 46]，但脐带MSC S 更原始，是介 于成体干细胞和胚胎干细胞之间的一种干细胞，表达Oct-4, Sox-2和Nanog等多 Risk of bias Item Authors' judgement Description Adequate sequence generation? Yes Prinicipal author stated that computer generated allocation was used Allocation concealment? Yes Prinicipal author stated that allocation was concealed Blinding? Unclear No mention of study personnel or participants being blind to treatment group Incomplete outcome data addressed? Yes All participants accounted for, one 'drop out' recorded but included by us in analysis Free of other bias? Unclear Possible uneven distribution of complete and incomplete paralysis at start of study between the two treatment groups Cochrane RCT质量评价标准： ①随机方法是否正确。 ②是否隐蔽分组。 ③盲法的使用情况。 ④失访或退出描述情况，有无采用意向性(ITT)分析。 以上质量标准中,如所有标准均为“充分”,则发生各种偏倚的可能性很小；如其中一条为不清楚,则有发生相应偏倚的中等度可能性；如其中一条为“不充分”或“未采用”,则有发生相应偏倚的高度可能性。 音响入门到高手必看知识音箱作为声频的终端器材，仿佛人的嗓门，在很大程度上决定了一套音响的好坏。可以毫不夸张地说：选择一对好的音箱是一套音响成功的关键所在，来不得半点马虎。然而纵观当今音响市场，成品音箱品牌不下数百种，其中不乏著名的国际品牌：如美国的BOSE（博士）、JBL、INFINITY（燕飞利仕）、Westlake Audio(西湖)、PolkAudio（音乐之声）：英国的ATC（皇牌）、B&W、T annoy(天朗)、MonitorAudio（猛牌）、KEF、HARBETH（雨后初晴）：丹麦的（皇冠）DYNAUD10（丹拿）、DALI（丹尼）、Jamo(尊宝)：德国的Heco(德高)、密力(Maagnat)、ELAC（意力）；法国的梦幻之声（VIS10NACOUSTIQUE）、JMLab(劲浪)：国产精品有美之声战神系列、金琅、惠威、新德克、福音、小旋风等等，林林总总、不胜枚举。质量参差不齐，价格天差地别。即便是同品牌同系列的音箱，往往音质高出一丁点，价格就会成几何积数倍上升。这正是因为自人类发明电子声频工程以来，唯音箱进步最慢、技术最薄弱。据英国《发烧天书》记载：一部成名多年的英国老牌长青树音相Rogersls 3/5自六十年代推出，畅销近四十年，其音色这纯正优雅，至今仍为众多资深Hi-Fi发烧友视为炙手可热的抢手货。在音响科技高度发展的今天，实在有些令人费解。所以您可千万别小看了音箱的打造，别以为音箱只不过是把几个喇叭与几个Hi-Fi或Hi-END箱。音箱的学问大了，大到没法用 书写，各家各派众说纷纭。正如医学界的中医与西医之争，或如医治一些疑难杂症：说得明白的治不好病，治得好病的却说不明白。然而对消费者而言，我们只要学会如何鉴别与挑选就成。那么有没有一种通俗简便的方法，让毫无经验的大多数消费者不是凭贵价、不是碰运气，而是凭下面介绍的音箱试听“七要点”来学会判断一对音箱的好坏： 1.试听前对音箱的初步了解 对于一对音箱的最初了解，可用“观、掂、敲、认”的步骤来鉴别：即一观工艺，二掂重量、三敲箱体、四认铭牌。 外观工艺就是从音箱外表的第一部象来判断该次和品质优劣：用天然原木精工打造的音箱当然最好，许多天价级的世界名牌至尊音箱，包括意大利的Chario（卓丽）、Guarneri Homage（名琴）等，但此类好箱因环保、资源匮乏加工工艺难度大，时间长等因素，绝不会普及得象随处可见的“飘柔”洗发水，价格肯定没法低。故常见的音箱均是以MDF中密度纤维板表面敷以一层薄薄的木皮做装饰：敷真木皮精工外饰的音箱，尤其是如酸枝、雀眼、花梨、胡桃、桢楠、红橡等珍稀木皮，其天然木纹视觉效果极好，手感滑腻舒适。尤其以对称蝴蝶花纹真木皮经多层涂复打磨钢琴亮漆者，大多均可视为中高档精品音箱，仿冒品极少。用PVC塑料贴皮的箱子属大路货，虽做工精细，最好也只能算中低档货色。而以本纹纸贴面装饰的箱子虽然看上去极时应多注意箱体背后的贴皮接缝和喇叭安装位挖扎工艺是否精确到位。假冒伪 精神分裂症的病因及发病机理 精神分裂症病因：尚未明，近百年来的研究结果也仅发现一些可能的致病因素。（一）生物学因素1．遗传遗传因素是精神分裂症最可能的一种素质因素。国内家系调查资料表明：精神分裂症患者亲属中的患病率比一般居民高6.2倍，血缘关系愈近，患病率也愈高。双生子研究表明：遗传信息几乎相同的单卵双生子的同病率远较遗传信息不完全相同 的双卵双生子为高，综合近年来11项研究资料：单卵双生子同病率（56.7%），是双卵双生子同病率（12.7%）的4.5倍，是一般人口患难与共病率的35-60倍。说明遗传因素在本病发生中具有重要作用，寄养子研究也证明遗传因素是本症发病的主要因素，而环境因素的重要性较小。以往的研究证明疾病并不按类型进行遗传，目前认为多基因遗传方式的可能性最大，也有人认为是常染色体单基因遗传或多源性遗传。Shields发现病情愈轻，病因愈复杂，愈属多源性遗传。高发家系的前瞻性研究与分子遗传的研究相结合，可能阐明一些问题。国内有报道用人类原癌基因Ha-ras-1为探针，对精神病患者基因组进行限止性片段长度多态性的分析，结果提示11号染色体上可能存在着精神分裂症与双相情感性精神病有关的DNA序列。2．性格特征：约40%患者的病前性格具有孤僻、冷淡、敏感、多疑、富于幻想等特征，即内向 型性格。3．其它：精神分裂症发病与年龄有一定关系，多发生于青壮年，约1/2患者于20～30岁发病。发病年龄与临床类型有关，偏执型发病较晚，有资料提示偏执型平均发病年龄为35岁，其它型为23岁。80年代国内12地区调查资料：女性总患病率（7.07%。）与时点患病率（5.91%。）明显高于男性（4.33%。与3.68%。）。Kretschmer在描述性格与精神分裂症关系时指出：61%患者为瘦长型和运动家型，12.8%为肥胖型，11.3%发育不良型。在躯体疾病或分娩之后发生精神分裂症是很常见的现象，可能是心理性生理性应激的非特异性影响。部分患者在脑外伤后或感染性疾病后发病；有报告在精神分裂症患者的脑脊液中发现病毒性物质；月经期内病情加重等躯体因素都可能是诱发因素，但在精神分裂症发病机理中的价值有待进一步证实。（二）心理社会因素1．环境因素①家庭中父母的性格，言行、举止和教育方式（如放纵、溺爱、过严）等都会影响子女的心身健康或导致个性偏离常态。②家庭成员间的关系及其精神交流的紊乱。③生活不安定、居住拥挤、职业不固定、人际关系不良、噪音干扰、环境污染等均对发病有一定作用。农村精神分裂症发病率明显低于城市。2．心理因素一般认为生活事件可发诱发精神分裂症。诸如失学、失恋、学习紧张、家庭纠纷、夫妻不和、意处事故等均对发病有一定影响，但这些事件的性质均无特殊性。因此，心理因素也仅属诱发因 功放与音箱匹配技巧与注意事项 对功放与音响之间的匹配问题，除了音色软搭配之外（音色搭配常说软硬之分，是根据设计者对音色走向的设计和用料，而具有的特征和个性）还有一些技术指标上的硬搭配。软搭配是经验积累和个人爱好以实际感受为主，硬搭配则以数据和基本技术常识来定夺，下列就来简述硬搭配有关方面的问题。 阻抗匹配 1. 真空管功放（胆机）与音箱匹配时，放大器的输出阻抗应与音箱阻抗相等，否则会出现降低输出功率和增大失真等现象。好在大都胆机都有可变输出阻抗匹配接口如4-8-16欧，与音箱阻抗匹配已趋简单。 2. 对于晶体管功放（石机）与音箱阻抗的匹配 A) 音箱阻抗比功放输出阻抗高时，除了输出功率不同程度的降低外，无其它影响。 B) 音箱阻抗比功放输出阻抗低时，输出功率相应成比例增加，失真度一般不会增加或增加一点点可忽略。但匹配时音箱阻抗不能太低，如低至2奥姆（指2只4奥姆音箱并联时），此时只有功放功率富裕量大，并使用性能良好的大功率管和多管并联推挽，一般对这样的功放无影响。反之，一般普通功放富裕量不大，而功放管的pcm、lcm不大，当音量又开得很大时，这时失真会明显增大，严重时机毁箱亡，切切注意。 功率匹配 1、从原则上来讲，音箱额定功率与功放额定功率不一致时，对于功放来说，它的功率大小只与音箱阻抗有关，而与音箱额定功率无关。无论音箱功率与功放功率是否相同，对功放工作无影响，只是对音箱本身安全有关。 2、如果音箱阻抗符合匹配要求，而承受功率比功放功率小，则推动功率充足，听起来很舒服。这就是常说的功放储备功率要大，才能充分地表现出音乐全部内涵，尤其是音乐中的低频部分，表现更为生动、有力。这是一种较好的匹配。 3、如果音箱的额定阻抗大于功放的额定功率，虽然二者都能安全的工作，但这时功率放大器推动功率显得不够，会觉得响度不足，往往出现已经开到饱和状态，失真加剧，仍感到力不从心。这是一种较差的匹配。 按阻尼系数匹配 脐带血造血干细胞库管理办法（试行） 第一章总则 第一条为合理利用我国脐带血造血干细胞资源，促进脐带血造血干细胞移植高新技术的发展，确保脐带血 造血干细胞应用的安全性和有效性，特制定本管理办法。 第二条脐带血造血干细胞库是指以人体造血干细胞移植为目的，具有采集、处理、保存和提供造血干细胞 的能力，并具有相当研究实力的特殊血站。 任何单位和个人不得以营利为目的进行脐带血采供活动。 第三条本办法所指脐带血为与孕妇和新生儿血容量和血循环无关的，由新生儿脐带扎断后的远端所采集的 胎盘血。 第四条对脐带血造血干细胞库实行全国统一规划，统一布局，统一标准，统一规范和统一管理制度。 第二章设置审批 第五条国务院卫生行政部门根据我国人口分布、卫生资源、临床造血干细胞移植需要等实际情况，制订我 国脐带血造血干细胞库设置的总体布局和发展规划。 第六条脐带血造血干细胞库的设置必须经国务院卫生行政部门批准。 第七条国务院卫生行政部门成立由有关方面专家组成的脐带血造血干细胞库专家委员会（以下简称专家委 员会），负责对脐带血造血干细胞库设置的申请、验收和考评提出论证意见。专家委员会负责制订脐带血 造血干细胞库建设、操作、运行等技术标准。 第八条脐带血造血干细胞库设置的申请者除符合国家规划和布局要求，具备设置一般血站基本条件之外， 还需具备下列条件： （一）具有基本的血液学研究基础和造血干细胞研究能力； （二）具有符合储存不低于1 万份脐带血的高清洁度的空间和冷冻设备的设计规划； （三）具有血细胞生物学、HLA 配型、相关病原体检测、遗传学和冷冻生物学、专供脐带血处理等符合GMP、 GLP 标准的实验室、资料保存室； （四）具有流式细胞仪、程控冷冻仪、PCR 仪和细胞冷冻及相关检测及计算机网络管理等仪器设备； （五）具有独立开展实验血液学、免疫学、造血细胞培养、检测、HLA 配型、病原体检测、冷冻生物学、 管理、质量控制和监测、仪器操作、资料保管和共享等方面的技术、管理和服务人员； （六）具有安全可靠的脐带血来源保证； （七）具备多渠道筹集建设资金运转经费的能力。 第九条设置脐带血造血干细胞库应向所在地省级卫生行政部门提交设置可行性研究报告，内容包括： 音响和音箱有什么区别_音响和音箱的区别介绍 一、音箱简介音箱指可将音频信号变换为声音的一种设备。通俗的讲就是指音箱主机箱体或低音炮箱体内自带功率放大器，对音频信号进行放大处理后由音箱本身回放出声音，使其声音变大。 音箱是整个音响系统的终端，其作用是把音频电能转换成相应的声能，并把它辐射到空间去。它是音响系统极其重要的组成部分，担负着把电信号转变成声信号供人的耳朵直接聆听的任务。 音箱的组成：市面上的音箱形形色色，但无论哪一种，都是由喇叭单元（术语叫扬声器单元）和箱体这两大最基本的部分组成，另外，绝大多数音箱至少使用了两只或两只以上的喇叭单元实行所谓的多路分音重放，所以分频器也是必不可少的一个组成部分。当然，音箱内还可能有吸音棉、倒相管、折叠的迷宫管道、加强筋/加强隔板等别的部件，但这些部件并非任何一只音箱都必不可少，音箱最基本的组成元素只有三部分：喇叭单元、箱体和分频器。 音箱是的分类：音箱的分类有不同的角度与标准，按音箱的声学结构来分，有密闭箱、倒相箱（又叫低频反射箱）、无源辐射器音箱、传输线音箱之分，它们各自的特点详见相关问答。倒相箱是目前市场的主流；从音箱的大小和放置方式来看，有落地箱和书架箱之分，前者体积比较大，一般直接放在地上，有时也在音箱下安装避震用的脚钉。落地箱由于箱体容积大，而且便于使用更大、更多的低音单元，其低频通常比较好，而且输出声压级较高、功率承载能力强，因而适合听音面积较大或者要求较全面的场合使用。书架箱体积较小，通常放在脚架上，特点是摆放灵活，不占空间，不过受箱体容积以及低音单元口径和数量的限制，其低频通常不及落地箱，承载功率和输出声压级也小一些，适合在较小的听音环境中使用；按重放的频带宽窄来分，有宽频带音箱和窄频带音箱之分，大多数音箱其设计目标都是要覆盖尽量宽的频带，属于宽频带音箱。窄频带音箱最常见的就是随家庭影院而兴起的超低音音箱（低音炮），仅用于还原超低频到低频很窄的一个频段；按有无内 浅析功放与音箱匹配技巧与注意事项 6月2日报道对功放与音响之间的匹配问题，除了音色软搭配之外（音色搭配常说软硬之分，是根据设计者对音色走向的设计和用料，而具有的特征和个性）还有一些技术指标上的硬搭配。软搭配是经验积累和个人爱好以实际感受为主，硬搭配则以数据和基本技术常识来定夺，下列就来简述硬搭配有关方面的问题。 一、阻抗匹配 1、电子管功放（胆机）与音箱匹配时，放大器的输出阻抗应与音箱阻抗相等，否则会出现降低输出功率和增大失真等现象。好在大都胆机都有可变输出阻抗匹配接口如4-8-16欧，与音箱阻抗匹配已趋简单。 2、对于晶体管功放（石机）与音箱阻抗的匹配 ①音箱阻抗比功放输出阻抗高时，除了输出功率不同程度的降低外，无其它影响。 ②音箱阻抗比功放输出阻抗低时，输出功率相应成比例增加，失真度一般不会增加或增加一点点可忽略。但匹配时音箱阻抗不能太低，如低至2欧（指2只4欧音箱并联时），此时只有功放功率富裕量大，并使用性能良好的大功率管和多管并联推挽，一般对这样的功放无影响。反之，一般普通功放富裕量不大，而功放管的pcm、lcm不大，当音量又开得很大时，这时失真会明显增大，严重时机毁箱亡，切切注意。 二、功率匹配 1、从原则上来讲，音箱额定功率与功放额定功率不一致时，对于功放来说，它的功率大小只与音箱阻抗有关，而与音箱额定功率无关。无论音箱功率与功放功率是否相同，对功放工作无影响，只是对音箱本身安全有关。 2、如果音箱阻抗符合匹配要求，而承受功率比功放功率小，则推动功率充足，听起来很舒服。这就是常说的功放储备功率要大，才能充分地表现出音乐全部内涵，尤其是音乐中的低频部分，表现更为生动、有力。这是一种较好的匹配。 3、如果音箱的额定阻抗大于功放的额定功率，虽然二者都能安全的工作，但这时功率放大器推动功率显得不够，会觉得响度不足，往往出现已经开到饱和状态，失真加剧，仍感到力不从心。这是一种较差的匹配。 三、按阻尼系数匹配 对于选一对hi-fi音箱来讲，应有最佳的特定的电阻尼要求（负责任的音箱厂家应该提供此数据，指的是对功放阻尼系数的要求。说清楚点就是如要配此音箱，要求所配的功放阻尼系数要达到多少）。一般情况下，功放的阻尼系数高一点为好，低档功放阻尼系数小于10时，音箱的低频特征，输出特征，高次谐波特征等都会变坏。（家用功放的阻尼数一般在几十至几百之间。） 四、线材的匹配。 进口发烧线、神经线林林总总，贵至万余元，次之也要千元至数千元，（当然也有百元以下的），使用效果那是见仁见智的事。好的线材一般情况下都会改善音响器材中某系不足。它的传输理论说起来太复杂，只能简述了。传输线的材料与结构，决定了三个重要参数，即电阻、电容、电感（还有电磁效应、集肤效应、近接效应、电抗等）别看这些参数微小的差距，会直接影响到音响系统频率特征，阻尼特征,信号速率，相位精度，也及音色取向和声场定位等。它的主要作用是，高速传输（尽可能减小信号损失）、抗震动、防杂讯、抗干扰（主要是无线电波rf1射频干扰和em1电磁波干扰等） 音箱功放匹配原则（摘自网络） 功放与音箱配接四要素功放与音箱配接讲究冷暖相宜、软硬适中，以实现整套器材还原音色 第十章脑卒中评定量表 附录Ⅰ脑血管疾病分类（1995年） （全国第四届脑血管病学术会议通过） 说明： 一、本分类系经全国脑防办专家、在京专家和全国第四次脑血管病会议代表讨论，由王新德执笔，综合成此《脑血管疾病分类（1995年）》。 二、按病程发展可分为短暂性脑缺血发作、可逆性缺血发作（发作后3周内症状消失），进行性卒中和完全性卒中，仅列入短暂性脑缺血发作，其他未列入。 三、括号内数字为世界卫生组织第10版《国家疾病分类》的编号。 1．脑卒中结局评定的基本模式-ICF 2001年5月22日，在日内瓦举行的第54届世界卫生大会上，根据近20年来的研究结果，世界卫生组织(WHO)提出并经会员国一致通过了一项WHA54.21决议:在会员国使用《国际功能、残疾和健康分类》(internatianal classification of functianing,disablity and health，简称ICF)。从而，提出了一个全新的有关“功能”、“残疾”和“健康”概念的新模式(图1-1) 一、身体的构成成分、活动和参与能力 1．身体的构成成分在这里包括身体的“结构”和“功能”。“身体结构”是指身体的解剖部位，如器官、肢体及其组成部分。“身体功能”是指身体各系统的生理功能(包括心理功能)，如精神功能、言语功能、感觉功能、心肺功能、消化功能、排泄功能、神经肌肉骨骼和运动功能等。 2．活动能力是指个体执行一项任务和行动的能力，如学习和应用知识的能力、完成一般任务和要求的能力、交流的能力、个体的活动能力、生活自理能力等。 3．参与能力指的是投人到一种生活情景中，如家庭生活的能力、人际交往和相处关系的能力、接受教育和工作就业的能力、参与社会和社区生活的能力等。 图1-1 WHO关于“功能”、“残疾”和“健康”概念的新模式 在ICF出台之前，有关康复医学的效果评定和质量控制的概念就已经有了很大的进展：在使用ICIDH 的年代，就己经逐步明确了不能只以“残损”（impairment)水平的积分改善来评定康复医疗的效果，而强调在“残疾”(disability)和“残障”( handicap)水平上积分的改善。通常，使用ADL(activity of daily living,日常生活活动能力)和IADL(instrumental activities of daily living，工具性日常生活活动能力)的积分(如巴氏指数-BI和功能独立性评定-FIM等)来定量“残疾”水平，使用QOL(生活质量)积分(如简表SF-36，世界卫生组织生活质量问卷 音响 扬声器材质与尺寸 低档塑料音箱因其箱体单薄、无法克服谐振，无音质可言(也有部分设计好的塑料音箱要远远好于劣质的木质音箱)；木制音箱降低了箱体谐振所造成的音染，音质普遍好于塑料音箱。 通常多媒体音箱都是双单元二分频设计，一个较小的扬声器负责中高音的输出，而另一个较大的扬声器负责中低音的输出。 挑选音箱应考虑这两个喇叭的材质：多媒体有源音箱的高音单元现以软球顶为主(此外还有用于模拟音源的钛膜球顶等)，它与数字音源相配合能减少高频信号的生硬感，给人以温柔、光滑、细腻的感觉。多媒体音箱现以质量较好的丝膜和成本较低的PV膜等软球顶的居多。 低音单元它决定了音箱的声音的特点，选择起来相对重要一些，最常见的有以下几种：纸盆，又有敷胶纸盆、纸基羊毛盆、紧压制盆等几种。 纸盆音色自然、廉价、较好的刚性、材质较轻灵敏度高，缺点是防潮性差、制造时一致性难以控制，但顶级HiFi系统中用纸盆制造的比比皆是，因为声音输出非常平均，还原性好。 防弹布，有较宽的频响与较低的失真，是酷爱强劲低音者之首选，缺点是成本高、制作工艺复杂、灵敏度不高轻音乐效果不甚佳。 羊毛编织盆，质地较软，它对柔和音乐与轻音乐的表现十分优异，但是低音效果不佳，缺乏力度与震撼力。 PP(聚丙烯)盆，它广泛流行于高档音箱中，一致性好失真低，各方面表现都可圈可点。此外还有像纤维类振膜和复合材料振膜等由于价格高昂极少应用于普及型音箱中。 扬声器尺寸自然是越大越好，大口径的低音扬声器能在低频部分有更好的表现，这是在选购之中可以挑选的。用高性能的扬声器制造的音箱意味着有更低的瞬态失真和更好的音质。普通多媒体音箱低音扬声器的喇叭多为3～5英寸之间。用高性能的扬声器制造的音箱也意味着有更低的瞬态失真和更好的音质。 音箱: 有源和无源 有源音箱（ＡｃｔｉｖｅＳｐｅａｋｅｒ）又称为“主动式音箱”。通常是指带有功率放大器的音箱，如多媒体电脑音箱、有源超低音箱，以及一些新型的家庭影院有源音箱等。有源音箱由于内置了功放电路，使用者不必考虑与放大器匹配的问题，同时也便于用较低电平的音频信号直接驱动。 精神分裂症的发病原因是什么 精神分裂症是一种精神病，对于我们的影响是很大的，如果不幸患上就要及时做好治疗，不然后果会很严重，无法进行正常的工作和生活，是一件很尴尬的事情。因此为了避免患上这样的疾病，我们就要做好预防，今天我们就请广州协佳的专家张可斌来介绍一下精神分裂症的发病原因。 精神分裂症是严重影响人们身体健康的一种疾病，这种疾病会让我们整体看起来不正常，会出现胡言乱语的情况，甚至还会出现幻想幻听，可见精神分裂症这种病的危害程度。 (1)精神刺激：人的心理与社会因素密切相关，个人与社会环境不相适应，就产生了精神刺激，精神刺激导致大脑功能紊乱，出现精神障碍。不管是令人愉快的良性刺激，还是使人痛苦的恶性刺激，超过一定的限度都会对人的心理造成影响。 (2)遗传因素：精神病中如精神分裂症、情感性精神障碍，家族中精神病的患病率明显高于一般普通人群，而且血缘关系愈近，发病机会愈高。此外，精神发育迟滞、癫痫性精神障碍的遗传性在发病因素中也占相当的比重。这也是精神病的病因之一。 (3)自身：在同样的环境中，承受同样的精神刺激，那些心理素质差、对精神刺激耐受力低的人易发病。通常情况下，性格内向、心胸狭窄、过分自尊的人，不与人交往、孤僻懒散的人受挫折后容易出现精神异常。 (4)躯体因素：感染、中毒、颅脑外伤、肿瘤、内分泌、代谢及营养障碍等均可导致精神障碍，。但应注意，精神障碍伴有的躯体因素，并不完全与精神症状直接相关，有些是由躯体因素直接引起的，有些则是以躯体因素只作为一种诱因而存在。 孕期感染。如果在怀孕期间，孕妇感染了某种病毒，病毒也传染给了胎儿的话，那么，胎儿出生长大后患上精神分裂症的可能性是极其的大。所以怀孕中的女性朋友要注意卫生，尽量不要接触病毒源。 上述就是关于精神分裂症的发病原因，想必大家都已经知道了吧。患上精神分裂症之后，大家也不必过于伤心，现在我国的医疗水平是足以让大家快速恢复过来的，所以说一定要保持良好的情绪。 浅谈音响功放的工作原理 音响中的功放是整个音响设备中的关键部件,所以音响发烧友们都在其上不惜花费人力物力财力进行"摩机",在电源部分,电路的整体布局,用料等方面进行不断改良.本人并不是超级发烧友,充其量算是一位音响爱好者吧,为此在这里我就以一个音响爱好者的身份谈一谈我对音响功放的看法. 功放分胆机与石机,先讨论石机.石机最初的功放为甲类功放,这类功放的功放管的工作点选在管子的线性放大区,所以就算在没有信号输入的情况下,管子也有较大的电流流过,且其负载是一个输出变压器,在信号较强时由于电流大,输出变压器容易出现磁饱和而产生失真,另外为了防止管子进入非线性区,此类放大器往往都加有较深度的负反馈,所以这种功放电路效率低,动态范围小,且频响特性较差.对此人们又推出了一种乙类推挽式功率放大器,这类功放电路其功放管工作在乙类状态,即管子的工作点选在微道通状态,两个放大管分别放大信号的正半周和负半周,然后由输出变压器合成输出.所以流过输出变压器的两组线圈电流方向相反,这就大大地减少了输出变压器的磁饱和现象.另外由于管子工作在乙类状态,这样不仅大大的提高了放大器的效率且也大大的提高了放大器的动态范围,使输出功率大大提高.所以这种功放电路曾流行一时.但人们很快发现,此种功电路由于其功放管工作在乙类工作状态,所以存在小信号交越失真的问题,而且电路需使用两个变压器(一个输出变压器,一个输入变压器),由于变压器是感性负载,所以在整个音频段内,负载特性不均衡,相移失真较严重.为此人们又推出了一种称为OTL的功率放大电路.这种电路的形式其实也是一种推挽电路形式,只不过是去掉了两个变压器,用一个电容器和输出负载进行藕合,这样一来大大的改善了功放的频响特性.晶体管构成的功放电路有了质的飞跃,后来人们又改良了此种电路,推出了OCL和BTL电路,这种电路将输出电容也去掉了,放大器与扬声器采取直接藕合方式,直到现在由晶体管组成的功放电路,其结构基本上是OCL电路或BTL电路.OCL电路与OTL电路不同之处是采取了正负电源供电法,从而能将输出电容取消掉.BTL电路是由两个完全独立的功放模块搭建组成,如图C所示.IC1放大输出的信号一部分通过IC2反相输入端,经IC2反相放大输出,负载(扬声器)则接在两放大器输出之间,这样扬声器就获得由IC1和IC2放大相位相差180度的合成信号了. 不论是OCL或BTL功放电路,由于其去除了输出变压器和输出电容器,使放大器的频响得到展宽。与扬声器配接方面，当功率放大器连接一个标称阻抗低于 托福口语成绩官方评分标准和计分 方式详细解读 托福考试中口语部分的分数往往较难预计，有时候考生自己觉得发挥得很好但实际得分却并不理想,今天给大家带来托福口语成绩官方评分标准和计分方式详细解读,希望能够帮助到大家，下面就和大家分享，来欣赏一下吧。 托福口语成绩官方评分标准和计分方式详细解读 托福口语成绩如何计算? 首先，在托福考试中，判分员分为E-Rater和Human-Rater。E-Rater即机器判分，比如我们的托福阅读和听力部分，包括写作也会用E-Rater先粗判一下基本的拼写和语法方面。 Human-Rater则是主要负责口语部分和写作更高层级的判分工作。 判分员****于不同的岗位，比如大学教授、国际学校教师、美国高等院校考试测评专业的学生等。在经过了笔试、面试和严格的筛选培训流程后才能上岗。然后分配到具体的某个科目专人专项进行判分。以托福口语为例，每个评分员开始判分工作之前都需要完成当日校准。即他们会被要求给一些“预置答案”判分， 这些答案都是由资深判分小组提前定义好了分数，用来检测当日判分员是否能达到准确判分的要求。只有通过了才会被分配真实考生的答案并进行判分。在当天的真实考试判分过程中，系统还会给他们随机分配这样的“预置答案”，以便监控全天判分过程中的准确度。 在我们的考试结束后，考生的口语部分录音回答将被送到ETS总部，由3 到6 位经认证的评分员按照0 到4 的评分标准(五个整数分数段)进行全面评分。判分员在进行判分时，判分系统上会有4、3、2、1、0各个档位的标准答案，供判分员参考以便矫正自己判分的准确度。若判分标答参考不足以帮助判分员界定分数，他们可以申请组长来帮助自己完成判分。最终六道口语题的分数加在一起(0-24分)，取算数平均值(0-4分之间，但会出现小数点后0/.83/.66/.50/.33/.16六种不同情况)根据转换表，来转换为0-30分的总分。 托福口语分数换算表格介绍 第一部分：音响基础知识 音箱参数 1．阻抗（想知道具体这个物流单位是什么意思，百度的知道一下，下同） 阻抗不是电阻，大家在这里常常犯错误，其实阻抗是电阻和电抗的总和。电阻是指在直流电中，物体对电流的阻碍作用。在交流点中，除了电阻会阻碍电流，电容和电感也会阻碍电流，这就是电抗了。据我查到的资料，阻抗值其实对音质没有关键性影响。但是，如果阻抗过低，造成电流过大，也容易使声音失真，对喜欢听音乐的玩家来说，阻抗就显得相对敏感。音箱常见的值有，4、6、8、16国际推荐值为8○（这个是物流欧姆的符号，找不到……用圈代替） 2.灵敏度 灵敏度，指的是音箱输入1W电功率时，在音箱正面，各个有事情的集合中心1M的距离，测试得来的声压级，单位是DB。换个简单的说法，就是灵敏度关系到音箱的音量大小。在同等音量条件下，灵敏度越高的音箱，声音失真的可能性要小得多。音箱高保真音箱的灵敏度在86db，专业级别的音箱在96db以上，选购音箱时可以参考。 3.功率 额定功率：（RMS）简而言之，称为有效功率，即不失真情况下，音箱长期安全使用的最大功率值。通常情况下，只有一些大型多媒体音箱的厂商才有标出该值，大部分厂商标注的是峰值音乐输出功率。 峰值音乐输出功率（PMPO）：多数厂商标的是这个参数，即不考虑失真的情况下，功放的瞬间最大输出功率。这个值即没有考虑失真，又超过一定范围，那它是否有意义呢？其实也可以通过换算得到我们需要的它与额定功率的比值，具体的我也不清楚，资料显示换算比是1比8. 4.信噪比 指的是音箱回放正常声音信号与无信号时噪声信号的比值，也用DB表示。这个值越高，代表音质越好，但是价格也越高…一般2.0音箱的信噪比达到80db 即可，大一点也可以。至于X.1音箱，只要大于75db就ok！ 5.扬声器口径 有的人认为，扬声器口径是越大越好，其实呢？当然不是。因为扬声器口径增大的同时，纸盆在振动的时候就容易变形、损坏，同样会影响音质。所以，低频扬声器口径一般为20-38cm，当然也有60或72cm的超大口径的大炮。中高音扬声器口径通常在2-6cm之间，偶尔有大于9cm的家伙 6.失真度 就是指没有经过放大器放大前的信号，与经过放大的信号作比较，被放大过的信号与未放大过的信号的差别。单位是百分比。对于多媒体音箱来说，失真无法避免，只要控制在一个合理的范围内就好。比如，2.0音箱必需在1%以下，X.1也要在5%以下2.0音箱必需在1%以下，X.1也要在5%以下。 7.重量 音箱越重，说明用的木材比较好，内部的磁钢比较大，这样可以有效提升音质。所以简而言之，重的好，因为舍得用料。（不排除无良商家塞砖块之类的事情，好像发生过……） 精神分裂症的病因是什么 精神分裂症是一种精神方面的疾病，青壮年发生的概率高，一般 在16～40岁间，没有正常器官的疾病出现，为一种功能性精神病。 精神分裂症大部分的患者是由于在日常的生活和工作当中受到的压力 过大，而患者没有一个良好的疏导的方式所导致。患者在出现该情况 不仅影响本人的正常社会生活，且对家庭和社会也造成很严重的影响。 精神分裂症常见的致病因素： 1、环境因素：工作环境比如经济水平低低收入人群、无职业的人群中，精神分裂症的患病率明显高于经济水平高的职业人群的患病率。还有实际的生活环境生活中的不如意不开心也会诱发该病。 2、心理因素：生活工作中的不开心不满意，导致情绪上的失控，心里长期受到压抑没有办法和没有正确的途径去发泄，如恋爱失败， 婚姻破裂，学习、工作中不愉快都会成为本病的原因。 3、遗传因素：家族中长辈或者亲属中曾经有过这样的病人，后代会出现精神分裂症的机会比正常人要高。 4、精神影响：人的心里与社会要各个方面都有着不可缺少的联系，对社会环境不适应，自己无法融入到社会中去，自己与社会环境不相 适应，精神和心情就会受到一定的影响，大脑控制着人的精神世界， 有可能促发精神分裂症。 5、身体方面：细菌感染、出现中毒情况、大脑外伤、肿瘤、身体的代谢及营养不良等均可能导致使精神分裂症，身体受到外界环境的 影响受到一定程度的伤害，心里受到打击，无法承受伤害造成的痛苦，可能会出现精神的问题。 对于精神分裂症一定要配合治疗，接受全面正确的治疗，最好的 疗法就是中医疗法加心理疗法。早发现并及时治疗并且科学合理的治疗，不要相信迷信，要去正规的医院接受合理的治疗，接受正确的治 疗按照医生的要求对症下药，配合医生和家人，给病人创造一个良好 的治疗环境，对于该病的康复和痊愈会起到意想不到的效果。 卫生部办公厅关于印发《脐带血造血干细胞治疗技术管理规 范(试行)》的通知 【法规类别】采供血机构和血液管理 【发文字号】卫办医政发[2009]189号 【失效依据】国家卫生计生委办公厅关于印发造血干细胞移植技术管理规范(2017年版)等15个“限制临床应用”医疗技术管理规范和质量控制指标的通知 【发布部门】卫生部(已撤销) 【发布日期】2009.11.13 【实施日期】2009.11.13 【时效性】失效 【效力级别】部门规范性文件 卫生部办公厅关于印发《脐带血造血干细胞治疗技术管理规范（试行）》的通知 （卫办医政发〔2009〕189号） 各省、自治区、直辖市卫生厅局，新疆生产建设兵团卫生局： 为贯彻落实《医疗技术临床应用管理办法》，做好脐带血造血干细胞治疗技术审核和临床应用管理，保障医疗质量和医疗安全，我部组织制定了《脐带血造血干细胞治疗技术管理规范（试行）》。现印发给你们，请遵照执行。 二〇〇九年十一月十三日 脐带血造血干细胞 治疗技术管理规范（试行） 为规范脐带血造血干细胞治疗技术的临床应用，保证医疗质量和医疗安全，制定本规范。本规范为技术审核机构对医疗机构申请临床应用脐带血造血干细胞治疗技术进行技术审核的依据，是医疗机构及其医师开展脐带血造血干细胞治疗技术的最低要求。 本治疗技术管理规范适用于脐带血造血干细胞移植技术。 一、医疗机构基本要求 （一）开展脐带血造血干细胞治疗技术的医疗机构应当与其功能、任务相适应，有合法脐带血造血干细胞来源。 （二）三级综合医院、血液病医院或儿童医院，具有卫生行政部门核准登记的血液内科或儿科专业诊疗科目。 1.三级综合医院血液内科开展成人脐带血造血干细胞治疗技术的，还应当具备以下条件： （1）近3年内独立开展脐带血造血干细胞和（或）同种异基因造血干细胞移植15例以上。 （2）有4张床位以上的百级层流病房，配备病人呼叫系统、心电监护仪、电动吸引器、供氧设施。 （3）开展儿童脐带血造血干细胞治疗技术的，还应至少有1名具有副主任医师以上专业技术职务任职资格的儿科医师。 2.三级综合医院儿科开展儿童脐带血造血干细胞治疗技术的，还应当具备以下条件： 功放和音箱的接线方法 1、功放分定压式与定阻式： 定压功放一般用于公共场合的公共广播，其特点为单声道输出、高电压低电流输出。 定阻功放多用于专业场合，其特点为立体声输出、低电压高电流输出。 2、我们的功放都是定阻式，下面主要讲定阻功放与音箱。 定阻即是指负载的阻抗要与功放输出阻抗相匹配，所以只要你系统中连接的音箱总电阻与功放一致就行了，不管你的音箱串联、并联或者混联都行。 关于串联和并联的电阻计算公式在初中就学了： 串联时：R=R1+R2 并联时：R=1/(1/R1+1/R2) 比如说， 有2只16Ω的音箱，用我们的CS功放（4Ω/8Ω）去推，可以将音箱并联得到8Ω； 有1台16Ω的功放，要推我们的2只E-8（8Ω），可以将音箱串联得到16Ω； 有1台16Ω功放，要推4只16Ω的音箱，可以将其中两只并联，再将另外两只并联，最后把两组音箱串联得到16Ω； 在我们常用的方案里，1台CS2000功放推4只E-8音箱，就是把E-8两两并联，音箱阻抗变为4Ω，功放自适应为4Ω，功率也相应加大了。 本帖最后由SVSZ 于2011-7-22 16:33 编辑 1、先常规解释功放桥接的定义： 桥接模式(bridge mode)是利用功放内部的两个放大电路相互推挽，从而产生更大输出电压的方式，功放设定为桥接模式后，成为一台单声道放大器，只可以接受一路输入信号进行放大，输出端为两路功放输出的正端之间。 桥接的定义说得很清楚了，设置成桥接模式往往是因为功放的功率不够，而桥接模式下功放的输出功率一般为普通模式下的2-3倍。但是在桥接模式下功放只是单声道输出（推一只音箱，比如常用来推一只低音炮）。 2、桥接方法： 将功放的模式开关调至Bridge，然后把音箱线的正极接到功放左声道的正极，音箱线的负极接到功放右声道的正极，咱们SVS各款功放的桥接开关和接线方法详见下图： （CS系列功放桥接开关，按下状态为桥接模式，弹出状态为立体声模式） （H系列功放桥接开关，从上到下依次为立体声、单声道、桥接模式） 1. 帕萨特前门6.5寸后门6.5寸多数喇叭需要垫喇叭圈原车1DIN可 安装2DIN 2.马自达6前门5*7后门5*7需要垫喇叭圈主机为非规则面板， 和空调共用显示部分 3.广本2.4前门6.5后台板6*9部分喇叭安装时,前门需垫喇叭圈 主机为非规则面板 4.普桑前门4*6后门5拆前喇叭只需翘下喇叭面盖主机1DIN 5.林宝坚尼MURCIELAGO前门 6.5后面6.5主机1DIN 6.保时捷911前门5*7后5*7主机1DIN面板 7.长安之星面包车前仪表台4寸后没有主机1DIN卡带 8.宝马Z4前门5后?主机非标准面板(横向狭长外型) 9.尼桑天籁JK版前6.5后6.5主机非标准 10别克君威：前门5寸套装，后门6×9机头2DIN 11.奥迪,前门6.5分体后门6.5分体 12.宝来前6。5中6。5一D 13.富康、爱丽舍前门：5"同轴后门：5"同轴(简装车型没有)主机：不规则 14.风神蓝鸟前门：6.5"同轴后门：6.5"同轴主机：1DIN(可装2DIN) 15.中华前门5.5代高音后门5.5或没主机1DIN可装2DIN 16.千里马前面5寸后面6.5寸主机1DIN 17.依蓝特前门6.5寸后面6X9 2DIN主机 18.捷达仪表3寸或高音前门没有或6.5寸后台5寸主机1DIN 19.两厢广本飞度前后门6.5寸部分喇叭需要加垫圈增高主机1DIN、2DIN均可 20.风度-2.0前门6寸后门6寸后窗台8寸低音主机2DIN 21.哈飞路宝，前5.25。后4 22.北斗星前5.25。后无 23.qq前4，后4*6 24.2000，仪表台4，前门可改6.5。后6.5但是喇叭罩是方型，最好改6*9 25.五菱之光前4后4 26.三菱帕杰罗v63000老款仪表台4后6*9 27.风神蓝鸟老款前门5*7后台6.5注意喇叭深度，小心碰到尾箱盖的钢簧 28.赛欧前门加垫4*6后台5.25 29.哈飞赛马前门6寸半后门6寸半 30.北斗星前门5寸后门5寸 31.新马自达6前门6寸半后门6寸半 32.凌志400前门4寸(带音箱)后台6X9 33.派里奥前门6寸半后台4X6 34.奇瑞(奇云)前门6寸半后台4X6 35.奇瑞QQ前门4寸后台4X6 36.307前门6寸分体，后门5寸分体头枕后6×9 1DIN可装2DIN 37.长城SAFE 04款前门四寸后侧车壁4寸同轴带小喇叭箱。主机双DIN换后厢喇叭时非常费劲，要把整个门板扒开。还容易断卡笋。 精神分裂症应该怎么治疗 1、坚持服药治疗 服药治疗是最有效的预防复发措施临床大量统计资料表明，大多数精神分裂症的复发与自行停药有关。坚持维持量服药的病人复发率为40%。而没坚持维持量服药者复发率高达80%。因此，病人和家属要高度重视维持治疗。 2、及时发现复发的先兆，及时处理 精神分裂症的复发是有先兆的，只要及时发现，及时调整药物和剂量，一般都能防止复发，常见的复发先兆为：病人无原因出现睡眠不好、懒散、不愿起床、发呆发愣、情绪不稳、无故发脾气、烦躁易怒、胡思乱想、说话离谱，或病中的想法又露头等。这时就应该及时就医，调整治疗病情波动时的及时处理可免于疾病的复发。 3、坚持定期门诊复查 一定要坚持定期到门诊复查，使医生连续地、动态地了解病情，使病人经常处于精神科医生的医疗监护之下，及时根据病情变化调整药量。通过复查也可使端正人及时得到咨询和心理治疗解除病人在生活、工作和药物治疗中的各种困惑，这对预防精神分裂症的复发也起着重要作用。 4、减少诱发因素 家属及周围人要充分认识到精神分裂症病人病后精神状态的薄弱性，帮助安排好日常的生活、工作、学习。经常与病人谈心，帮助病人正确对待疾病，正确对待现实生活，帮助病人提高心理承受能力，学会对待应激事件的方法，鼓励病人增强信心，指导病人充实生活，使病人在没有心理压力和精神困扰的环境中生活。 首先是性格上的改变，塬本活泼开朗爱玩的人，突然变得沉默寡言，独自发呆，不与人交往，爱干净的人也变的不注意卫生、生活 懒散、纪律松弛、做事注意力不集中，总是和患病之前的性格完全 相悖。 再者就是语言表达异常，在谈话中说一些无关的谈话内容，使人无法理解。连最简单的话语都无法准确称述，与之谈话完全感觉不 到重心。 第三个就是行为的异常，行为怪异让人无法理解，喜欢独处、不适意的追逐异性，不知廉耻，自语自笑、生活懒散、时常发呆、蒙 头大睡、四处乱跑，夜不归宿等。 还有情感上的变化，失去了以往的热情，开始变的冷淡、对亲人不关心、和友人疏远，对周围事情不感兴趣，一点消失都可大动干戈。 最后就是敏感多疑，对任何事情比较敏感，精神分裂症患者，总认为有人针对自己。甚至有时认为有人要害自己，从而不吃不喝。 但是也有的会出现难以入眠、容易被惊醒或睡眠不深，整晚做恶梦或者长睡不醒的现象。这些都有可能是患上了精神分裂症。 1.加强心理护理 心理护理是家庭护理中的重要方面，由于社会上普遍存在对精神病人的歧视和偏见，给病人造成很大的精神压力，常表现为自卑、 抑郁、绝望等，有的病人会因无法承受压力而自杀。家属应多给予 些爱心和理解，满足其心理需求，尽力消除病人的悲观情绪。病人 生活在家庭中，与亲人朝夕相处，接触密切，家属便于对病人的情感、行为进行细致的观察，病人的思想活动也易于向家属暴露。家 属应掌握适当的心理护理方法，随时对病人进行启发与帮助，启发 病人对病态的认识，帮助他们树立自信，以积极的心态好地回归社会。 2.重视服药的依从性 精神分裂症病人家庭护理的关键就在于要让病人按时按量吃药维持治疗。如果不按时服药，精神病尤其是精神分裂症的复发率很高。精神病人在医院经过一系统的治疗痊愈后，一般需要维持2~3年的脐带干细胞综述
cochrane评分表
音响入门到高手必看知识
精神分裂症的病因及发病机理
功放与音箱匹配技巧与注意事项
脐带血造血干细胞库管理办法(试行)
音响和音箱有什么区别_音响和音箱的区别介绍
功放与音箱的阻抗匹配
脑卒中评定量表
音响参数分析及图片大全
精神分裂症的发病原因是什么
浅谈音响功放的工作原理
托福口语成绩官方评分标准和计分方式详细解读
音响常识
精神分裂症的病因是什么
卫生部办公厅关于印发《脐带血造血干细胞治疗技术管理规范(试行)
功放和音箱的接线方法
原车汽车音响喇叭尺寸对照表
精神分裂症应该怎么治疗