Diffusion

Neuroscience Letters424(2007)

127–132

Diffusion tensor imaging of white matter in the superior temporal

gyrus and temporal stem in autism?

Jee Eun Lee a,Erin D.Bigler e,f,g,k,Andrew L.Alexander a,b,c,?,Mariana Lazar a, Molly B.DuBray i,Moo K.Chung a,d,Michael Johnson f,Jubel Morgan f,

Judith https://www.wendangku.net/doc/137836868.html,ler f,William M.McMahon f,k,Jeffrey Lu h,

Eun-Kee Jeong g,j,Janet https://www.wendangku.net/doc/137836868.html,inhart f,i,j,k

a Waisman Laboratory for Brain Imaging and Behavior,Waisman Center,Madison,WI,United States

b Department of Medical Physics,University of Wisconsin,Madison,WI,United States

c Department of Psychiatry,University of Wisconsin,Madison,WI,Unite

d States

d Department of Biostatistics and Medical Informatics,University of Wisconsin,Madison,WI,United States

e Department o

f Psychology,Brigham Youn

g University,Provo,UT,United States

f Department of Psychiatry,University of Utah,Salt Lake City,UT,United States

g Department of Radiology,University of Utah,Salt Lake City,UT,United States

h Department of Anesthesiology,University of Utah,Salt Lake City,UT,United States

i Neuroscience Program,University of Utah,Salt Lake City,UT,United States

j Center for Advanced Imaging Research,Salt Lake City,UT,United States

k The Brain Institute at The University of Utah,Salt Lake City,UT,United States

Received23April2007;received in revised form2July2007;accepted24July2007

Abstract

Recent MRI studies have indicated that regions of the temporal lobe including the superior temporal gyrus(STG)and the temporal stem(TS) appear to be abnormal in autism.In this study,diffusion tensor imaging(DTI)measurements of white matter in the STG and the TS were compared in43autism and34control subjects.DTI measures of mean diffusivity,fractional anisotropy,axial diffusivity,and radial diffusivity were compared between groups.In all regions,fractional anisotropy was signi?cantly decreased and both mean diffusivity and radial diffusivity were signi?cantly increased in the autism group.These results suggest that white matter microstructure in autism is abnormal in these temporal lobe regions,which is consistent with theories of aberrant brain connectivity in autism.

?2007Published by Elsevier Ireland Ltd.

Keywords:Autism;Diffusion tensor imaging;Superior temporal gyrus;Temporal stem;White matter;Anisotropy;Diffusivity;Magnetic resonance imaging

A prevalent hypothesis is that brain connectivity in autism is aberrant(e.g.[6,11]).Regional abnormalities in cerebral white matter(WM)can result in impaired brain connectivity.Conse-Abbreviations:Da,axial(parallel)diffusivity;Dr,radial(perpendicular) diffusivity;DTI,diffusion tensor imaging;FA,fractional anisotropy;MD,mean diffusivity;STG,superior temporal gyrus;TS,temporal stem;WM,white matter ?This study was approved by the following Institutional Review Boards: University of Utah IRB:IRB00010391(PI:Lainhart,approval9May2007). University of Wisconsin Health Sciences IRB:H-2003-0548(PI:Alexander, approval12March2007).

?Corresponding author at:Waisman Laboratory for Brain Imaging and Behav-ior,Waisman Center,1500Highland Avenue,Madison,WI53705,United States. Tel.:+16082658233.

E-mail address:alalexander2@https://www.wendangku.net/doc/137836868.html,(A.L.Alexander).quently,evidence of abnormal white matter would signi?cantly strengthen the case for the disconnectivity hypothesis in autism.

Traditionally,the superior temporal gyrus(STG)has been de?ned primarily by its role in auditory processing[19,22]. Contemporary cognitive neuroscience views the STG as equally important in social cognition,regulation of behavior,and neu-ral mechanisms of imitation[1,16].As such,the role of the STG in autism has become the focus of several structural and functional neuroimaging studies[9,13,21].Despite the func-tional abnormalities associated with the autistic temporal lobe, studies of overall STG volumetric differences between autism and controls have yielded inconsistent?ndings.One volumet-ric study reported smaller left STG volumes in autism[24], whereas other studies have reported no volumetric differences

0304-3940/$–see front matter?2007Published by Elsevier Ireland Ltd. doi:10.1016/j.neulet.2007.07.042

128J.E.Lee et al./Neuroscience Letters424(2007)127–132

[7,8].Since autism has features of both impaired communica-tion and social processing[4],investigation of the white matter projections to the STG may help to understand abnormal STG function in autism[21].

Major afferent and efferent connections of the temporal lobe (including STG)enter and exit via the temporal stem(TS)[18]. This deep WM area bridges the temporal cortex with important limbic,thalamic,striatal,and frontal regions[18].The tempo-ral stem includes portions of the uncinate fasciculus and inferior occipitofrontal fasciculus.Several analyses have shown that sub-tle reduction in white matter volume of the TS area may occur in autism[8,20].V olumetric reduction of the TS area may be a sign of impaired connectivity between the temporal lobe and the rest of the brain.

Diffusion tensor imaging(DTI)is a promising method for characterization of tissue microstructure in the CNS[5].In WM, the membranes of the axons and myelin cause the apparent (radial)diffusivities of water perpendicular to the white mat-ter tracts to be decreased relative to the(axial)diffusivities in the directions parallel to the white matter?bers.Changes in the WM microstructure(e.g.,myelination,axonal density,etc.) will consequently affect the diffusion anisotropy.Thus,DTI measurements of WM in the STG and TS may be used to char-acterize microstructural abnormalities in the autistic temporal lobe that may be undetectable at the volumetric level.Two DTI studies of the autistic temporal lobe reported reduced fractional anisotropy(FA)bilaterally adjacent to the superior temporal sulcus[3]and in deeper WM in the right posterior limb of the internal capsule[17].These studies suggest abnormalities in the superior and deeper temporal white matter microstruc-ture and warrant further investigation.Recent DTI studies have also demonstrated microstructural abnormalities in the corpus callosum in autism[2].In the current study,the microstruc-tural properties of temporal lobe WM in regions of the STG and TS in autism were examined using the DTI measures of mean diffusivity(MD),fractional anisotropy(FA),radial dif-fusivity(Dr),and axial diffusivity(Da).Measurements were compared between subjects with high functioning autism and controls.

Forty-three subjects with a lifetime-diagnosis of autism-spectrum disorder(38autism,5PDD-NOS)were compared to34control https://www.wendangku.net/doc/137836868.html,rmed consent and assent were obtained for all subjects prior to participation.All aspects of the study had received IRB approval.All subjects were males, non-mentally retarded(IQ>85),from the greater Salt Lake City,Utah region,and the two groups were matched in terms of age(autism:16.2±6.7with range=7–33years;control: 16.4±6.0with range=8–29years;p=0.89),performance IQ (autism:107.5±13.0;control:112.8±12.0;p=0.07),hand-edness(autism:80.81±21.7;control:72.79±29.0;p=0.17), and head circumference(autism:56.6±2.3;control:56.1±2.0; p=0.34).Head circumference was used as a matching variable to control for the increased rate of macrocephaly in autism.A volumetric study showed that white matter volume differences between autism and control subjects were non-signi?cant when the effect of the increased rate of macrocephaly was controlled [8].All subject testing and imaging experiments were performed at the University of Utah.Image analysis was performed at the University of Wisconsin.

Autism and control(typically developing)subjects were recruited during a3-year period(2002–2005)from commu-nity sources,including parent support groups,youth groups,and schools,and from clinic social skills groups as part of an ongoing longitudinal study of autism.

Autism was rigorously diagnosed,as has been described else-where[8],based on the Autism Diagnostic Interview-Revised (ADI-R),Autism Diagnostic Observation Schedule-Generic (ADOS-G),and DSM-IV and ICD-10criteria.History,observa-tion,Fragile-X gene testing,and karyotype were used to exclude medical causes of autism.None of the autism subjects had a history of seizures.

Control subjects had no history of learning,developmen-tal,cognitive,neurological,or neuropsychiatric problems.All controls had extensive testing,including the ADOS-G,IQ,lan-guage,and psychiatric testing,to con?rm that they were typically developing.

Diffusion tensor(DT)images were acquired on a Siemens Trio3.0Tesla MRI Scanner.Four of the children with autism were sedated by an anesthesiologist(JL)for scanning,and were continuously monitored according to American Society of Anesthesiology standards.There were no complications associ-ated with the sedation.A wide range of other pulse sequences (T1-weighted Magnetization-Prepared Rapid Gradient-Echo (MP-RAGE),and T2-weighted Turbo Spin Echo)were collected for both clinical review and quantitative analyses although these data were not used in the current analysis.An eight-channel RF receiver coil was used to acquire the imaging data.DTI was per-formed using a product single-shot,echo planar imaging pulse sequence with dual-refocusing and bipolar diffusion-weighting gradients to reduce eddy currents.Parallel imaging with SENSE (Sensitivity Encoding)was performed using a reduction factor of 2to reduce image distortion.The in-plane resolution was2mm isotropic(?eld of view=256mm;matrix=128×128).A sin-gle(b=0)reference image volume and12diffusion-weighted image volumes with non-collinear diffusion encoding directions and diffusion weighting b=1000s/mm2were obtained.Each image volume covered the cerebrum and cerebellum with?fty 2.5mm thick contiguous axial slices.Other imaging parameters were TR(repetition time)=7000ms,TE(echo time)=84ms, acquisition sampling bandwidth per pixel=1345Hz,and3 averages.A?eld map was generated from a pair of2D gradient echo images with different echo times(TE1=7ms, TE2=10ms).

All of the image processing was performed using cus-tom software and command-line scripts developed in-house. Misregistration effects from eddy currents and head move-ments were?rst corrected using af?ne registration software (AIR—https://www.wendangku.net/doc/137836868.html,/AIR5/).Spatial distortions in the EPI data from magnetic?eld(B0)inhomogeneities were corrected using?eld map correction software scripts with‘prelude’and‘fugue’from the FMRIB software library (https://www.wendangku.net/doc/137836868.html,/fsl/).Corrected images were inter-polated to2mm isotropic voxels and diffusion tensor maps were subsequently estimated.Maps of the diffusion tensor eigenval-

J.E.Lee et al./Neuroscience Letters424(2007)127–132

129

Fig.1.Example ROI overlays on the segmented WM regions on af?ne normalized image data for both control(left)and autistic(right)subjects.The coronal cross-sections are the segmented white matter maps.The STG–WM regions are labeled in blue(right)and green(left),and the TS regions are labeled in red(right) and yellow(left).Only voxels that intersect both the ROI template and WM mask were used in the analyses.

ues(λ1,λ2,λ3),MD,FA,Da(=λ1),and Dr(=(λ2+λ3)/2)were generated.

In this study,WM regions of interest identifying the STG–WM and TS were extracted in two steps.First,cerebral WM was segmented using the mFAST algorithm in the FMRIB software library with maps of the major and minor eigenval-ues(λ1andλ3,respectively)as the inputs.This combination of eigenvalues appeared to yield the most robust white matter segmentation(compared with any single eigenvalue,MD,FA or any other combination).In each subject,voxels with MD values two standard deviations from the average MD in the total WM were excluded from the WM segmentation as these were likely contaminated with CSF.The segmented WM vol-ume masks were then co-registered to a custom WM template. Regions in the STG and TS were then identi?ed on the mask average and regions were labeled on the WM template.The right and left STG–WM and TS region templates were then transformed back to the native space of each subject’s DTI data and the regions were overlaid on the segmented DTI maps for that subject.Example overlays are illustrated in Fig.1.This provided a semi-automated method for labeling these regions on each subject in the native space.Mean values of MD,FA,Da and Dr were extracted in each region.Manual inspection of the automated STG–WM and TS labeling demonstrated consistent extraction of these regions.

DTI measurements of FA,MD,Da and Dr were compared using a one-way ANCOV A(using custom Matlab software and veri?ed using SPSS version14.0)with group as the independent variable,DTI measurements as the dependent variables,and age as the covariate.Age was covaried because DTI measures have age-dependence.The four regions—right and left STG–WM and TS were analyzed independently.Since four regions were eval-uated,the effects of multiple comparisons were compensated using a Bonferroni correction,such that results were thresh-olded at an uncorrected p<0.013.All reported p-values are uncorrected.

Statistical analyses for the study are summarized in Table1, including the summary statistics(means and standard deviations of the DTI measures in both autism and controls),group com-parisons using ANCOV A,and the correlation coef?cients(R)of the regional measures with age over all subjects.In all regions,Dr was signi?cantly elevated in autism relative to controls.MD was signi?cantly higher in autism for the right TS and right STG–WM,and in the left STG–WM.FA measurements were signi?cantly lower in autism for all regions.Signi?cant group differences in Da were observed in right STG–WM.The regional volumes were not signi?cantly different between groups.

In general,both MD and Dr decreased with age for both groups(see Fig.2a and Table1).FA appeared to increase with age for controls whereas very little age-related changes were detected for the autism group(see Fig.2b).However, only the right STG–WM appeared to demonstrate signi?cant age×group interactions for FA(F=15.02;p=0.0002).Con-versely,Da appeared to decrease with age for the autism group, whereas Da showed minimal age-related changes in controls except in the left STG–WM.However,the age×group interac-tions for Da were again only signi?cant for the right STG–WM (F=9.52;p=0.0029).None of the other regions demonstrated signi?cant age×group interactions(F<3.85).The age×group interactions for FA and Da in the right STG–WM mean that the results will depend upon the age composition of the subjects being studied for these measures.Plots of all DTI measures ver-sus age for all regions are available as on-line supplementary material.

The potential effects of medication on the DTI measure-ments were also investigated.Twenty-six(60%)of the autism subjects were taking at least one psychotropic medication and 38%were taking multiple medications.Seventy-three percent of the autism subjects were taking SSRI’s,35%stimulants,11% valproic acid,and7%atypical neuroleptics.There were no sig-ni?cant differences in either the mean age or any of the DTI measures in autism subjects taking psychotropic medications versus those not on medications.The signi?cant regions were the same when autism subjects were split into the medication and non-medication groups except the MD in the left TS dropped below signi?cance for the autism medication subgroup.

Four of the younger subjects with autism(ages7–10)were scanned with sedation.We compared the DTI measurements of the autism subjects with sedation(n=4)against those from the autism subjects without sedation in the same age range(n=6). Although the MD and Dr measures were generally larger in the sedated group,the differences were nearly signi?cant only

130J.E.Lee et al./Neuroscience Letters424(2007)127–132

Table1

Group comparisons of anisotropy and diffusivities

Autism(n=43)Control(n=34)Age correlation ANCOV A(w/age)group comparison

Mean S.D.Mean S.D.R p F p(uncorrected)

Mean diffusivity(10?3mm2/s)

Left temporal stem0.8750.0240.8660.023?0.300.007* 3.60.063

Right temporal stem0.8860.0250.8670.021?0.370.001*14.60.000*

Left STG–WM0.8360.0330.8180.033?0.540.000*7.90.006*

Right STG–WM0.8300.0330.8070.028?0.590.000*16.40.000*

Fractional anisotropy

Left temporal stem0.4000.0210.4150.0230.240.0399.10.004*

Right temporal stem0.3920.0270.4100.0290.220.0548.20.005*

Left STG–WM0.3140.0220.3310.0210.300.009*13.90.000*

Right STG–WM0.3110.0180.3220.0260.400.000* 6.80.011*

Axial diffusivity(10?3mm2/s)

Left temporal stem 1.2770.032 1.2790.035?0.140.2280.10.776

Right temporal stem 1.2830.027 1.2770.031?0.190.096 1.00.327

Left STG–WM 1.1160.042 1.1080.041?0.490.000*0.70.402

Right STG–WM 1.1070.042 1.0860.032?0.450.000*7.80.007*

Radial diffusivity(10?3mm2/s)

Left temporal stem0.6750.0280.6590.027?0.300.008* 6.90.011*

Right temporal stem0.6880.0340.6620.031?0.320.004*12.70.001*

Left STG–WM0.6970.0340.6730.033?0.500.000*12.60.001*

Right STG–WM0.6910.0320.6680.032?0.580.000*16.20.000*

V olume(voxels)

Left temporal stem245.831.8242.634.30.320.005*0.20.639

Right temporal stem235.631.5239.235.70.170.1510.20.649

Left STG–WM321.3115.2371.2110.30.420.000* 4.30.042

Right STG–WM343.196.2394.1127.80.560.000* 5.60.020

*Statistically signi?cant at the thresholded uncorrected p<0.013,determined by Bonferroni correction for multiple comparisons.

in right STG–WM for MD(p=0.018),Da(p=0.03),and Dr (p=0.057).When the four sedated subjects were removed from the overall ANCOV A,the regions with signi?cant differences were similar to those in Table1except for Dr in the left TS was not quite signi?cant(F=4.42;p=0.039).

In the current study,we implemented a semi-automated ROI approach for obtaining DTI measures in speci?c temporal lobe regions.Since the ROIs were applied to segmented WM data, the contamination from gray matter and CSF was minimal.Also, the regions were large enough to accommodate errors in mis-registration.

The current?ndings demonstrated DTI differences in the WM of the STG and TS,implicating dissimilarities in microstructural organization of these temporal lobe regions in autism compared to controls.Since these are critical pathways involved in language and social cognition,WM abnormali-ties within these regions may contribute to the neurobehavioral features observed in autism.The radial diffusivity,Dr,was con-sistently elevated in autism.The differences in Dr appear to be the primary cause for changes in MD and FA measures.This observation of increased Dr was consistent with DTI measure-ments of the corpus callosum in autism[2].Recent studies in a mouse model of dysmyelination have suggested that increases in the radial diffusivity are related to myelination[23].How-ever,it was not clear if differences in myelination were the primary mechanism for the DTI changes reported here.Changes in axonal density,organization or gliosis might also affect the radial diffusivity.Psychotropic medication use did not appear to have a major effect on the?ndings.

It is interesting that the MD and Dr measurements appear to be quite elevated in autism for the youngest subjects(ages 7–13,for example,see Fig.2a for Dr in right TS).Whether these increased diffusivities in mid-childhood are indicative of an aberrant developmental trajectory is not clear.Currently,we are performing a longitudinal DTI study on these subjects,which will be better for assessing differences in the developmental trajectories between groups.Sedation for scanning of4young subjects did not appear to have a major effect on the overall results.

In this study,it was hypothesized that the microstructural fea-tures of speci?c WM regions in the temporal lobe are affected in autism,and the data were consistent with the prediction.How-ever,it is likely that other brain regions in autism will also show WM abnormalities.Indeed,the corpus callosa in these same subjects were abnormal[2]and a small voxel-based analysis study by Barnea-Goraly et al.[3]suggested diffuse WM differ-ences though not speci?cally in the TS and STG.Future studies will investigate whether other WM regions are likewise affected. Finally,it is also possible that gray matter regions are also affected in autism;however,characterization of cortical gray matter with DTI is extremely challenging because it is relatively narrow and adjacent to CSF.

The results from this study demonstrate that WM regions of the temporal lobe–the STG and TS–appear to be abnormal in

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Fig.2.(a)Measurements of Dr vs.age in right TS.The plot shows a similar decline with age for both groups and an increased Dr in the autism group.The results for the other regions were similar.(b)Measurements of FA vs.age in right STG–WM.FA appears to increase with age for the controls;however,the autistic subjects demonstrated minimal changes with age.The age-dependence was signi?cantly different between groups.Similar trends were observed for the other regions;however,the group difference was not signi?cant.

subjects with autism.These regions are critical to language and social function,which are affected in autism.These?ndings add to functional neuroimaging studies demonstrating abnor-malities of the STG in autism[10,12],and support the hypothesis that autism involves abnormal brain connectivity[14,15].Future studies are necessary to determine how speci?cally related these WM abnormalities are to language and social impairments. Acknowledgments

This work was supported by the NIH grants HD35476, NIMH62015,NIDA15879,the NICHD/NIDCD Collaborative Programs of Excellence in Autism(CPEA),the NIH Mental Retardation/Developmental Disabilities Research Center(Wais-man Center),the Autism Society of Southwestern Wisconsin, and the National Alliance for Research in Schizophrenia and Affective Disorders(NARSAD).We thank Brad Wright and the PIs and staff of the Utah Autism Research Program:Dr.Hilary Coon,Dr.Robert Fujinami,Tami Elsner,Lori Krasny, Megan Farley,Heidi Block,Lindsey Warner,Barbara Young, Tracy Abildskov,and JoAnn Petrie.We also thank Melody John-son,Henry Buswell,and the rest of the UCAIR staff.We express our sincere gratitude to the children and adults who participated in this study and their families.

Appendix A.Supplementary data

Supplementary data associated with this article can be found, in the online version,at doi:10.1016/j.neulet.2007.07.042. References

[1]R.Adolphs,Cognitive neuroscience of human social behaviour,Nat.Rev.

Neurosci.4(2003)165–178.

[2]A.L.Alexander,J.E.Lee,https://www.wendangku.net/doc/137836868.html,zar,R.Boudos,M.B.DuBray,T.R.Oakes,

https://www.wendangku.net/doc/137836868.html,ler,J.Lu,E.K.Jeong,W.M.McMahon,E.D.Bigler,https://www.wendangku.net/doc/137836868.html,inhart, Diffusion tensor imaging of the corpus callosum in Autism,Neuroimage 34(2007)61–73.

[3]N.Barnea-Goraly,H.Kwon,V.Menon,S.Eliez,L.Lotspeich,A.L.Reiss,

White matter structure in autism:preliminary evidence from diffusion ten-sor imaging,Biol.Psychiatry55(2004)323–326.

[4]S.Baron-Cohen,M.K.Belmonte,Autism:a window onto the develop-

ment of the social and the analytic brain,Annu.Rev.Neurosci.28(2005) 109–126.

[5]P.J.Basser,J.Mattiello,D.LeBihan,MR diffusion tensor spectroscopy and

imaging,Biophys.J.66(1994)259–267.

[6]M.K.Belmonte,G.Allen,A.Beckel-Mitchener,L.M.Boulanger,R.A.

Carper,S.J.Webb,Autism and abnormal development of brain connectivity, J.Neurosci.24(2004)9228–9231.

[7]E.D.Bigler,S.Mortensen,E.S.Neeley,S.Ozonoff,L.Krasny,M.Johnson,

J.Lu,S.L.Provencal,W.McMahon,https://www.wendangku.net/doc/137836868.html,inhart,Superior temporal gyrus, language function,and autism,Dev.Neuropsychol.31(2007)217–238.

[8]E.D.Bigler,D.F.Tate,E.S.Neeley,L.J.Wolfson,https://www.wendangku.net/doc/137836868.html,ler,S.A.Rice,

H.Cleavinger,C.Anderson,H.Coon,S.Ozonoff,M.Johnson,E.Dinh,J.

Lu,W.McMahon,https://www.wendangku.net/doc/137836868.html,inhart,Temporal lobe,autism,and macrocephaly, AJNR Am.J.Neuroradiol.24(2003)2066–2076.

[9]N.Boddaert,P.Belin,N.Chabane,J.B.Poline,C.Barthelemy,M.C.

Mouren-Simeoni,F.Brunelle,Y.Samson,M.Zilbovicius,Perception of complex sounds:abnormal pattern of cortical activation in autism,Am.J.

Psychiatry160(2003)2057–2060.

[10]N.Boddaert,N.Chabane,H.Gervais,C.D.Good,M.Bourgeois,M.H.

Plumet,C.Barthelemy,M.C.Mouren,E.Artiges,Y.Samson,F.Brunelle, R.S.Frackowiak,M.Zilbovicius,Superior temporal sulcus anatomical abnormalities in childhood autism:a voxel-based morphometry MRI study, Neuroimage23(2004)364–369.

[11]E.Courchesne,K.Pierce,Why the frontal cortex in autism might be talking

only to itself:local over-connectivity but long-distance disconnection,Curr.

Opin.Neurobiol.15(2005)225–230.

[12]I.Gendry Meresse,M.Zilbovicius,N.Boddaert,L.Robel,A.Philippe,

I.Sfaello,https://www.wendangku.net/doc/137836868.html,urier,F.Brunelle,Y.Samson,M.C.Mouren,N.Chabane,

Autism severity and temporal lobe functional abnormalities,Ann.Neurol.

58(2005)466–469.

[13]G.J.Harris, C.F.Chabris,J.Clark,T.Urban,I.Aharon,S.Steele,

L.McGrath,K.Condouris,H.Tager-Flusberg,Brain activation during semantic processing in autism spectrum disorders via functional magnetic resonance imaging,Brain Cogn.61(2006)54–68.

[14]J.Hendry,T.DeVito,N.Gelman,M.Densmore,N.Rajakumar,W.

Pavlosky,P.C.Williamson,P.M.Thompson,D.J.Drost,R.Nicolson,White matter abnormalities in autism detected through transverse relaxation time imaging,Neuroimage29(2006)1049–1057.

[15]M.R.Herbert,Large brains in autism:the challenge of pervasive abnor-

mality,Neuroscientist11(2005)417–440.

132J.E.Lee et al./Neuroscience Letters424(2007)127–132

[16]M.Iacoboni,Neural mechanisms of imitation,Curr.Opin.Neurobiol.15

(2005)632–637.

[17]T.A.Keller,R.K.Kana,M.A.Just,A developmental study of the struc-

tural integrity of white matter in autism,Neuroreport18(2007)23–

27.

[18]E.L.Kier,L.H.Staib,L.M.Davis,R.A.Bronen,MR imaging of the tem-

poral stem:anatomic dissection tractography of the uncinate fasciculus, inferior occipitofrontal fasciculus,and Meyer’s loop of the optic radiation, AJNR Am.J.Neuroradiol.25(2004)677–691.

[19]M.Meyer,T.Zaehle,V.E.Gountouna,A.Barron,L.Jancke,A.Turk,

Spectro-temporal processing during speech perception involves left poste-rior auditory cortex,Neuroreport16(2005)1985–1989.

[20]E.S.Neeley,E.D.Bigler,L.Krasny,S.Ozonoff,W.McMahon,https://www.wendangku.net/doc/137836868.html,in-

hart,Quantitative temporal lobe differences:autism distinguished from

controls using classi?cation and regression tree analysis,Brain Dev.29 (2007)389–399.

[21]K.Pelphrey,R.Adolphs,J.P.Morris,Neuroanatomical substrates of social

cognition dysfunction in autism,Ment.Retard.Dev.Disabil.Res.Rev.10 (2004)259–271.

[22]S.A.Ruschemeyer,S.Zysset,A.D.Friederici,Native and non-native read-

ing of sentences:an fMRI experiment,Neuroimage31(2006)354–365.

[23]S.K.Song,S.W.Sun,M.J.Ramsbottom,C.Chang,J.Russell,A.H.Cross,

Dysmyelination revealed through MRI as increased radial(but unchanged axial)diffusion of water,Neuroimage17(2002)1429–1436.

[24]G.D.Waiter,J.H.Williams,A.D.Murray,A.Gilchrist,D.I.Perrett,A.

Whiten,Structural white matter de?cits in high-functioning individuals with autistic spectrum disorder:a voxel-based investigation,Neuroimage 24(2005)455–461.

名词解释1

1．丙氨酸-葡萄糖循环 肌肉中的氨基酸将氨基转给丙酮酸生成丙氨酸，后者经血液循环转运至肝脏经过联合脱氨基作用再脱氨基，放出的氨用于合成尿素；生成的丙酮酸经糖异生转变为葡萄糖后再经血液循环转运至肌肉重新分解产生丙酮酸，丙酮酸再接受氨基生成丙氨酸。丙氨酸和葡萄糖反复地在肌肉和肝之间进行氨的转运，股将这一循环过程称为丙氨酸-葡萄糖循环。 2．光合磷酸化 光合磷酸化(photophosphorylation)是植物叶绿体的类囊体膜或光合细菌的载色体在光下催化腺二磷（ADP）与磷酸（Pi）形成腺三磷（ATP）的反应。 3．底物水平磷酸化 物质在生物氧化过程中，常生成一些含有高能键的化合物，而这些化合物可直接偶联ATP 或GTP的合成，这种产生ATP等高能分子的方式称为底物水平磷酸化 4．酶的共价修饰调节 某些酶蛋白肽链上的侧链基团在另一酶的催化下可与某种化学基团发生共价结合或解离，从而改变酶的活性，这一调节酶的活性的方式成为酶的共价修饰调节 5．酮体 在肝脏中，脂肪酸氧化分解的中间产物乙酰乙酸、β-羟基丁酸及丙酮，三者统称为酮体。肝脏具有较强的合成酮体的酶系，但却缺乏利用酮体的酶系。酮体是脂肪分解的产物，而不是高血糖的产物。进食糖类物质也不会导致酮体增多。 6．P/O比值 物质氧化时，每消耗1克原子氧所消耗无机磷的摩尔数（或ATP摩尔数），即生成ATP的克分子数 7．脂肪酸的β-氧化 脂酰CoA在线粒体基质中进入β氧化要经过四步反应，即脱氢、加水、再脱氢和硫解，生成一分子乙酰CoA和一个少两个碳的新的脂酰CoA。 8．暗反应 暗反应是激发分子的热力学的缓和过程，是电荷的分离、电子的传递、磷酸化或短命的中间体形成等多种基本过程。 9．光反应 光反应又称为光系统电子传递反应(photosythenic electron-transfer reaction)。在反应过程中,来自于太阳的光能使绿色生物的叶绿素产生高能电子从而将光能转变成电能。 10．转氨基作用 指的是一种α-氨基酸的α-氨基转移到一种α-酮酸上的过程。转氨基作用是氨基酸脱氨基作用的一种途径。其实可以看成是氨基酸的氨基与α-酮酸的酮基进行了交换11．脂肪动员 在病理或饥饿条件下，储存在脂肪细胞中的脂肪，被脂肪酶逐步水解为游离脂酸（FFA）及甘油并释放入血以供其他组织氧化利用，该过程称为脂肪动员 12．EMP途径 又称糖酵解或己糖二磷酸途径，是细胞将葡萄糖转化为丙酮酸的代谢过程，总反应为：C6H12O6+2NAD+ +2Pi+2ADP→2CH3COCOOH（丙酮酸）+2NADH+2H+ +2ATP+2H2O 13．氧化磷酸化 氧化磷酸化，生物化学过程，是物质在体内氧化时释放的能量供给ADP与无机磷合成ATP 的偶联反应。主要在线粒体中进行。在真核细胞的线粒体或细菌中，物质在体内氧化时释放

作业及答案

2.诚信公司20 x9年10月发生部分经济业务如下: (1) 10月2日，将款项交存银行，开出银行汇票一张，金额为 40000元，由采购员王强携往沈阳以办理材料采购事宜。 (2) 10月5日，因临时材料采购的需要，将款项50000元汇往上海交通银行上海分行，并开立采购专户，材料采购员李民同日前往上海。 (3) 10月9日，为方便行政管理部门办理事务，办理信用卡一张，金额为12000元。 (4) 10月13日，采购员王强材料采购任务完成回到企业，将有关材料采购凭证交到会计部门。材料采购凭证注明，材料价款为31000元，应交增值税为5270元。 (5) 10月14日，会计入员到银行取回银行汇票余款划回通知，银行汇票余款已存入企业结算户。 (6) 10月17日，因采购材料需要，委托银行开出信用证，款项金额为150000元。 (7) 10月20日，材料采购员李民材料采购任务完成回到本市，当日将采购材料的有关凭证交到会计部门，本次采购的材料价款为40000元，应交增值税为6800元。 (8) 10月22日，企业接到银行的收款通知，上海交通银行上海分行采购专户的余款已转回结算户。 (9) 10月25日，行政管理部门小王用信用卡购买办公用品，支付款项3200元。 (10) 10月28日，为购买股票，企业将款项200000元存入海通证券公司。 要求:根据上述经济业务编制会计分录。 （1）借：其他货币资金——银行汇票40 000 贷：银行存款40 000 （2）借：其他货币资金——外埠存款50 000 贷：银行存款50 000 （3）借：其他货币资金——信用卡12 000 贷：银行存款12 000 （4）借：材料采购31 000 应交税费——应交增值税（进项税额） 5 270 贷：其他货币资金——银行汇票36 270 （5）借：银行存款 3 730 贷：其他货币资金——银行汇票 3 730 （6）借：其他货币资金——信用证150 000 贷：银行存款150 000 （7）借：材料采购40 000 应交税费——应交增值税（进项税额） 6 800 贷：其他货币资金——外埠存款46 800 （8）借：银行存款 3 200 贷：其他货币资金——外埠存款 3 200 （9）借：管理费用 3 200 贷：其他货币资金——信用卡 3 200 （10）借：其他货币资金——存出投资款200 000 贷：银行存款200 000 3．3.星海公司20 x9年6月30日银行存款日记账的余额为41 100 元，同日转来的银行对

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九、设置保存路径。一定要记住保存的名称。点击确定 打开自己建立的库文件 一、创建一个新的Part，再点击 二、用浏览打开库文件，双击PowerCopy, 再双击input，再双击文档名称， 三、这里是什么平面，然后就在特征树上选择那个平 面，最后点击确定

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名词解释1

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作业习题及答案

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材料学基础-固体中的扩散 (Diffusion)

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CATIA参数化建模理念教程文件

C A T I A参数化建模理 念

CATIA参数化建模理念 1.CATIA参数化建模思路 1.1. 逆向建模 现阶段我们是运用大坝的CAD二维图来画三维图，也就是说先有二维图，后有三维图；基于CATIA的逆向建模是先建模，再出二维图。 1.2. 骨架设计 在传统的三维设计包含两种设计模式： ①自下而上的设计方法是在设计初期将各个模型建立，在设计后期将各模型按照模型的相对位置关系组装起来，自下向上设计更多应用于机械行业标准件设计组装。 ②自上而下设计的设计理念为先总体规划，后细化设计。 大坝骨架设计承了自上而下的设计理念，在大坝三维设计过程中，为了定义各建筑物相对位置关系，骨架包含整个工程的关键定位，布置基准，定义各个建筑物间相关的重要尺寸，自上向下的传递设计数据，应用这种技术就可更加有目的，规范地进行后续的工程设计。 1.3. 参数化模板设计 一、参数化设计基本原理 参数化设计基本原理：建立一组参数与一组图形或多组图形之间的对应关系，给出不同的参数，即可得到不同的结构图形。参数化设计的优点是对设计人员的初始设计要求低，无需精确绘图，只需勾绘草图，然后可通过适当的约束得到所需精确图形，便于编辑、修改，能满足反复设计的需要。 ①参数（Parameter）是作为特征定义的 CATIA文档的一种特性。参数有值，能够用关系式（Relation）约束。

②关系式（relation）是智能特征的一般称谓，包括：公式（formulas）、规则（ rules）、检查（checks）和设计表（design tables）。 ③公式（formulas）是用来定义一个参数如何由其他参数计算出的。 ④零件设计表：设计表是 Excel或文本表格，有一组参数。表格中的每列定义具体参数的一个可能的值。每行定义这组参数可能的配置。零件设计表是创建系列产品系列的最好方法，可以用来控制系列产品的尺寸值和特征的激活状态，表格中的单元格通常采用标准形式，用户可以随时进行修改。 ⑤配置（Configuration）是设计表中相关的参数组的一组值。 ⑥超级副本（PowerCopy）：超级副本是一组经过分组以用于不同上下文的特征（几何元素、公式、约束等），它提供了在粘贴时根据上下文重新指定特征的能力。超级副本可捕获设计者的设计意图和知识技能，因此可以提高重用性和效率。 ⑦用户特征（UDF）：在常规设计工作中，经常会有类似相同的设计，只是设计所用数据不一样；对于这种情况，可以用数据表控制数据源，在需要某数据时，指定相应数据；将以上重用数据表设计过程封装成 UDF，并发布相应数据，达到重用设计的效果。 二、参数化模板设计主要技术特征 参数化模板设计主要技术特征是：基于特征、全尺寸约束、尺寸驱动设计修改、全数据相关。 ①基于特征：将某些具有代表性的平面几何定义为特征，并将其所有尺寸存为可调参数，进而形成实体，以此为基础进行更为复杂的几何形体的构造。

名词解释1

上古歌谣：上古时期的民歌、民谣，是民间文学的一种。我国古代，以合乐为歌，徒歌为谣。上古歌谣是先民表达思想、抒发感情、促进生产的重要工具，是在生产力极为低下的原始时代产生的，是出现最早的文学样式。按题材内容，可分为劳动歌谣、祭祀歌谣、图腾歌谣、婚恋歌谣、战争歌谣等。它们具有集体性、综合性和再现生活的直接性，词句简朴，节奏流畅，以赋为其主要表现手法。 《周易》：先秦时的一部卜筮书。其文字分经、传两部分。其中的卦、爻辞为《易经》，约成于西周初年。它们记载了上古社会的一些情况，保存了一些具有朴素色彩的上古歌谣。《易传》是对经的说明和解释，大部分作于战国时期，反映了当时的哲学思想。 神话：神话是上古先民通过幻想以一种不自觉的艺术方式对自然现象和社会生活所作的形象描述和解释，用虚幻的想象表现了先民们征服自然、战胜自然的强烈愿望和乐观主义、英雄主义精神，是人类早期不自觉的积极浪漫主义艺术创作。它是原始文学的一种重要样式，是后世文学艺术的重要土壤和武库。 《山海经》：一部与巫术有关的古代地理著作，作者不详，约成书于战国时，秦汉时又有增补。共18卷，以记载传说中的地理知识为主，兼及民俗、物产、医药、巫术、祭祀等，尤其是保存了大量上古神话传说，如精卫填海、夸父逐日、黄帝杀蚩尤、鲧禹治水等，是我国先秦保存神话最多的古籍，具有重要的文学价值。 《诗三百》：即《诗经》。《诗经》在先秦时不称“经”，而是称“诗”或“诗三百”，如《论语》引《诗》评《诗》即是如此。《诗经》本有305篇，举其整数，故称“诗三百”。西汉初成为官学，被尊为经，始称《诗经》，后世也有沿称“诗三百”的。 风雅颂：是《诗经》的三个组成部分，也是根据地域和音乐的不同对《诗经》的分类。风也叫国风，是带有诸侯各国地方特色的乐歌，共有十五国风，160篇，多是民歌，少数是贵族作品。雅是周王朝京都地区的乐歌，分大雅、小雅。大雅31篇，多朝会宴享之作；小雅74篇，多个人抒情之作。雅诗中也有部分民歌。颂是王室宗庙祭祀或举行重大典礼时的乐歌，分周颂、鲁颂、商颂三颂，共40篇。 四家诗：指汉初出现的传授《诗经》的齐、鲁、韩、毛四家诗。前三家属“今文诗”，西汉时立于学官，分别亡于三国、西晋和宋时。《毛诗》属“古文诗”，东汉时立于学官，训诂多用《尔雅》，事实多本《左传》，流传至今。 毛传郑笺：汉代毛亨、毛苌为《诗经》所作的注解名为《毛诗故训传》，简称“毛诗”。东汉郑玄又为“毛诗”作笺注，名为《毛诗传笺》，简称“郑笺”。 赋比兴：《诗经》常用的三种艺术表现手法。赋指的是铺陈直叙事物的方法。比即比喻或比拟。兴即托物起兴，先言他物，以引起所咏之辞。 诸子百家：指春秋战国时出现的代表不同阶级和阶层利益的各种学术派别。当时，各派纷纷著书立说，招徒授学，宣扬自己的主张，互相辩难，形成了百家争鸣的局面。据《汉书·艺文志》记载，诸子百家主要有儒、道、阴阳、法、名、墨、纵横、农、杂、小说十家，影响较大的为儒、道、墨、法四家，尤以儒、墨为显学。 孔孟：孔子和孟子的合称。孔子是儒家学派的创始人，后人称为“至圣”，《论语》是以记载孔子言行为主的语录体著作。孟子是战国中期儒家的重要代表，后世称为“亚圣”，《孟子》是以记载孟子言行为主的语录体散文。 老庄：老子和庄子的合称。老子是道家学派的创始人，《老子》是道家后学对他思想的记载和发挥。庄子是战国中期道家的代表，《庄子》是他与其后学的著作的合辑。 《韩非子》：战国末期法家代表人物韩非子创作的一部政治哲学文集，今存55篇，少数篇章为后人窜入。其书融合并发展前人之说，建立了以法为本，法、术、势融为一体的极权主义的法制学说体系。其文多为说理文，逻辑严密，分析透彻，深刻明切，辞锋犀利，风格峻峭，善于分析类比，归纳总结，善于用历史故事和寓言故事阐明事理。

自动化仪表作业及答案参考

第一章： 作业： 1.DDZ与QDZ 得信号传输标准，DCS与FCS得名词解释 2.某压力表刻度0～１0０ｋPa，在5０kPa处测量值为49、5kPａ，求在５0kPa 处仪表示值得绝对误差、示值相对误差与示值引用误差？ 3.某台测温仪表得测温范围为—100~70０℃，校验该表时测得全量程内最大绝 对误差为+５℃,试确定该仪表得精度等级。 4.某台测压仪表得测压范围为0～8ＭPa.根据工艺要求，测压示值得误差不允 许超过±0、０5 ＭPa，问应如何选择仪表得精度等级才能满足以上要求? 5.某待测电流约为100mA，现有0、5级量程为0～400ｍA与1、５级量程 为0~10０mA得两个电流表,问用哪一个电流表测量比较好？ 6.某DDＺ－Ⅲ型温度变送器测量范围就是300-70０℃，当温度由４00℃变化到 60０℃时,变送器得输出如何变化？ 7.差压变送器得量程为0~１00 KＰa,现负迁移50%，仪表得量程与测量范围分 别为? 答案: 1、 QDZ信号标准:2０kPa~100ｋPa DCS：集散控制系统FCS:现场总线控制系统 2、 3、

4、 5、 解:用0、５级量程为0~400ｍA电流表测100mA时,最大相对误差：用1、5级量程为０～１00mA得电流表测１00mA时，最大相对误差： 说明选择合理得量程，即使用1、5级表也可以比０、5级表准确。 6、8mA ~16mA 7、仪表得量程为10０Kpａ仪表得测量范围为-５０～５０Kｐa 第二章: 作业:课后2，4,5，６，7，８，９,1１，1９，20 ２－2用热电偶测温时，为什么要进行冷端温度补偿？其冷端温度补偿得方法有哪几种？ 2-5由K 分度号热电偶(包括补偿导线）、冷端温度补偿器与配Ｋ分度号得动圈仪表组成一个温度检测系统,测量显示7８2℃,此时室温为３2℃,后来发现所用得冷端补偿器型号为S，与K分度号热电偶不配套，则实际温度？ 2-6用K型热电偶测某设备得温度,测得得热电势为20mV,冷端（室温）为2５C，求设备得温度?如果改用E型热电偶来测温,在相同得条件下，E热电偶测得得热电势为多少?

diffusion of innovation

1.Relative advantage is the degree to which an innovation is perceived as being better than the idea it supersedes(取代). The degree of relative advantage is often expressed as economic profitability, social prestige, or other benefits. The relative advantage of an innovation, as perceived by members of social system, is positively related to its rate of adoption. Preventive innovations: a preventive innovation has a particularly slow rate of adoption because individuals have difficulties in perceiving its relative advantage. Effects of incentives: many change agencies award incentives or subsidies to clients to speed up the rate of adoption of innovations. The main function is to increase the degree of relative advantage of the new idea. It can take a variety of form: 1) Adopter versus diffuser incentives 2) individual versus system incentives 3) positive versus negative incentives 4) monetary versus nonmonetary incentives 5) immediate versus delayed incentives. Incentives increase the rate of adoption of an innovation: adopter incentives increase relative advantage and infuser incentives increase the observability with which an innovation is perceived. Adopter incentives lead to adoption of an innovation by individuals different from those who would otherwise adopt. Although incentives increase the quantity of adopters of an innovation, the quality of such adoption decisions may be relatively low, limiting the intended consequences of an adoption. Mandates for adoption https://www.wendangku.net/doc/137836868.html,patibility is the degree to which an innovation is perceived as consistent with the existing values, and needs of potential adopters. An idea that is more compatible is less uncertain to the potential adopter, and fits more closely with the individual’s life situation. An innovation can be compatible or incompatible (1)with sociocultural value and beliefs (2) with previously introduced ideas, or (3)with client needs for the innovation. The compatibility of an innovation, as perceived by members of a social system, is positively related to its rate of adoption. Past diffusion research suggests that compatibility may be of relatively less importance in predicting rate of adoption than relative advantage. Compatibility withvalues and beliefs: an innovation’s incompatibility wi th cultural values can block its adoption. Compatibility with previously introduced ideas: an innovation may be compatible not only with deeply imbedded cultural values but also with previously adopted ideas. Compatibility of an innovation with a proceeding idea can either speed up or retard its rate of adoption. However, presumed compatibility with a previously introduced idea can cause overadoption or misadoption. The rate of adoption of a new idea is affected by the old, idea that it supersedes. Obviously, however, if a new idea were completely congruent with existing practice, there would be no innovation, at least in the minds of the potential adopters. In other words, the more compatible an innovation is, the less of a change in behavior it represents. How useful, then, is the introduction of a very highly compatible innovation? Quite useful, perhaps, if the compatible innovation is seen as the first step in a series of innovations that are to be introduced sequentially. The compatible innovation can pave the way for later, less compatible innovations.Innovation negativism is the degree to which one innovation's failure conditions a potential adopter to reject future innovations. When one

名词解释 1

第五章离子聚合（Ionic Polymerization） 活性聚合（Living Polymerization）：当单体转化率达到100%时，聚合仍不终止，形成具有反应活性聚合物（活性聚合物）的聚合叫活性聚合。 化学计量聚合（Stoichiometric calculation Polymerization）：阴离子的活性聚合由于其聚合度可由单体和引发剂的浓度定量计算确定，因此也称为化学计量聚合。 开环聚合（Ring-Opening Polymerization）：环状单体在引发剂作用下开环，形成线形聚合物的聚合反应。 第六章配位聚合(Coordination Polymerization) 配位聚合(Coordination Polymerization)：单体与引发剂经过配位方式进行的聚合反应。具体的说，采用具有配位（或络合）能力的引发剂、链增长（有时包括引发）都是单体先在活性种的空位上配位（络合）并活化，然手插入烷基—金属键中。配位聚合又有络合引发聚合或插入聚合之称。 定向聚合(Stereo-regular Polymerization)：任何聚合过程（包括自由基、阳离子、阴离子、配位聚合）或任何聚合方法（如本体、悬浮、乳液和溶液等），只要它是经形成有规立构聚合物为主，都是定向聚合。定向聚合等同于立构规整聚合 (Stereo-specific Polymerization)。 Ziegler-Natta聚合(Ziegler –Natta Polymerization)：采用Zigler-Natta引发剂的任何单体的聚合或共聚合。 立体异构(Stereo-isomerism)：分子中的原子的不同空间排布而产生不同的构型。可分为光学异构体和几何异构体。 构型(Configuration)：是由原子（或取代基）在手性中心或双键上的空间排布顺序不

作业及答案

一、（20分）考察教育对工资收入的影响，模型设定如下： 201234()Log wage educ exper exper female u βββββ=+++++ 其中，wage 表示工资（美元/小时），educ 表示教育（年），exper 表示工龄（年），female 为虚拟变量（如果是女士，female=1；如果是男士，female=0）。回归结果如下（括号内的数字表示t 统计量）。 2()0.390.080.040.00070.34Log wage educ exper exper female e =++--+ (3.8) (12.1) (8.1) (-6.4) (-9.8) N=526，R 2=0.40 请回答如下问题：（括号内的数字为回归系数对应的t 统计量，显著水平α=0.05） （1） 解释educ 估计量0.08的经济含义？（4分） （2） 工龄达到多少时，工资收入最高？（4分） （3） 其它变量相同时，男女之间的工资差异是多少？（4分） （4） 写出White 异方差检验的辅助回归方程（没有交叉项）？如果检验统计量为NR 2=14.7，存在明显的异方差吗？ （8分） 二、（10分）考虑以下用来解释月度啤酒消费量的线性模型： beer =β0+β1inc+β2price+β3educ+β4female+u E(u)=0 Var(u)=σ2inc 2 其中beer 为月度啤酒消费量，inc 为消费者的月度收入，price 代表啤酒价格，female 为性别虚拟变量。将以上模型转化为同方差模型，写出转化后的方程。 三、（20分）根据我国1980-2000年投资总额X 与工业总产值Y 的统计资料，应用OLS 估计得到如下结果： 2?ln 1.45210.8704ln (2.957)(7.490)0.99860.452t t Y X R DW =+== 请回答下列问题（检验水平为5％）： （1） 模型中是否存在一阶自相关？写出判断依据。 （2） 自相关会带来哪些问题，如何解决这些问题？ 四、（20分）考察中国1982年1季度至1988年4季度的市场煤炭销售量的季节变化，构建如下模型 01223344coal time D D D u βββββ=+++++ 其中，coal 表示煤炭销售量（万吨），time 表示时间趋势变量（time =1, 2, …, ），D 2, D 3, D 4表示三个季度虚拟变量，定义如下。 2 12 0D ?=? ?第季度其他季度， 3 13 0D ?=? ? 第季度其他季度，4 14 0D ?=? ?第季度其他季度 模型回归结果如下（括号内的数字表示t 统计量）： y t = 2431.20 + 49.00 time + 85.00 D 2 + 201.84 D 3 +1388.09 D 4 (26.04) (10.81) (0.83) (1.96) (13.43) R 2 = 0.95, DW = 1.2, s.e. = 191.7 请回答以下问题： （1） 解释D 4对应的参数估计量1388.09的经济含义（4分） （2） 检验变量D 2的显著性（检验水平为0.05）（4分）

CATIA全参数化建模理念

CATIA参数化建模理念 1.CATIA参数化建模思路 1.1.逆向建模 现阶段我们是运用大坝的CAD二维图来画三维图，也就是说先有二维图，后有三维图；基于CATIA的逆向建模是先建模，再出二维图。 1.2.骨架设计 在传统的三维设计包含两种设计模式： ①自下而上的设计方法是在设计初期将各个模型建立，在设计后期将各模型按照模型的相对位置关系组装起来，自下向上设计更多应用于机械行业标准件设计组装。 ②自上而下设计的设计理念为先总体规划，后细化设计。 大坝骨架设计承了自上而下的设计理念，在大坝三维设计过程中，为了定义各建筑物相对位置关系，骨架包含整个工程的关键定位，布置基准，定义各个建筑物间相关的重要尺寸，自上向下的传递设计数据，应用这种技术就可更加有目的，规范地进行后续的工程设计。 1.3.参数化模板设计 一、参数化设计基本原理 参数化设计基本原理：建立一组参数与一组图形或多组图形之间的对应关系，给出不同的参数，即可得到不同的结构图形。参数化设计的优点是对设计人员的初始设计要求低，无需精确绘图，只需勾绘草图，然后可通过适当的约束得到所需精确图形，便于编辑、修改，能满足反复设计的需要。 ①参数（Parameter）是作为特征定义的CATIA文档的一种特性。参数有值，能够用关系式（Relation）约束。 ②关系式（relation）是智能特征的一般称谓，包括：公式（formulas）、规则（rules）、检查（checks）和设计表（design tables）。 ③公式（formulas）是用来定义一个参数如何由其他参数计算出的。 ④零件设计表：设计表是Excel或文本表格，有一组参数。表格中的每列定义具体参数的一个可能的值。每行定义这组参数可能的配置。零件设计表是创建系列产品系列的最好方法，可以用来控制系列产品的尺寸值和特征的激活状态，表格中的单元格通常采用标准形式，用户可以随时进行修改。 ⑤配置（Configuration）是设计表中相关的参数组的一组值。

名词解释1

名词解释1.形训——是以形说义的方法，即通过对字的形体结构“当的分析来寻求解释词义的释词方法。 2.互训——即以意义相同之字，相互训释。 3.犹——相当于现代汉语的“等于说”，一般用于以同义词或近义词作释。 4.读曰——又称“读为”“破字”，即用本字本义来说明假借字。 5.当为——校勘术语，用以直接指明正字以纠正误字。也称作”。 6、句读：我国古代文章断句的符号和方法的名称，相当于今天标点符号的作用。 7、断章取义：，此赋诗不泥其本义，而借古人的话说自己的意思，来表达自己的观点。 8、连类并称：指两个字或词的义类相因而牵连之，但所指只取其中一词之义。 9、反义词对举：，则是连用词义对立，矛盾的两个词，但只强调矛盾的一个方面。 10、章句：，汉代注释家解释古书体例，往往在解释词义之外，再串计文章大意，这种解说方法叫章句。（流传到现在的以“章句”为名的注释书，有后汉赵岐的《孟子章句》和王逸的《楚辞章句》。 11、以形说义：，是指通过字形的分析，来了解字所记录的词的本义，即体现在造字意图中的基本词义。通假，就是在用字时不写本字而取另一个声音相同或相近的字来代替。 异言就是同一事物因时代不同或地域不同而有不同的称呼。 道形貌对文献语言的具体含义进行形象的描绘、说明。 注释工作用现代易知易懂的语言来解释古代难知难懂的文献语言。注释工作通常是随文释义的。 纂集工作一种有目的的字、词、义的类聚工作；一是为了集中使用某些材料而编纂；二是集中某些材料之外，还要通过编纂来证实某种理论。 考证工作考释和证明的合称。考释是指找出已经作出的训释的原始依据；证明是提出有力的证据。 训诂原理从训诂工作和训诂材料中总结出的文献词义理论。 □ 训诂用语言来解释语言的工作与材料。 训诂学以前代训诂材料和前人的训诂工作为研究对象而建立起来的一门科学，是研究语言意义的理论科学。 再度注释所谓再度注释，指的是针对汉代的经注，再作进一步的解释。

作业习题及答案

作业习题及答案 一、是非题（是画√，非画×） 1. 工件旋转作主运动，车刀作进给运动的切削加工方法称为车削。（√） 2. 变换主轴箱外手柄的位置可使主轴得到各种不同的转速。（√） 3. 卡盘的作用是用来装夹工件，带动工件一起旋转。（√） 4. 车削不同螺距的螺纹可通过调换进给箱内的齿轮实现。（×） 5. 光杠是用来带动溜板箱，使车刀按要求方向作纵向或横向运动的。（√） 6. 光杠用来车削螺纹的。（×） 7. 变换进给箱手柄的位置，在光杠和丝杠的传动下，能使车刀按要求方向作进给运动。（√） 8. 小滑板可左右移动角度，车削带锥度的工件。（√） 9. 床鞍与车床导轨精密配合，纵向进给时可保证径向精度。（×） 10. 机床的类别用汉语拼音字母表示，居型号的首位，其中字母“C”是表示车床类。（√） 11. 对车床来说，如第一位数字是“6”，代表的是落地及卧式车床组。（√） 12. C6140B表示第二次改进的床身上最大工件回转直径达400mm的卧式车床。（）√ 13. CM6140 车床比C620车床床身上最大工件回转直径要大。× 14. CQM6132车床型号中的32表示主轴中心高为320mm。（×） 15. 在机床型号中，通用特性代号应排在机床类代号的后面。（√） 16. 车床工作中主轴要变速时，变换进给箱手柄位置要在低速时进行。（√） 17. 为了延长车床的使用寿命，必须对车床上所用摩擦部位定期进行润滑。（√） 18. 车床漏在外面的滑动表面，擦干净后用油壶浇油润滑。（√） 19. 主轴箱和溜板箱等内的润滑油一般半年更换一次。（×） 20. 主轴箱换油时，现将箱体内部用煤油清洗干净，然后再加油。（√） 21. 车床主轴箱内注入的新油油面不得高于油标中心线。（×） 22. 车床尾座中、小滑板摇动手柄转动轴承部位，每班次至少加油一次。（√） 23. 油脂杯润滑每周加油一次，每班次旋转油杯盖一圈。（√） 24. 对车床进行保养的主要内容是：清洁和必要的调整。（×） 25. 车床运转500h，需要进行一级保养。（√） 26. 一级保养以操作工人为主，维修人员进行配合。（√） 27. 开机前，在手柄位置正确的情况下，需低速运转约2min后，才能进行车削。（√） 28. 装夹较重较大工件时，必须在机床导轨面上垫上木块，防止工件突然坠下砸伤导轨。（√） 29. 在车削时，车刀出现溅火星属正常现象，可以继续切削。（×） 30. 车工在操作中严禁戴手套。（√）