K-band Spectroscopy of Clusters in NGC 40384039

Massachusetts Institute of TechnologyThe Artificial Intelligence LaboratoryA.I.Memo No.1105A May1989Height and Gradient from ShadingBerthold K.P.HornAbstract:The method described here for recovering the shape of a surface from a shaded image can deal with complex,wrinkled surfaces.Integrability can be enforced easily because both surface height and gradient are represented(A gra-dientfield is integrable if it is the gradient of some surface height function).The robustness of the method stems in part from linearization of the reflectance map about the current estimate of the surface orientation at each picture cell(The reflectance map gives the dependence of scene radiance on surface orientation). The new scheme canfind an exact solution of a given shape-from-shading prob-lem even though a regularizing term is included.The reason is that the penalty term is needed only to stabilize the iterative scheme when it is far from the correct solution;it can be turned offas the solution is approached.This is a reflection of the fact that shape-from-shading problems are not ill-posed when boundary conditions are available,or when the image contains singular points.This paper includes a review of previous work on shape from shading and photoclinometry.Novel features of the new scheme are introduced one at a time to make it easier to see what each contributes.Included is a discussion of im-plementation details that are important if exact algebraic solutions of synthetic shape-from-shading problems are to be obtained.The hope is that better perfor-mance on synthetic data will lead to better performance on real data.Key Words:Photoclinometry,Shape from Shading,Integrability,Smoothness constraint,Variational methods,Depth and Slope,Height and Gradient,Digital Elevation Models.©Massachusetts Institute of Technology,1989 Acknowledgements:This paper describes research done in part at the Artificial Intelli-gence Laboratory of the Massachusetts Institute of Technology.Support for the labora-tory’s artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-85-K-0124.1.BackgroundThefirst method developed for solving a shape-from-shading problem was restricted to surfaces with special reflecting properties[Rindfleisch66]. For the surfaces that Rindfleisch considered,profiles of the solution can be obtained by integrating along predetermined straight lines in the im-age.The general problem was formulated and solved later[Horn70, 75],using the method of characteristic strip expansion[Garabedian64] [John78]applied to the nonlinearfirst-order partial differential image ir-radiance equation.When the light sources and the viewer are far away from the scene being viewed,use of the reflectance map makes the anal-ysis of shape-from-shading algorithms much easier[Horn77][Horn& Sjoberg79].Several iterative schemes,mostly based on minimization of some functional containing an integral of the brightness error,arose later[Woodham77][Strat79][Ikeuchi&Horn81][Kirk84,87][Brooks& Horn85][Horn&Brooks86][Frankot&Chellappa88].The new method presented here was developed in part as a response to recent attention to the question of integrability1[Horn&Brooks86] [Frankot&Chellappa88]and exploits the idea of a coupled system of equations for depth and slope[Harris86,87][Horn88].It borrows from well-known variational approaches to the problem[Ikeuchi&Horn81] [Brooks&Horn85]and an existing least-squares method for estimat-ing surface shape given a needle diagram(see[Ikeuchi84],chapter11 in[Horn86],and[Horn&Brooks86]).For one choice of parameters,the new method becomes similar to one of thefirst iterative methods ever developed for shape from shading on a regular grid[Strat79],while it degenerates into another well-known method[Ikeuchi&Horn81]for a different choice of parameters.If the brightness error term is dropped, then it becomes a surface interpolation method[Harris86,87].The com-putational effort grows rapidly with image size,so the new method can benefit from proper multigrid implementation[Brandt77,80,84][Brandt &Dinar79][Hackbush85][Hackbush&Trottenberg82],as can existing iterative shape-from-shading schemes[Terzopolous83,84][Kirk84,87]. Alternatively,one can apply so-called direct methods for solving Poisson’s equations[Simchony,Chellappa&Shao89].Experiments indicate that linear expansion of the reflectance map about the current estimate of the surface gradient leads to more rapid convergence.More importantly,this modification often allows the scheme to converge when simpler schemes diverge,or get stuck in local minima of the functional.Most existing iterative shape-from-shading methods1A gradientfield is integrable if it is the gradient of some surface height function.2Height and Gradient from Shadinghandle only relatively simple surfaces and so could benefit from a retrofit of this idea.The new scheme was tested on a number of synthetic images of in-creasing complexity,including some generated from digital terrain mod-els of steep,wrinkled surfaces,such as a glacial cirque with numerous gullies.Shown in Figure1(a)is a shaded view of a digital terrain model, with lighting from the Northwest.This is the input provided to the algo-rithm.The underlying231×178digital terrain model was constructed from a detailed contour map,shown in Figure2,of Huntington ravine on the eastern slopes of Mount Washington in the White Mountains of New Hampshire2.Shown in Figure1(b)is a shaded view of the same digital terrain model with lighting from the Northeast.This is not available to the algorithm,but is shown here to make apparent features of the sur-face that may not stand out as well in the other shaded view.Figure1(c) shows a shaded view of the surface reconstructed by the algorithm,with lighting from the Northwest—it matches Figure1(a)exactly.More impor-tantly,the shaded view of the reconstructed surface with lighting from the Northeast,shown in Figure1(d),matches Figure1(b)exactly also3.With proper boundary conditions,the new scheme recovers surface orientation exactly when presented with noise-free synthetic scenes4.Pre-vious iterative schemes do notfind the exact solution,and in fact wander away from the correct solution when it is used as the initial guess.To ob-tain exact algebraic solutions,several details of the implementation have to be carefully thought through,as discussed in section6.Simple sur-faces are easier to process—with good results even when several of the implementation choices are not made in an optimal way.Similarly,these details perhaps may be of lesser importance for real images,where other error sources could dominate.In the next few sections we review image formation and other elemen-tary ideas underlying the usual formulation of the shape-from-shading problem.Photoclinometry is also briefly reviewed for the benefit of re-searchers in machine vision who may not be familiar with thisfield.We then discuss both the original and the variational approach to the shape-2The gullies are steep enough to be of interest to ice-climbers.3For additional examples of reconstructions from shaded images,see section7. 4In the examples tried,the algorithm always recovered the underlying surface orientation exactly at every picture cell,starting from a random surface ori-entationfield,provided that boundary information was available.Since the question of uniqueness of solutions has not been totally resolved,one cannot be quite certain that there may not be cases where a different solution might be found that happens to alsofit the given image data exactly.1.Background3Figure1.Reconstruction of surface from shaded image.See text.4Height and Gradient from ShadingFigure2.Contour map from which the digital terrain model used tosynthesize Figures1(a)and(b)was interpolated.The surface was mod-eled as a thin plate constrained to pass through the contours at thespecified elevations.The interpolating surface was found by solvingthe biharmonic equation,as described at the end of section5.4.from-shading problem.Readers familiar with the basic concepts may wish to skip over this material and go directly to section5,where the new scheme is derived.For additional details see chapters10and11in Robot Vision[Horn86]and the collection of papers,Shape from Shading[Horn &Brooks89].2.Review of Problem Formulation2.1Image Projection and Image IrradianceFor many problems in machine vision it is convenient to use a camera-2.Review of Problem Formulation5centered coordinate system with the origin at the center of projection and the Z-axis aligned with the optical axis(the perpendicular from the center of projection to the image plane)5.We can align the X-and Y-axes with the image plane x-and y-axes.Let the principal distance(that is,the perpendicular distance from the center of projection to the image plane) be f,and let the image plane be reflected through the center of projection so that we avoid sign reversal of the coordinates.Then the perspective projection equations arex=f XZand y=fYZ.(1)The shape-from-shading problem is simplified if we assume that the depth range is small compared with the distance of the scene from the viewer (which is often the case when we have a narrowfield of view,that is,when we use a telephoto lens).Then we havex≈fZ0X and y≈fZ0Y,(2)for some constant Z0,so that the projection is approximately orthographic. In this case it is convenient to rescale the image coordinates so that we can write x=X and y=Y.For work on shape from shading it is also convenient to use z,height above some reference plane perpendicular to the optical axis,rather than the distance measured along the optical axis from the center of projection.If we ignore vignetting and other imaging system defects,then im-age irradiance E at the point(x,y)is related to scene radiance L at the corresponding point in the scene by[Horn86]E=L π4df2cos4α,(3)where d is the diameter of the lens aperture,f is the principal distance, and the off-axis angleαis given bytanα=1fx2+y2.(4)Accordingly,image irradiance6is a multiple of the scene radiance,with the factor of proportionality depending inversely on the square of the f-5In photoclinometry it is customary to use an object-centered coordinate system.This is because surface shape can be computed along profiles only when strong additional constraint is provided,and such constraints are best expressed in an object-centered coordinate system.Working in an object-centered coordinate system,however,makes the formulation of the shape-from-shading problem considerably more complex(see,for example,[Rindfleisch66]).6Grey-levels are quantized estimates of image irradiance.6Height and Gradient from Shadingnumber7.If we have a narrowfield of view,the dependence on the off-axis angleαcan be neglected.Alternatively,we can normalize the image by dividing the observed image irradiance by cos4α(or whatever the actual vignetting function happens to be).We conclude from the above that what we measure in the image is directly proportional to scene radiance,which in turn depends on(a)the strength and distribution of illumination sources,(b)the surface micro-structure and(c)surface orientation.In order to be able to solve the shape from shading problem from a single image we must assume that the surface is uniform in its reflecting properties.If we also assume that the light sources are far away,then the irradiance of different parts of the scene will be approximately the same and the incident direction may be taken as constant.Finally,if we assume that the viewer is far away,then the direction to the viewer will be roughly the same for all points in the scene.Given the above,wefind that scene radiance does not depend on the position in space of a surface patch,only on its orientation.2.2Specifying Surface OrientationMethods for recovering shape from shading depend on assumptions about the continuity of surface height and its partial derivatives.First of all, since shading depends only on surface orientation,we must assume that the surface is continuous and that itsfirst partial derivatives exist.Most formulations implicitly also require that thefirst partial derivatives be continuous,and some even require that second partial derivatives exist. The existence and continuity of derivatives lends a certain“smoothness”to the surface and allows us to construct local tangent planes.We can then talk about the local surface orientation in terms of the orientation of these tangent planes.There are several commonly used ways of specifying the orientation of a planar surface patch,including:•Unit surface normalˆn[Horn&Brooks86];•Point on the Gaussian sphere[Horn84];•Surface gradient(p,q)[Horn77];•Stereographic coordinates(f,g)[Ikeuchi&Horn81];7The f-number is the ratio of the principal distance to the diameter of the aper-ture,that is,f/d.2.Review of Problem Formulation7•Dip and strike(as defined in geology)8;•Luminance longitude and latitude(as defined in astrogeology)9;•Incident and emittance angles(i and e)10;For our purposes here,the components of the surface gradientp=∂z∂xand q=∂z∂y,(5)will be most directly useful for specifying surface orientation.We can convert between different representations easily.For exam-ple,suppose that we are to determine the unit surface normal given the gradient components.We know that if we move a small distanceδx in x, then the change in height isδz=pδx(since p is the slope of the surface in the x direction).Thus(1,0,p)T is a tangent to the surface.If we move a small distanceδy in y,then the change in height isδz=qδy(since q is the slope of the surface in the y direction).Thus(0,1,q)T is also a tangent to the surface.The normal is perpendicular to all tangents,thus parallel to the cross-product of these particular tangents,that is parallel to(−p,−q,1)T.Hence a unit normal can be written in the formˆn=11+p2+q2(−p,−q,1)T.(6)Note that this assumes that the z-component of the surface normal is pos-itive.This is not a problem since we can only see surface elements whose normal vectors point withinπ/2of the direction toward the viewer—other surface elements are turned away from the viewer.We can use the same notation to specify the direction to a collimated light source or a small portion of an extended source.We simply give the orientation of a surface element that lies perpendicular to the incident8Dip is the angle between a given surface and the horizontal plane,while strike is the direction of the intersection of the surface and the horizontal plane.The line of intersection is perpendicular to the direction of steepest descent.9Luminance longitude and latitude are the longitude and latitude of a point ona sphere with the given orientation,measured in a spherical coordinate systemwith the poles at right angles to both the direction toward the source and the direction toward the viewer.10Incident and emittance angles are meaningful quantities only when there is a single source;and even then there is a two-way ambiguity in surface orienta-tion unless additional information is provided.The same applies to luminance longitude and latitude.8Height and Gradient from Shading light rays.So we can write11ˆs=11+p2s+q2s(−p s,−q s,1)T,(7)for some p s and q s.2.3Reflectance MapWe can show the dependence of scene radiance on surface orientation in the form of a reflectance map R(p,q).The reflectance map can be depicted graphically in gradient space12as a series of nested contours of constant brightness[Horn77,86].The reflectance map may be determined experimentally by mount-ing a sample of the surface on a goniometer stage and measuring its brightness under the given illuminating conditions for various orienta-tions.Alternatively,one may use the image of a calibration object(such as a sphere)for which surface orientation is easily calculated at every point.Finally,a reflectance map may be derived from a phenomenolog-ical model,such as that of a Lambertian surface.In this case one can integrate the product of the bidirectional reflectance distribution function (BRDF)and the given distribution of source brightness as a function of incident angle[Horn&Sjoberg79].An ideal Lambertian surface illuminated by a single point source pro-vides a convenient example of a reflectance map13.Here the scene radi-ance is given by R(p,q)=(E0/π)cos i,where i is the incident angle(the angle between the surface normal and the direction toward the source), while E0is the irradiance from the source on a surface oriented perpendic-ular to the incident rays.(The above formula only applies when i≤π/2; the scene radiance is,of course,zero for i>π/2.)Now cos i=ˆn·ˆs,soR(p,q)=E0π1+p s p+q s q1+p2+q21+p2s+q2s,(8)as long as the numerator is positive,otherwise R(p,q)=0.11There is a small problem,however,with this method for specifying the direction toward the light source:A source may be“behind”the scene,with the direction to the source more thanπ/2away from the direction toward the viewer.In this case the z-component of the vector pointing toward the light source is negative. 12The coordinates of gradient space are p and q,the slopes of the surface in the x and y direction respectively.13Note that shape-from-shading methods are most definitely not restricted to Lambertian surfaces.Such special surfaces merely provide a convenient peda-gogical device for illustrating basic concepts.2.Review of Problem Formulation92.4Image Irradiance EquationWe are now ready to write down the image irradiance equation E(x,y)=βR p(x,y),q(x,y) ,(9)where E(x,y)is the irradiance at the point (x,y)in the image,while R(p,q)is the radiance at the corresponding point in the scene,at which p =p(x,y)and q =q(x,y).The proportionality factor βdepends on the f -number of the imaging system (and may include a scaling factor that depends on the units in which the instrument measures brightness).It is customary to rescale image irradiance so that this proportionality factor may be dropped.If the reflectance map has a unique global extremum,for example,then the image can be normalized in this fashion,provided that a point can be located that has the corresponding surface orientation 14.Scene radiance also depends on the irradiance of the scene and a re-flectance factor (loosely called albedo here).These factors of proportion-ality can be combined into one that can be taken care of by normaliza-tion of image brightness.Then only the geometric dependence of image brightness on surface orientation remains in R(p,q),and we can write the image irradiance equation in the simple form E(x,y)=R p(x,y),q(x,y) (10)orE(x,y)=R z x (x,y),z y (x,y) ,(11)where p =z x and q =z y are the first partial derivatives of z with respect to x and y .This is a first-order partial differential equation;one that is typically nonlinear,because the reflectance map in most cases depends nonlinearly on the gradient.2.5Reflectance Map Linear in GradientViewed from a sufficiently great distance,the material in the maria of the moon has the interesting property that its brightness depends only on luminance longitude,being independent of luminance latitude [Hapke 63,65].When luminance longitude and latitude are related to the incident and emittance angles,it is found that longitude is a function of (cos i/cos e).From the above we see that cos i =ˆn ·ˆs ,while cos e =ˆn ·ˆv ,where ˆv =14If there is a unique maximum in reflected brightness,it is convenient to rescale the measurements so that this extremum corresponds to E =1.The same applies when there is a unique minimum,as is the case for the scanning electron microscope (SEM).10Height and Gradient from Shading (0,0,1)T is a unit vector in the direction toward the viewer.Consequently,cos i cos e =ˆn·ˆsˆn·ˆv=11+p2s+q2s(1+p s p+q s q).(12)Thus(cos i/cos e)depends linearly on the gradient components p and q, and we can writeR(p,q)=f(c p+s q),(13) for some function f and some coefficients c and s.Both Lommel-Seeliger’s and Hapke’s functionsfit this mold[Minnaert61][Hapke63,65].(For a few other papers on the reflecting properties of surfaces,see[Hapke81, 84][Hapke&Wells81]and the bibliography in[Horn&Brooks89].)We can,without loss of generality15,arrange for c2+s2=1.If the function f is continuous and monotonic16,we canfind an in-versec p+s q=f−1E(x,y).(14)The slope in the image direction(c,s)ism=c p+s q√c2+s2=1√c2+s2f−1E(x,y).(15)We can integrate17out this slope along the linex(ξ)=x0+cξand y(ξ)=y0+sξ,(16) to obtainz(ξ)=z0+1√c2+s2ξf−1Ex(η),y(η)dη.(17)An extension of the above approach allows one to take into account per-spective projection as well asfinite distance to the light source[Rind-fleisch66].Two changes need to be made;one is that the reflectance map now is no longer independent of image position(since the directions to the viewer and the source vary significantly);and the other that the integral is for the logarithm of the radial distance from the center of projection, as opposed to distance measured parallel to the optical axis.The above was thefirst shape-from-shading or photoclinometric prob-lem ever solved in other than a heuristic fashion.The original formulation was considerably more complex than described above,as the result of the15We see that c:s=p s:q s,so that the direction specified in the image by(c,s) is the direction“toward the source,”that is,the projection into the image plane of the vectorˆs toward the light source.16If the function f is not monotonic,there will be more than one solution for certain brightness values.In this case one may need to introduce assumptions about continuity of the derivatives in order to decide which solution to choose. 17The integration is,of course,carried out numerically,since the integrand is derived from image measurements and not represented as an analytic function.2.Review of Problem Formulation 11use of full perspective projection,the lack of the notion of anything like the reflectance map,and the use of an object-centered coordinate system[Rindfleisch 66].Note that we obtain profiles of the surface by integrating along pre-determined straight lines in the image.Each profile has its own unknown constant of integration,so there is a great deal of ambiguity in the recov-ery of surface shape.In fact,if z(x,y)is a solution,so isz(x,y)=z(x,y)+g(s x −c y)(18)for an arbitrary function g !This is true becausez x =z x +s g (s x −c y)and z y =z y −c g (s x −c y),(19)so c p +s q =c p +s q,(20)where p =z x and q =z y .It follows that R(p,q)=R(p,q).This ambi-guity can be removed if an initial curve is given from which the profiles can be started.Such an initial curve is typically not available in practice.Ambiguity is not restricted to the special case of a reflectance map that is linear in the gradient:Without additional constraint shape-from-shading problems typically do not have a unique solution.2.6Low Gradient Terrain and Oblique IlluminationIf we are looking at a surface where the gradient (p,q)is small,we can approximate the reflectance map using series expansionR(p,q)≈R(0,0)+p R p (0,0)+q R q (0,0).(21)This approach does not work when the reflectance map is rotationally symmetric,since the first-order terms then drop out 18.If the illumination is oblique,however,we can apply the method in the previous section to get a first estimate of the surface.Letting c =R p (0,0),s =R q (0,0)and f −1 E(x,y) =E(x,y)−R(0,0),(22)we find thatz(ξ)=z 0+1R 2p (0,0)+R 2q (0,0) ξ0 E x(η),y(η) −R(0,0)dη.(23)(For a related frequency domain approach see [Pentland 88].)One might imagine that the above would provide a good way to get initial conditions for an iterative shape from shading method.Unfortu-nately,this is not very helpful,because of the remaining ambiguity in the 18The reflectance map is rotationally symmetric,for example,when the source is where the viewer is,or when an extended source is symmetrically distributed about the direction toward the viewer.12Height and Gradient from Shadingdirection at right angles to that of profile integration.Iterative methods already rapidly get adequate variations in height along“down-sun pro-files,”but then struggle for a long time to try to get these profiles tied together in the direction at right angles.The above also suggests that errors in gradients of a computed so-lution are likely to be small in the direction towards or away“from the source”and large in the direction at right angles.It should also be clear that it is relatively easy tofind solutions for slowly undulating surfaces (where p and q remain small)with oblique illumination(as in[Kirk87]).It is harder to deal with cases where the surface gradient varies widely,and with cases where the source is near the viewer(see also the discussion in section7.3).3.Brief Review of PhotoclinometryPhotoclinometry is the recovery of surface slopes from images[Wilhelms64] [Rindfleisch66][Lambiotte&Taylor67][Watson68][Lucchitta&Gam-bell70][Tyler,Simpson&Moore71][Rowan,McCauley&Holm71][Bonner &Small73][Wildey75][Squyres81][Howard,Blasius&Cutt82].Many pa-pers and abstracts relating to this subject appear in places that may seem inaccessible to someone working in machine vision[Davis,Soderblom, &Eliason82][Passey&Shoemaker82][Davis&McEwen84][Davis& Soderblom83,84][Malin&Danielson84][Wilson et al.84][McEwen85] [Wilson et al.85](For additional references see Shape from Shading[Horn &Brooks89]).Superficially,photoclinometry may appear to be just an-other name for shape from shading.Two different groups of researchers independently tackled the problem of recovering surface shape from spa-tial brightness variations in single images.Astrogeologists and workers in machine vision became aware of each other’s interests only a few years ago.The underlying goals of the two groups are related,but there are some differences in approach that may be worthy of a brief discussion.3.1Photoclinometry versus Shape from Shading•First,photoclinometry has focused mostly on profile methods(pho-toclinometrists now refer to existing shape-from-shading methods as area-based photoclinometry,as opposed to profile-based).This came about in large part because several of the surfaces of interest to the astrogeologist have reflecting properties that allow numeri-cal integration along predetermined lines in the image,as discussed3.Brief Review of Photoclinometry13above in section2.5[Rindfleisch66].Later,a similar profile integra-tion approach was applied to other kinds of surfaces,by using strong assumptions about local surface geometry instead.The assumption that the surface is locally cylindrical leads to such a profile integra-tion scheme[Wildey86],for example.More commonly,however,it has been assumed that the cross-track slope is zero,in a suitable object-centered coordinate system[Squyres81].This may be reason-able when one is considering a cross-section of a linearly extended feature,like a ridge,a graben,or a central section of a rotationally symmetric feature like a crater.•The introduction of constraints that are easiest to express in an object-centered coordinate system leads away from use of a camera-centered coordinate system and to complex coordinate transformations that tend to obscure the underlying problem.A classic paper on photo-clinometry[Rindfleisch66]is difficult to read for this reason,and asa result had little impact on thefield.On the other hand,it must beacknowledged that this paper dealt properly with perspective projec-tion,which is important when thefield of view is large.In all but the earliest work on shape from shading[Horn70,75],the assump-tion is made that the projection is approximately orthographic.This simplifies the equations and allows introduction of the reflectance map.•The inherent ambiguity of the problem does not stand out as ob-viously when one works with profiles,as it does when one tries to fully reconstruct surfaces.This is perhaps why workers on shape from shading have been more concerned with ambiguity,and why they have emphasized the importance of singular points and occlud-ing boundaries[Bruss82][Deift&Sylvester81][Brooks83][Blake, Zisserman&Knowles85][Saxberg88].•The recovery of shape is more complex than the computation of a set of profiles.Consequently much of the work in shape from shading has been restricted to simple shapes.At the same time,there has been extensive testing of shape from shading algorithms on synthetic data.This is something that is important for work on shape from shading, but makes little sense for the study of simple profile methods,except to test for errors in the procedures used for inverting the photometric function.•Shape-from-shading methods easily deal with arbitrary collections of collimated light sources and extended sources,since these can be ac-commodated in the reflectance map by integrating the BRDF and the。

丛生蛋白在肾远曲小管的表达及其与肾结石关系的初步研究刘俊江;李守宾;李瑾宜;冯启红;王刚;魏东;孙振福;杨涛;张蕴霞【摘要】目的探讨Clusterin在肾脏远曲小管的表达与肾结石的关系.方法用免疫组化方法检测肾结石患者及对照组肾脏组织切片中clusterin表达情况,并作比较分析.结果 Clusterin在肾结石组及对照组肾远曲小管均有阳性表达,45例肾结石组患者平均表达强度评分为190.73±80.00,38例对照组为97.76±63.57,肾结石组表达强度评分明显高于对照组(P＜0.001).结论 clusterin表达于肾远曲小管,在肾结石患者中表达明显增强,提示肾远曲小管损伤与肾结石的形成有关.【期刊名称】《现代泌尿外科杂志》【年(卷),期】2016(021)001【总页数】3页(P24-26)【关键词】肾结石;结石形成;从生蛋白;肾远曲小管;免疫组化【作者】刘俊江;李守宾;李瑾宜;冯启红;王刚;魏东;孙振福;杨涛;张蕴霞【作者单位】河北省人民医院泌尿外科,河北石家庄050051;开滦总医院泌尿外科,河北唐山063000;西奈山医院,美国纽约;开滦总医院泌尿外科,河北唐山063000;河北省人民医院泌尿外科,河北石家庄050051;河北省人民医院泌尿外科,河北石家庄050051;河北省人民医院泌尿外科,河北石家庄050051;河北省人民医院泌尿外科,河北石家庄050051;河北省人民医院妇产科,河北石家庄050051【正文语种】中文【中图分类】R692.4·临床研究·肾结石是泌尿外科最常见的疾病之一，但是泌尿系结石的发生机制仍不十分明确，关于肾结石形成起源部位也存在争议。

丛生蛋白(Clusterin)是一种广泛存在于人体组织和体液中的凋亡相关蛋白，参与多种生理过程，在很多肾脏损害模型中表达明显升高，且早于肌酐的变化[1]。

肾结石的发生也伴随着肾小管上皮损伤等病理过程，Clusterin是否参与肾结石的发生过程，目前尚无相关研究，为了探讨Clusterin与肾结石发生的关系，我们检测了肾结石患者和非泌尿系结石患者肾组织中Clusterin的表达，并做比较分析。

科谱类的小作文100字左右英文回答：Spectroscopy is a fascinating field that involves the study of the interaction between matter and electromagnetic radiation. It helps us understand the composition, structure, and properties of substances. There are various types of spectroscopy, such as UV-Vis spectroscopy,infrared spectroscopy, and nuclear magnetic resonance spectroscopy.UV-Vis spectroscopy measures the absorption of ultraviolet and visible light by a substance. It is commonly used in chemistry to determine the concentration of a compound in a solution. For example, I once used UV-Vis spectroscopy to measure the concentration of a dye in a fabric sample. By analyzing the absorption spectrum, I was able to determine the dye concentration accurately.Infrared spectroscopy, on the other hand, measures theabsorption of infrared light by a substance. It provides information about the functional groups present in a molecule. I remember using infrared spectroscopy toidentify the type of alcohol in a solution. The characteristic peaks in the infrared spectrum helped me determine whether it was a primary, secondary, or tertiary alcohol.Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for determining the structure of organic molecules. It utilizes the magnetic properties of certain atomic nuclei to provide detailed information about the connectivity and environment of atoms in a molecule. For instance, I used NMR spectroscopy to determine thestructure of an unknown compound. By analyzing the chemical shifts and coupling patterns in the NMR spectrum, I was able to identify the different functional groups present in the molecule.Overall, spectroscopy plays a crucial role in various scientific fields, including chemistry, biochemistry, and materials science. It allows us to analyze and understandthe properties of substances in a non-destructive manner, making it an indispensable tool in research and industry.中文回答：科谱学是一门迷人的领域，涉及物质与电磁辐射之间的相互作用的研究。

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Astronomical ScienceStar-Forming Nuclear Rings in Spiral GalaxiesJesús Falcón-Barroso1Torsten Böker1Eva Schinnerer2Johan H. Knapen3Stuart Ryder41E uropean Space Agency, Noordwijk, the Netherlands,2M ax-Planck-Institut für Astronomie,H eidelberg, Germany3I nstituto de Astrofísica de Canarias, Tenerife, Spain4A nglo-Australian Observatory, Epping, AustraliaThe study of gas transport to the inner regions of galaxies is a fundamentala spect in our understanding of the way galaxies evolve. In this context, star-forming nuclear rings are key features as they contain large amounts of gas and are the sites where a significant fraction of the current star formation is taking place in their host galaxies. Here we present some results from a study of how star formation progresses along nuclear star-forming rings in five spiral galaxies, based on near-infrared SIN-FONI integral-field observations at the VLT.Nuclear RingsThe basic picture of how nuclear rings form is well established, both from a the-oretical and an observational perspective (see Buta and Combes 1996 for a review). They are usually associated with the in-terplay between bar-driven gas inflow and the bar resonances. Perturbations in the gravitational potential, nearly always due to the presence of a stellar bar or oval distortion, causes the gas to loose angu-lar momentum and spiral in towards the nucleus. Because of its dissipative na-ture, gas accumulates at the radii where the stellar orbits experience dynamical resonances with the rotating bar poten-tial. In the case of the nuclear rings dis-cussed here, this gas accumulation typ-ically happens at the so-called Inner Lindblad resonance. When observed in more detail, the gas is found to enter the ring via two tightly wound spiral arms or dust lanes. At the contact points between the dust lanes and the ring, the gas be-comes less turbulent, and enters almostcircular orbits, which delineate the ring.While it is clear that there is abundant(mo l ecular) gas throughout the ring, therehas been an on-going debate about howand where star formation occurs.Integral-field observations of nuclear ringsIntegral-field spectroscopy allows thes imultaneous measurement of a largenumber of spectra over a two-dimen-sional field of view. We used SINFONI H-and K-band spectroscopy to study thetwo-dimensional morphology and kine-matics of star-forming nuclear rings in fivespiral galaxies drawn from a large sampleof galaxies observed in H a by Knapenet al. (2006). In Figure 1 we show a col-our-composite image of one of the galax-ies in our sample (NGC 613), highlightingthe main structural features and in par-ticular the nuclear ring discussed in thefollowing.Figure 2 shows the intensity and veloc -ity maps for some of the most promi-nent spectral features in NGC 613. TheBr g emission shows a clearly definedring structure, composed of seven almostregularly spaced bright clumps that arethe sites of current massive star forma-tion. These ‘hot spots’ are brightest alongthe southern half of the ring, while thenorthern half shows a well-defined ‘gap’at PA 30˚ which is also evident in the[Fe ii] emission map. This direction agreeswell with that of the radio jet found byHummel et al. (1987). It thus appears thata mechanical outflow from the centrala ctive black hole has disturbed the ringmorphology.H2 emission is also apparent in the nu-clear ring, but is strongest in the nucleus.The H2 in the ring is not composed of dis-tinct hot spots like the Br g emission, butis more smoothly distributed. There aretwo emission peaks, found on oppositesides of the ring, at approximate PAs of90˚ and 270˚. If the H2 emission in the ringof NGC 613 were caused purely by UVradiation, one might expect a spatial cor-respondence between H2 and the ionisedgas traced by Br g and/or He i. However,many of the Br g hot spots are not brightin H2. Therefore, the H2 emission proba-bly contains a non-negligible contributionfrom shock-heated molecular gas.The nuclear spectrum shown in the bot-tom panel of Figure 2 highlights the pres-ence of molecular emission (H2) and thecomplete absence of hydrogen recombi-nation lines (e.g. Br g). In contrast, then uclear spectra of the remaining galaxiesin our sample (not shown here) appearrather quiescent, i.e. their spectra are de-void of any line emission. This is not un-expected in a scenario in which gas ac-cumulates at the nucleus over time until acritical density is reached. Star formationis then triggered, but can continue onlyuntil the gas supply is consumed or theenergetic outflow from supernova explo-Figure 1: Colour-composite image ofNGC 613 taken with FORS1 andFORS2 instruments (ESO Press Photo33a/03). Labels highlight some of themain morphological features.Nuclear RingBarSpiral Arms40The Messenger 130 – December 200741The Messenger 130 – December 2007‘quenching’ the star formation. This sce-nario is entirely consistent with observa-tions, at least for late-type spirals: only about 10% of nuclear star clusters cur-rently show emission lines, although most of them harbour a young stellar popula-tion of less than 100 Myr old (Rossa et al. 2006). This can naturally be explained if star formation in galactic nuclei is epi-sodic in nature, with a duty cycle of about 10%.In Figure 2 we also show the stellar and ionised-gas kinematics for NGC 613. The stellar velocity field appears rather regular, despite the intense star forma -tion within the nuclear ring. Because Br g is generally the most prominent emis- sion line in our data, we used it to make an estimate of the ionised gas kinemat -ics. In all galaxies of our sample, the ve-locity gradients within the nuclear rings are smooth and the ionised gas has the same sense of rotation as the stars.Measuring the relative ages of the differ-ent stellar clusters (i.e. hot spots) along the ring is a difficult task. The orbital time-scales in the ring are short (e.g. a few tens of Myr). In order to perform the age dating, it is therefore imperative that one uses tracers that are sensitive to these time-scales. The most widely used diag-nostic for this purpose is the H a emission line. There are several reasons why this line is a popular choice. First, it is an opti-cal emission line that can easily be meas-ured. Second, its equivalent width (EW) decreases almost monotonically with time for an instantaneous burst allowing one to determine the evolutionary stage of a cluster from the EW value alone. The use of this emission line, however, is limited to clusters in the age range be-tween 3 and 10 Myr, and therefore any in-ferred age differences have to be small (few Myr). Below 3 Myr, the EW of the H a is almost constant, and above 10 Myr thevalue is well below typical detection limits (~ 1 Å).An alternative approach is to make use of several spectral lines, whose emission peaks at different cluster ages. In our case, we use the flux of three emission lines that are prominent in the NIR spec-tra of the star-forming regions in ours ample of galaxies: He i , Br g , and [Fe ii ]. Under the assumption that the underly-ing bulge/disc can be considered quies-cent, and that most of the emission is produced in the ring itself, line fluxes are a better probe than the EWs. The reason is that EWs require an accurate knowl-edge of the continuum emission, not only for the hot spot itself, but also for the un-derlying bulge and/or disc, which is very hard to measure. The He i and Br g lines are both produced by photoionisation in the vicinity of hot O- or B-type stars. Given that the ionisation energy for the He i line is higher than that of Br g , it re-quires the presence of hotter and more massive stars, and hence its brightness falls off more rapidly after an instantane-ous burst than that of the Br g line. The time range covered by these two lines is from 0 to 10 Myr. Larger ages can be probed with the [Fe ii ] line (a tracer of fast shocks produced in supernova remnants)whose contribution is almost constant from 3 to 35 Myr, and decreases sharply after that. Using the relative strength of those three lines, we are therefore able to probe ages in the range between 0 and 35 Myr, which represents a good match to the expected travel time of gas and star clusters along the nuclear ring. Star formation along the ringsFigure 3 illustrates two plausible mecha-nisms that describe how star formation could proceed along the circumnuclear rings. In the first scenario, the popcorn model, gas enters the ring and accumu-1.0E -16/5.0E -14–22a r c s e cFe II–202arcsec–22a r c s e c1.0E -16/2.5E -14H 21.0E -16/5.0E -14He I arcsec1.0E -16/5.0E -14Br γarcsecFigure 2: SINFONI near-infrared integral-field spec-troscopy of NGC 613. Top row shows the morphol-ogy in the [Fe ii ], He i and Brackett-g emission; lower row the H 2 emission morphology, the stellar kine-matics (V(star)) and the Brackett-g kinematics (V(Br g )) of the nuclear ring in this galaxy. The black contours delineate the K -band light measured from the SIN-FONI observations while ellipses in the Br g map de-limit the extension of the ring. Bottom panel shows the nuclear spectrum of NGC 613 with the main spectral features highlighted.42The Messenger 130 – December 2007Astronomical Science Falcón-Barroso J. et al., Star-Forming Nuclear Rings in Spiral GalaxiesFigure 3: Two possible scenarios describing how star formation pro g resses along a nuclear ring. Left: the popcorn model, where star formation occurs randomly along the ring. Right: the pearls on a string scenario, where the ages of the stellar cluster de- fine two sequences of increasing age along the ring. (Courtesy of J. Paillet, ESA)lates around it with no preferred location. Once a critical density is reached, the gas becomes unstable to gravitational collapse and star formation is triggered. In this model, individual hot spots col-lapse at random times and locations within the ring, and therefore there is no systematic age sequence. In the figure (left plot) the different starbursts are de-noted by the star symbols and the differ-ent colours indicate different ages of the hot spots. In the second scenario (right), gas enters the ring at the intersection be-tween the bar major axis and the inner Lindblad resonance. Downstream from this location, at the so-called over-den-sity region (ODR), the gas density be-comes sufficiently high to ignite star for-mation in a short-lived burst. A young cluster formed there will continue its orbit around the ring, but star formation will cease as soon as the first supernova ex-plosions expel the gas. A series of star-bursts triggered in the ODR will then pro-duce a sequence of star clusters thatenter the ring like pearls on a string . In this scenario, the star clusters should show a bipolar age gradient along the ring, with the youngest clusters found close to the ODR, and increasingly older cluster ages in the direction of rotation, up to the opposite ODR. This is shown in the figure, where the colour sequence blue-green-red denotes clusters with in-creasing age.In Figure 4 we put these two models to the test by showing the observations for NGC 613. In the left panel we display an F666W HST image of the nuclear regions. The ring is outlined with an ellipse, and two star symbols mark roughly the posi-tions of the ODRs (based on the regions with highest dust extinction in the ring). In the right panel we present a false-col-our image constructed from the SINFONI emission line maps of He i , Br g , and [Fe ii ] assigned to the blue, green, and redc olour channels, respectively. The bot-tom half of the ring shows the trends ex-odrodrpected under the pearls on a string pic-ture: an age sequence (blue-green-red) in the different hot spots. The sequence is less obvious in the top part of the ring due to the strong interaction between the ring and the radio jet. In the full sample, not shown here, three out of five galaxies show some evidence for an age gradient of hot spots along the ring, while the re-maining two galaxies have incompletei nformation and thus are consistent withe ither model. A more detailed account of the results presented here can be found in Böker et al. (2007).ReferencesBöker T. et al. 2007, AJ, in pressButa R. and Combes F. 1996, Fund. Cosmic Physics 17, 95Hummel E. et al. 1987, A&A 172, 51Knapen J. et al. 2006, A&A 448, 489Rossa J. et al. 2006, AJ 132, 1074Figure 4: Evidence in support of the pearls on astring scenario in NGC 613. Left: HST F666W image. Right: He i -Br g -Fe ii (blue-green-red) composite image of NGC 613 nuclear ring. Solid ellipse lines mark the lo c ation of the ring, star symbols the po-sitions of the over-dense regions (ODRs), and arrows the sense of rotation of the stars and gas in the gal-axy.A ‘Popcorn’B‘Pearls on a string’。

Spectroscopy and Spectral AnalysisSpectroscopy is a branch of science that deals with the study of the interaction between matter and electromagnetic radiation. Spectral analysis is a technique that is used to identify and measure the properties of substances based on the electromagnetic radiation that they emit, absorb, or scatter. The study of spectroscopy and spectral analysis is essential to many fields, including chemistry, physics, environmental science, and biomedical research.Types of SpectroscopyThere are several types of spectroscopy, each based on the type of electromagnetic radiation used. The most common types of spectroscopy include:1. Absorption SpectroscopyAbsorption spectroscopy is a technique that measures the amount of radiation absorbed by a sample. This type of spectroscopy is used to identify the chemical composition and concentration of a substance. Absorption spectroscopy can be used in the ultraviolet, visible, and infrared regions of the electromagnetic spectrum.2. Emission SpectroscopyEmission spectroscopy measures the amount of radiation emitted by a substance. This type of spectroscopy is used to identify the chemical composition of a substance and the temperature and pressure of the environment. Emission spectroscopy can be used in the ultraviolet, visible, and infrared regions of the electromagnetic spectrum.3. Fluorescence SpectroscopyFluorescence spectroscopy is a technique that measures the amount of radiation emitted by a substance when it is excited by light of a particular wavelength. This type of spectroscopy is used to identify the presence of certain substances in a sample, such as proteins and DNA molecules. Fluorescence spectroscopy can be used in the ultraviolet and visible regions of the electromagnetic spectrum.4. Raman SpectroscopyRaman spectroscopy is a technique that measures the scattered radiation produced when a sample is irradiated with a laser beam. This type of spectroscopy is used to identify the chemical composition and structure of a substance. Raman spectroscopy can be used in the visible and near-infrared regions of the electromagnetic spectrum.Applications of Spectroscopy and spectral analysis have a wide range of applications in various fields, including:1. ChemistrySpectroscopy is used extensively in chemistry to identify the chemical composition and properties of substances. Spectroscopy is used to determine the purity of a substance, study chemical reactions, and analyze the structure of molecules.2. PhysicsIn physics, spectroscopy is used to study the properties of materials, such as their electronic and magnetic properties. Spectroscopy is used to study the interactions between atoms and molecules and to investigate the behavior of quantum systems.3. Environmental ScienceSpectroscopy is used in environmental science to study the properties of soil, water, and air. Spectroscopy can be used to identify pollutants in the environment and to monitor the quality of drinking water and industrial wastewater.4. Biomedical ResearchIn biomedical research, spectroscopy is used to study the properties of biological molecules, such as proteins and DNA. Spectroscopy is used to image and diagnose diseases, such as cancer, and to monitor the effectiveness of treatments.ConclusionSpectroscopy and spectral analysis are powerful tools for studying the properties of matter and electromagnetic radiation. There are several types of spectroscopy, each with its own strengths and applications. Spectroscopy and spectral analysis are used in many fields, including chemistry, physics, environmental science, and biomedical research, and have a wide range of applications.。

幻灯片1Spectroscopy of Coordination Chemistry幻灯片2The frequency of the absorbed radiation is related to the energy of the transition by Plank’s Law:Efinal-Einitial =E=hν= hc/λWhen exists, the radiation can be absorbed;When does not satisfy the Plank expression, then the radiation will be transmitted.A plot of the frequency of the incident radiation vs.some measure of the percent radiation absorbedby the sample is the absorption spectrum of thecompound.幻灯片3The type of absorption spectroscopy depends onthe type of transition involved and accordingly onthe frequency range of the electromagneticradiation absorbed.If the transition is from one rotation energy level toanother, microwave spectroscopy;Vibrational energy level to another, infrared spectroscopy;If the transition alters the configuration of the valence electrons in the molecule,Ultraviolet-visible absorption spectroscopy幻灯片4幻灯片53.1 Ultraviolet and Visible Absorption Spectroscopy (UV-Vis)Beer’s Law states that:A = εbc3.1.1 Electronic TransitionsThere are three types of electronic transition :1. Transition involving π,σand n electrons;2. charge-transfer electrons3. d and f electrons.幻灯片63.1.2 Absorbing Species Containing π,σand n electronsSince there are superposition of different transition,a continuous absorption band appears.幻灯片7●σσ* Transitions●Transition from a bonding σorbital to the corresponding antibonding orbital (energyis generally large).●CH4 (125 nm) not seen in typical UV-Vis region (200-700 nm).●n σ* Transitions●Saturated compounds containing atoms with lone pairs (non-bonding electrons) arecapable of this type of transitions. In the range of 150-250 nm.●n π* and ππ* Transitions●Most organic compounds have the transitions of n or πelectrons to●the π* excited state and fall in the range of 200-700 nm.●Unsaturated groups providing the πelectrons.●ε= 10 to 100 L·mol-1·cm-1 for n π* transitions.●ε= 1000 to 10000 L·mol-1·cm-1 for ππ* transitions●Solvent effects: blue shift for n π* transitions and red shift for●ππ* transitions with increasing solvent polarity.幻灯片8幻灯片9Charge-Transfer AbsorptionA number of inorganic compounds show charge-transfer absorption.For a complex, if one of its components has electron donating properties and another component can accept electrons.The absorption involves the electron transitions from donor orbital to acceptor orbital. ε> 10000 L·mol-1·cm-1for examples: KMnO4, K2Cr2O7.3.1.3 Electronic Absorption Spectrum of Coordination ComplexThree kinds of electronic transitions: d d transition; MLCT andLMCT(metal-to-ligand charge transfer and ligand-to-metal charge transfer); LC (ligand centered transitions).幻灯片10● d d transitions●According to the selection rules, some transitions are strong (Td●complexes), and others are weak (Oh complexs).●Taking the hydrogen atom as an example:In which the 1s 2p transition is allowed,whereas the 1s 2s transition is “symmetryForbidden”. The reason is that the hydrogen atom possesses a center of inversion.The SALC (Symmetry Adapted Linear Combination)stated that if there is a inversion centre, we require the initial and final states have different parity.Then for a Oh complex, which has an inversion centre, the d d transition is forbidden. Meanwhile, for a Td compound, the d d transition is allowed. Therefore, the d d adsorption intensity of Td complexes is much higher than in Oh complex.We can still observe some d d adsorption in Oh complexes, this is due to the break of Oh symmetry.幻灯片11For example, when a Oh complex vibrate and in some cases the inversion centre does not exist. When this asymmetry is present, a weak absorption is present.This weak relaxation of the Laporte selection rule is known as vibronic（振动） coupling because it arises from the interaction of vibrational modes with the electronic transition modes.This weak absorptions fall in the visible region, which can be used in the explanation of coordination complexes’ colors.(2) MLCT or LMCT transitionThese transitions generally occur in the complexes which involved the metal centered dπground state and ligand π * states and the transitions can be observed in the visible region.For example, for a d6 octahedral metal complex, the molecularorbital diagram is in the following:幻灯片12From the Fig. 3.4, it is clear that the HOMO orbital is predominantlymetal dπorbital based and the LOMO orbital is predominantly ligandπ* orbital based. Normally, π-acceptors ligands will present a low-lying π* orbital and in the same time stabilize the dπorbital centeredon the metal by retro-coordination.Light absorber molecule.幻灯片13The major electronic transition that occur in d6 metal complexeswith unsaturated ligands are ligand based n π*, ππ*, MLCT and LF( ligand field transition) (Fig. 3.5).The intensity of a transition is determined by selection rule.both Laporte and spin rules.(1)Ligand ππ* transition and MLCT are both rules allowed, theεis 103 ~105 L·mol-1·cm-1.(2) LF is spin allowed but Laporte forbidden,εis 102 ~103 L·mol-1·cm-1.幻灯片14The compound [Ru(bpy)3]2+ is a photostable compound(τ=640 nsand emission quantum yield Φ= 0.062). The electronic absorptionspectrum of [Ru(bpy)3]2+ is:幻灯片153.1.4 InstrumentUV-Vis spectrometer:Lamp: a deuterium discharge lamp for UV measurement and a tungsten-halogen lamp for visible and NIR measurements.a normal UV-Vis 190~900 nm. Nitrogen, vacuum detector.幻灯片163.2 Infrared Spectroscopy● 3.2.1 Several types of molecular motion●Translational motion●move through space in some arbitrary direction with a particular velocity.●Rotational motion●rotate about some internal axis.●Vibrational motion●the molecule may vibrate. As shown in Fig. 3.9, a polyatomic molecule has total3N freedom. When abstracting the 3 translational and 3 rotational degrees of freedom, the vibrational freedom is 3N-6.幻灯片17For water molecule, the vibrational freedom is 3*3 –6 = 3.Each of the vibrational motions of a molecule occurs with a certainFrequency, which is characteristic of the molecule and of the particularvibration. The energy involved in particular vibration is characterizedby the amplitude of the vibration, so that the higher the vibrationalEnergy, the larger the amplitude of the motion.Since most vibrational motions in molecules occur at 1014 sec-1. thenLight of wavelength = 3μm will be required to cause transition fromone vibrational energy level to another. This wavelength lies in the so-called infrared region of the spectrum. So, IR spectroscopy deals withvibrational motion of the molecules. Vibrational spectroscopy.幻灯片18● 3.2.2 Application of IR●IR spectrum of organic molecules could be divided into three regions: ●4000 ~ 1300 cm-1 (specific functional groups and bond types);●1300~ 909 cm-1 (the fingerprint region);●909 ~ 605 cm-1( the presence of benzene rings).幻灯片19幻灯片20Here, we consider the IR spectroscopy of inorganic compounds.For example: KNO2, in its lattice, the K+ and NO2- is independently arranged. Therefore, we consider only the NO2- anion (the K+ ionhas no vibrational motion).the nitrite anion has 3 vibrational freedom.One is symmetric stretch at 1335 cm-1,Another is asymmetric stretch at 1250 cm-1,The last one is bending vibration at 830cm-1. and their frequencies are almostSame regardless of the counter ion. So, it can be used for the diagnosis the presence of nitrite ions in a compound.幻灯片21For another salt, NaNO3, it is more complex.For another salt, NaNO3, it is more complex.It should have 3x4-6 = 6 vibrational modes.But its IR spectra exhibit only threeabsorption band centered at 831, 1405 and692 cm-1. it is that the symmetricstretching is not IR active. The reason forthis is that this type of motion gives no rise to the change of thedipole moment of the ion.Among the remaining 5, there are two sets of doubly degeneratevibrations, that is each 2 motions has one band in IR.The IR spectra for some of the more common ions are listed in thefollowing table.幻灯片22幻灯片23The IR absorption bands listed in the above table are for the free ions. When they coordinated with metal ions, the absorption peaks will move. For nitrite anion, it has at least two coordination modes:When coordinated, there willbe an increase of the vibrationalfrequency for the nitrite ionin the order: N-single bondedO (in O-bonded) < NO (in N-bonded) < N-double bond-O(in O-bonded) .幻灯片24In agreement with this, it has been found that in complexes in which NO2- is bonded through oxygen, the two N-O stretching frequencies lie in the ranges 1500~1400 cm-1 for N=O and 1100-1000 cm-1 for N-O.In complexes in which NO2- is bonded through nitrogen, the bands occur at similar frequencies which are intermediate between the range above; namely, 1340~1300 cm-1 and 1430 ~1360 cm-1. Thus it is relatively easy to tell whether a nitrite ion is coordinated through O or N on the basis of IR whether it is coordinated.幻灯片25For nitrate complexes, the nitrate can coordinated with metal atomin the following ways:In the free nitrate ion, thethree oxygen atoms areidentical, but no longeridentical in the coordinatednitrate ion.In all three cases, two of theoxygen atoms are identicaland the third one is unique.we say that the AB3 typeion is to change to an AB2C type species. Then the IR inactive symmetric stretching mode for the free nitrate ion (AB3) type becomes IR active when coordinated to metal atoms(AB2C).幻灯片26Similarly, the doubly degenerated asymmetric stretch in AB3becomes two asymmetric stretch with different energy in AB2C.Free nitrate ion: single band; coordinated nitrate ion: two bands.The more symmetrical a molecules or ion is, the fewer the number of bands that will appearin the IR spectrum.幻灯片27principle of Raman spectroscopyRayleigh散射：弹性碰撞；无能量交换，仅改变方向；Raman散射：非弹性碰撞；方向改变且有能量交换；Rayleigh散射Raman散射E0基态，E1振动激发态；E0 + h0 ，E1 + h0 激发虚态；获得能量后，跃迁到激发虚态.（1928年印度物理学家Raman C V 发现；1960年快速发展）幻灯片28基本原理E0E1 V=1V=0- 激发虚态1. Raman 散射Raman 散射的两种跃迁能量差： E=h(0 - )产生stokes 线；强；基态分子多； E=h(0 + ) 产生反stokes 线；弱； Raman 位移：Raman幻灯片29 2. Raman 位移对不同物质：对同一物质： -转能级的特征物理量；定性与结构分析的依据；Raman 散射的产生：光电场E= E 分子极化率； 幻灯片30E0E1V=1V=0-ANTI-STOKES-RayleighSTOKES诱导偶极矩 = E非极性基团，对称分子；拉曼活性振动—伴随有极化率变化的振动。