SCALING SPECTRA AND RETURN TIMES

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红外光谱波数英文

红外光谱波数英文全文共四篇示例，供读者参考第一篇示例：One of the key parameters in infrared spectroscopy is wavenumber, which is the reciprocal of the wavelength of the infrared radiation. Wavenumber is measured in units of reciprocal centimeters (cm-1) and serves as a scale for the infrared spectrum. In the infrared spectrum, the x-axis represents the wavenumber (in cm-1), while the y-axis shows the absorbance of the sample at each wavenumber. By examining the peaks and valleys in the spectrum, chemists can identify the functional groups and bonds present in the molecule.第二篇示例：One of the key parameters used in infrared spectroscopy is wavenumber, which is defined as the reciprocal of wavelength and is usually expressed in units of reciprocal centimeters (cm-1). Wavenumber is directly related to frequency, with higher wavenumbers corresponding to higher frequencies of vibration. Infrared spectra are typically displayed as a plot of intensityversus wavenumber, with peaks observed at specific wavenumbers corresponding to specific vibrational modes.第三篇示例：红外光谱是一种常用的分析技术，通过测量物质吸收、散射或反射红外辐射的能力来确定物质的结构和组成。

(英文)合成,与DNA和两个新的铜(II)的抗增殖活性相互作用配合甲斑蝥素和苯并咪唑衍生物

Synthesis,interaction with DNA and antiproliferative activities of two novel Cu(II)complexes with norcantharidin and benzimidazolederivativesWen-Ji Song a ,b ,Qiu-Yue Lin a ,b ,⇑,Wen-Jiao Jiang b ,Fang-Yuan Du b ,Qing-Yuan Qi b ,⇑,Qiong Wei ba Zhejiang Key Laboratory for Reactive Chemistry on Solid Surfaces,Zhejiang Normal University,321004,PR China bCollege of Chemical and Life Science,Zhejiang Normal University,321004,PR Chinah i g h l i g h t sTwo novel Cu(II)complexes withnorcantharidin derivatives have been synthesized.Complexes structure was determined by X-ray diffraction.The complexes and ligands bound DNA moderately via partial intercalation modes.Complexes could cleave plasmid DNA via hydroxyl radical mechanism. Complex(1)has strongest activity against human hepatoma cells.g r a p h i c a l a b s t r a c tTwo novel complexes [Cu(L)2(Ac)2]Á3H 2O(1)(L =N-2-methyl benzimidazole demethylcantharate imide,C 15H 13N 2O 3,Ac =acetate,C 2H 3O 2)and [Cu(bimz)2(DCA)](2)(bimz =benzimidazole,C 7H 6N 2;DCA =dem-ethylcantharate,C 8H 8O 5)were synthesized and characterized.The DNA-binding properties of complexes were investigated by electronic absorption spectra,ﬂuorescence spectra,viscosity measurements and agarose gel electrophoresis.The interaction between the complexes and bovine serum albumin (BSA)was investigated by ﬂuorescence spectra.The antiproliferative activities of the complexes against human hepatoma cells (SMMC7721)were tested in vitro .a r t i c l e i n f o Article history:Received 23June 2014Received in revised form 17August 2014Accepted 23August 2014Available online 1September 2014Keywords:NorcantharidinBenzimidazole derivatives Copper complex DNA bindingAntiproliferative activitya b s t r a c tTwo novel complexes [Cu(L)2(Ac)2]Á3H 2O (1)(L =N-2-methyl benzimidazole demethylcantharate imide,C 16H 15N 3O 3,Ac =acetate,C 2H 3O 2)and [Cu(bimz)2(DCA)](2)(bimz =benzimidazole,C 7H 6N 2;DCA =dem-ethylcantharate,C 8H 8O 5)were synthesized and characterized by elemental analysis,infrared spectra and X-ray diffraction techniques.Cu(II)ion was four-coordinated in complex 1,Cu(II)ion was ﬁve-coordi-nated in complex 2.A large amount of intermolecular hydrogen-bonding and p –p stacking interactions were observed in these complex structures.The DNA-binding properties ofthese complexes were inves-tigated using electronic absorption spectra,ﬂuorescence spectra,viscosity measurements and agarose gel electrophoresis.The interactions between the complexes and bovine serum albumin (BSA)were investi-gated by ﬂuorescence spectra.The antiproliferative activities of the complexes against human hepatoma cells (SMMC7721)were tested in vitro .And the results showed that these complexes could bind to DNA in moderate intensity via partial intercalation,and complexes 1and 2could cleave plasmid DNA through hydroxyl radical mechanism.Title complexes could effectively quench the ﬂuorescence of BSA through/10.1016/j.saa.2014.08.0691386-1425/Ó2014Elsevier B.V.All rights reserved.⇑Corresponding authors.Address:Zhejiang Key Laboratory for Reactive Chemistry on Solid Surfaces,Zhejiang Normal University,321004,PR China (Q.Y.Lin).Tel.:+8657982283353;fax:+8657982282269.E-mail addresses:sky51@ (Q.-Y.Lin),Qingyuanqi@ (Q.-Y.Qi).static quenching.Meanwhile,title complexes had stronger antiproliferative effect compared to L and Na2(DCA)within the tested concentration range.And complex1possessed more antiproliferative active than complex2.Ó2014Elsevier B.V.All rights reserved.IntroductionIn recent years,the interactions of Cu(II)complexes with DNA and protein molecules drew more and more scholars’attention [1,2].Copper(II)complexes are well suited for DNA hydrolysis due to the strong Lewis acid properties of the cupric ion.Several copper(II)complexes have been developed as artiﬁcial nucleases, and showed versatile DNA cleavage properties in the absence or presence of a redox agent[3,4].Planar heterocyclic based complexes have received consider-able interest in nucleic-acid chemistry because of their diverse chemical reactivity,unusual electronic properties,and peculiar structure,which results in non-covalent interactions with DNA [5].Benzimidazole derivatives possess a variety of biological activ-ities and pharmacological effects.Several compounds containing benzimidazole group,have been reported to exhibit antimicrobial, anticancer,antifungal and anti-inﬂammatory activities[6]. Especially,the combinations of the pharmaceutical agents with some metal ions can further improve their biological activity.Demethylcantharidin(NCTD,7-oxabicyclo[2,2,1]heptane-2,3-dicarboxylc acid anhydride)and disodium demethylcantharate (Na2(DCA)),as the derivatives of cantharidin,have been applied in clinical use[7].Meanwhile,demethylcantharate(DCA)could inhibit the activities of protein phosphatases1(PP1)and2A(PP2A)effec-tively[8,9].A range of amines were applied to react with norcantha-ridin,and results showed high level of cytotoxicity[10,11].Based on our previous investigations and as a continuation of our research program on complexes containing demethylcanthari-din[12,13],we synthesized two novel Cu(II)complexes containing demethylcantharidin.The interactions of these complexes with DNA and bovine serum albumin(BSA)were investigated.In addi-tion,antiproliferative activities against human hepatoma cells (SMMC-7721)were tested in vitro.Experimental sectionsMaterials and instrumentsAll reagents and chemicals were obtained from commercial sources.Demethylcantharidin(NCTD,C8H8O4)was obtained from Nanjing Zelang Medical Technology Co.Ltd.;Na2(DCA)was prepared in accordance with the literature described technique[14];2-ami-nomethylbenzimidazole dihydrochloride(ambiÁ2HCl)was pre-pared using the literature technique[15];benzimidazole(bimz, C7H6N2)and ct-DNA were obtained from Sinopharm Chemical Reagent Co.Ltd.;ct-DNA(q=200l g mLÀ1,c=3.72Â10À4mol LÀ1), with A260/A280=1.8–2.0,was prepared using50mmol LÀ1NaCl; Plasmid DNA(pDsRed2-C1)was purchased from Clontech Co.Ltd. America;Bovine Serum Albumin(BSA)was purchased from Beijing BioDee BioTech Co.Ltd.and was stored at4°C;BSA(q= 500l g mLÀ1,c=7.47Â10À6mol LÀ1)was prepared using 5mmol LÀ1NaCl solution;MTT(methyl thiazolyl tetrazolium)was purchased from the Sigma Company;Human hepatoma cells (SMMC-7721)was purchased from Shanghai Institute of Cell Bank. Other chemical reagents in analytical reagent grade were used with-out further puriﬁcation.Elemental analyses of C,H and N were carried out in Vario EL III elemental analyzer.Infrared spectra were obtained using the KBr disc method by NEXUS-670FT-IR spectrometer in the spectral range of4000–400cmÀ1.Diffraction intensities of the complexes were collected at293K on Bruker SMART APEX II CCD diffractom-eter.Electronic absorption spectra were obtained using UV-2501 PC spectrophotometer.Viscosity experiments were carried on Ubbelodhe viscometer.Fluorescence emission spectra were obtained by Perkin–Elmer LS-55spectroﬂuorometer.Agarose gel electrophoresis was performed on PowerPac Basic electrophoresis apparatus(BIO-RAD).Gel image formation were obtained on UNI-VERSAL HOOD11-S.N.(BIO-RAD Laboratories).Synthesis of LN-2-methyl benzimidazole demethylcantharate imide (L=C16H15N3O3)was prepared in accordance to the literature tech-niques[16].Mixture of1mmol norcantharidin(NCTD),1mmol2-aminomethylbenzimidazole dihydrochloride,1mmol cadmium acetate,and10mL distilled water was sealed in a25mL Teﬂon-lined stainless vessel and heated at433K for3d,then cooled slowly to room temperature.The solution was thenﬁltered and was allowed to stand still for3weeks until forming colorless crystals.Anal.Calcd. (%)for C16H15N3O3:C,64.65;H,5.05;N,14.14.Found(%):C,64.62;H, 5.03;N,14.16.IR(KBr pellet,cmÀ1):1617,1392(t(C@O));1446 (t(C@N));1258,1033,1001(t(C A O A C)).Synthesis of the complexesSynthesis of the complex1In a20mL weighing bottle,Cu(Ac)2ÁH2O(0.06g,0.3mmol)was dissolved in water(2mL).The L(0.089g,0.3mmol)solution in mixed solvents of water and ethanol(2:1,v/v)(10mL)was then added dropwisely with stirring under room temperature.The mix-ture solution wasﬁltered after two hours.One week after,blue crystals with suitable size for single-crystal X-ray diffraction were obtained.Anal.Calcd.(%)for C36H42N6O13Cu(1):C,52.05;H,5.06; N,10.12.Found(%):C,52.01;H,5.03;N,10.29.IR(KBr pellet, cmÀ1):3445(t(OH));1572,1395(t(C@O));1464(t(C@N));1254, 1057,984(t(C A O A C)).Synthesis of the complex2A mixture of Cu(Ac)2ÁH2O(0.5mmol)and Na2DCA(0.5mmol) was dissolved in water.And1.0mmol benzimidazole(bimz)in ethanol was added dropwisely into the mixed solution and stirring at room temperature.The solution wasﬁltered after two hours. One week later,blue crystals with suitable size for single-crystal X-ray diffraction were obtained.Anal.Calcd.(%)for Cu(C22H20 N4O5)(2):C,54.55;H,4.13;N,11.57.Found(%):C,54.25;H, 4.01;N,11.78.IR(KBr pellet,cmÀ1):3432(t(OH));1635,1396 (t(C@O));1432(t(C@N));1251,1032,981(t(C A O A C)).DNA bindingElectronic absorption spectraElectronic absorption spectra were collected at25°C byﬁxing the concentrations of the complexes,with DNA concentration ranging from0to7.44Â10À5mol LÀ1.Absorption spectra mea-surements were carried out at200–400nm,and DNA in Tris–HCl buffer solution(pH=7.4)was used as reference.W.-J.Song et al./Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy137(2015)122–128123Fluorescence spectraFluorescence quenching experiments were carried out by add-ing DNA solutions(0–7.44Â10À4mol LÀ1)to the samples contain-ing2.00Â10À5mol LÀ1complexes.The mixture were diluted by Tris–HCl buffer solution(pH=7.4).Fluorescence for1was recorded at excitation wavelength(k ex)of248nm and emission wavelength(k em)between250nm and500nm.Fluorescence for 2was recorded at244nm excitation wavelength(k ex)and emis-sion wavelength(k em)between255nm and450nm(k em).Viscosity measurementViscosity measurements were pounds were added to DNA solution(3.72Â10À4mol LÀ1)with microsyringes. The concentration of the compounds were controlled within the range of0–3.33Â10À6mol LÀ1.The relative viscosities g were cal-culated using equation[17]:g=(t–t0)/t0,where t0and t represent theﬂow time of DNA solution through the capillary in the absence and presence of complex.The average values of three replicated measurements were used to evaluate the viscosity of the samples. Data were presented as(g/g0)1/3versus the ratio of the concentra-tion of compounds to DNA,where g was the viscosity of DNA in the presence of compound and g0was the viscosity of DNA. Interaction with pDsRed2-C1plasmid DNAInteractions between the complexes and pDsRed2-C1plasmid DNA were studied using agarose gel electrophoresis.The samples were incubated at37°C for3h,followed by addition of0.25% bromo-phenol blue and1mmol LÀ1EDTA.The DNA cleavage prod-ucts were submitted to electrophoresis in1.0%agarose gel contain-ing0.5l g mLÀ1ethidium bromides.The bands were photographed.Interaction with BSAFluorescence spectraThe complexes(0–26.7Â10À9mol LÀ1)were added to solution containing4.98Â10À7mol LÀ1BSA and Tris–HCl buffer(pH=7.4). Fluorescence spectra were obtained by recording the emission spectra(285–480nm)at excitation wavelength of280nm.Antiproliferative activity evaluationThe antiproliferative activities of the compounds(1,2,L and Na2(DCA))were evaluated by human hepatoma cells(SMMC-7721).The MTT assay was applied to measure the antiproliferative activities[18].The compounds were dissolved in DMSO as 100mmol LÀ1stock solutions,and diluted in culture medium before using.The target concentration of DMSO in the medium was less than0.1%,and it did not interfere with the tested bioactiv-ity results[19].Cells were seeded for24h before adding com-pounds,and incubated for72h.Then100l L MTT(1mg mLÀ1, dissolved in DMEM nutrient solution)was added into each well and incubated for4h(37°C).The absorbance was measured by microplate reader at570nm.The inhibition rate was calculated accordingly.The errors quoted were standard deviations,which three replicates were involved in the calculation[20].Crystal structure determinationSingle crystals,sized0.345mmÂ0.279mmÂ0.214mm(1) and0.345mmÂ0.287mmÂ0.156mm(2),were used for X-ray diffraction analysis.The structures were solved by direct methods and reﬁned by full-matrix least-squares techniques using the SHEL-XTL-97program package[21,22].All non-hydrogen atoms were reﬁned anisotropically.Besides the hydrogen atoms on oxygen atoms,which were located from the difference Fourier maps,other hydrogen atoms were generated geometrically.Crystal data and experimental details for structural analyses are listed in Table1. Results and discussionStructural description of complexesTwo novel complexes have been characterized by X-ray single crystal diffraction.The spectral results indicated that the space groups of the complexes were C2/C(1)and Pna21(2).Selected bond lengths and angles of complexes1,2were listed in Tables2and3. Hydrogen bond lengths and angles of complex1,2were listed in Tables S1and S2.Molecular structures of the title complexes were shown in Fig.1.The packing diagram was shown in Fig.S1.In complex1,the Cu(II)ion was four-coordinated.Each Cu(II) coordinated with two imine nitrogen N(2)(or N(2A))from ligand (L),and two oxygen atoms of different carboxyl groups from acetate ions,forming electrically neutral complex.This molecule was cen-trally symmetric,with the symcenter at the centre of CuN2O2.The bond angles of O(1)A Cu(1)A O(1)#1,O(1)A Cu(1)A N(2),O(1)#1A Cu(1)A N(2)#1and N(2)A Cu(1)A N(2)#1are88.38(14)°,90.23 (10)°,90.23(10)°and97.25(14)°,respectively,all of which are close 90°.Thus,a slightly distorted quadrangle was formed around Cu(1) by N(1),N(2),O(1),and O(3).The composition of the complex was [Cu(L)2(Ac)2]Á3H2O(1).Fig.S1showed that the hydrogen-bonding formed due to the presence of the nitrogen atoms and the oxygen atoms from the imide(L)and acetate ligands,and crystallization water molecules.The complex is rich in intramolecular and intermo-lecular hydrogen bonds,such as N(1)A H(1A)...O(1W);O(3W)A H(3WA)...O(4);O(2W)A H(2WA)...O(2).These hydrogen-bonding stabilized this crystal structure.In complex2,Cu(II)ion wasﬁve-coordinated.Each Cu(II)coor-dinated with two azomethine nitrogen N(1)(or N(3))from two bimz,two carboxylate oxygen atoms O2and O3in two different carboxylate groups,and one bridge oxygen atoms O1from dem-ethylcantharate,forming a distorted tetragonal pyramid structure. The composition of the complex was[Cu(bimz)2(DCA)](2).Fig.S1 showed that the hydrogen-bonding formed due to the presence of the nitrogen atom from the bimz and the oxygen atoms from demethylcantharate,such as N(2)A H(2A)...O(5)#1,N(4)A H(4A)... O(3)#2.Meanwhile,complexes1and2contain the benzimidazole group,resulting k–k stacking effects among the complexes.There-fore,we concluded that the synergistic effect,including p–p stack-ing and hydrogen-bonding interactions,existed between the complexes and biomacromolecule,which could be the fundamen-tal cause of the biological activity change found in macromolecules [23].DNA binding studiesElectronic absorption spectraThe application of electronic absorption spectroscopy is one of the most useful techniques in DNA-binding studies[24].Changes observed in the UV spectra upon titration can provide evidence for the intercalative interaction mode pattern,since hypochro-mism would occur from p–p stacking interactions[25].To further investigate the possible binding modes and to obtain the binding constants(K b)of complex to DNA,we also studied the effect of DNA titration to the title complexes by electronic absorption spec-tra at298K.Results are shown in Fig.2((a):1;(b):2).The intrinsic binding constant(K b)was determined by the equa-tion:[DNA]/(e A–e F)=[DNA]/(e B–e F)+1/[K b(e B–e F)],where[DNA] was the concentration of DNA,e A,e F and e B corresponded to the apparent extinction coefﬁcient,the extinction coefﬁcient for the124W.-J.Song et al./Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy137(2015)122–128W.-J.Song et al./Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy137(2015)122–128125Table1Crystal data of complex1and2.Complex12Chemical formula CuC36H42N6O13CuC22H20N4O5 Formula weight794.28483.97Crystal system Monoclinic Orthorhombic Space group C2/C Pna21a(Å)21.572(4)15.8667(3) b(Å)11.3687(19)9.9975(2)c(Å)17.371(4)12.5228(2) a(°)90.0090.00b(°)111.528(18)90.00c(°)90.0090.00Volume(Å3)3963.0(13)1986.46(6) Z44Crystal size(mm)0.345Â0.279Â0.2140.345Â0.287Â0.156 Shape Block BlockFig. beled ORTEP diagrams of complex1(a)and2(b)with30%thermalprobability ellipsoids shown.complexes1and2are quenched in presence of DNA.The plexes showed strong emission bands at around297nm(1 nm(2),as shown in Fig.3.According to the Stern–Volmer equation:F0/F=1+K sv[Q],F0and F represent theﬂuorescence intensities in the absence and presence of quencher,respectively [Q]is the quencher concentration and K sv is the Stern–Volmer constant,K sv were calculated as 4.26Â103mol LÀ1(1)Â103mol LÀ1(2).The binding intensity of complex1 stronger than complex2,this is consistent to the results found electronic absorption spectra.Viscosity measurementsfurther study the binding mode of the compounds interact-with DNA,DNA viscosity at25°C was investigated(Fig.experimental data showed that the relative viscosity of steadily decreased after adding complexes and L,and it increase after adding benzimidazole.But there was no signiﬁcant viscosity change occurred after adding Na2DCA.The possible expla-nation is that the complexes and L were partially inserted to DNA base pairs and resulting in a kink in the DNA helix,therefore decreased the DNA effective length[29].Because of the planar benzimidazole ring could also insert to the DNA base pair,and the steric hindrances of complexes were enhanced due to the non-planar structure of demethylcantharate(DCA).From Fig.4, the interactions of complex(1)with DNA is signiﬁcantly stronger than complex(2).The result agrees with the electronic absorption spectra andﬂuorescence spectra conclusion.Interaction with pDsRed2-C1plasmid DNAThe cleavage reaction on pDsRed2-C1plasmid DNA can be mon-itored by agarose gel electrophoresis.When pDsRed2-C1plasmid DNA is subjected to electrophoresis,different migration speeds were observed[30].Relatively fast migrations were observed at the intact supercoil form(Form I).If scission occurs on one strand (nicking),the supercoil will partially relax to generate a slow moving open-circular form(Form II)[31].Absorption spectra of the complex1(a)and2(b)in the presence of increasing amount of DNA.[complex]=3.00Â10À6mol LÀ1,from(1)to(5):Â105=0,0.74,1.48,2.24and2.98mol LÀ1,respectively.(b).[DNA]Â103.72,5.58and7.44mol LÀ1,respectively.3.Fluorescence spectra of the complex1(a)and2(b)in the absence presence of increasing the amount of DNA;insert in Figs.3–5:ﬂuorescence quenching curve of the complex by DNA.k ex=248nm(1),k ex=244nm [complex]=2Â10À5mol LÀ1;[DNA]/(10À4mol LÀ1),from1to5:0,1.86,3.72,7.44,respectively.4.Effect of increasing amounts of the compounds on the relative viscosity[DNA]=3.72Â10À4mol LÀ1;[complex]/10À6=0,0.67,1.33,2.00,2.67mol LÀ1,respectively.5gave the electrophoretograms of the interactionRed2-C1plasmid DNA with increasing concentrations of complexes. Complexes are capable of cleaving plasmid DNA when the concen-of complexes was greater than500l M.When the concentra-complexes increased,the amount of Form I diminished gradually,and Form II paring channel4–6, cleavage ability of complexes was enhanced by adding ascorbic order to investigate the reaction mechanism,dimethylsulfox-(DMSO)was introduced to the experimental design.DMSO scavenger could inhibit the cleavage ability of complexes signiﬁcantly in channel5and7.With increasing amount of acid(V c),Cu(II)complex was reduced to Cu(I)complex.complex then reacts with dissolved oxygen generating superoxide anion(O2À),hydrogen peroxide(H2O2)and hydroxyl (ÅOH).Finally,the ROS attacks the plasmid DNA leading single and double DNA strand breaks.So the cleavage hydroxyl radical mechanism[32].Interaction with BSAFluorescence spectra and quenching mechanismresults of title complexes quenching the BSAﬂuorescence ing,which generated via intense interaction[36].Binding constants and binding sitesAssuming there were n identical and independent binding sites in protein,the binding constant K A can be calculated using equation[37]:lg(F0–F)/F=lg K A+n lg[Q].The values of K A were 1.59Â106L molÀ1(1), 5.4Â104L molÀ1(2),and 2.78Â104L molÀ1(Na2DCA).The values of n were0.88(1),0.68(2)and 0.66(Na2DCA).The results indicated that strong bindingElectrophoretic separation of pDsRed2-C1DNA induced by complexesLane1:DNA alone;lane2:DNA+complex(250l M);lane3:DNA(500l M);lane4:DNA+complex(750l M);lane5:DNA++DMSO(750l M);lane6:DNA+complex(750l M)+V c(750complex(750l M)+V c(750l M)+DMSO(750l M).[DNA]=3.06.Fluorescence spectra of BSA in the absence and the presence of complex2(b)Inset:Stern–Volmer plots of theﬂuorescence titration data ofcomplexes.[BSA]=4.98Â10À7mol LÀ1;[complex]Â109=0,6.67,13.3,20.0,mol LÀ1,from(1)to(5),respectively(a):complex1,(b):complex2.7.Inhibition effects of compounds on SMMC-7721cell growth.Data representmean+S.D.and all assays were performed in triplicate for three independentexperiments.interaction existed between the complexes and BSA.The binding intensity of complexes was stronger than Na2DCA,and the binding site of complexes was one.Antiproliferative activity evaluationAs shown in Fig.7,the antiproliferative activity of complex1, complex2,L and Na2DCA at the given concentration showed a dose-dependent manner against human hepatoma cells(SMMC-7721)in vitro.The inhibition ratios tested revealed that complex1and2had strong antiproliferative activities against human hepatoma cells (SMMC-7721)lines in vitro compare to L and Na2DCA.The inhibi-tion rates of complex(1)against SMMC-7721lines(IC50=24.55±0.48l mol LÀ1)is much higher than that of L(IC50=116.63±2.66 l mol LÀ1)[38].The inhibition rates of complex(1)against SMMC-7721lines is much higher than complex(2)(IC50=41.82±3.90 l mol LÀ1).The inhibition rates of two novel complexes were higher than that of the transition metal complexes of demethyl-cantharate and thiazole derivatives[12,13]against SMMC-7721 cells.which suggests that various compositions and structures of complexes would lead to different antiproliferative activities,and this can be important in designing and synthesizing novel anti-cancer drugs[39].It is clear that the strong interaction found between complexes and biomacromolecules(DNA or BSA)is directly correlated to the antiproliﬁferative activity of complexes.ConclusionsTwo novel Cu(II)complexes[Cu(L)2(Ac)2]Á3H2O(1)(L=N-2-methyl benzimidazole demethylcantharate imide,C16H15N3O3, Ac=acetate,C2H3O2)and[Cu(bimz)2(DCA)](2)(bimz=benzimid-azole,C7H6N2;DCA=demethylcantharate,C8H8O5)were synthe-sized and characterized.The crystal structure of complex1and2 were determined by X-ray diffraction.These complexes had strong DNA and BSA binding intensity and high inhibition rates against human hepatoma cells(SMMC-7721)in plex(1)had intense antiproliferative activities against the human hepatoma cells(SMMC-7721)in vitro,which had the potential to develop as an anti-cancer drug in the future.AcknowledgmentWe thank Institute of Zhejiang Academy of Medical Science for helping with antiproliferative activity test.Appendix A.Supplementary materialCrystallographic data for the structure reported in this article has been deposited with the Cambridge Crystallographic Data Center CCDC909444(1),918105(2).Copies of the data can be obtained free of charge on application to the CCDC,12Union Road,Cambridge CB21EZ,UK(deposit@).The packing diagrams of complexes were shown in Fig.S1.Hydrogen bond lengths and angles of complex1,2were listed in Tables S1and S2.Supplementary data associated with this article can be found,in the online version,at 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Annual and interannual (ENSO) variability of spatial scaling properties of (NDVI) in Amazonia

Annual and interannual (ENSO)variability of spatial scaling propertiesof a vegetation index (NDVI)in AmazoniaGerma ´n Poveda *,Luis F.SalazarPosgrado en Recursos Hidra ´ulicos,Escuela de Geociencias y Medio Ambiente,Universidad Nacional de Colombia,Medellı´n,ColombiaReceived 15January 2004;received in revised form 3August 2004;accepted 5August 2004AbstractThe space–time variability of the Normalized Difference Vegetation Index (NDVI)over the Amazon River basin is quantified through thebi-dimensional Fourier spectrum,and moment-scaling analysis of monthly imagery at 8km resolution,for the period July 1981–November 2002.Monthly NDVI fields exhibit power law Fourier spectra,E (k )=ck Àb ,with k denoting the wavenumber,c the prefactor,and b the scaling exponent.Fourier spectra exhibit two scaling regimes separated at approximately 29km,above which NDVI exhibit long-range spatial correlations (0b b b 2),and below which NDVI behaves like white noise in space (b g 0).Series of monthly values of c (t )and b (t )exhibit high negative correlation (À0.88,P N 0.99),which suggest their linkages in power laws,but also that E t (k )=c (t )k Àb (t ),with t the time index.Results show a significant negative simultaneous correlation (À0.82,P N 0.95)between monthly series of average precipitation over the Amazon,h P (t )i ,and scaling exponents,b (t );and high positive lagged correlation (0.63,P N 0.95),between h P (t )i and h NDVI(t +3)i .Parameters also reflect the hydrological seasonal cycle over Amazonia:during the wet season (November–March),b (t )ranges between 0.9and 1.15,while during the dry season (May–September),b (t )g 1.30.These results reflect the more (less)coherent spatial effect of the dry (wet)season over Amazonia,which translates into longer (shorter)-range spatial correlations of the NDVI field,as witnessed by higher (lower)values of b (t ).At interannual timescales,both phases of ENSO reflect on both parameters,as b (t )is higher during El Nin ˜o than during La Nin ˜a,due to the more coherent effects of El Nin ˜o-related dryness,whereas NDVI spatial variability is enhanced during La Nin ˜a,due to positive rainfall anomalies.Results from the moment-scale analysis indicate the existence of multi-scaling in the spatial variability of NDVI fields.Departures from single scaling exhibit also annual and interannual variability,which consistently reflect the effects from both phases of ENSO.Furthermore,departures from single scaling are independent of the order moment,q ,as the PDF of departures scaled by the mean collapse to a unique distribution.These results point out that ideas of spatial scaling constitute a promising framework to synthesize important hydro-ecological processes of Amazonia.D 2004Elsevier Inc.All rights reserved.Keywords:Annual and interannual variability;Spatial scaling;Amazonia1.Introduction1.1.NDVI and the hydrologic cycleSatellite information has contributed to improve our understanding of the spatial variability of hydro-climatic and ecological processes.Vegetation activity is tightlycoupled with climate,hydro-ecological fluxes,and terrain dynamics,and it controls water,energy and carbon budgets in river basins at a wide range of space–time scales.Indices of vegetation activity are constructed using satellite infor-mation of reflectance of the relevant spectral bands which enhance the contribution of vegetation.One such an index is the Normalized Difference Vegetation Index (NDVI),defined as the ratio of (NIR ÀRed)and (NIR+Red),where NIR is the surface-reflected radiation in the near-infrared band (0.73–1.1A m),and Red is the reflected radiation in the red band (0.55–0.68A m).Theoretically,NDVI takes values in the range from À1to 1,but the observed range is usually0034-4257/$-see front matter D 2004Elsevier Inc.All rights reserved.doi:10.1016/j.rse.2004.08.001*Corresponding author.School of Geosciences and Environment,Universidad Nacional de Colombia,Carrera 80x Calle 65,Bloque M2-315,Medellin AA1027,Colombia.Tel.:+5744255122;fax:+5744255003.E-mail address:gpoveda@.co (G.Poveda).Remote Sensing of Environment 93(2004)391–401smaller,with values around0for bare soil(low or no vegetation),and values of0.9or larger for dense vegetation. The work of Tucker(1979)pioneered the study of vegetation dynamics using red and near infrared spectral measurements.Sellers(1985)showed that NDVI is directly related to the photosynthetic capacity of plant canopies, which explains why NDVI is highly and directly correlated to the intercepted fraction of photosynthetically active radiation.As such,NDVI is independent of solar radiation, although variations in solar radiation can affect retrievals of NDVI.The meaning of diverse spectral vegetation indices is explained and summarized in Myneni et al.(1995).As NDVI represents the photosynthetic capacity or photosynthetic active radiation(PAR)absorption by green leaves,it is associated with fundamental hydro-ecological processes such as precipitation,which in turn is also directly linked to photosynthesis and hence plant growth.A recent work by Lotsch et al.(2003b)provides a comprehensive global analysis of NDVI and precipitation.Other variables pertaining to the hydrologic cycle have also been linked to NDVI,such as evaporation(Szilagyi et al.,1998;Lotsch et al.,2003b),and soil moisture(Nicholson&Farrar,1994; Farrar et al.,1994;Poveda et al.,2001).A strong relation-ship between evapotranspiration and NDVI have been identified in wet environments by Seevers and Ottmann (1994),and Nicholson et al.(1996),but also in water-limited environments,as reported by Tucker and Choudhury (1987),Malo and Nicholson(1990),Nicholson et al.(1994), Grist et al.(1997),Szilagyi et al.(1998),and Lotsch et al. (2003a).Changes in vegetation patterns have been studied at a global scale through NDVI estimates(Lucht et al., 2002).In turn,Nemani et al.(2003)identify those regions of the world where primary production is limited by water,by temperature or by both.1.2.Physical settingThe Amazon River basin provides an excellent example of the coupling and feedbacks in the land surface–atmos-phere system,due to its area larger than6.4million km2, constitute largest in the world,its tropical setting,and complex eco-hydro-climatological dynamics that exert a global influence.Scientific research towards understanding the hydro-climatic and ecological functioning of the Amazon is currently undergoing within the b Large-Scale Atmos-phere–Biosphere Experiment in Amazonia Q(LBA)(see Avissar and Nobre,2002;Roberts et al.,2003).Both observations and modelling results suggest strong changes in global,regional and local atmospheric circulation patterns associated with deforestation or perturbations in the land surface–atmosphere interactions over the Amazon(Salati& V ose,1984;Silva Dias et al.,1987;Zeng et al.,1996;Zhang et al.,1996;Poveda&Mesa,1997;Marengo&Nobre,2001; Werth&Avissar,2002;Nobre et al.,2004).The seasonal cycle of precipitation exhibits a wet season during Novem-ber–March and a dry season during May–September,as a result of the latitudinal migration of the Intertropical Convergence Zone(Obregon&Nobre,1990;Zeng,1999), which interacts with the seasonal cycle of moisture-laden low level winds from the Atlantic Ocean,but also with complex feedbacks of the land surface–atmosphere system,including the significant role of evapotranspiration in precipitation recycling(Salati,1985;Eltahir&Bras,1994).This work aims to quantify how the spatial statistics of NDVI reflect the seasonal hydro-climatic variability of the Amazon.1.3.Interannual variability at ENSO timescaleAt interannual timescales,tropical South America exhib-its coherent hydro-climatic anomalies during both phases of the El Nin˜o/Southern Oscillation(ENSO)(Aceituno,1988; Kiladis&Diaz,1989;Chu,1991;Marengo&Hastenrath, 1993;Ropelewski&Halpert,1996;Poveda et al.,2001; Waylen&Poveda,2002).With minor regional exceptions in timing and amplitude,the region experiences negative anomalies in rainfall,river discharges,and soil moisture during the warm phase of ENSO(El Nin˜o),and positive anomalies during the cold phase(La Nin˜a).Both large-scale forcing and land surface hydrology play a key role on the dynamics of hydro-climatic effects of ENSO over the region (Marengo&Hastenrath,1993;Poveda&Mesa,1997), which lag anomalies in the tropical Pacific sea surface temperatures by several months.The ENSO signal prop-agates to the east in northern South America,leading hydrological anomalies by1month over western Colombia (Poveda&Mesa,1997)and by6–10months in the Amazon River basin(Richey et al.,1989;Chu,1991;Eagleson, 1994).Consistently,NDVI diminishes over tropical South America during the occurrence of the warm phase of ENSO (Myneni et al.,1996;Asner et al.,2000;Poveda et al.,2001). This work aims to quantify how the spatial statistics of NDVI reflect the interannual hydro-climatic variability of the Amazon,associated with both phases of ENSO.1.4.Scaling theories of hydro-ecological processesScaling theories have provided important clues towards understanding and modelling the space–time dynamics of diverse bio-geophysical processes,such as vegetation sur-face fluxes(Katul et al.,2001),tropical convective storms (Yano et al.,2001),modeling of rainfall fields through fractal,multi-scaling,and random cascade models(Lovejoy, 1981,1982;Lovejoy&Schertzer,1991,1992;Gupta& Waymire,1990;Over&Gupta,1994;Perica&Foufoula-Georgiou,1996;Foufoula-Georgiou,1998;Deidda et al., 1999;Harris et al.,2000;Jotithyangkoon et al.,2000; Nordstrom&Gupta,2003),maximum annual river flows (Gupta&Waymire,1990;Gupta&Dawdy,1995;Goodrich et al.,1997;Ogden&Dawdy,2003),infiltration in porous media(Barenblatt,1996),low river flows(Furey&Gupta, 2000),ecological processes(Tilman&Kareiva,1997; Bascompte&Sole,1998),and vegetation dynamics(HarteG.Poveda,L.F.Salazar/Remote Sensing of Environment93(2004)391–401 392et al.,1999;Milne&Cohen,1999;Milne et al.,2002).For instance,in the study of river floods,Gupta(2004)has explained how scaling statistics in maximum annual river flows can be used to test different physical hypotheses covering complex runoff dynamics on channel networks.Diverse multi-scale statistical techniques are used to characterize and quantify the scale dependence of geo-biophysical fields,including Fourier spectra,structure and moment-scale functions.These functions are easily comput-able and allow an understanding of the spatial structure of the fields over a wide range of scales.Also,the use of multi-scale functions allows one to identify the range of scales where the scale dependence of modelled and observed variability may deviate,and the range of scales where the two agree(Harris et al.,2000).Towards those ends,we estimate the bi-dimensional Fourier spectra of monthly NDVI fields over Amazonia,and quantify the time variability of its parameters,and how they reflect the time–space variability of NDVI and precipitation fields at annual and interannual timescales.By the same token,we like to investigate whether monthly NDVI fields exhibit simple of multi-scaling properties in space,and how they reflect the annual and interannual variability of NDVI. Thirdly,we investigate the time correlation between series of monthly values of c and b with average values of NDVI and precipitation over the entire Amazon,so as to encapsulate the hydro-ecological dynamics of Amazonia. The data sets and methodologies are described in Section2, while results are presented in Section3,and the conclusions are provided in Section4.2.Data sets and methodologiesWe used digital maps of monthly NDVI from the NASA Global Inventory Modeling and Mapping Studies (GIMMS NDVI),covering the period July1981through November2002.The imagery,which consists of8km spatial resolution NDVI images,was provided by C.J. Tucker and his colleagues at NASA Goddard Space Flight Center.The GIMMS NDVI database exhibits a great deal of improvements with respect to previous NDVI data sets, including corrections for:(i)residual sensor degradation and sensor intercalibration differences;(ii)distortions caused by persistent cloud cover in tropical evergreen broadleaf forests;(iii)solar zenith angle and viewing angle effects;(iv)volcanic aerosols;(v)missing data in the Northern Hemisphere during winter using interpolation; and(vi)short-term atmospheric aerosol effects,atmos-pheric water vapor effects,and cloud cover.For details of the GIMMS NDVI data set,see Pinzo´n et al.(submitted for publication).The GIMMS NDVI data set has been rescaled in such a way that the original values in theÀ1 to1range are obtained as ndvi=(NDVIÀ1)/249À0.05, with values larger than1representing water bodies or bad data.Precipitation data for the Amazon basin were obtained from the data set produced by the Earth Observing System-Amazon Project(EOSAP)developed by Instituto Nacional de Pesquisas Espaciais(INPE),Brazil,and the University of Washington,and contains gridded monthly rainfall(0.28 latitudeÂ0.28longitude),for the period1972–1992.This data set was provided by the Global Hydrology and Climate Center of NASA.For details of this data set,see http:// /.With the purpose of implementing the spatial scaling analysis,a2048km scale region was defined inside the Amazon basin.The observed NDVI field for July1981is shown in Fig.1,aggregated at a32km scale.Character-ization of the spatial scaling properties of NDVI monthly fields was performed through estimation of the bi-dimen-sional Fourier spectrum,and moment-scale analysis.A detailed description of the methods is provided in the following section.2.1.Bi-dimensional Fourier spectrumMany geophysical phenomena exhibit power law decay-ing Fourier spectra,(Korvin,1992;Mandelbrot,1998),i.e., E kðÞf kÀb¼ckÀbð1Þwith k being the wavenumber,c is the prefactor,and b is the scaling exponent.The spectral slope,b,becomes a measure of roughness(Davis et al.,1996;Harris et al., 1996),with low spectral slopes corresponding to rougher, less correlated fields.Scaling exponents in Fourier spectra contain key insights on the dynamics underlying the physics of highly complex phenomena.For instance,the well-known behavior of dissipation of kinetic energy in turbulent flows,for which E(k)~k5/3(Kolmogorov,1941, 1962;Frisch,1995),whose scaling exponent,5/3,summa-rizes the rate at which kinetic energy is gradually trans-ferred from larger to smaller spatial scales,such that the mean kinetic energy per unit mass per unit time is conserved.Many other geophysical phenomena exhibit power law Fourier spectra,whose scaling exponents reflect different types of statistical memory and the scale of fluctuation which is inherent to their space–time correla-tions(Korvin,1992;Mesa&Poveda,1993;Turcotte, 1997;Mandelbrot,1998;Yano et al.,2001).The bi-dimensional power spectrum is computed using standard2-D Fast Fourier Transform(FFT)algorithms (Press et al.,1992).The Fourier power or energy spectrum, E(k x,k y)of a two-dimensional field,is found by multiplying the2-D FFT by its complex conjugate,where k x and k y are the wavenumber components(Harris et al.,2000).To facilitate visualization and comparison,the2-D power spectra from the NDVI fields are averaged angularly about k x=k y=0to produce the isotropic energy spectrum,E(k), with k¼ﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃk2xþk2yq.Such isotropic energy spectrum does not mean that the field is isotropic,but rather that the angularG.Poveda,L.F.Salazar/Remote Sensing of Environment93(2004)391–401393averaging about k x =k y =0integrates the anisotropy (Harris et al.,2000).2.2.Moment-scaling analysisMoment-scaling analysis allows the quantification of the spatial intermittency (roughness)of a field,and provides a test for the type of spatial (single or multi-)scaling behavior of random fields (Over &Gupta,1994;Harris et al.,2000).Statistical self-similarity can be thought of as statistical similarity of a random field across multiple scales,then simple scaling is a type of statistical self-similarity.Consider a random field,{X (t );t a I },where I represents an index set,and an arbitrary scalar k N 0.The random field is defined to be simple scaling if the following holds,X k t ðÞ¼dk h X t ðÞð2Þwhere the equality is understood in the sense of all finite dimensional distribution functions.From the definition of statistical moments given by E [X q]=R x q f (x )d x ,q =1,2,3,...,it is concluded that for a simple scaling random field,X (t ),E X q k t ðÞ½ ¼k h q E X q t ðÞ½ ;q ¼1;2;3;Nor ;log E X q k t ðÞ½ ¼q h log k þc q t ðÞ;ð3Þwhere c q (t )=log E [X q (t )].Eq.(3)shows that simple scaling must satisfy two conditions:(i)log–log linearity;(ii)linear slope growth,i.e.,s (q )=q h ,whereas multi-scaling holds for a nonlinear slope growth.In our case,the expected value in Eq.(3)arises from the equation that defines the scaling moments of a field X j ,which are computed for a range of averaging scales,r ,with higher values of r implying examining the phenomena at finer spatial resolution.Therefore,M q r ðÞ¼hj X r x ;y ðÞj q ið4Þwhere X r represents field values at scale r ,q is the order of the moment,and h ...i denotes the expected value of NDVI over all pixels at scale r .Typically,the scale of the image is dyadically reduced from its original highest resolution (r =1/(1pixel))by successive spatial averaging of the field by a factor of 2at each step,i.e.,r =1/(2pixels)=0.5,r =1/(4pixels)=0.25,...,r =1/(256pixels)=3.9Â10À3.Scaling of the moments means that (Gupta &Waymire,1993),M q r ðÞf r Às q ðÞð5Þwhere s (q )is the moment scaling exponent function that is estimated by log–log linear regressions of the q th moment of the NDVI field,on a scan by scan basis,as |X r |vs.log r ,for each q .It is easy to check that s (1)=0since the mean of the entire field does not depend upon the scale.Thelog–logFig.1.Location of the study region depicting the NDVI field for July 1981,aggregated at a 32km scale.G.Poveda,L.F .Salazar /Remote Sensing of Environment 93(2004)391–401394linearity of log M q (r )vs.log r provides a test of the scaling hypothesis for the moment of order q .3.Results3.1.Bi-dimensional Fourier spectrumOur generalized results indicate that the Fourier spectra exhibit two regions characterized by different scaling exponents,b ,separated at the wavenumber k =0.034km À1,which corresponds to 28.6km.Fig.2shows the 2-D Fourier spectra for the September 1989NDVI field.At larger spatial scales,the NDVI fields exhibit long-range correlations characterized by 0b b b 2,whereas for larger wavenumbers (smaller spatial scales),the spectrum becomes scale independent,with b g 0,thus meaning that the spatial variability of NDVI behaves irregularly,as white noise in space.Long-range correlations in the spatial distribution of water and energy-limited vegetation have been identified for the Columbia River basin in the USA (Milne et al.,2002).Analysis of the time evolution of monthly estimated values of scaling exponents,b (t ),and prefactors,c (t ),t =1,...,257,indicates a high negative correlation coefficient (À0.88,P N 0.95),as shown in Fig.3,which means that c (t )=f [b (t )],with f [d ]representing a linear function.This result points out to the existence of a strong association between these two parameters in power laws and scaling relationships;an idea that was introduced in the context of the Hurst effect in geophysical records (Mesa &Poveda,1993),which deserves further investigation.Furthermore,our results indicate that both parameters of the Fourier spectra vary with time,and thus E t (k )=c (t )k Àb (t ),where k denotes the wavenumber,and t represents the time index.Time series of monthly values of average precipitation and NDVI over the Amazon were estimated by averaging values of each field for a fixed month,as,h P t ðÞi ¼1=nXn i ¼1p i !t;and h NDVI t ðÞi ¼1=nX n i ¼1ndvi i!tð6Þwhere n denotes the number of pixels with information foreach field:12,991for precipitation,and 65,536for NDVI.Results show a significant negative correlation (À0.82,P N 0.95)between monthly values of average precipitation,h P (t )i over the Amazon and scaling exponents,b (t ),as illustrated in Fig.4.Such negative correlation indicates that wet months exhibit rougher (less spatially correlated)NDVI fields,which are encapsulated in lower values of b (t ).On the contrary,dry periods are associated with more coherent and longer-range correlated NDVI fields,which are reflected in higher values of b (t ).Accordingly,the afore-mentioned seasonal cycle of average precipitation,and the concomitant spatial variability of NDVI are also reflectedinFig.2.Bi-dimensional Fourier spectra of the NDVI field for September 1989,with scaling exponent,b =1.11,and prefactor,c =0.034.E (k )has arbitrary units,as NDVI is dimensionless.Values of NDVI are rescaled is such a manner that original data are recovered as ndvi=(NDVI À1)/249–0.05.The range of spatial scales covers from 512to 16km.The dotted line separates the two scaling regions of the spectrum at k =0.035km À1,which corresponds to a spatial scale of 28.6km.Fig.3.Time evolution of prefactors,c (t ),and scaling exponents,b (t ),for estimated bi-dimensional Fourier spectra of NDVI monthly fields,during the study period.Simultaneous correlation coefficient is À0.88(P N0.99).Fig. 4.Time evolution of monthly mean precipitation,h P (t )i ,over Amazonia and scaling exponents,b (t ).Simultaneous correlation is À0.82(P N 0.95).G.Poveda,L.F .Salazar /Remote Sensing of Environment 93(2004)391–401395a high positive correlation coefficient (0.72,P N 0.95)between the monthly series of average precipitation,h P (t )i and that of 6-month lagged scaling exponents,hb (t +6)i (not shown here).Despite that no significant correlation (À0.062)appears between the series of h P (t )i and h NDVI(t )i ,there is a significant positive correlation at 3-month lag (0.63,P N 0.95),see Fig.5,when precipitation leads NDVI.Such time lag suggests an integrated timescale at which rainfall affects NDVI dynamics at basin scale.The physical origin of this observation lies in the complex interactions of the land surface–atmosphere system,which include the afore-mentioned important effect of precipitation recycling in Amazonia (Salati,1985;Eltahir &Bras,1994).This observation deserves further investigation.3.1.1.Annual and interannual timescalesThe average long-term annual cycle of b (t )and c (t )were estimated from the 257estimated values (July 1981–November 2002).There is a strong negatively correlated seasonal cycle of prefactors,c (t ),and scaling exponents,b (t ),as evidenced in Fig.6.During the wet season (November–March),the estimated values of b (t )lie between 0.9and 1.15,while during the dry season (May–September),higher values are on the order of b (t )=1.30.These results are explained by the more coherent spatial effects of the dry season over the Amazon basin,which produce long-range spatial correlations in the NDVI field,reflected in higher estimates of b (t ).The annual cycle of prefactors,c (t ),exhibit higher values (~0.09–0.10)during the wet season,and lower values (~0.02–0.30)during the dry season.An understanding of the physical processes that govern such a strong association between scaling exponents and prefactors at seasonal scales is a topic of further research.At interannual timescales,ENSO strongly affects vege-tation activity and NDVI variability in Amazonia (Gutman,1991;Kogan &Sullivan,1993;Myneni et al.,1996;Asner et al.,2000;Poveda et al.,2001;Pinzo ´n,2002).Fig.7shows the annual cycle of scaling exponents,b (t ),during two contrasting ENSO years,i.e.,the 1991–1992El Nin ˜o,and the 1988–1989La Nin ˜a,as well as the average during normal years.The annual cycle is defined from June (year 0)through May (year +1),to better capture the aforementioned delayed effects of both ENSO phases.Overall,results indicate that the phase of the annual cycle of b (t )remains unchanged during both phases of ENSO,but there is a clear-cut effect on its amplitude.This is evidenced by higher values of b (t )during El Nin ˜o as compared with those during La Nin ˜a and normal years,throughout the annual cycle.Interestingly enough,the highest values of the scaling exponent are attained during August for both ENSO phases,and the lower values appears in February–March during El Nin ˜o,and in November–February during La Nin ˜a.This observation can be explained by the spatially coherent dryness caused over the Amazon by the warm phase of ENSO.It is well known that,in general,the Amazon basin experiences strong droughts during El Nin ˜o,and positive rainfall anomalies during La Nin ˜a (Richey et al.,1989;Fig.5.Time evolution of average values of monthly precipitation,h P (t )i ,and NDVI h NDVI(t )i ,over Amazonia.The caption of Fig.2explains the range of NDVI values.The low simultaneous correlation coefficient (À0.06)increases to À0.63(P N 0.95),when precipitation lead values of NDVI by 3months.Fig.6.Long-term annual cycle of estimated prefactors,c (t ),and scaling exponents,b (t ),from the estimated 2-D Fourierspectra.Fig.7.Annual cycle of scaling exponents,b (t ),during the 1991–1992El Nin ˜o event,the 1988–1989La Nin ˜a event,and during normal years.G.Poveda,L.F .Salazar /Remote Sensing of Environment 93(2004)391–401396Marengo,1992;Marengo &Hastenrath,1993;Obregon &Nobre,1990;Poveda &Mesa,1997;Poveda et al.,2001),whose effects are stronger in northern and central Amazonia(Marengo et al.,1998).The most remarkable differences occur in the November–March wet season during both phases of ENSO.During this epoch,both ENSO phases attain their maximum amplitude,and the associated tele-connections are more strongly developed,which in con-junction with land surface–atmosphere feedbacks cause stronger hydro-ecological anomalies,which affect the NDVI response over the Amazon.Our results confirm the coherent large spatial scale effects of El Nin ˜o-related drought over the Amazon basin,as a result of the 1991–1992event.It is concluded that scaling exponents,b (t ),exhibit significant variability at ENSO timescales,which are consistent with and reflect the identified hydrological anomalies.Similar to the temporal behavior of h NDVI(t )i ,results for the scaling exponents confirm that NDVI fields are more spatially correlated during El Nin ˜o than during La Nin ˜a.The interannual variability associated with both phases of ENSO is consistently exemplified by the evolution of b (t )and c (t )during the 1997–1998El Nin ˜o event,and during the 1998–2000La Nin ˜a event,shown in Fig.3.3.2.Moment-scaling analysisMoment-scale analysis were performed after checking for the condition that b (t )b 2(Harris et al.,2000).Fig.8shows the results for July 1991,with the scaling of marginal moments with q =0.5,1.0,...,4(top),and the estimated s ðq ˆÞcurve (bottom).Results indicate that monthly NDVI fields exhibit multi-scaling behavior in space,as indicated by the nonlinear behavior of the s ðq ˆÞfunction.Deviations from simple scaling were quantified as D q ¼s ðq ˆÞobserved Às q ðÞtheoretical ,e.g.,the difference between the sample values of the function s ðq ˆÞ,with respect to the linear growth for simple scaling (see Fig.9).Two features are worth mentioning:(i)there is a clear-cut annualandFig.8.Scaling of marginal moments with q =0.5,1.0,...,4(top),and estimated s ðq ˆÞcurve (bottom),for NDVI in July 1991.The straight continuous line and 95%confidence intervals (dashed)in the bottom pannel denote the theoretical behavior for simplescaling.Fig.9.Time evolution of departures from simple scaling,of the estimated s ðq ˆÞcurve,for q =1.5,...,4.0,during the study period.G.Poveda,L.F .Salazar /Remote Sensing of Environment 93(2004)391–401397。

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CRSP MANUAL-- FTP VERSION

CRSP MANUAL--FTP VERSIONThe following is a version of the CRSP Operating Manual(version7)for retrieval via anonymous FTP from NOAO.If you are reading this,you have obviously used the proper pro-cedure to retrieve,uncompress,and print the manual,so no further comments on this will ensue. However,there are some differences from the hardcopy manual.1.A number ofﬁgures from the Manual section were generated on a PC CAD program and are not amenable to conversion into the PostScript format.For the most part,theseﬁgures are descriptive of the instrument itself and are not critical to evaluating the performance or prepar-ing for use of the instrument.We are in the process of formatting this manual for the WWW, and will scan theseﬁgures for inclusion in that version.2.Due to an apparent bug(or feature)in the itroff preprocessor,some of the double-column tables(observing checklists and calibration line lists)destroy the formatting of succeeding pages.These items of text will thus appear at the end of the printed manual.3.For similar reasons,it appears impossible to embed the plots within the text,so they have been put in a separate PostScriptﬁle crsp.7.ﬁgs.ps.Z4.A separate PostScriptﬁle crsp.7.cal.ps.Z contains identiﬁed spectra of Ar,Kr,and HeNeAr sources for reference in wavelength calibration using these lamps.The overall order of the output is:crsp.7.ps.Z*This page*Table of Contents and Reference Tables(pp.i-iv)*Instrument Manual(pp.1-21)*Appendices(excluding plots and line lists)*Line lists(pp.45-48of Appendices)crsp.7.ﬁgs.ps.Z*Sky Background Spectra(13plots)*Standard Spectra(4plots)*Grating Efﬁciency Comparisons(4plots)*Identiﬁed Sky Line Spectra(7plots)*Table of Contents and Reference Tables(p.v)crsp.7.cal.ps.Z*HeNeAr lamp spectra,grating1(12plots)*Ar lamp spectra,gratings,2,3,4(6plots)TABLE OF CONTENTS1.Quick Reference Tables Foreword (i)CRSP Status Reference Tables (ii)2.CRSP Instrument Manual Introduction (1)Instrument Description (1)Telescope Performance and Preparation (6)Calibration (9)WILDFIRE (12)Observing Procedures (18)3.AppendicesAppendix I. 2.1-m Telescope Checklist (1)Appendix II.4-m Telescope Checklist (4)Appendix III.Speciﬁc WILDFIRE Commands (7)Appendix IV.Speciﬁc CRSP Commands (10)Appendix V.Troubleshooting (12)Appendix VI.Sky Background and Standard Spectra (16)Appendix VII.Suggested Grating Settings (39)Appendix VIII.Wavelength Calibration Tables (44)Appendix IX.Data Reduction Guide (56)Appendix X.TCL Scripts (64)CRSP User Manual7th Printing...........................................................................................................(Aug1995) v7.1......................................................................................................................(June1997) v7.1.1....................................................................................................................(July1997)FOREWORDNothing has changed except the hardware and the software--J.J.CharfmanVersion seven of the CRSP manual reports a number of changes made since the last hard-copy version was published in April1994.One of the most signiﬁcant changes,although not in the instrument,has been the closure of the1.3-m telescope.This manual has thus been exten-sively revised to reﬂect this fact.1.Since the baseline signal levels presented in the manual were obtained on the1.3-m with a4 arcsec slit,the tables have been revised to present the expected signal at the2.1-m telescope. Note,however,that a4arcsec slit at this telescope is the widest possible with CRSP,and almost all observations will be made with a narrower slit,with a consequent reduction in signal.2.The procedure for logging into the SUN workstations and the Wildﬁre environment has been changed to make it similar to that used in CCD observing with ICE.The procedure for starting Wildﬁre itself is unchanged.3.In summer1994,the old60l/mm grating4was replaced with a200l/mm grating blazed at 3µm,to provide a high-efﬁciency intermediate resolution complement to grating3in the H and I bands.This will probably be the last major hardware upgrade to this instrument.An ancillary effect is that the wavelength vs encoder relations for gratings2and3are somewhat different,as noted in the tables in Appendix VII and in the lambda command.4.In addition,the line lists for the calibration lamp and OH lines have been extended down to 0.9µm and the wavelengths of the OH lines not observed by Brault and Hubbard have been cal-culated from the energy levels of Coxon and Foster.This has resulted in small changes in some of the calculated wavlengths from the list in previous editions.Keep in mind that all these are vacuum wavelengths!5.The Wildﬁre section was revised slightly for clarity and a troubleshooting table added(June 1997).dj(16June1997)--v7.1CRSP InSb Status DisplayDetector Temp= 1.099Detector Htr Power(mw)=20.444 LN2(cy7)=0.938LHe(cy7)= 3.103 Stage(cy7)= 1.138VDet=-3.038VDDuc=-3.624 VOff=0.444VDDout=-1.055VGG=-1.514 V3=-2.686Data Offset0=-2.515Data Offset1=-2.002Typical CRSP ped Displaytitle[]Alpha Nuti g1K2.280microns600scoadds[1]1lnrs[1]8pics[1]1integration_sec[50]600ﬁlename[data%03d]data%03dheader_dir/data2/ir2meter/crsp/29febpixel_dir/data2/ir2meter/crsp/29feb/pixelsmode[stare]starepic_num[41]41ucode[CrspMed01_01]CrspMed01_01display[only]onlyra[0:00:00]dec[0:00:00]epoch[1950]offset[0]0type[object]objectairmass[1]comment[]CRSP2.1-m29Feb1939UT Charfman im_list[/tmp/list]var1[]var2[]var3[]var4[]save[only]onlyarchive[only]onlyTypical CRSP?ﬁlter DisplayThe grating is at position2580The slit is at380um(position3)The rotator is at position2179Theﬁlter is at j(position4)The limit switches are set to0x008Grating number1is in the beam.Detector Array:135columns illuminated(16-150);rotator position angle on left side256rows in dispersion axis;wavelength increases bottom to top30x30µm pixels,∼100%ﬁll factorgain:7.2electrons per ADU(analog-digital units=signal counts)quantum efﬁciency:approximately90-80%,1-3µmfull well capacity:∼1.3×104ADU(600mv bias)dark current:∼0.2ADU sec-1pixel-1bias level:∼0ADUreadout noise:∼4.5ADU pixel-1rms(single read)minimum integration time:315ms per low-noise read(see manual)GENERAL SPECIFICATIONSGRATINGS FILTERS SLITSNo.l/mm blaze(˚)pos.bandwidth(µm)pos.width(µm)width(pixels) 1300.36.81 2.90-5.501610 6.4275.10.2 1.92-2.582510 5.33150.17.53 1.40-1.823380 4.04200.17.54 1.14-1.364270 2.750.9-1.205125 1.3TYPICAL SIGNALS:0.0mag STAR on2.1-mgrating band orderλo∆λ/pixel0.0mag(ADU/s)τmax(s)1J3 1.24.000437.6×105>1000.H2 1.65.000698.4×105500.K2 2.05.00051 3.1×1051000.L1 3.50.00133 1.8×1050.5-2 2I4 1.05.00175 2.2×106>1000.J4 1.22.00173 2.0×106500.H3 1.50.00227 3.3×106300.K2 2.12.00346 2.0×10660.L1 3.60.00707.8×1050.315 3I3 1.07.00113 1.3×106>1000.J3 1.25.00110 2.0×106600.H3 1.50.00104 4.2×105>1000.K2 2.05.001587.8×105600.L1 3.50.0033 3.9×1050.5-1 4I30.99.00082 1.3×106>1000.J2 1.28.00126 2.8×106600.H2 1.55.0012 1.7×106500.K1 2.12.00254 1.4×106300.L1 3.50.00239 3.3×1050.5-1People:Support ScientistsDick Joyce--work8323,home9-299-3457(X533from mtn.)Ron Probst--email rprobst@Mike Merrill--work8319,home9-749-2924(X546from mtn.)Downtown IR Labs--8326;8384;8507Mountain Technical Assistantsofﬁce-X8607radio-X8721[give message and your telephone number twice;hit"#"key;hang up] radio-The portable radios in the control rooms may be used to call for assistance after0000hr--TA should give nightime phone,or call2.1-m LTO X8630 Engineers and Programmers(contact through the support scientists)Other Informationservice on SUN workstation to enter work requestsweather on SUN workstation to check on permission to open domeswd in IRAF on SUN workstation displays satellite weather mapSpeciﬁc comments on CRSP or WILDFIRE should be emailed to wﬁre@lemmingCRSP INSTRUMENT MANUAL1.IntroductionThe infrared Cryogenic Spectrometer (CRSP)is a longslit spectrometer designed for use at the f/15Cassegrain foci of the KPNO 2.1-m and 4-m telescopes.It incorporates a SBRC 256×256InSb array,gaining a signiﬁcant improvement in spatial and spectral resolution,dark current,and read noise over the 58×62array previously installed in the instrument.CRSP operates over the 1-5µm range,and interchangeable gratings permit spectroscopy at low (λ/∆λ∼300),moderate (λ/∆λ∼700),or intermediate (λ/∆λ∼1500)spectral resolution.Five slit widths,ranging from 1.2to 7pixels at the array,may be selected to achieve the desired compromise between spectral resolution and throughput.A dedicated instrument rotator permits slit position angles between -5and 185degrees on the sky.2.Instrument Description2.1.The Detector ArrayThe heart of the Cryogenic Spectrometer is a 256×256hybrid focal plane array from Santa Barbara Research Corporation.It consists of a photovoltaic InSb detector array mated to a silicon direct readout multiplexer via indium bumps.The readout is a p-channel MOSFET device.The device is presently operated in a destructive readout mode providing double correlated sampling.A representation of the voltage on a single pixel during an integration and readout is shown in Fig.1.An address cycle consists of a "reset"to the canonical detector bias voltage,a "read",followed by a second "read".During the reset operation,the voltage on each pixel is set to the value V R .When the reset switch is opened,the voltage left on the sense node will differ slightly from V R ,due to charge spillback from the reset gate and from kTC noise.After a time ’fdly’,the voltage on the pixel is sampled nondestructively (i.e.,without resetting),yielding V 1.After a second time interval,deﬁned as the integration time,the voltage is again sampled,yield-ing V 2.The "signal"is the difference between the two reads.Note that this technique,known as "double correlated sampling"eliminates the effect of the transient following the reset opera-tion.The intervals indicated (not to scale)at the bottom of the ﬁgure represent the time required to carry out each operation on the entire array;thus,on an absolute frame,the time at which a given pixel is reset and read depends on its location in the array.The operating microcode includes a provision for "multiple correlated sampling",in which the "reads"consist of a series of N nondestructive reads coadded to yield the values V 1and V 2.This greatly reduces (by approximately √N)the array read noise on long,low-background integrations.An additional factor is the time interval ’fdly’,between the reset and the ﬁrst read cycle,which is designed to permit the array to thermally restabilize after the heat dissipation resulting from the reset cycle.This variable is an important factor whose effects have not been com-pletely explored.On one hand,the need for a signiﬁcant (1sec)’fdly’seems necessary to achieve the lowest noise for long integrations at low background in terms of eliminating any bias between the ﬁrst and second reads.On the other hand,the existence of a delay between the reset and ﬁrst read means that one will be operating on the (nonlinear)voltage vs time curve in Fig.1at a point which is not inherently obvious from the observed signal.If the integration time is less than the nominal value of ’fdly’,the actual value of ’fdly’defaults to the integration time.Thus,at a minimum integration time of 315ms,the reset,read,read operations occur with no intervening pause.One should study Fig.1to note the effects of both ’fdly’and the readout time on the observed signal.With the present CRSP microcode,the time to read out the array is 315ms;by deﬁnition,this is also the minimum integration time.If the number of low-noise reads (’lnrs’)is greater than 1,the minimum integration time is <0.315*’lnrs’>sec.The interval toreset the entire array is about70ms.As a result,if one is operating the array at maximum speed,the actual’fdly’on a pixel will vary from70to315ms,depending on the location of the pixel in the array.The interval between reads will be a constant315ms for all pixels.Note that when one operates at the minimum possible integration time,the interval over which the array accumulates charge is up to twice the integration time,and one will beﬁlling the wells to twice the charge level suggested by the observed signal.Nonlinearity and saturation effects will thus occur for smaller observed signals.Table I summarizes the device characteristics and measured performance levels of the CRSP array SBRC41.Telescope performance will be covered in a later section.Due to imper-fect bonding,a section of the array(row>170)is inoperative,but the operable portion meets the speciﬁcations for a science-grade array.Since the slit covers only135pixels in the spatial dimension,the array was installed so that the spectrum covers the full256pixel column axis and is centered in the operable portion of the row axis.Table I.Device Characteristics for SBRC41256×256InSb Array.Array geometry30x30micron pixels,>90%ﬁll factor,256×256format,overall size7.68mm square.Well capacity1x105electrons/pixel(600mv bias)Readout noise∼30-35electrons/pixel,double correlated sampling,one read∼15electrons,8readsDark current<2electrons/pixel-second(600mv bias).Much of this isprobably scattered thermal radiation within the instrument Gain7.2electrons/ADUQuantum efﬁciency0.9(1-2µm);0.85(2.2µm);0.8(3.3µm)Response uniformity±15%;see Fig.8cCosmetics A few isolated dead pixels and a few with higher darkcurrent within the illuminated portion of the array;more high darkcurrent pixels at bias>600mv.See Fig.8cFurther information on the array design and operation may be found in Fowler et al.,Opt. Eng.,26,232(1987),and in Fowler and Heynssens,Proc.SPIE,1946,(April1993).The mul-tiple correlated sampling technique used for read noise reduction is described in Fowler and Gatley,Ap.J.(Letters),353,L33(1990).2.2.Spectrometer Description2.2.1.Optical DescriptionThe optical layout of CRSP,also known as"SALLY",is shown in Fig.2.The telescope focal plane is located just outside the entrance window on the top of the instrument.CRSP is now used exclusively at f/15.The input mirror M1forms an image of the telescope exit pupil on the mirror M2,which is masked to the exit pupil image diameter to serve as an optical cold stop.M2reimages the focal plane onto the physical slit S,which is located behind theﬁlter wheel FW,containing the order separationﬁlters.The spectrometer section consists of the col-limator M7,the four-grating turret G,and the achromatic camera C,which focuses the spectrum on the array.The actuator used previously for switching from f/15to f/30foreoptics has been converted to manually insert a dark slide(DS)into the beam for dark observations.Because this instrument was modiﬁed from an earlier prototype,some compromises were inevitable.The25˚off-Littrow operation results in signiﬁcant anamorphic magniﬁcation of the slit at large grating angles with the high-resolution grating.The inherent spectral line curvature is also exaggerated somewhat at large grating angles.The available space within the spectrome-ter section limits the collimator diameter,resulting in coverage of only135pixels in the spatial dimension.The pixel scale and spatial coverage at the two telescopes are summarized in Table II.Table II.Telescope f/ratio arcsec/pixel#pixels coverage(arcsec)2.1-m150.61135814m150.3613549Filters--Theﬁlter wheel containsﬁlters for order separation.All of the gratings are blazed in the vicinity of4µm,so operation at shorter wavelengths requires isolationﬁlters to prevent order overlap.Selection of the desiredﬁlter is through a computer-controlled stepper motor. Theﬁlter bandpasses and the expected order for typical use with high and low-resolution grat-ings(see below)are given in Table III:Table III.Order Separation Filterspos.bandwidth(µm)band order(low)order(med)order(high)1 2.90-5.50L,M1112 1.92-2.58K2223 1.40-1.82H3224 1.14-1.36J43350.90-1.20I†434†due to the width of thisﬁlter,order overlap will occur forλ>1.12µm(m=4)Entrance Slit--The spectrometer slit jaws are razor blades,one of which is supported by paral-lel leaf springs and positioned by a cam,which determines its separation from the stationary edge.Control is by a motor identical to that used forﬁlter selection;theﬁve possible widths in microns,pixels(one pixel is96µm at the focal plane),and arcsec at the telescopes are tabulated below in Table IV.Table IV.CRSP Slitspos.width arcsecµm pixels 2.1-m4-m1610 6.4 3.9 2.32510 5.3 3.3 1.93380 4.0 2.5 1.54270 2.7 1.7 1.05125 1.30.80.46Gratings--The gratings are mounted in a turret capable of holding four gratings which rotates, on an axis passing through the front surface of the selected grating,to the desired angle.To change gratings,the turret itself rotates about a central axis,accessible from outside the cryostat when the grating tilt is set to the proper value.There is one grating providing low resolution (λ/∆λ∼300),two of intermediate resolution(700),and one of high resolution(1200-2000);a resolution element is assumed to cover two pixels.Since the spectral coverage of the new array is60%greater than that of the old,a single setting of grating2will provide complete coverage of each of the I,J,H,K,and L bands.Grating3is blazed at4microns to yield optimum perfor-mance in the short K band;with the256×256array,it can cover the entire J band and most of the K band at a single setting.However,the efﬁciency in the H band is very poor.Grating4 will work efﬁciently in the L(m=1),H(m=2)and I(m=3)bands.Operation in the I band at m=3alleviates the order overlap encountered at m=4with this relatively broadﬁlter.Table V.CRSP Grating SpeciﬁcationsNo.l/mm blaze(˚)blaze(µm)bands1300.36.8 4.0I,J,H,K,L275.10. 4.5I,J,H,K,L3150.17.5 4.0I,J,K,L4200.17.5 3.0I,J,H,K,L2.2.2.Mechanical DescriptionLocated at the telescope focal plane are the spectrometer cryostat,instrument rotator,and associated warm electronics in two boxes mounted to the instrument.This assembly mounts to the off-axis acquisition/guiding box also used with IRIM for operation at the4-m telescope,or to the standard guider at the2.1-m.Figures3,4,and5illustrate the complete assembly from different views.CRSP communicates with a remotely located instrument computer and ulti-mately with the user in a remote observing room(Fig.6).Even though the f/15focal plane at the4-m is well back from the"nominal"focal plane of the telescope,a reimaging lens in each guide probe assembly permits them to be used for guiding and precision offsetting.Because the instrument rotators on the2.1-m and4-m telescopes differ in capability and operation,a dedicated rotator was constructed for this instrument.Slit position angles from-5 to185degrees are possible,although there will generally be some motion of the optical axis after a position angle change,since the optical and mechanical axes of the instrument may not be precisely coincident.Cryogenically,CRSP is a double reservoir system.Most of the internal parts,includingthe gratings,optics,andﬁlters,are cooled to77K with LN2.The array itself is operated at∼30K by a thermal strap to a LHe reservoir plus a closed loop heater circuit.The hold time ofthe LN2is∼20hours;the LHe will last∼14hours with power applied to the heater and∼24hours with the power off.On long nights a LHe reﬁll may be necessary during the night,partic-ularly if the system is operated at large zenith distances.Special"in-place"transfer lines on theinstrument permit reﬁlling the LN2and LHe without removal from the telescope.Thus,afterinstallation by the support scientist,the user need never concern herself with removing thedewar from the telescope.In any event,the cryostat should not be removed from the tele-scope without contacting mountain technical staff and/or the support scientist.Cryogen transfers are the responsiblity of the mountain technical staff;observers should work out a mutu-ally agreeable schedule for cryogen reﬁll with the staff if a nonstandard observing schedule is anticipated.Refer to Figures3,4,and5to identify the external features of the instrument.CRSP will be cabled upon installation,and should not be uncabled for any reason without contacting KPNO staffﬁrst.The only necessary user contacts with the focal plane instrument are the blue "activate"button on the analog electronics box,the mechanism for inserting the dark slide,and the mechanism for changing from one grating to another.The activate button closes the last relay between the external electronics and the array;the user will be prompted to push this but-ton as part of the startup procedure.This will also turn on a green LED visible through a hole in the analog electronics box.The grating change mechanism can be used only if the grating angle has been preset to the proper position;its use will be covered in the procedures section. Finally,note that there is no external index or means of inspection to verify the grating angle independent of computer control.Its position is derived from an absolute encoder coupled to the stepper motor,and so does not require any initialization upon startup or rebooting.mand,Communication,and ControlFig.6diagrams the complete system,including components remote from the focal plane. Power,command and dataﬁber optic lines run between the focal plane electronics and equip-ment in the computer rooms at the various telescopes.The FIRE system,orginally developed for SQIID,has evolved into the WILDFIRE sys-tem,which is now employed for all IR instrumentation at KPNO,including CRSP.CRSP is controlled from a SPARC2computer by the WILDFIRE system,a transputer based system which communicates over opticalﬁbers.WILDFIRE supports fast co-adding in place,movie mode,and data transfer directly to the SUN.The WILDFIRE system uses transputers and transputer links to control and acquire data from CRSP.A transputer is a single-chip microcomputer with its own local memory and com-munication links,which can operate either by itself or in conjunction with other elements linked to form computing arrays and networks.The WILDFIRE system consists of three main hardware components:The CRSP instrument control unit(inside the DCU box)contains two transputers which provide housekeeping data and control andgenerate the sequences which operate each array.The motor controllermodule is also inside the DCU,eliminating the need for the separatemotor controller box.All motor,data,and power cables are connectedto the DCU.The DSP unit(a VME based digital signal processor system located inside theblack Heurikon box in the computer room)contains eight transputers whichprovide the math processing needed to do coadding as the data is taken andbuffer space forﬁnished data before it is transferred to the SUN computer.The B016unit(a programmable dual-port memory and interface board locatedinside the black Heurikon box in the computer room)interfaces thetransputers and the SUN and handles the formatting of data before it issaved to disk.Communications between CRSP and the DSP take place over transputer links implemented on an opticalﬁber cable.The B016interconnects the transputer DSP to the SUN SparcStation computer via a VME to SBUS converter within the Heurikon box.(No more GETPIX!) The WILDFIRE user interface on the SUN is implemented within the TCL(tool command language)environment.The data appear as IRAF images,produced(in IEEE32-bitﬂoating point format)via IMFORT routines so that they can be manipulated and archived to tape insideIRAF.It is important to note that these images are NOT PROTECTED in any way and can be overwritten if the full path names of existing and new images are the same.The data may be written to Exabyte or DAT on local tape drives or sent via’ftp’to one’s home institution. Depending on the amount of header information,a single FITSﬁle of a256×256image is about270KB.At each of the telescopes where CRSP is used are two SUN workstations for data acquisi-tion and reduction.Under the present version of WILDFIRE,the secondary workstation[cocoa (4-m)and royal(2.1-m)]is used for data acquisition.The primary workstation[khaki and lapis at the two telescopes]has common access to the data disk,so additional observers can reduce and analyze the data independently.A third SUN serves as the telescope control,with a termi-nal at the LTO station;a hardwire link between the TCS and instrument control computers is used to send TCS commands to the telescope(singly,or within TCL scripts)and to retrieve telescope information for the image header.3.Telescope Performance and Observing Run PreparationThe limiting performance of CRSP depends on a number of factors.It is considerably more difﬁcult to estimate the signal/noise for a given observation than with IRIM,since the noise limitations in a spectrum often result from uncorrected systematic effects rather than sta-tistical noise.In addition,even the statistical noise in a spectrum is wavelength dependent, being limited by the shot noise of the sky background.At wavelengths short of2.3µm,the sky background consists of a series of emission lines,primarily OH airglow,which is both strong and temporally variable.At longer wavelengths,atmospheric absorption lines in continuum spectra will also show up as emission lines in the sky background.Because the sky background has numerous spectral features,it cannot be used forﬂatﬁelding,as with IRIM;observations of the dome"white spot"are necessary.The philosophy which will be stressed in the use of this instrument is one of conservatism and redundancy,with the aim of reducing the effects of sys-tematics on the observations.3.1.System ResponsivityTypical signals for representative grating settings are listed in Table VI.These are the maximum within the bandpass,summed over the width of the spectrum,in ADU/s,for a0.0 magnitude star.These were measured on the1.3-m with a4arcsec slit,so use of a narrower slit or bad seeing will result in less signal,which will be distributed over more than one row of pix-els on the array.The values were converted to those expected at the2.1-m telescope through multiplication by the ratio of collecting areas of the two telescopes(2.8).Keep in mind that these signals would be equivalent to those measured with the widest slit(#1)on the2.1-m,so that one might expect smaller signals with the slit widths likely to be used for observing.The conversion gain is7.2e/ADU.For gratings2and3,virtually all of a photometric window (except for L with grating3)is covered at a given grating setting,so the signal in Table VI is the maximum within the window.For grating1,the signal in Table VI is the maximum seen throughout the photometric window,which is typically4times wider than the free spectral range on the array.Observations at wavelengths other than those listed will probably yield less signal.The maximum integration times listed are for the same telescope and slit width,to avoid saturation at the wavelength of highest background within the bandpass.These results are plot-ted in Appendix Vl.。

Optical properties of SiO2-TiO2 sol-gel thin films

J O U R N A L O F M A T E R I A L S S C I E N C E39(2004)2835–2839Optical properties of SiO2-TiO2sol-gel thinﬁlms P.CHRYSICOPOULOUHarokopio University,Department of Home Economics and Ecology,70El.Venizelou St., 17671Athens,GreeceE-mail:pchrys@hua.grD.DAVAZOGLOUNCSR”Demokritos,”Institute of Microelectronics,P.O.Box60228,15310Agia Paraskevi, Attiki,GreeceC.TRAPALIS,G.KORDASNCSR”Demokritos,”Institute of Material Science,P.O.Box60228,15310Agia Paraskevi, Attiki,GreeceThe optical properties of thin SiO2-TiO2sol-gel compositeﬁlms were investigated using exact optical models and the Forouhi-Bloomer model,(Phys.Rev.B34,7018(1986)),which describes the optical dispersion of amorphous dielectrics.Films deposited on glass and silicon substrates,were characterized by optical transmission and reﬂection measurements.Theoretical spectra have been generated andﬁtted to the experimental ones via standard regression analysis techniques.The(ﬁve)adjustable Forouhi-Bloomer parameters describing the dispersion of the complex refractive index,as well as theﬁlm thickness were determined.The refractive index and absorption coefﬁcient of theﬁlms were found to depend on the molar contents of the component oxides.C 2004Kluwer Academic Publishers1.IntroductionThe preparation of amorphous glasses through thesol-gel process in the past few decades has experiencedremarkable growth and has found an increasing num-ber of applications such as coatings,sensors,photocat-alysts,precursors for preparation of ceramic materials,etc.[1–8].Among them titania-silica composite oxidesare noted for their interesting physical and chemicalproperties which include a very low or negative thermalexpansion,a high refractive index,solid acidic proper-ties,photocatalysis and alkali passivation mechanisms[9–15].In the present work,we have studied the optical pa-rameters of sol-gel SiO2-TiO2compositeﬁlms as afunction of the various molar component concentra-tions.The experimental transmittance and reﬂectancespectra of the system,ﬁlm-substrate-ﬁlm,wereﬁtted totheoretical ones,calculated using the Forouhi-Bloomer(FB)physical model[16]to describe the optical disper-sion in the compositeﬁlms.2.ExperimentalThin compositeﬁlms SiO2-TiO2were produced viathe sol-gel method by hydrolysis of the correspondingmetal alkoxides in alcoholic solutions.The followingcompositions were prepared:x SiO2·(100−x)TiO2, with x=0,25,50and100mol%.For the preparationof the100mol%SiO2ﬁlm the precursor was silicontetraethoxide(Si(OC2H5)4,Merck)and was dissolvedin absolut(99.8%)ethanol(C2H5OH,Merck),followed by the addition of HNO3(65vol%,Farmitalia-Carlo Erba)as the acid catalyst and of distilled water.Then the mixture was stirred at60◦C for two hours to initiate the hydrolysis and polycondensation.Correspondingly,the 100mol%TiO2ﬁlm was produced through hydrolysis of titanium tetraethoxide(Ti(OC2H5)4,Alfa Products, Germany)in absolut ethanol,with the addition of nitric acid,sealing the mixture from atmospheric air and stir-ring it at room temperature for about two hours as well. The composite SiO2-TiO2ﬁlms were made following the same procedure as for the SiO2ﬁlms with the dif-ference that,at the end of the stirring,Ti(OC2H5)4was added and the mixture was sealed from atmospheric air and left to stir for another half hour at room temper-ature.In all solutions the molar ratio of water to the TEOS alkoxide was kept equal to four.The amount of HNO3added to the solutions was enough to ensure that the pH values ranged between0.5and2. Amorphous uniform gel coatings were formed on both sides of substrates immersed in the above so-lutions,by dipping-withdrawing in an ambient atmo-sphere,a few hours after the sol preparation.The thick-nesses of the highly uniform coatings,thus produced, are easily controlled through regulation of the with-drawal speed of the substrates from the solutions.For the cases of x=0,25and50the substrates were 1mm thick glass microscope slides and the withdrawal speed was set to50cm/min,and for the case of x= 100,where the sol-gelﬁlms would have a composi-tion similar to that of the glass microscope slide and0022–2461C 2004Kluwer Academic Publishers2835consequently similar optical properties,the substrate used,instead was a silicon wafer,withdrawn with a speed of40cm/min.All samples were heat treated af-ter their formation for30min,at400◦C in a Carbolite RHF1200oven,in air,at a rate of2◦C/min,leading to oxideﬁlm structures.The temperature of400◦C was chosen so that it was high enough to ensure complete burning of the organic components,yet being within the range allowed by the glass substrate.The heating time of30min was selected to ensure sufﬁcient time for densiﬁcation and burning of organics,as well as to minimize the diffusion of alkali ions present in the glass substrate,as conﬁrmed by references[17–19]. Transmittance spectra of theﬁrst three cases(Samples 1,2and3),mentioned above,were recorded using a UV/VIS/NIR Lamda19spectrophotometer of Perkin Elmer.With the same spectrophotometer,specular re-ﬂectance spectra were taken for Sample4,deposited on an opaque Si substrate.Doubly polished Si wafers were used as standards for the reﬂection.These wafers were covered with an oxide layer,approximately50nm thick, as determined by one wavelength(632.8nm)ellipsom-etry.The reﬂection spectra of these mirrors were syn-thesized using refractive index data found in the litera-ture for crystalline Si[20]and Malitson’s formula[21], to describe the refractive index dispersion of the top oxide.3.Theoretical procedureThe spectra obtained were analyzed using exact optical models[22,23]for the transmittance and reﬂectance of a stack ofﬁlms,combined with the physical model of Forouhi-Bloomer[16],for the optical constants of amorphous materials.The calculation principles of the optical models have been presented in earlier publica-tions[24–26].The optical models includeﬁve phases: air-compositeﬁlm-substrate-compositeﬁlm-air and the transmittances and reﬂectances of the composite sys-tem are calculated using the“effective”reﬂection and transmission Fresnel coefﬁcients described in detail in reference[24].These coefﬁcients are functions of the real,n,and imaginary,k,part of the complex refractive index of theﬁlms and the substrate,and also of their respective thicknesses.The FB model, which has been extensively described in previous papers[24–26],assumes electronic transitions only be-tween two parabolic bands,the valence and conduc-tion bands,originating from superposition of molec-ular orbital states,the valence from bonding and the conduction band from antibonding states.These bands are separated by an energy gap E g while the en-ergy distance between bonding and antibonding states equals to B/2.The dispersion relations n(E)and k(E), which are Kramers-Kronig related,are then derived to be[16]:n(E)=n(∞)+B0E+C0E(1)k(E)=A(E−E g)2E2−BE+C(2)whereB0=AQ−B22+E g B−E2g+C,C0=AQE2g+CB2−2E g CandQ=12(4C−B2)1/2Except n(∞),which is the refractive index at high ener-gies,A is related to the position matrix element and thelifetime of the electronic transitions involved and C isrelated to B and the lifetime.This rather simple math-ematical model describes well the excitations near theabsorption threshold in disordered dielectrics[25–28]and the results are physically meaningful provided that[25]:(i)E g,as deﬁned by the FB model,takes smallervalues than B/2,(ii)E g takes values close to those ob-tained using other physical models(e.g.,Tauc’s[29]model),and(iii)Q is positive.Under the above condi-tions,the FB model relates n and k to parameters per-taining to the dielectric’s electronic structure,unlikeother formulas(e.g.,Cauchy’s formula).It should beemphasized at this point that although the crystallinityof the samples of this investigation is unclear,the FBmodel for disordered dielectrics can be applied,even inthe case of their being polycrystalline.This is possiblebecause the model is being applied within the low en-ergy domain,where the existence of sharp structures inthe dielectric constants of the samples is not expected.Moreover,the model permits the determination of nand k from one and only measurement.We have useda modiﬁed version of the FB model which demandsthat the extinction coefﬁcient,k,vanishes for energiesbelow the energy gap E g.This version has been pre-viously used to describe optical dispersion in siliconoxynitride[28],tin oxide[25,26],silicon nitride[27],amorphous[25]and polycrystalline Si thinﬁlms[30].4.Results and discussionIn Table I are presented the values of theﬁve FB modelparameters and the corresponding90%conﬁdence in-tervals which are estimated byﬁtting the calculatedtransmittance and reﬂectance spectra to those experi-mentally recorded,minimizing the quantity(unbiasedestimator):f=1NNT exp(λ)−T calc(λ)2(3)by standard regression analysis techniques[31].N rep-resents the number of points used for the minimizationprocess(about800points),T exp(λ)the experimental,T calc(λ)the calculated values of the transmittance andσ(λ)the uncertainty of the measurement at each wave-length.The uncertaintyσ(λ)varied with each wave-length in an unknown way so,an uncertainty equal to0.05T exp has been attributed to each value.A corre-sponding estimator is deﬁned for the reﬂectance spec-tra.The thicknesses d,of theﬁlms are also estimated2836T A B L E I Forouhi-Bloomer model parameters,ﬁlm thicknesses d ,and unbiased estimators f for the four samples studied.The corresponding 90%conﬁdence intervals are also shown Composition x =0x =25x =50x =100x mol%SiO 2y =100y =75y =50y =0y mol%TiO 2Sample 1Sample 2Sample 3Sample 4n (∞) 1.9811±0.0030 1.8012±0.0042 1.6501±0.0038 2.3759±0.0365A0.1686±0.01280.3015±0.02050.2113±0.01500.7083±0.0095B (eV)8.5837±0.00038.6740±0.02069.1227±0.02719.7520±0.4735C (eV 2)18.685±0.01319.275±0.080821.4690±0.125391.5020±2.8506E g (CV) 3.0020±0.0235 3.3769±0.0172 3.3372±0.021710.0060±0.2475d (nm)93.516±0.237100.430±0.434109.20±0.91104.09±0.13F0.37970.20050.44560.2395through the minimization process and are reported in the above table.It must be noted that the results from ﬁtting to reﬂectance experimental values are less accu-rate than those obtained from ﬁtting to transmittance values.This is related to the uncertainties pertaining to the calibration of the reference mirrors,as well as to the ﬁtting procedure.Within this procedure data from the literature referring to the silicon wafer have been used,obtained for ultra pure silicon,cleaned at the mo-ment of the measurement.These conditions were not fulﬁlled in this investigation.It can be observed that for the ﬁrst three samples the ﬁrst of the previously mentioned,conditions (E g <B /2)is fulﬁlled.On the contrary,this is not the case for the fourth sample composed exclusively of SiO 2.This is because SiO 2starts to absorb at much higher energies than those in this study hence,the k is not involved in the calculation of the theoretical spectra,and consequently,the minimization program does not optimize E g and B simultaneously (see Equation 2).Another observation that can be made concerning Table I,is that E g and B do not vary appreciably with the molar content of the components.This is because E g ,within the FB model,is deﬁned in such a way that the absorption threshold and the so-called Urbach’s tail [29]are both described by this parameter (we return to this point further on).In Fig.1are presented the experimental and the calcu-lated transmittance spectra for Sample 3and the good agreement between the two is apparent.In Fig.2areFigure 1UV-Vis transmittance spectra,experimental (solid line)and calculated (dashed line)for Sample 3,with composition 50mol%SiO 2·50mol%TiO 2.Figure 2UV-Vis reﬂectance spectra,experimental (solid line)and cal-culated (dashed line)for Sample 4,with composition 100mol%SiO 2.Figure 3Wavelength dependence of the real part of the refractive index,n ,of ﬁlms,with compositions:(a)100mol%TiO 2,(b)25mol%SiO 2·75mol%TiO 2,(c)50mol%SiO 2·50mol%TiO 2,and (d)100mol%SiO 2.presented the experimental and calculated reﬂectance spectra for Sample 4.The good agreement between the two is also observed.The real part,n ,of the (complex)refractive index,calculated by using the FB parameters presented in Table I and Equation 1,is plotted in Fig.3,for each sample composition,as a function of the wavelength.As expected,the n of the composite ﬁlms,varies be-tween the values corresponding to pure SiO 2and TiO 2.The n value of 1.43for the 100mol%SiO 2sample is in rather good agreement with the 1.421value reported for the sol-gel 100mol%SiO 2ﬁlms sintered at 500◦C,on silicon wafers,of ref.[33].It is a value somewhat2837lower than that of ref.[32](1.47)for non-crystalline SiO 2which may be attributed to incomplete densiﬁ-cation of the coatings due to the low temperature and short duration of the thermal treatment.It is worth noting at this point that,in spite of the fail-ure of the minimization program to obtain a physically acceptable value of B ,for the 100mol%SiO 2com-position,it gives overall good results.This is due to the mathematical similarity of Equation 1to formulas describing the refractive index dispersion.Our n values for the 100mol%TiO 2(2.18)are,in good agreement with the n values (2.1)for the 100mol%TiO 2ﬁlms on soda-lime-silicate glass sub-strates of reference [34],sintered at 450◦C.They are lower than those reported in ref.[16]for TiO 2ﬁlms produced by anodic oxidation of titanium,which can be assumed to be more dense.This fact could be at-tributed to differences in the preparation method,that induce differences in ﬁlm structure.It is also to be noted in Fig.3that the increase in the n values with the increase of the TiO 2molar content is pared to other values obtained for sol-gel ﬁlms of similar compositions [18,33],the com-posite SiO 2-TiO 2ﬁlms (Samples 2,3)exhibit compa-rable indices of refraction,taking into account the dif-ferences in preparation,and nature of substrates.Our refractive index values can also be compared to the cor-responding values 1.48–2.39obtained in ref.[35]for composite ﬁlms of similar compositions on fused silica substrates,but produced with an ion beam sputtering process.In that study,where the nature of the substrate remains unchanged throughout the samples,there is,as in our study,a smooth increase in the values of n with the increase of the TiO 2component molar content.Differences between our results and those of ref.[35],apart from discontinuities in the nature of the substrate for x =0,25,and 50,could also arise from the fact that the ratios of components of composite oxides we quote represent the ratio of the alkoxides in the prepar-ing solutions and not necessarily the actual ratios of the components in the ﬁlms.Fig.4shows (α·E )1/2as a function of the pho-ton energy for the various ﬁlm compositions,where α[=(4πk /λ)]is the absorption coefﬁcient.ForSampleFigure 4Optical absorption spectra of ﬁlms with compositions:(a)100mol%TiO 2,(b)25mol%SiO 2·75mol%TiO 2,and (c)50mol%SiO 2·50mol%TiO 2.Extrapolating the linear part of each graph the Tauc energy gap value is estimated.4(x =100)there is no curve in Fig.4because,as men-tioned above,the FB model has been modiﬁed,in that k has been set to zero for energies smaller than E g .It is observed that for all of the samples,the absorption edge presents a linear part at higher energies.For the Sam-ples 1,2,and 3,the slope of this linear part decreases with the increase of the SiO 2content while,the Tauc energy gap [29](deﬁned as the point of interception of the linear part of the absorption edge with the energy axis)is blue shifted with it.It is worth noting at this point the signiﬁcance of the different deﬁnitions of the energy gaps within the FB and Tauc’s model.While the ﬁrst indicates the onset of absorption,the second is a means of describing higher values of absorption.In view of the above,the small variations of E g ,as deﬁned by the FB model,reported in Table I,are justiﬁed.5.ConclusionsWe have measured the refractive index dispersion for very thin SiO 2-TiO 2sol-gel composite ﬁlms,from their transmittance/or reﬂectance spectra using a straightfor-ward method.The n ,k and ﬁlm thickness have been de-termined by one and only measurement with the use of a physical and an exact optical model.The ﬁlm optical properties were described satisfactorily by the physi-cal method in the range 200–2500nm and the index of refraction values were observed to increase mono-tonically with the increase of the TiO 2molar content,ranging between 1.43for pure SiO 2to 2.18for pure TiO 2.The energy gap values,as deﬁned by the model did not vary appreciably with the TiO 2molar content,while the Tauc energy gap increases with the SiO 2mo-lar content.AcknowledgementsWe thank EIIET II 296and GSRT for funding.References1.H .K .P U L K E R ,“Coatings on Glass”(Elsevier Amsterdam-Oxford-New York-Tokyo,1984).2.J .R A N C O U R T ,“Optical Thin Films-User’s Handbook”(MacGraw Hill,New York,1987).3.J .A U G U S T Y N S K I ,“Aspects of Photo-Electrochemical and Sur-face Behaviour of Titanium (IV)Oxide”(Springer-Verlag,Berlin,1988).4.M .F L E I S H E R and H .M E I X N E R ,Sensors Actuators B 4(1991)437.5.C .J .B R I N K E R and G .W .S C H E R E R ,“The Physics and Chemistry of Sol-Gel Processing”(Academic Press,Inc.,New York,1990).6.H .D .G E S S E R and P .C .G O S W A M I ,Chem.Rev.89(1989)765.7.D .G A L L A G H E R and T .A .R I N G ,Chimia 43(1989)298.8.D .Y .J E N G and M .N .R A H A M A N ,J.Mater.Sci.28(1993)4964.9.K .K A M I Y A and S .S A K K A ,J.Non-Cryst.Solids 52(1982)357.10.T .H A N A D A ,T .A I K A W A and N .S O G A ,J.Amer.Ceram.Soc.67(1984)52.11.H .D I S L I C H and E .H U S S M A N ,Thin Solid Films 77(1981)129.12.M .A N P O ,H .N A K A Y A ,S .K O D A M A ,Y .K UB O 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C.Bernard(Electrochem.Soc.Proc.,1997) V ol.97,No.25,p.796.31.F.J A M E S,Function Minimization,in Proceedings of the1972CERN Computing and Data Processing School,Pertisau,Austria, 10–24Sept.1972.32.H.R.P H I L I P P,“Properties of Silicon,”INSPEC(The Instituteof Electrical Engineers,1987)p.1015.33.S.M.M E L P O L D E R,A.W.W E S T,C.L.B A R N E S andT.N.B L A N T O N,J.Mater.Sci.26(1991)3585.34.K.B A N G E,C.R.O T T E R M A N,O.A N D E R S O N,U.J E S C H K O W S K I,M.L A U B E and R.F E I L E,Thin Solid Films 197(1991)279.35.H.D E M I R Y O N T,Appl.Opt.26(16)(1985)2647.Received2December2002and accepted5January20042839。

211251873_牡蛎源肽锌纳米粒体外胃肠道消化稳定性及作用机制

惠森，朱旭浩，刘小玲，等. 牡蛎源肽锌纳米粒体外胃肠道消化稳定性及作用机制[J]. 食品工业科技，2023，44（11）：38−44. doi:10.13386/j.issn1002-0306.2022110206HUI Sen, ZHU Xuhao, LIU Xiaoling, et al. Stability and Mechanism of Oyster Peptide Hydrolysate Zinc Nanoparticles during in Vitro Gastrointestinal Digestion[J]. Science and Technology of Food Industry, 2023, 44(11): 38−44. (in Chinese with English abstract). doi:10.13386/j.issn1002-0306.2022110206· 青年编委专栏—食品营养素包埋与递送（客座主编：黄强、蔡杰、陈帅） ·牡蛎源肽锌纳米粒体外胃肠道消化稳定性及作用机制惠　森1，朱旭浩1，刘小玲1，张自然2,*（1.广西大学轻工与食品工程学院，广西南宁 530000；2.北部湾大学食品工程学院，广西钦州 535011）摘　要：本研究旨在探究体外模拟消化对牡蛎源肽锌纳米粒（OPH-Zn ）稳定性及其结构的影响，揭示OPH-Zn 在胃肠道消化过程中的动态变化规律。

采用各种光谱仪（紫外、红外和荧光）、电镜（扫描和透射）以及粒度仪测定模拟消化液中OPH-Zn 的锌含量、表面形貌、二级结构以及粒径分布变化。

研究发现，OPH-Zn 总锌含量高达228.89±2.53 mg/g ；在模拟胃液消化过程中，OPH-Zn 和ZnSO 4对照中可溶性锌含量变化不大，且两个样品无显著差异（P >0.05）；转为模拟肠液消化时，OPH-Zn 和ZnSO 4的锌溶解性分别降低了28.07%和55.31%（P <0.05），与ZnSO 4相比，OPH-Zn 可溶性锌含量显著高于ZnSO 4（P <0.05）；光谱分析发现，OPH-Zn 在模拟胃液和肠液中保持相对稳定，但在由胃液过渡到肠液时，Zn 2+与肽键中氧原子和氮原子的配位作用发生变化，电镜结果显示不同消化程度的OPH-Zn 表面微观结构和颗粒大小也存在一定差异。

Universal 1f noise, cross-overs of scaling exponents, and chromosome specific patterns of G

a r X i v :q -b i o /0411016v 1 [q -b i o .G N ] 3 N o v 2004Universal 1/f noise,cross-overs of scaling exponents,and chromosome speciﬁcpatterns of GC content in DNA sequences of the human genomeWentian Li ∗The Robert S.Boas Center for Genomics and Human Genetics,North Shore LIJ Institute for Medical Research,350Community Dr.,Manhasset,NY 10030.Dirk Holste †Department of Biology,Massachusetts Institute of Technology,Cambridge,MA 02139.Spatial ﬂuctuations of guanine and cytosine base content (GC%)are studied by spectral analysis for the complete set of human genomic DNA sequences.We ﬁnd that (i)the 1/f αdecay is universally observed in the power spectra of all twenty-four chromosomes,and that (ii)the exponent α≈1extends to about 107bases,one order of magnitude longer than what has previously been observed.We further ﬁnd that (iii)almost all human chromosomes exhibit a cross-over from α1≈1(1/f α1)at lower frequency to α2<1(1/f α2)at higher frequency,typically occurring at around 30,000–100,000bases,while (iv)the cross-over in this frequency range is virtually absent in human chromosome 22.In addition to the universal 1/f αnoise in power spectra,we ﬁnd (v)several lines of evidence for chromosome-speciﬁc correlation structures,including a 500,000bases long oscillation in human chromosome 21.The universal 1/f αspectrum in human genome is further substantiated by a resistance to variance reduction in guanine and cytosine content when the window size is increased.PACS numbers:87.10.+e,87.14.Gg,,02.50.-r,,02.50.Tt,89.75Da,89.75.Fb,05.40.-aI.INTRODUCTIONBy measuring the proportion of a signal’s power S (f )falling into a range of frequency components f ,a power spectrum of the form S (f )∼1/f αdistinguishes be-tween two prototypes of noise:white noise (α=0)and Brownian noise (α=2).The intermittent range,termed “1/f noise”,can practically be deﬁned as 1/f α(0.5 α 1.5).1/f noise was experimentally observed ﬁrst in electric current ﬂuctuations of the thermionic tube at the beginning of the nineteenth century [1].Since then,1/f noise has been found repeatedly in many other conducting materials [2].More generally,it has also been observed in wide ranges of natural as well as human-related phenomena,including traﬃc ﬂow,star light,speech,music and human coordination [3,4].For biological sequences,such as DNA,the concept of slow-varying,multiple-length variations in the power of fre-quency components can be translated to long-ranging correlations in the spatial arrangement of the four bases adenine (A),cytosine (C),guanine (G)and thymine (T).One can categorize chemically A,C,G,and T as strong (G or C)or weak (A or T)bonding.It has been shown that ﬂuctuations of the GC base content along a DNA se-quence are typically stronger correlated when compared to other possible binary classiﬁcations [5,6].Initial stud-ies of 1/f noise in DNA sequences were motivated by a model of spatial 1/f noise of symbolic sequence evolu-tion [7].Subsequently,empirical 1/f spectra were indeed observed in non-protein-coding DNA sequences [8],and2sequence length [bases]n u m b e r o f s e q u e n c esFIG.1:Double-logarithmic representation of the human genome-wide length distribution of interspersed repeat se-quences,non-repetitive sequences,and sequences of unknown base composition (gaps).The length distribution of in-terspersed repeats and non-repetitive sequences exhibits a power-law-like decay,while that of gap sequences is scattered across diﬀerent sequence length.The peaks at ∼300bases and several kb correspond to Alu and possibly LINE repeats.chromosomes 21and 22are about 34Mb long,in order to estimate the limit of the range of 1/f αspectrum,longer sequences are necessary.After the release of the draft of the human genome se-quence in February 2001,about three years later in 2004,a dozen (out of 24)human chromosomes have been com-pleted with a sequence accuracy to following the standard of less than one error per 10,000DNA bases (99.99%accuracy)[21].Building upon the release of updated,high-quality sequence data,in the era of genomics we can now conduct a systematic analysis of several issues of 1/f noise in the DNA sequences of our own species Homo sapiens ,which have been pursued over the last decade in a fragmentary manner.In this paper,we use the DNA sequences of the com-plete set of twenty-two autosomes and two sex chromo-somes to address the following issues:Is 1/f noise uni-versally present across the entire set of human genome sequences?Does 1/f noise extend to lower frequency ranges in longer DNA sequences?Is the decay of S (f )characterized by a single exponent α,or does it exhibit cross-overs (multiple scaling exponents)?Given the pres-ence of universal variations at multiple scales,do these co-exist with variations at chromosome-speciﬁc scales?II.DATA AND METHODSIn this section,we introduce the data for human genome sequences,as well as the notation and deﬁni-tions used throughout this study.Twenty-four chromo-somes are assembled in build 34of the NCBI (human genome hg16release).Sequence data were downloaded from the UCSC human genome repository (available atGC base content [%]n u m b e r o f s e q u e n c e sFIG.2:Distribution of genome-wide GC content (GC%)of the human genome for interspersed repeat sequences,non-repetitive sequences,and all (“overall”)sequences with se-quence segments of 20kb.The mode (peak location)of non-repetitive sequences is at ∼35%,while the mode of repetitive sequences shifted to a higher GC%(∼42%).The fraction of non-repetitive sequences with GC%>50%is markedly larger as compared to the repetitive sequences./).Unsequenced bases are kept to preserve spacing between bases.Human chromosomes (Chr)13,14,15,21,and 22contain large amount of un-sequenced bases in the left end of their DNA sequences,consisting of about 15%,17%,18%,21%,and 29%of the individual chromosome size,respectively;51%of chro-mosome Y are unsequenced.Our analysis on human DNA sequences is conducted using coarse-grained data.Each original sequence was transformed into a spatial series of GC content (GC%)values.To this end,we evenly partition a DNA sequence into N non-overlapping windows of length w bases,com-pute ρi (w )=GC%i for each window i ,to obtain a spatial GC%series:{ρi }≡{ρi (w )}≡{GC%i }i=1,2,...,N(1)Table 1lists the corresponding window sizes for each hu-man chromosome.Since diﬀerent human chromosomes have diﬀerent sizes,whereas the number of partitions (N )is the same,the window lengths vary.Human DNA sequences contain a large fraction of in-terspersed repeats,i.e.,copies of an ancestral sequence fragment that possess a high similarity between the duplicated and the ancestral sequence.One can de-tect interspersed repeats by using the program Repeat-Masker [22].“Soft-masked”annotations of interspersed repeats are taken from the DNA sequences of the UCSC human genome repository (/),where repetitive (non-repetitive)bases are annotated in small (capital)letters.Figure 1shows the length dis-tribution of the three sequences classes of uninterrupted non-repetitive,interspersed repeat,and gap sequences.Figure 2shows the corresponding distribution of the genome-wide GC%for these three sequences classes.To investigate the eﬀect of interspersed repeats,we3 TABLE I:Average GC content(ρ),the window size(w)for partitions using N=217non-overlapping windowsfor twenty-four human chromosomes.Low-frequency scalingexponentsα1are estimated from S(f;s=3)∼1/fα1inthe range of10−7<f<10−5base−1,and high-frequencyscaling exponentsα2are estimated in the range of10−5< f<2×10−4base−1.The diﬀerence between the two scaling exponents,∆α≡α2−α1,are listed in theﬁfth column. Low-and high-frequency exponents for S(f)with substituted interspersed repeats are indicated byα′1andα′2,and their diﬀerence by∆α′≡α′2−α′1.Chr GC%α1α2α′1α′241.70.880.460.800.292 1.860.480.6639.70.950.430.880.274 1.460.530.5739.50.890.390.880.236 1.300.630.6340.70.970.460.870.338 1.120.550.6641.30.960.390.900.2810 1.030.460.6141.6 1.050.500.970.3512 1.010.590.6138.50.830.330.730.24140.800.660.6842.20.900.500.830.39160.690.400.4545.50.980.570.890.44180.580.720.8348.4 1.000.560.810.37200.490.360.5340.90.910.330.860.22220.380.280.4539.40.930.380.730.18Y0.380.450.49NN k=1ρk·e−i2πkf/N2.(2)where N is the total number of windows,and f is mea-sured in units of cycle/window,which can be converted to units of cycle/base by the window size(cf.Table1). Coarse-graining“hides”base-base correlations at scales smaller than w bases.The choice of N=217 windows was made such that it is(i)suﬃciently large to cover small-scaleﬂuctuations,while(ii)at the same time suﬃciently small so that the spectral analysis is compu-tationally feasible.As diﬀerent chromosomes have diﬀer-ence lengths,equal number of partitions leads to diﬀerent window sizes w.The unsmoothed S(f),or periodogram,contains N/2 independent spectral components.One canﬁlter pe-riodograms to obtain a“smoothed”spectrum S(f;s), where s is the span-size parameter.Sinceﬁltering with a relatively large s-value possibly distorts the shape of S(f;s)at lower frequency components,diﬀerent span-sizes are applied for diﬀerent frequency ranges.The second measure applied to the{ρi}series is the correlation function,Γ(d),which is computed from two truncated series of{ρi},ρ′={ρk}(k=1,2,...,N−d) andρ′′={ρk}(k=d+1,d+2,...,N):Γ(d)≡Cov(ρ′,ρ′′)Var(ρ′)w· 1+24III.1/f NOISE IS A UNIVERSAL FEATURE OF HUMAN DNA SEQUENCESIn this section,we use the power spectrum S(f)to study GC%of human genome sequences,with the goals of testing the universality of1/f noise,quantifying diﬀer-ent decay ranges for S(f)∼1/fα,and comparing S(f) across DNA sequences of diﬀerent human chromosomes. Figure3shows for N=217GC%values the power spectra S(f)across all human chromosomes.Weﬁnd that S(f)exhibits no clear plateau at low frequency (<10−6cycle/base)and increases steadily with decreas-ing frequency.The decay can be mathematically ap-proximated by a power-law of the form S(f)∼1/fαwithα≈ 1.Table1lists for the frequency range f=10Mb−1–100kb−1the estimated scaling exponent α1for all chromosomes,using a best-ﬁt regression of log10S(f;s=3)=a+α1log10(f).Weﬁnd thatα1is typically close toα1≈1with practically little variation across chromosomes.A closer inspection of Fig.3shows that the major-ity of1/f spectra undergo a cross-over fromα1≈1to α2<1at high frequency.The deviation fromα1≈1 starts about30–100kb and continues at smaller dis-tances.Figure4illustrates this feature for S(f;s=31) of the DNA sequences of Chr15,Chr21,and Chr22in more detail.Weﬁnd that chromosomes15and21exhibit clear cross-overs at about100kb,while chromosome22 exhibits no apparent break-point.Table1contains for the frequency range of f=100kb−1–5kb−1the cor-responding scaling exponentsα2,obtained from the re-gression log10S(f;s=3)=a+α2log10(f).Weﬁnd a pronounced diﬀerence in absolute values betweenα1≈1 andα2<1,indicating a transition from the universal 1/fα1(α1≈1)spectrum at low frequency to a more ﬂattened1/fα2(α2<1)spectrum at higher frequency. Figure5(a)shows for all human chromosomesα1and α2as a function of chromosome-speciﬁc GC%.The ma-jority of human chromosomes have a speciﬁc GC con-tent ranging between38–43%,whereas chromosomes16, 17,19,20,and22have higher GC%up to49%.While the low-frequency scaling exponentα1remains approx-imately independent of GC%,Fig.5(a)shows thatα2 increases with increasing GC%and gives rise to a posi-tive correlation betweenα2and GC%.The three chromosomes illustrated in Fig.4exhibit diﬀerent degrees of transition from the1/fα1(α1≈1) to theﬂattened1/fα2(α2<1)spectrum,with chromo-some21(22)undergoing the sharpest(smoothest)tran-sition.This observation can be further quantitized by the change in scaling exponentsα1andα2.Table1lists for all chromosomes∆α=α2−α1.Chromosome22is distinct from all other human chromosomes as the most scale-invariant one(same or similar scaling exponent at diﬀerent length scales).The same observation that hu-man chromosome22was perhaps diﬀerent from the re-maining human chromosomes was made using limited se-quence data in[14,20].IV.INTERSPERSED REPEATS ARE NOT RESPONSIBLE FOR1/f SPECTRUM About45%of human genomic DNA sequences are in-terspersed repeats[19].Interspersed repeats consist of copies of the same sequence segment that are inserted in the human genome,possess a high similarity between the duplicated and ancestral sequence,and have been implicated in a variety of biological functions,includ-ing genome organization,human chromosome segrega-tion,or regulation of gene expression[24].Large copy numbers increase the sequence redundancy and it has been shown,e.g.,that about10%interspersed Alu re-peats signiﬁcantly increase base-base correlations in the range up to300bases[6].Figure6shows the power spectrum S(f)for the original human chromosome1and for the transformed sequence in which interspersed repeats are substituted.Weﬁnd in the low-frequency range of10−7<f<10−5cycle/base that S(f)decays in the original sequence withα1≈0.88 and in the transformed sequence withα′1≈0.80,indicat-ing only marginal diﬀerences in the decay properties of S(f)due to repetitive sequences.In contrast,in the high frequency range of10−5<f<2×10−4weﬁndα2≈0.46 andα′1≈0.29,and thus interspersed repeats contributes to the decay properties of S(f)for high-frequency com-ponents byﬂattening the power spectrum.The scaling exponentsα′1andα′2for repeat-substituted DNA sequences of all24human chromosomes are shown in Table 1.The diﬀerence between low-and high-frequency ranges for DNA sequences of original chromo-somes,∆α=α2−α1,is smaller than the diﬀerence be-tween low-and high-frequency ranges for transformed se-quences,∆α′=α′2−α′1.When we compareα1andα′1,as well asα2andα′2,weﬁnd that the magnitude ofα′1(α′2) is always smaller than that ofα1(α2),which means aﬂat-tened spectrum due to the substitution of interspersed repeats.The average change of low-frequency scaling exponents,α1−α′1,is about0.07,whereas the average change of high-frequency scaling exponents,α2−α′2,is about0.14.This conﬁrms that the universal presence of1/f spectrum at low frequency is not caused by inter-spersed repeats,but that interspersed repeats aﬀect S(f) predominantly at high frequencies.A similar conclusion that the decay rate of base-base correlations in DNA se-quences of human chromosomes20,Chr21,and Chr22is not markedly aﬀected by the substitution of interspersed repeats was reached in[6].We note that the extent of deviation,|α′−α|,depends on how the replacement of interspersed repeats is con-ducted.Possible substitutions of interspersed repeats in-clude the substitution by a constant value or a randomly sampled value.In general,the substitution of GC%val-ues calculated from the repetitive sequences by random values enhances the deviation andﬂattens the spectrum S(f)more than the substitution by a constant value(e.g., average GC%).5l o g S (f )-3-10123110Mb1Mb100kb(a)23456710Mb1Mb100kb(b)89101112frequency fl o g S (f )10^-810^-610^-4-3-1012313(c)1415161718frequency f10^-810^-610^-419(d)202122X YFIG.3:Double-logarithmic representation of power spectra S (f )of GC%of all twenty-four human chromosomes.Each plot shows S (f )of six chromosomes (shifted on the y -axis for clearer representation):chromosomes (a)1–6;(b)7–12;(c)13–18;(d)19–22,X,and Y.The x -axis (in logarithmic scale)is converted from cycle/window to cycle/base by using the window sizes listed in Table 1.S (f )is ﬁltered at diﬀerent levels for diﬀerent frequency ranges:S (f ;s =1)for the ﬁrst ten spectral components,S (f ;s =3)for the components 11–30,S (f ;s =31)for the components 31–400,and S (f ;s =501)for the components 400–65536(=216).frequency fl o g 10[S (f )]10^-710^-610^-510^-410^-3-3-2-11Ch15Ch21Ch2210Mb 100kb 5kbalpha1=0.900.910.900.620.33alpha2=0.50FIG.4:Cross-over from S (f )∼1/f α1to S (f )∼1/f α2illustrated for human chromosomes 15,21,and 22(smoothed with the span size of 31,and shown in double-logarithmic scale).The scaling exponents α1and α2are shown for the frequency ranges 10Mb −1–100kb −1and 100kb −1–5k −1.V.RESISTANCE TO V ARIANCE REDUCTIONAT LARGER WINDOW SIZESIn this section,we study the decay properties of the variance (σ2)of spatial GC%series as a function of dif-ference window sizes w ,and we compare the scaling of σ2with the scaling of the power spectrum S (f ).Early experimental measurement of theGC%distribu-tion by using cesium chloride (CsCl)proﬁle [25]showedGC%s c a l i n g e x p o n e n t a l p h a0.380.420.460.20.40.60.81.01.2GC% (exclude repeats)0.360.400.440.48FIG.5:(a)Scaling exponents α1and α2for ﬁtting the power spectrum S (f )∼1/f αi (i =1,2)at the frequency range of 10Mb −1–100kb −1,and 100kb −1–5kb −1,respectively,versus the chromosome-speciﬁc GC content of all 24humanchromosomes.(b)Scaling exponents α′1and α′2for S (f )with substituted interspersed repeats.for mouse Mus musculus genomic DNA sequences that the variance of GC%values does not markedly decreases with the DNA segment size [26].This experimental ob-servation is directly related to the presence of 1/f spec-tra in DNA sequences [14,27].If the variance of the6frequency fl o g [S (f )]10^-710^-610^-510^-4-3-2-11................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................10Mb100kb 5kbalpha1=0.88alpha1’=0.80alpha2=0.46alpha2’=0.29original sequence transformed sequence FIG.6:Power spectra S (f )of GC%for the original andthe transformed (interspersed repeats substituted)DNA se-quence of human chromosome 1.The scaling exponent for low-frequency (10Mb–100kb)and high-frequency (100kb–5kb)ranges are obtained by a best-ﬁt regression of log 10S (f )over log 10f .spatial GC%series calculated at the window size w is σ2(w ),then a scaling of σ2(w )∼1/w βimplies a corre-sponding scaling in the power spectrum S (f )∼1/f 1−β[14,28].If GC%is obtained from w uncorrelated bases,it follows a binomial distribution.Consequently,σ2(w )∼ ρ (1− ρ )/w ∼1/w with β=1.The corresponding scaling exponent of the power spectrum is α=1−β=0,and thus the S (f )∼cons.is equivalent to the white noise.Figure 7shows σ2(w )as a function of window size w for all human chromosomes.In a double-logarithmic repre-sentation,we ﬁnd that log(σ2(w ))decays approximately linearly with log(w ).A decay according to σ2(w )∼1/w βwith β=1leads to white noise.This situation is in-dicated in Fig.7by the straight line.An inspection of Fig.7shows,however,that the variance decays at a much slower rate than what would be for white noise.The variance of the DNA sequence of human chromosome 1,e.g.,gives rise to β≈0.12,and the corresponding scal-ing exponent α1≈1−β=0.88is indeed close to the estimated exponent listed in Table 1.The scaling of the variance with the exponent β<<1is in accord with the low-frequency 1/f noise.The scaling of σ2(w )shown in Fig.7diﬀers from one human chromosome to another.For instance,in the range of w =1kb–5Mb,for example,human chro-mosome 13exhibit a clear transition from β2≈0.27(w <50kb)to β1≈0.10(w >50kb),corresponding to S (f )∼1/f 0.63and S (f )∼1/f 0.9,respectively,at high-and low-frequency ranges.Other human chromosomes,although generally exhibiting a power-law scaling form of σ2(w ),show deviations from σ2(l )∼1/l βline for the largest window sizes tested.The investigation of σ2(w )as a function of diﬀerent window sizes w requires careful examination [29,30].v a r i a n c e0.00050.0050(a)(b)window size (Mb)v a r i a n c e0.0010.0100.100 1.00010.0000.00050.0050(c)window size (Mb)0.0010.0100.100 1.00010.000(d)FIG.7:Double-logarithmic representation of the variance σ2(w )of the spatial GC%series for all human chromosomes (Chr)as a function of the window size w :(a) Chr1,△Chr2,+Chr3,×Chr4,♦Chr5,▽Chr6;(b) Chr7,△Chr8,+Chr9,×Chr10,♦Chr11,▽Chr12;(c) Chr13,△Chr14,+Chr15,×Chr16,♦Chr17,▽Chr18;(d) Chr19,△Chr20,+Chr21,×Chr22,♦ChX,▽ChrY.Straight lines indicate σ2(w )∼1/w (corresponding to white noise).One regression line for Chr1(β≈0.12)and a piece-wise regression for Chr13(β≈0.27and β≈0.10)are drawn.The 95%conﬁ-dence interval for the σ2(w )estimation of Chr1at each point of w is marked by a vertical dashed line.First,since we partition each human chromosome in 2k (k =17,16,...)windows,the variance of GC%series {ρi }could be accidentally large when windows reside on the isochore borders,and small by chance if they start/end within an isochore.Second,when the number of windows is small (e.g.the last point of σ2(w )for each chromosome in Fig.7is calculated with the largest window size that gives rise to 32windows),the standard error of the sam-ple variance is large.The 95%conﬁdence interval for σ2(w )of Chr1is shown in Fig.7(a),using the interval:[(w −1)σ2/t 0.025,(w −1)σ2/t 0.975],where t x is deﬁned by t x −∞χ2(df =w −1)dt =x (where χ2(df)is the chi-square distribution with df degrees of freedom)[31].Figure 7(a)shows that for fewer windows (and larger window sizes),the 95%conﬁdence interval of σ2(w )could be large such that the estimated value of βmay change from sample to sample.Finally,the relationship between scaling exponents α+β=1[14,28],is based on the assumption that both S (f )and σ2(w )are theoretical power-law functions.If S (f )is a piece-wise power-law function,as in the case of GC%ﬂuctuation of human chromosomes,a correction term to the relationship α+β=1is expected.7c o r r e l a t i o n f u n c t i o n-0.10.10.31100kb 1Mb10Mb(a)2345.................................................................... (67)100kb1Mb10Mb(b)891011...............................................................................12distance (Mb)c o r r e l a t i o n f u n c t i o n0.050.50 5.00-0.10.10.313(c)14151617..........................................................................18distance (Mb)0.050.50 5.0019(d)202122..............................................................................X ............................................................................Y FIG.8:Correlation function Γ(d )for 24human chromosomes(Chr)as a function of the window distance d (converted to bases by the window size listed in Table 1).The distance is represented on a logarithmic scale.(a)Chr1–6;(b)Chr7–12;(c)Chr13–18;and (d)Chr19–22,ChrX,and ChrY.distance (Mb)c o r r e l a t i o n f u n c t i o n0.00.5 1.0 1.52.0 2.50.160.180.200.220.24500kb1Mb1.5Mb2MbFIG.9:Correlation function Γ(d )for human chromosome 21as a function of the window distance d (converted to bases by the window size given in Table 1).The oscillation in Γ(d )is highlighted by vertical lines,indicating the distances of d =500kb,1Mb,1.5Mb,and 2Mb.VI.CHROMOSOME-SPECIFIC CORRELATIONSTRUCTURESApparently,1/f noise in music and speech signals [32]does not prevent music and speech from sounding diﬀer-ently.Similarly,universal 1/f αspectra in GC%ﬂuctu-ations across human chromosomes do not imply that all chromosomes exhibit the same detailed correlation struc-ture.The generic trend of S (f )spectra to increase at low frequency may “co-exist”with small peaks at higher fre-quency.Such chromosome-speciﬁc characteristic length scales can be more intuitively examined by correlation functions.In this section,we investigate the correla-tion function Γ(d )of coarse-grained DNA sequences of human chromosomes with the aim of further examin-ing chromosome-speciﬁc structures,such as characteristiclength scales and oscillation detected by Γ(d ).Figure 8shows for all human chromosomes the Γ(d )’s of GC%series {ρi }calculated for the window sizes given in Table 1,of all human chromosomes.For each chromo-some,the minimum (maximum)distance is 80(16,000)windows.Since each chromosome is partitioned into 217windows,the maximum distance d at which the correla-tion is examined is about 16,000/217≈12%of the total sequence length.An inspection of Fig.8shows that the magnitude of correlation at the distance of d =1Mb is clearly above the noise level.With the exceptions of Chr15,Chr22,and ChrY,the correlation function Γ(d )>0.1at d =1Mb for all other chromosomes.The low correlation in ChrY is due to the fact that about half of the bases are unse-quenced,and the substitution of gaps by random values lowers the correlation.At even longer distances such as d =10Mb,correlations Γ(d =10Mb)for chromosomes 1and 6are still above the 0.1level.Given diﬀerent windows (w )due to diﬀerent chromo-some sizes and provided that the covariance of GC%is approximately independent of w ,a scaling of the variance according to 1/w βimplies that the correlation function Γ(d )in Eq.(3)increases with the window size as ∼w β.Test calculations of covariance for 215and 217windows show that the covariance diﬀers by less than 1%(and hence is fairly independent in this range of window sizes).Consequently,for a detailed comparison of correlation functions calculated for diﬀerent chromosomes one has to take into account diﬀerent windows sizes.Any deviation from the monotonic decrease of Γ(d )might be indicative of correlations at characteristic length scales (visible as “bumps”).For example,Fig.8shows for chromosome 1such a bump at d ≈21–23Mb.Bumps or sharper peaks in other chromosomes include d ≈9.3Mb (Chr2),7.2Mb (Chr10),3.2–3.8Mb (Chr12),and 2.4–3.1Mb (Chr19).One plausible explanation is that for chromosomes 2,10,12,and 19one or few al-terations of GC-rich/low isochores [13]with these length scales enhance the correlation.Chromosome 21stands out among all human chromo-somes for having a comparatively higher correlations at distances of several Mb (despite having a smaller w βfac-tor than other chromosomes due to a smaller window size).A detailed inspection of Fig.9uncovers an oscilla-tion of Γ(d )of about 500kb,ranging from d =500kb to d =2Mb,which has not been reported before.It can be further shown that this oscillation is not due to the sub-stitution of interspersed repeats [33],and it is localized to about one-eighth of the right distal end of chromosome 21[33].VII.DISCUSSIONSWe study correlation structures and spectral compo-nents in the set of human chromosomes,using power spectra,coarse-grained correlation functions,and the。

爱丁堡仪器 Photoluminescence 光致发光光谱仪微观升级 - MicroPL说明书

Upgrade For Edinburgh Instruments Photoluminescence Spectrometers MicroPLThe MicroPL Upgrade for Edinburgh Instruments Photoluminescence Spectrometers such as the FLS1000 or FS5 allows the study of spectral or time-resolved photoluminescence of samples in the microscopic scale.An Edinburgh Instruments photoluminescence (PL) spectrometer can be converted into a combined spectrometer and microscope system with this user-friendly upgrade.A wide range of microscope configurations, source couplingand detector options are available enabling both steady state and fluorescence lifetime microscopy, as well as automated maps, using the same setup.Just like Edinburgh Instruments spectrometers, the PL microscope is fully configurable to meet your specific needs and can be upgraded with additional capability in the future. It is also possible to couple your own microscope to theFLS1000 or FS5 for a custom MicroPL upgrade (please get in touch for models supported).Key FeaturesEXCITATION SOURCE FLEXIBILITY TO SUIT YOUR APPLICATIONMicroPL is coupled to the spectrometer via liquid light guides or fibres. It is possible to excite the full field of view of the microscope’s objective (widefield excitation), or a specific point in the sample with a laser (point excitation).WIDEFIELD EXCITATIONIn widefield excitation, the spectrometer’s lamp andmonochromator are used to select the wavelength of the light exciting the sample. Wavelength and bandwidth of the excitation light can be set in the software. This provides much more flexibility than traditional microscopy and removes the need for excitation filters – however, an additional white light excitation lamp can be fitted directly to the microscope if desired.POINT EXCITATIONPoint excitation can be performed with either CW or pulsed lasers for spectral or lifetime PL measurements. MicroPL is compatible with Edinburgh Instruments EPL, HPL, and VPL diode lasers. A spot size of ~2 μm (source and objective dependent) is achievable, enabling to resolve PL spectra and lifetimes in the micrometer scale. Both Time-Correlated Single Photon Counting(TCSPC) and Multi-Channel Scaling (MCS) operating modes are compatible, covering a wide range of photoluminescence lifetimes, from a few ps up to seconds. Non-standard applications such as upconversion PL microscopy are possible with theappropriate choice of filters and laser coupling.Widefield microscopy imaging setup (above) and image of BPAE cells labelled with BODIPY , Texas Red and DAPI dyes (below), using FS5 Spectrofluorometer and MicroPL.Point excitation micro-spectroscopy setup (above right), PL spectrum (below) and TCSPC lifetime (below right) of a perovskite sample studied in an FLS1000 Spectrometer with MicroPL upgrade.CameraLaserFromSpectrometer Excitation PathT o SpectrometerEmission PathFLIM ADD-ONMicroPL can be configured with a computer-controlled XYZ stage for Fluorescence Lifetime Imaging Microscopy (FLIM). This upgrade is designed with user-friendliness in mind: you do not need to be a microscopy expert to acquire good quality FLIM data.The FLIM add-on unlocks special features in theFluoracle software including control of the stage and advanced analysis options for maps, such as multi-component decay fitting algorithms.No additional software packages are required to obtain and analyse data.To acquire a FLIM map, the user defines the area or volume to scan across, as well as the spacing between data points and the lifetime acquisition parameters. The software then moves the stage acquiring a fluorescence decay in each data point.The result is a map which can be represented according to intensity, average lifetime or single-component lifetime in each data point, amongst other options. Surface topography and 3D maps can be analysed and displayed in Fluoracle.FLIM MICROSCOPY MADE SIMPLEThe user can define the mapping area and distance between points, view live data to adjust measurement parameters and access a range of map analysis and display options.FLIM map of stained convallaria acquired in FS5 with MicroPL FLIM add-on. Results displayed as colour maps of fluorescence intensity (left) and intensity-weighted average lifetime (right).Registered in England and Wales No: 962331 VAT No:GB 271 7379 37All specifications are correct at the time of production. We reserve the right to change our specifications without notice. ©Edinburgh Instruments Ltd. 2022F / 03.22SpecificationsMANUFACTURED WITH PRIDE IN THE UNITED KINGDOMA MICROSCOPE TAILORED TO YOUR EXACT NEEDSMICROSCOPE MODELSUpright: Nikon NiU, Olympus BX53Inverted: Nikon Ti2-UEXCITATION / EMISSION RANGE 360 nm – 850 nm (std)Can be extended with non-standard UV and NIR objectivesEXCITATION MODESWidefield: tunable continuous source from spectrometer (steady state)Point: EPL/HPL/VPL pulsed lasers (TCSPC or MCS lifetime) and CW lasers (steady state)DETECTION MODESMicro-PL spectroscopy with spectrometerFluorescence Microscopy with additional camera OBJECTIVEMAGNIFICATION Options available from 5X to 100XSAMPLE STAGEManual or PC-controlled XYZ stage with specifications: 75 mm x 50 mm or 130 mm x 85 mm options XY resolution 0.01 µm Z resolution 0.002 µmSOFTWARE Mapping features in Fluoracle included with PC-controlled XYZ stage ACCESSORIESSoftware-controlled cryostat upgradeLight guides coupling to the spectrometer can be configured for the spectral range of interest.Point excitation option adds a laser mount and additional dichroic turret.Widefield excitation allows steady-state spectroscopy with tunable wavelength.White light source for sample visualisation.Sample visualisation camera included. Upgrade to sensitive camera for microscopy images.Binoculars for easier focusing.Dichroic filter cubes customisable to your application.Sample stage can be manual or software controlled.。

近红外光谱法英文

近红外光谱法英文Near-Infrared SpectroscopyNear-infrared spectroscopy (NIRS) is a powerful analytical technique that has gained widespread recognition in various scientific and industrial fields. This non-invasive method utilizes the near-infrared region of the electromagnetic spectrum, typically ranging from 700 to 2500 nanometers (nm), to obtain valuable information about the chemical and physical properties of materials. The versatility of NIRS has led to its application in a diverse array of industries, including agriculture, pharmaceuticals, food processing, and environmental monitoring.One of the primary advantages of NIRS is its ability to provide rapid and accurate analysis without the need for extensive sample preparation. Unlike traditional analytical methods, which often require complex sample extraction and processing, NIRS can analyze samples in their natural state, allowing for real-time monitoring and decision-making. This efficiency and non-destructive nature make NIRS an attractive choice for applications where speed and preservation of sample integrity are crucial.In the field of agriculture, NIRS has become an invaluable tool for the assessment of crop quality and the optimization of farming practices. By analyzing the near-infrared spectra of plant materials, researchers can determine the content of various nutrients, such as protein, carbohydrates, and moisture, as well as the presence of contaminants or adulterants. This information can be used to guide precision farming techniques, optimize fertilizer application, and ensure the quality and safety of agricultural products.The pharmaceutical industry has also embraced the use of NIRS for a wide range of applications. In drug development, NIRS can be used to monitor the manufacturing process, ensuring the consistent quality and purity of active pharmaceutical ingredients (APIs) and finished products. Additionally, NIRS can be employed in the analysis of tablet coatings, the detection of counterfeit drugs, and the evaluation of drug stability during storage.The food processing industry has been another significant beneficiary of NIRS technology. By analyzing the near-infrared spectra of food samples, manufacturers can assess parameters such as fat, protein, and moisture content, as well as the presence of adulterants or contaminants. This information is crucial for ensuring product quality, optimizing production processes, and meeting regulatory standards. NIRS has been particularly useful in the analysis of dairy products, grains, and meat, where rapid and non-destructive testing is highly desirable.In the field of environmental monitoring, NIRS has found applications in the analysis of soil and water samples. By examining the near-infrared spectra of these materials, researchers can obtain information about the presence and concentration of various organic and inorganic compounds, including pollutants, nutrients, and heavy metals. This knowledge can be used to inform decision-making in areas such as soil management, water treatment, and environmental remediation.The success of NIRS in these diverse applications can be attributed to several key factors. Firstly, the near-infrared region of the electromagnetic spectrum is sensitive to a wide range of molecular vibrations, allowing for the detection and quantification of a variety of chemical compounds. Additionally, the ability of NIRS to analyze samples non-destructively and with minimal sample preparation has made it an attractive choice for in-situ and real-time monitoring applications.Furthermore, the development of advanced data analysis techniques, such as multivariate analysis and chemometrics, has significantly enhanced the capabilities of NIRS. These methods enable the extraction of meaningful information from the complex near-infrared spectra, allowing for the accurate prediction of sample propertiesand the identification of subtle chemical and physical changes.As technology continues to evolve, the future of NIRS looks increasingly promising. Advancements in sensor design, data processing algorithms, and portable instrumentation are expected to expand the reach of this analytical technique, making it more accessible and applicable across a wider range of industries and research fields.In conclusion, near-infrared spectroscopy is a versatile and powerful analytical tool that has transformed the way we approach various scientific and industrial challenges. Its ability to provide rapid, non-invasive, and accurate analysis has made it an indispensable technology in fields ranging from agriculture and pharmaceuticals to food processing and environmental monitoring. As the field of NIRS continues to evolve, it is poised to play an increasingly crucial role in driving innovation and advancing our understanding of the world around us.。

Agilent U8903A音频分析器数据手册说明书

Agilent U8903A Audio AnalyzerMake an Audible DifferenceData SheetCapabilities• Select generator, analyzer, graph, and sweep modes with one-button access • Measure at DC and from 10 Hz to 100 kHz • Characterize signal-to-noise ratio, SINAD, IMD, DFD, THD+N ratio, THD+N level, crosstalk, and more • Apply weighting functions, standard filters, and custom filters • Stimulate the device with high-quality signals and arbitrary waveforms • View numerical and graphical displays of measurement results • Connect to a PC through GPIB, LAN/LXI C, and USB interfaces • Code compatible with HP8903B • 2 in 1 screen (generator and analyzer in the same display screen)Whether listening to mono, stereo, or surround, the human ear knows what sounds good. Measuring “how good,” however, can be a challenge. The Agilent U8903A audio analyzer helps you measure and quantify audio performance in applications such as wireless audio, analog components and ICs, and consumer audio.Across the audio spectrum and beyond, this scalable, single-unit solution provides versatile measurement functions, diverse test signals, and powerful analysis capabilities.The U8903A audio analyzer combines the functionality of a distortion meter, SINAD meter, frequency counter, AC voltmeter, DC voltmeter, and FFT analyzer with a low-distortion audio source. On the bench or in a test system, its accu-racy and versatility helps you make an audible difference in your end product.LXI class C certified1981Table 1. Comparison of frequency range and accuracyFrequency range DC and 10 Hz to 100 kHz20 Hz to 100 kHz Frequency accuracy 5 ppm (0.0005%)0.004%Table 2. Comparison of accuracy and ranges in AC and DC level measurementsAC voltage input range0 V to 140 Vrms 0.3 mVrmsto 300 VrmsAC accuracy± 1%± 4%DC voltage input range0 to ± 200 V 4 to 300 VDC accuracy± 1%± 1%Table 3. Comparison of range and residual THD+N measurements Frequency range10 Hz to 100 kHz20 Hz to 100 kHzResidual THD+N (signal distortion) at 80 kHz BW ≤ –101 dB (at 1 kHz, 1 Vrms),20 Hz to 20 kHz–80 dB (or 15 µV),20 Hz to 20 kHzAccuracy± 0.5 dB (< 20 kHz)± 0.7 dB (< 100 kHz)± 1 dB (20 Hz to 20 kHz)± 2 dB (20 to 100 kHz)Figure 1. The new U8903A audio analyzer (left) offers numerous improvements over the widely used HP 8903B (right). Replace your 8903B and addnext-generation capabilitiesFor nearly two decades, the HP 8903Bprovided unparalleled versatility andperformance in audio applications.The U8903A builds on the legacy ofthe 8903B by offering faster single-point measurements (0.4 sec versus3.0 sec) as well as a wider frequencyrange, expanded performance, andgreater functionality (Tables 1, 2, and3). With the U8903A, you can con-figure measurements faster throughits graphical user interface (GUI)and one-button selection of majoroperating modes. The color screenlets you view dual-parameter displaysfrom one or two channels as wellas graphical displays of sweeps, fre-quency spectra, and more (Figure 1).To makes the transition easy, thenext-generation replacement for theHP 8903B audio analyzer featuresa built-in code emulator whichautomatically converts 8903B R2D2code directly into SCPI commandsused by the U8903A. The Agilentapplication note Migrating Code fromthe 8903B to U8903A (5990-4135EN)and the U8903A Programming Guide(U8903-90027) provide additionalresources to assure you get the mostfrom this new class of audio analyzer.23Measure and analyze essential audio parametersWith the U8903A, you can measure below, across, and above the audio spectrum with its 10 Hz to 100 kHz frequency range and built-in DC mea-surements. Its dual input channels let you perform stereo audio, frequency response, wireless and component tests—all at a single-channel price.Easily characterize parameters such as signal-to-noise ratio, SINAD, intermodulation distortion (IMD), different-frequency distortion (DFD), total harmonic distortion (THD+N ratio, THD+N level), crosstalk, and more. Additional measurementcapabilities include AC level, DC level, frequency count, frequency spectrum, and FFT analysis (Figure 2).For all measurements, you canapply weighting functions as well aslow-pass, high-pass, and standardFigure 2. Perform FFT analysis with up to 32 Kpoints and a wide selection ofinformative graphing functions Figure 3. Apply an extensive selection of filters, including a variety of weightingfunctionsFigure 4. Utilize high-quality test signals that provide low distortion and low noise levelFigure 5. 2 in 1 screen generator and analyzer in the same display screenAddress Challenging Audio Applicationsfilters (Figure 3). You can also create custom filters using MATLAB ® and other applications, and upload them through the analyzer’s USB port.Filters and weighting functions can be applied one, two, or three at a time.U8903A also provides a 2 in 1 screen, which simultaneously displays the generator and analyzer information (Figure 5). This allows the user to change the generator (source) setting while monitoring the analyzer results in real time.Generate high-quality test signalsThe built-in, dual-channel signal gen-erator lets you stimulate your device with a variety of high-quality signals: sine (–105 dB noise floor), square, rectangular, noise (Gaussian andrectangular), two-tone, and multi-tone (up to 60) (Figure 4). To simulate com-plex and real-world signals, you can also create arbitrary waveforms with up to 16,384 points and at 312.5 kHz sampling rate.The output voltage range is 0 V to 8 V rms with 1% accuracy. For unbal-anced connections, you can select 50 or 600 Ω output impedance.Easily perform manual and automated testsOne-button access makes it easy to select the four main operating modes: analyzer, generator, graph, and sweep. The 5.7-inch color display provides numeric readouts as well as graphical views of analog sweeps, FFT spectra, and more.For PC-based control on the bench or in a test system, the U8903A includes GPIB, LAN/LXI C, and USB interfaces.4Take a Closer LookFront panelPlug-and-play USB 2.0 connectivityFront-panel output on/off button for DUT protectionQuick buttons for graphical analysisOne-button access to analyzer, generator, and sweep modes5.7-inch color displaySoftkeys for easy function selectionDual-channel generator outputs and analyzer inputs with XLR connectorsFigure 6. U8903A audio analyzer, front viewRear panelGPIB, LAN/LXI C, and USB interfacesFigure 7. U8903A audio analyzer, rear view5Advance Measurement TestingGeneral audio testingThe U8903A provides essentialmeasurement capabilities that enable efficient analysis of audio amplifiers and other devices in the audio chain. For example, the analyzer includes balanced and unbalanced outputs and inputs. It also provides a wide selection of filters and enhances your flexibility by making it easy to upload customized filters. With an array of sweep functions and flexible data display formats for each measure-ment, you’ll be ready to address a wide range of challenging audio applications.Balanced inputsIn the quest for higher output power, many audio amplifiers use bridged output stages. Such amplifiers can be difficult to characterize because their outputs cannot be grounded. To test these devices, the usual approach has been to use a balanced, calibrat-ed isolation transformer connected to an analyzer with an unbalanced input.The widely used HP 8903B eliminated the need for a transformer, but it was still necessary to float the analyzer input before connecting the bridged device and making measurements. With the U8903A, you simply make a balanced connection with an XLR connector and make measure-ments—no floating required.Standard and custom filtersA selection of built-in filters simplifies audio measurements by providing weighting networks required by inter-national standards. These include CCIR, CCIR/ARM, and CCIT weighting filters; a C message filter; and an ANSI “A” weighting filter. In addition to the standard filters, you can create custom filters using applications such as MATLAB or Agilent VEEand upload the filters through theAmplifier testingGenerator outputAudio amplifierAnalyzer inputFigure 8. Audio testing using the U8903AFigure 9. Use a single button to access the swept measurement modeanalyzer’s USB port. The U8903A also includes selectable 15, 20, and 30 kHz low-pass filters to reject unwanted, out-of-band signals and noise.Display scaling and formatting U8903A gives you flexible control over data displays. For example, you can choose volts, millivolts, dBm into 600 Ω (or other resistance values), or watts for AC level measurements, and select percent or dB for distortion measurements.Swept measurementsWith its internal audio source and precise digital control, the U8903A can perform automatic swept mea-surements of frequency response, distortion, and signal-to-noise. For example, to check the frequencyresponse of an active filter, only a few steps are required. After connecting the device and setting the required source level, simply enter the start and stop frequencies, and then press the “Sweep” key (Figure 9).6Transmitter and receiver testingThe U8903A includes severalmeasurement features that simplify the testing of the transceivers used in devices such as car radios,telephones, mobile radios, broadcast radios, FM tuners, and television. The U8903A can handle all of these applications when combined with a modulating signal generator for receiver testing and a signal analyzer for transmitter testing (see diagrams on next page).True-RMS detectionTo accurately characterize signals with high noise content, true-RMS detection is required. The U8903A employs true-RMS detection for all signals with crest factor less than three. In addition, quasi-peak detec-tion (CCIR 468-4) and peak-to-peak detection are also available through softkey selections.Built-in filtersThe U8903A includes a variety of essential filters for transmitter and receiver testing. Its CCITT, CCIR, and C-message weighting filters meet international standards for receiver testing. For transmitter testing, the seven-pole 400 Hz high-pass filter provides better than 40 dB rejection of signals up to 250 Hz, letting you measure transmitter audiodistortion to 1% without disabling squelch signals.For even greater flexibility, you can apply custom filters created using applications such as MATLAB and Agilent VEE. Once you’ve uploaded a filter via the U8903A’s USB port, it can be applied to your measurements through a softkey selection. In all, you can apply up to three filters at a time.SINAD and THD+N measurementU8903A gives you the flexibility to lock down the generator frequency under the Frequency Lock features. With this feature, users can set the generator frequency in order to tell the location of the fundamental signal. In this case, users have the flexibility to lock the external source’s fundamental frequency to make SINAD and THD+N measurements more accurately because the mea-surements are based on the actual source fundamental signal rather than the detected fundamental signal. Sometimes the other order signal and noise is stronger than the actual source fundamental signal which will impact the measurement reading.Reference/relative measurements This features allows users to perform measurement on level, frequency, and ratio based on the selected impedance value, frequency, or ratio reference value. This simplifies manual data measurement and data collection because the calculations are automatically generated inside the equipment in real time. This fea-ture provides users with the flexibility to decided which signal sources to perform Signal-to-Noise (SNR) mea-surement without solely depending on the U8903A generator source. SINAD measurementsCommonly used to test FM receivers, SINAD measurements must be made repeatedly when checking receiver sensitivity or adjacent-channel selectivity. To smooth out the typi-cally noisy signals that are present during receiver testing, the analyzer’s SINAD mode employs extra filtering circuits. These are optimized for high speed and excellent repeatability: the U8903A provides distortion and SINAD measurements with an acqui-sition time of less than 1.5 seconds and a measurement rate of greater than two reading per second after locking.Signal-to-noise ratioTo characterize signal quality in AM receivers, the U8903A can automatically make the necessary signal-to-noise ratio measurements. It does this by monitoring the incoming AC signal level while turning its low-distortion source on and off.The U8903A provides the average point features which allows users to set the number of readings used for averaging. The display value will be the averaged value based on the number of points selected. This allows users to analyze noisy signals using an increased number of average points for greater accuracy.7Figure 10. Receiver testing using the U8903AGenerator outputModulated signalAnalyzer inputTwo-way Signal generatorReceiver testingTransmitter testingFigure 11. Transmitter testing using the U8903A and a spectrum analyzerGenerator outputModulated signalSpectrum analyzerTransmitter and receiver testing8CharacteristicsPower consumption 250 VA Power requirements • 100 to 240 V ac • 47 to 63 Hz Operating environment• Operating temperature from 0 to 55 °C• Relative humidity at 20 to 80% RH (noncondensing)• Altitude up to 3000 m • Pollution degree 2•Installation category IIStorage compliance –55 to 75 °C (23 to 167 °F)Safety complianceCertified with:• IEC 61010-1:2001/EN61010-1:2001 (2nd Edition)• Canada: CAN/CSA-C22.2 No. 61010-1-04• USA: ANSI/UL 61010-1:2004EMC compliance• IEC 61326-1:2005/EN 61326-1:2006• Canada: ICES-001:2004• Australia/New Zealand: AS/NZS CISPR11:2004Dimensions (W x D x H)425.6 mm x 405.0 mm x 133.6 mm (16.76 inches x 15.94 inches x 5.25 inches)Weight < 8.5 kg (< 18.74 lb) (without cards)Warranty• One year for U8903A• Three months for standard-shipped accessories (see page 13)SpecificationsThe following specifications are based on performance with 30 minutes of warm-up time and a temperature from 0 to 55 °C, unless stated otherwise.Generated waveformSine, dual sine, variable phase, square, noise (Gaussian and rectangular), arbitrary, DC, multitone, SMPTE IMD (1:1, 4:1, and 10:1), DFD (IEC 60118/IEC 60268)Sine, dual sine, and variable phaseFrequency Range Accuracy Resolution5 Hz to 80 kHz 5 ppm 0.1 HzOutputRange (balanced) Range (unbalanced/common) Amplitude accuracy Amplitude resolution 0 V to 16 V rms 0 V to 8 V rms ± 1%1 μV rms (limited to five digits of resolution)Flatness20 Hz to 20 kHz 5 Hz to 80 kHz ± 0.01 dB ± 0.1 dBTHD + N at 1 kHz, 1 V rms , 20 Hz to 20 kHz bandwidth ≤ –95 dB (at 23 °C ± 5°C)≤ –92 dB (from 0 to 55 °C)Dual sine ratio range 0 to 100 dB Phase –180 ° to 179.99 °SweepFrequency, amplitude, phaseOutput levelRangeAmplitude accuracy –11.3 to 11.3 V ± 1.5%9Output characteristic Connection typeBalancedUnbalancedCommon mode XLR BNC XLRImpedanceBalanced Unbalanced 100, 600 Ω50, 600 ΩOutput current limit (typical)50 mA Maximum output power into 600 ΩBalanced (600 Ω) Unbalanced (600 Ω)20 dBm 14 dBmCrosstalk20 Hz to 20 kHz 20 to 80 kHz ≤ –101 dB (at 23 °C ± 5 °C)≤ –99 dB (from 0 °C to 55 °C)≤ –85 dBInput characteristics Connection typeBalanced Unbalanced XLR BNCCoupling DC, AC Measurement bandwidthLow High 30 kHz 100 kHzInput ranges400 mV to 140 VrmsMeasurement range< 1 μV1 to 140 VrmsMaximum rated input200 Vp for altitude up to 3,000 m (1.86 miles) ImpedanceBalanced Unbalanced 200 kΩ100 kΩFlatness20 Hz to 20 kHz 20 to 100 kHz ± 0.01 dB2 (at 23 °C ± 5 °C)± 0.012 dB3 (from 0 °C to 55 °C)± 0.1 dB (at 23 °C ± 5 °C)± 0.15 dB (from 0 °C to 55 °C)CMRR≤ 20 kHz (input range ≤ 6.4 V)≤ 20 kHz (input range > 6.4 V)≥ 70 dB4≥ 40 dB4Crosstalk20 Hz to 20 kHz≤ –101 dBInput protection Overload protection for all ranges, onscreen warning message on the front panel1. Defined by 24-bit measurement.2. ± 0.01 dB – 0.001 dB/Hz below 50 Hz.3. ± 0.012 dB – 0.001 dB/Hz below 50 Hz.4. When AC coupled, CMRR will deteriorate at low frequencies.10Range10 Hz to 100 kHz Minimum input 1 mV (S/N > 40 dB) Accuracy 5 ppm Resolution 6 digitsGraph modeSize/acquisition length256, 512, 1024, 2048, 4096, 8192, 16384, 32768Window Rectangular, Hann, Hamming, Blackman-Harris, Rife-Vincent 1 and 3, Flattop Amplitude accuracy (flattop window)± 0.1 dB (± 1.2%)Display modeTime domainFrequency domain Normal, interpolate, peak, absolute value Displays highest FFT bin between graph pointsAudio filtersLow pass filter• 15 kHz low pass• 20 kHz low pass• 30 kHz low pass• User-defined1High pass filter• 20 Hz high pass• 100 Hz high pass• 400 Hz high pass• User-defined1Weighting filter• A-weighting (ANSI-IEC “A” weighted, per IEC Rec 179)• CCIR 1K weighted (CCIR Rec. 468)• CCIR 2K weighted (Dolby 2K)• C-Message (C-Message per IEEE 743)• CCITT (ITU-T Rec. O.41, ITU-T Rec. P.53)• User-defined11. User-defined filters can be uploaded through standard I/O connections.Figure 12. “A”weighting filter frequency responseFigure 13. CCIR-2K weighting filterFigure 14. CCIR-1K filter and CCIR-2K filter frequency responseFigure 15. CCITT filter frequency response“A” weighting filter frequency responseR e s p o n s e (d B )Frequency (Hz)“A” Weighting Filter (ANSI-IEC “A” weighted, per IEC Rec. 179)Deviation from ideal response:±0.1 dB at 1 kHz±0.5 dB, 20 Hz to 10 kHz ±1.0 dB, at 10 to 20 kHzR e s p o n s e (d B )Frequency (Hz)CCIR-2K weighting filter (Dolby 2K)Deviation from ideal response: same as listed previously under CCIR-1K weighting filterC-Message weighting filter (C-Message per IEEE 743)Deviation from ideal response:±0.1 dB, at 1 kHz±1.0 dB, 60 Hz to 5 kHz R e s p o n s e (d B )R e s p o n s e (d B )CCIR-1K filter and CCIR-2K filter frequency response CCITT filter frequency responseFrequency (Hz)Frequency (Hz)CCIR-1K weighting filter (CCIR Rec. 468)Deviation from ideal response:±0.1 dB, at 6.3 kHz±0.2 dB, at 6.3 to 7.1 kHz ±0.4 dB, at 7.1 to 10 kHz ±0.5 dB, at 200 Hz to 6.3 kHz±1.0 dB, at 31.5 to 200 kHz, 10 to 20 kHz±2.0 dB, at 20 to 31.5 kHzCCITT message weighting filter (ITU-T Rec. 0.41, ITU-T Rec. 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The absorption spectrum of V838 Mon in 2002 February - March. I. Atmospheric parameters and

a r X i v :a s t r o -p h /0411032v 1 1 N o v 2004Mon.Not.R.Astron.Soc.000,1–7(2004)Printed 2February 2008(MN L A T E X style ﬁle v2.2)The absorption spectrum of V838Mon in 2002February -March.I.Atmospheric parameters and iron abundance.⋆Bogdan M.Kaminsky 1†,Yakiv V.Pavlenko 1‡1Main Astronomical Observatory of Ukrainian Academy of Sciences,Golosiiv woods,03680Kyiv-127,UkraineReceived ;acceptedABSTRACTWe present a determination of the eﬀective temperatures,iron abundances,and mi-croturbulent velocities for the pseudophotosphere of V838Mon on 2002February 25,and March 2and 26.Physical parameters of the line forming region were obtained in the framework of a self-consistent approach,using ﬁts of synthetic spectra to observed spectra in the wavelength range 5500-6700˚A .We obtained T eﬀ=5330±300K,5540±270K and 4960±190K,for February 25,March 2,and March 26,respectively.The iron abundance log N (Fe)=−4.7does not appear to change in the atmosphere of V838Mon from February 25to March 26,2002.Key words:stars:atmospheres –stars:abundances –stars:individual:V838Mon1INTRODUCTIONThe peculiar variable star V838Mon was discovered during an outburst in the beginning of 2002January (Brown 2002).Two further outbursts were then observed in 2002February (Munari et al.2002a;Kimeswenger et al.2002;Crause et al.2003)and in general the optical brightness in V-band of the star increased by 9mag.Since 2002March,a gradual fall in V-magnitude began which,by 2003January,was re-duced by 8mag.The suspected progenitor of V838Mon was identiﬁed by Munari et al.(2002a)as a 15mag F-star on the main sequence.Possibly V838Mon might have a B3V companion (Desidera &Munari 2002),but it could be a background star.The discovery of a light echo (Henden et al.2002)allowed an estimate of the distance to V838Mon and,according to recent works based on HST data (Bond et al.2003;Tylenda 2004)its distance is 5-6kpc.If these estimations are correct,at the time of maximum brightness V838Mon was the most luminous star in our Galaxy.Details of the spectral evolution of the star are described in Kolev et al.2002;Wisniewski et al.2003;Osiwala et al.2002).During outbursts (except for the last)the spec-trum displayed numerous emission lines with P Cyg pro-ﬁles,formed in the expanding shell and around an F-or A-star (Kolev et al.2002).On the other hand,absorption spectra appropriate to a red giant or supergiant were ob-served in quiescent periods.Strong lines of hydrogen,D lines of sodium,triplets of calcium and other elements show P⋆Based in part on observations collected with the 1.83m tele-scope of the Astronomical Observatory in Asiago,Italy †E-mail:bogdan@mao.kiev.ua ‡E-mail:yp@mao.kiev.uaCyg proﬁles.They have similar proﬁles and velocities vary-ing from −500km s −1in late January to −280km s −1in late March (Munari et al.2002a).Since the middle of 2002March,the emissions are considerably weakened and the spectrum of V838Mon evolved to later spectral classes.In middle of 2002April,there were present some lines of TiO;in May the spectrum evolved to the“very cold”M-giant (Banerjee &Ashok 2002).In October Evans et al.(2003)characterized it as a L-supergiant.Recently Kipper et al.(2004)found for iron group ele-ments [m/H]=−0.4,while abundances of lithium and some s-process elements are clearly enhanced.This results was obtain using the static LTE model.These results are very dependent on the model atmo-sphere and spectrum synthesis assumptions.The nature of the outbursts remains a mystery.Possible explanations include various thermonuclear processes (very slow nova,ﬂare post-AGB),and the collision of two stars (Soker &Tylenda 2003).Munari et al.(2002a)suggested that V838Mon is a new type of a variable star,because comparison with the closely analogous V4334Sgr and M31RV has shown signiﬁcant enough diﬀerences in the observed parameters.In this paper we discuss the results of the determina-tion of iron abundance and atmospheric parameters of V838Mon.These we obtained from an analysis of absorption spec-tra of V838Mon on 2002February 25and March 2and 26.The complexity and uniqueness of the observed character-istics of V838Mon practically excluded a deﬁnition of the parameters of the atmosphere using conventional methods,based on calibration on photometric indices,ionization bal-ance,proﬁles of hydrogen lines.Indeed,the presence around the star of a dust shell,and the uncertain determination of2Bogdan M.Kaminsky,Yakiv V.Pavlenko interstellar reddening(from E B−V=−0.25to E B−V=−0.8 Munari et al.2002a),aﬀects the U−B and B−V colours. Emission in the hydrogen lines provides severe problems for their application in the estimation of eﬀective temperature. Moreover,both the macroturbulent motions and expansion of the pseudophotosphere merges the numerous lines in wide blends.As a result,a single unblended line in the spectrum of V838Mon cannot be found at all,and any analysis based on measurements of equivalent widths is completely excluded.The observational data used in this paper are described in section2.Section3explains some background to our work and some details of the procedure used.We attempt to de-termine T eﬀ,the microturbulent velocity V t and the iron abundance log N(Fe)in the atmosphere of V838Mon in theframework of the self-consistent approach in section4.Some results are discussed in section5.2OBSER V ATIONSSpectra of V838Mon were obtained on2002February25 and March26with the Echelle+CCD spectrograph on the 1.82m telescope operated by Osservatorio Astronomico di Padova on Mount Ekar(Asiago),and freely available to the community from http://ulisse.pd.astro.it/V838Mon/.A 2arcsec slit was used withﬁxed E-W orientation,produc-ing a PSF with a FWHM of1.75pixels,corresponding to a resolving power close to20000.The detector was a UV coated Thompson CCD1024×1024pixel,19micron square size,covering in one exposure the wavelength range4500to 9480˚A(echelle orders#49to#24).The short wavelength limit is set by a2mm OG455long-passﬁlter,inserted in the optical train to cut the second order from the cross-disperser. The wavelength range is covered without gaps between ad-jacent echelle orders up to7300˚A.The spectra have been extracted and calibrated using IRAF software running un-der Linux operating system.The spectra are sky-subtracted andﬂat-ﬁelded.The wavelength solution was derived simul-taneously for all26echelle orders,with an average r.m.s of 0.18km s−1.The8480-8750˚A wavelength range of these Asi-ago spectra has been described in Munari et al.(2002a,b).Another set of spectra(R∼32000)for March2was obtained with the echelleﬁbre-fed spectrograph on the1.9-m SAAO telescope kindly provided for us by Dr.Lisa Crause (see Crause et al.2003for details).3PROCEDURETo carry out our analysis of V838Mon we used the spectral synthesis techniques.Our synthetic spectra were computed in the framework of the classical approach:LTE,plane-parallel media,no sinks and sources of energy inside the atmosphere,and transfer of energy provided by the radia-tionﬁeld and by convection.Strictly speaking,none of these assumptions is100% valid in atmosphere of V838Mon.Clearly we have non-static atmosphere which may well have shock waves mov-ing trough it.Still we assumed that in any moment the structure of model atmosphere of V838Mon is similar to model atmospheres of supergiants.Indeed,temporal changes of the absorption spectra on the days were rather marginal.0.00050.0010.00150.0020.00250.0030.00350.004-200-150-100-50 0 50 100 150 200Velocity (km s-1)V exp=160 km s-1V*sin i=80 km s-1V macro=50 km s-1parison of expansion(V exp=160km s−1),rota-tional(v∗sin i=80km s−1)and macroturbulent(V macro=50 km s−1)proﬁles used in this paper to convolve synthetic spectra.Most probably,for this object,we see only a pseudophoto-sphere,which is the outermost part of an expanding enve-lope.Therefore,ourﬁrst goal was to determine whether it is possible toﬁt our synthetic spectra to the observed V838 Mon spectra.At the time of the observations the spectral class of V838Mon was determined as K-type(Kolev et al.2002). Absorption lines in spectrum of V838Mon form compara-tively broad blends.Generally speaking,there may be a number of broad-ening mechanisms:•Microturbulence,which is formed by small scale(i.e τ≪1)motions in the atmosphere.In the case of a super-giant,V t usualy does not exceed10km s−1.In our analysis we determined V t from a comparison of observed and com-puted spectra.•Stellar rotation.Our analysis shows that,in the case of V838,we should adopt v∗sin i=80km s−1toﬁt the observed spectra.This value is too high for the later stages of stellar evolution,for obvious reasons.In reality rotation cannot contribute much to the broadening of lines observed in spectra of most supergiants.•Expansion of the pseudophotosphere of the star.Asym-metrical proﬁles of expansion broadening can be described, to aﬁrst approximation,by the formulaG(v,λ,∆λ)=const∗∆λThe absorption spectrum of V838Mon3−0.50.511.522.5566056705680569057005710N o r m a l i s e d F l u xWavelength (Å)February 3February 25March 2March 26Figure 2.Spectra of V838Mon observed on February 3,Febru-ary 25,March 2and March 262002emission:many lines are observed in emission.This demon-strates that eﬀects of the radial expansion of the line-forming layers were not signiﬁcant for the dates of our data and for-mally obtained value V exp =160km s −1is not real.•Macroturbulence.After the large increase of luminos-ity in 2002January-February,large scale (i.e.of magnitude τ>1)macroturbulent motions should be very common in the disturbed atmosphere of V838Mon.Our numerical ex-periments showed that,to get appropriate ﬁts to the ob-served spectra taking into account only macroturbulent ve-locities,we should adopt V macro ∼50km s −1.In any case,for the times of our observations the spectra of V838Mon resemble the spectra of “conventional”super-giants.Our V838Mon spectra for February 25,March 2and 26agree,at least qualitatively,with the spectrum of Arcturus (K2III),convolved with macroturbulent velocity proﬁle,given by a gaussian of half-width V macro =50km s −1(Fig.3).The observed emissions in the cores of the strongest lines are formed far outside,perhaps at the outer boundary of the expanding envelope,i.e.in the region which is heated by shock wave dissipation.As result of our ﬁrst numerical experiments,we con-cluded that the spectra of V838Mon in 2002February -March were similar to the spectrum of a normal late (su-per)giant,broadened by strong macroturbulence motions and/or expansion of its pseudophotosphere.Unfortunately we cannot,from the observed spectra,distinguish between broadening due to the macroturbulence and expansion (see next section).It is worth noting that the observed spectra of V838Mon are formed in a medium with decreasing temperature to the outside,i.e.in the local co-moving system of co-ordinates the atmosphere,to a ﬁrst approximation,can be described by a “normal”model,at least in the region of formation of weak or intermediate strength atomic lines.0.10.20.3 0.4 0.5 0.6 0.7 0.8 0.91 1.1 570057105720573057405750N o r m a l i s e d F l u xWavelength (Å)V 838 Mon ArcturusArcturus conv. V macro =50 km s −1Figure parison of the spectrum of V838Mon and that of Arcturus,convolved with macroturbulent proﬁle V macro =50km s −13.1Fits to observed spectraWe computed a sample of LTE synthetic spectra for a grid of Kurucz (1993)model atmospheres with T eﬀ=4000–6000K using the WITA612program (Pavlenko 1997).Synthetic spectra were computed with wavelength step 0.02˚A ,micro-turbulent velocities 2–18km s −1with a step 1km s −1,iron abundances log N (Fe)=−5.6→−3.6dex 1,with a step 0.1dex.Then,due to the high luminosity of the star,we formally adopt log g =0.Synthetic spectra were computed using the VALD (Kupka et al.1999)line list.For atomic lines the line broadening constants were taken from VALD or computed following Unsold (1955).For the dates of our observations lines of neutral iron dominate in the spectra.Fortunately,they show rather weak gravity/pressure dependence,therefore the uncertainty in the choice of log g will not be important in determining our main results;the dependence of the computed spectra on T eﬀis more signiﬁcant (see Fig.4).The computed syn-thetic spectra were convolved with diﬀerent proﬁles,and then ﬁtted to the observed spectra following the numeri-cal scheme described in Jones et al.(2002)and Pavlenko &Jones (2002).In order to determine the best ﬁt parameters,we com-pared the observed residual ﬂuxes r obsλwith computed values H theorλ+f s .We let H obs λ= F theor x −y ∗G (y )∗dy ,where F theor λis the theoretical ﬂux and G (y )is the broadening proﬁle.In our case G (y )may be wavelength dependent.To get the best ﬁt we ﬁnd the minima per point of the 2D functionS (f s ,f g )=Σ(1−H synt /H obs )2.We calculated these minimization parameters for our grid of synthetic spectra to determine a set of parameters f s (wavelength shift parameter)and f g (convolution parame-ter).The theoretical spectra were convolved with a gaussian proﬁle.Our convolution proﬁle is formed by both expan-sion and macroturbulent motions.We cannot distinguish between them in our spectra.To get a numerical estimate1in the paper we use the abundance scaleN i =14Bogdan M.Kaminsky,Yakiv V.Pavlenko0.60.650.7 0.75 0.8 0.85 0.90.95 1 6306 6308 6310 6312 6314 6316 6318 6320 6322 6324N o r m a l i s e d F l u xWavelength (Å)T eff =4000 KT eff =5000 K logg=0T eff =5000 K logg=1T eff =6000 KFigure 4.Dependence of computed spectra on T eﬀand log gof the broadening processes in the pseudophotosphere,we use a formal parameter V g ,which describes the cumulative eﬀect of broadening/expansion motions.The parameters f s and f g were determined by the min-imization procedure;the procedure was carried out for dif-ferent spectral regions.We selected for analysis 6spectral orders in the interval 5600-6700˚A .In the red,spectral lines are blended by telluric spectra,and are of lower S/N.In the blue the blending of the spectra are rather high.Our main intention was to obtain a self-consistent solution sep-arately for diﬀerent echelle orders,and then compare them.If we could obtain similar parameters from diﬀerent spec-tral regions it can be evidence of the reality of the obtained solution.4RESULTS 4.1The SunTo be conﬁdent in our procedure,we carried out a similar analysis for the Sun.For this case we know the solar abun-dances and other basic parameters,therefore our analysis provides an independent estimation of the quality of our procedure:•From the solar atlas of Kurucz et al (1984)we ex-tract spectral regions corresponding to our observed orders of V838Mon;•we convolve the solar spectra with a gaussian of V macro =50km s −1.•we carried out a spectral analysis of the spectral regions with our procedure;again,model atmospheres from Kurucz (1993)with a grid of diﬀerent log g ,T eﬀ,log N (Fe)were used.The results of our “re-determination”of parameters of the solar atmosphere are given in Table 1.The best ﬁt to one spectral region is shown in Fig.5.From our analysis of the solar spectrum we obtained T eﬀ=5625±125K,log N (Fe)=−4.48±0.15dex,V t =1.2±0.4km s −1.Here and below we used the standard deviation for error esti-mates.All these parameters are in good agreement with theTable 1.Parameters of the solar atmosphere116480–668555001-4.545.8126300–649057502-4.646.4136125–631557501-4.442.9145960–614557501-4.244.1165660–581055001-4.643.9175520–567055001-4.642.9Averaged56251.2-4.4844.3The absorption spectrum of V838Mon5–For February25we obtained T eﬀ=5330±300K,log N(Fe)=−4.7±0.14dex and V t=13.±2.8km s−1.–For the March26data the mean values are T eﬀ=4960±270K,log N(Fe)=−4.68±0.11dex,V t=12.5±1.7km s−1.–And for March2the mean values are T eﬀ=5540±190K,log N(Fe)=−4.75±0.14dex,V t=13.3±3.2kms−1.–We obtained V g=54±3,47±3and42±5km s−1for February25,March2and March26,respectively.–The f s parameter provides the heliocentric velocity ofV838Mon.We obtained V radial=−76±3,−70±3and−65±3km s−1for February25,March2and March26,respectively.Most probably,we see some reduction in theexpansion velocity of the envelope.5DISCUSSIONFrom a comparison of our results for all three dates we see that:•The eﬀective temperature for March26is somewhat lower then for the previous dates.This is an expected re-sult,in view of the gradual cooling of envelope.However, for March2we found a slightly higher value of temperature than for February25.A possible explanation is the heating of the pseudophotosphere as result of the third outburst.•The microturbulent velocities are very similar and ex-tremely high for all three dates.•Our analysis shows a lower value of V g for the later dates:the eﬀects of expansion and macroturbulence were weakened at the later stages of evolution of the pseudopho-tosphere of V838Mon.•The iron abundances log N(Fe)=-4.7±0.14are similar for all dates.Our estimates of eﬀective temperature are in a good agreement with Kipper et al.(2004),although we used dif-ferent procedures of analysis.The iron abundance([Fe/H]=−0.4)and microturbulent velocity(V t=12km s−1)found by Kipper et al.(2004)for March18are in agreement with our results.Our deduced“eﬀective temperatures”as well as those in Kipper et al(2004)do not correspond with values ob-tained from photometry(T eﬀ∼4200K).We assume that in our analysis we deal with temperatures in the line forming region,rather than with the temperatures at photospheric levels which determine the spectral energy distribution of V838Mon and the photometric indices.Indeed,the formally determined microturbulent velocity V t=13km s−1exceeds the sound velocity in the atmosphere(4-5km s−1).This means that the region of formation of atomic lines should be heated by dissipation of supersonic motions:the temper-ature there should be higher than that given in a plane-parallel atmosphere of T eﬀ∼4200K.Certainly the eﬀect cannot be explained by sphericity eﬀects:the temperature gradients in the extended atmo-spheres should be steeper(see Mihalas1978),therefore tem-peratures in the line forming regions should be even lower, in contradiction with our results.Strong deviations from LTE are known to occur during the photospheric stages of the evolution of novae and super-0.40.50.60.70.80.911.16480 6500 6520 6540 6560 6580 6600 6620 6640 6660 6680 6700 NormalisedFluxWavelength (Å)V 838 MonT eff=5250 KT eff=4500 K0.40.50.60.70.80.911.16300 6320 6340 6360 6380 6400 6420 6440 6460 6480 6500 NormalisedFluxWavelength (Å)V 838 MonT eff=5000 KT eff=4500 K0.40.50.60.70.80.911.16120 6140 6160 6180 6200 6220 6240 6260 6280 6300 6320 NormalisedFluxWavelength (Å)V 838 MonT eff=5250 KT eff=4500 KFigure6.The bestﬁts of synthetic spectra to11-13orders of the observed spectrum of V838Mon on February25,found by the minimization procedure.novae.The main eﬀect there should be caused by deviations from LTE in the ionization balance.However,in our case we used lines of the neutral iron,which dominate by number. We cannot expect a reduction in the density of Fe I atoms in the comparatively cool atmosphere of the star.Further-more,we exclude from our analysis strong lines with P Cyg proﬁles.Lines of interest in our study have normal proﬁles.6Bogdan M.Kaminsky,Yakiv V.PavlenkoTable2.Atmospheric parameters for V838MonAsiago spectraFebruary25116480–6685525015-4.753.2-79.6126300–6490500014-4.954.5-76.3136125–6315525010-4.756.0-82.7145960–6145575017-4.552.5-79.5165660–581050009-4.960.7-67.1175520–5670575014-4.751.1-73.6Averaged533013.2-4.7354.7-76.5March26116480–6685475012-4.843.7-67.3126300–6490475014-4.844.7-68.3136125–6315475010-4.546.0-74.3145960–6145500015-4.842.1-65.8165660–5810500011-4.738.8-52.2175520–5670550013-4.539.7-63.6Average496012.5-4.6842.5-65.2SAAO spectraMarch2116480–6685550012-4.645.3-80.6126300–6490525016-4.955.8-77.3136125–631552507-4.642.8-78.9145960–6145575014-4.849.0-80.6165660–5810550015-4.951.7-68.1175520–5670600016-4.742.1-80.0Average554013.3-4.7547.8-77.6The absorption spectrum of V838Mon70.40.50.6 0.7 0.8 0.9 1 1.1 5960 5980 6000 6020 6040 6060 6080 6100 6120 6140 6160N o r m a l i s e d F l u xWavelength (Å)V 838 Mon T eff =5750 K T eff =4500 K0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 5660 5680570057205740576057805800N o r m a l i s e d F l u xWavelength (Å)V 838 Mon T eff =5000 K T eff =4500 K0.40.50.6 0.7 0.8 0.9 1 1.1 5500 5520 5540 5560 5580 5600 5620 5640 5660 5680N o r m a l i s e d F l u xWavelength (Å)V 838 Mon T eff =5750 K T eff =4500 K Figure 7.The best ﬁts of synthetic spectra to orders 14,16and 17of the observed spectrum of V838Mon on February 25,found by the minimization procedure.•most probably,the line-forming region is heated by su-personic motions –our spectroscopic temperatures exceed photometrically determined T eﬀby ∼1000K;•we do not ﬁnd any signiﬁcant change in the iron abun-dance in atmosphere V838from February 25to March 26.•we derived a moderate deﬁcit of iron log N (Fe)∼−4.7in the atmosphere of V838Mon.ACKNOWLEDGMENTSWe thank Drs.Ulisse Munari,Lisa Crause,Tonu Kipper and Valentina Klochkova for providing spectra and for discus-sions of our results.We thank Dr.Nye Evans for improving text of paper.We thank unknown referee for many helpful remarks.This work was partially supported by a PPARC visitors grants from PPARC and the Royal Society.YPs studies are partially supported by a Small Research Grant from American Astronomical Society.This research has made use of the SIMBAD database,operated at CDS,Strasbourg,France.REFERENCESAllen C.W.,1973,Astrophysical quantities,3rd edition,TheAthlone Press,LondonBanerjee D.P.K.,Ashok N.M.,2002,A&A,395,161Bond H.E.,et al.,2003,Natur,422,405Brown N.J.,2002,IAU Circ,7785,1Crause L.A.,Lawson W.A.,Kilkenny D.,van Wyk F.,MarangF.,Jones A.F.,2003,MNRAS,341,785Desidera,S.,Munari,U.,2002,IAU Circ,7982,1Evans A.,Geballe T.R.,Rushton M.T.,Smalley B.,van LoonJ.Th.,Eyres S.P.S.,Tyne V.H.,2003,MNRAS,343,1054Henden A.,Munari U.,Schwartz M.B.,2002,IAU Circ,7859Jones H.R.A.,Pavlenko Ya.,Viti S.,Tennyson J.,2002,MNRAS,330,675JKimeswenger S.,Ledercle C.,Schmeja S.,Armsdorfer B.,2002,MNRAS,336,L43Kipper T.,et al.,2004,A&A,416,1107Kolev D.,Mikolajewski M.,Tomow T.,Iliev I.,Osiwala J.,Nirski J.,Galan C.,2002,Collected Papers,Physics (Shu-men,Bulgaria:Shumen University Press),147Kupka F.,Piskunov N.,Ryabchikova T.A.,Stempels H.C.,WeissW.W.,1999,A&AS,138,119Kurucz R.L.,Furenlid I.,Brault J.,Testerman L.,1984,Nationalsolar obs.-Sunspot,New Mexico Kurucz R.L.,1993,CD-ROM 13Mihalas D.,1978,Stellar atmospheres,Freeman &Co.Munari U.,et al.,2002a,A&A,389,L51Munari U.,Henden A.,Corradi R.M.L,Zwitter T.,2002b,in”Classical Nova Explosions”,M.Hernanz and J.Jos´e eds.,AIP Conf.Ser.637,52Osiwala J.P.,Mikolajewski M.,Tomow T.,Galan C.,Nirski J.,2003,ASP Conf.Ser.,303,in pressPavlenko Y.V.,1997,Astron.Reps,41,537Pavlenko Ya.V.,Jones H.R.A.,2002.A&A,397,967Pavlenko Ya.V.,2003.Astron.Reps,47,59Soker N.,Tylenda R.,2003,ApJ,582,L105Tylenda R.,2004,A&A,414,223Unsold A.,1955Physik der Sternatmospheren,2nd ed.Springer.BerlinWisniewski J.P.,Morrison N.D.,Bjorkman K.S.,MiroshnichenkoA.S.,Gault A.C.,Hoﬀman J.L.,Meade M.R.,Nett J.M.,2003,ApJ,588,486This paper has been typeset from a T E X/L A T E X ﬁle preparedby the author.。

地震波的三个来源及特点

地震波的三个来源及特点时程分析中，所⽤的地震波主要有三个来源：实际加速度记录（recorded accelerograms or real accelerograms）地震台⽹的发展，使得实际地震动记录数量不断增加。

常⽤地震记录数据库：PEER Strong Motion DatabasePacific earthquake engineering research center：NGA databaseCOSMOS Virtual Data CenterEuropean Strong motion database优点：反映了地震动的各种特性（幅值、频谱和能量特性、持时及相位等）；反映了震源、传播路径及场地⼟的影响。

缺点：⽬前，地震动记录数量是有限的，完全和设计场地特性（震级、震中距、场地⼟特性等）匹配的地震动记录更加有限。

为了使实际加速度记录和设计反应谱吻合，通常需要对其进⾏修正。

修正⽅法有三种：a) 在时域内对加速度记录的进⾏调幅（scaling on amplitude in time domain）：在整个持时内，加速度记录被简单地放⼤或缩⼩若⼲倍数。

具体⽅法⼜分为四种：⼀是根据加速度记录的峰值（PGA）确定缩放系数，保证其反应谱和⽬标谱在T=0处的谱加速度值相等，这是我国规范采⽤的⽅法；⼆是依据加速度记录在特定周期点T0对应的加速度值确定缩放系数，保证其反应谱和⽬标谱在T0处的谱加速度值相等；三是依据加速度记录的反应谱和⽬标反应谱在感兴趣的周期区间内离散最⼩的原则，采⽤最⼩⼆乘法确定缩放系数；四是同时考虑多条加速度记录，依据多条波的平均加速度反应谱和⽬标谱离散最⼩的原则，确定各条加速度记录的缩放系数。

b）在频域范围内进⾏谱吻合（Spectra matching in frequency domain）：通过在频域范围内调整实际加速度记录的傅⾥叶谱值，产⽣⼀个和⽬标谱吻合的加速度记录。

kbr压片法测红外光谱英文

kbr压片法测红外光谱英文When it comes to measuring infrared spectra, the KBr pellet method is a commonly used technique. It's pretty straightforward and effective. Basically, you mix your sample with a fine powder of potassium bromide (KBr) and then compress it into a transparent disk or "pellet". The KBr acts as a diluent and helps distribute the sample evenly.The key to getting good results is having a finely ground sample and using the right amount of KBr. Too much or too little can affect the quality of the spectrum. Once you've got your mixture ready, you use a special press to compress it into a pellet.Measuring the infrared spectrum of the pellet is then done using an infrared spectrometer. The instrument shines infrared light through the pellet and measures how much of each wavelength is absorbed. This gives you a unique "fingerprint" of your sample's chemical composition.One of the advantages of the KBr pellet method is that it works well for a wide range of samples. Whether you're dealing with solids, liquids, or even gases, you can often adapt the technique to get the data you need. Plus, the pellets are easy to handle and store, making it a convenient choice for labs of all sizes.In summary, the KBr pellet method is a solid way to measure infrared spectra. With the right tools and technique, you can get reliable and accurate results in no time.。

长波红外分光镜的作用

长波红外分光镜的作用英文回答：A long-wave infrared spectrometer is a device used to analyze and measure the wavelengths of infrared radiation in the long-wave infrared region. It plays a crucial role in various fields, including scientific research, industrial applications, and environmental monitoring.In scientific research, a long-wave infrared spectrometer is used to study the composition and properties of materials. For example, it can be used to analyze the infrared spectra of molecules, which provides valuable information about their chemical structure and bonding. This is particularly useful in organic chemistry, where infrared spectroscopy is commonly used to identify and characterize organic compounds.In industrial applications, a long-wave infrared spectrometer is used for quality control and processmonitoring. It can be used to analyze the composition of raw materials, monitor the progress of chemical reactions, and detect impurities or contaminants in products. For example, in the food industry, a spectrometer can be used to analyze the infrared spectra of food samples to ensure their quality and authenticity.In environmental monitoring, a long-wave infrared spectrometer is used to study and monitor the Earth's atmosphere. It can be used to measure the concentrations of greenhouse gases, such as carbon dioxide and methane, which are important for understanding climate change. It can also be used to detect pollutants in the air, such as volatile organic compounds (VOCs) and particulate matter, which are harmful to human health.Overall, a long-wave infrared spectrometer is a versatile and powerful tool for analyzing and measuring infrared radiation. It enables scientists and researchers to gain insights into the composition, properties, and behavior of materials in various fields.中文回答：长波红外分光镜是一种用于分析和测量长波红外辐射波长的设备。

安捷伦600MHz NMR 使用指南 TOPSPIN INSTRUCTIONS说明书

TOPSPIN INSTRUCTIONS1.How to start TOPSPIN?2.The TOPSPIN window3.How to open an old dataset?4.How to create a new dataset?5.How to lock and shim?6.How to acquire FID signal and modify acquisition parameters?7.How to process 1D spectrum and modify process parameters?8.How to process a 2D NMR spectrum?9.How to display multiple 1D /2D spectra?10.How to perform multiplet analysis?1. How to start TOPSPINa. Login using your group ID and passwordb. Double click TOPSPIN iconto start TOPSPIN software2.This is the TOPSPIN window:3. How to open an old dataset:The popup Menua) In the Browser window, locate your data, right-click a dataset name, and choose Displayin the popup menu b) Or, click a dataset name and hold, then drag it to the datawindow The display of title and pulse in the Browser window can be switched on or off by right-clicking anywhere in the Browser window and selecting On/Off Show PULPROG/Titlein the popup menu If you have a top level data directory which is not shown in the Browser window (such as D:\ rather then C:\Bruker\Topspin), you can right-click anywhere in the Browser window, and choose Add New Data Dir in thepopup menu4. How to create a new dataset:a. Click File → New ; ORclick the button in the upper toolbar; OR type edc inthe command lineIn the popup dialog box:b.Specify name, expno, procno, dir and userc.Click the down-arrow of the Solvent box to choose a solvent from the listd.In Experiment box, select Use current paramse.Type the dataset title in the TITLE boxf.Type rpar in the command line to choose a parameter set from the listFor example:Parameter set name: proton experiment =1_protonstdCarbon experiment = 1_carbonstd5.How to lock and shim?a.Type lockdisp in the command line OR click the button in the upper toolmenu to open the lock display windowb.Type lopo in the command line and select a solvent from the popup list,c.On the BSMS keyboard:•Press the FIELD button, and move the lock signal to the centerof the lock display window•Press the PHASE button, and adjust the lock signal in-phase•Press the X (or X+Z0), the Y (or Y+Z0), the Z1 (or onaxis+Z1),OR Z2 (or onaxis+Z2) shim buttons, and optimize these shimsiteratively to make lock-ring-down pattern observable•Press the LOCK button•Press the SPIN button (for 2D NMR experiments, spin has to beoff), and wait for spin indicator to stop blinking•Optimize Z1 and Z2 shim iteratively by turning the whirl andobserving the lock signal level moving up as high as we can•If necessary, press the LOCK GAIN button to decrease/increaselock gain•Then press the STDBY buttond.If shim is messed up, type rsh currshim in the command line to read mostcurrent shim file ine.Autoshim: type topshim. In the popup window, choose1D shim and turn Z6 off,then click start(only for TOPSPIN 2.0 and newer)6.How to acquire FID signal and modify acquisition parametersa.Type rga in the command line, thenb.Type zg in the command linec.Sometimes it is necessary to modify acquisition parameters•Modify acquisition parameters•Clicking AcquPars tab in the tab bar of the data window•OR type eda in the command line•Modify pulse program parameters•Click the button in the toolbar•OR type ased in the command lineOther buttons in AcquPars toolbarSet probehead/solvent dependant parameters [getprosol]Set nuclei and routing [edasp]parameter columns and value of the acquisition parameter PARMODE7.How to process 1D spectrum and modify process parametersa.Modify process parameters•Click ProcPars tab in the tab bar of the data window•OR type edp in the command lineb.Fourier Transform:•Type efp in the command linec.Phase correction:¾Manual method•Click phase correction button in the upper toolbar•The Tab bar of the active data window will be replaced by thefollowing toolbarreference peak is exactly in absorption mode•Left-click-hold the button and move the mouse until theentire spectrum is exactly in absorption mode•Click the button to save and execute the phase correction¾Automatic method:•Type apk in the command line to execute automatic phase correctiond.Chemical shift calibration•Click the button in the upper toolbar, and the Tab bar of the active data window will be replaced by the following toolbar•Position the red cursor line at the reference peak•Left-click at that position and enter the chemical shift of thereference peak at the popup dialog boxe.Integration•Click the button in the upper toolbar, and the Tab bar of the active data window will be replaced by the following toolbar•Define integral regions: Note: the active button is highlighted ingreen: define integral region interactively: define integral region via dialog: cut integral region¾When this button is highlighted in green, put thered cursor line at one edge of a peak or multiplet, thenleft-click-hold and drag the cursor line to the other edgeof the peak or multiplet.¾Use or buttons to modify the integral region.•Select a single integral region¾Right-click in the integral region you want to select¾Choose Select/Deselect from the popup menu: select the next integral region: select the previous integral region: select all integrals: delete selected integral region from the display•Calibrate integrals¾Right-click in the reference integral region¾Choose Calibrate from the popup menu¾Enter the desired value for the reference integral andclick OK•Other buttons:: Scale selected integrals: Move all the integrals up and down: Change the mouse sensitivity: Perform interactive Bias and Slope correction: Save integrals and return: Return, discarding any changesf.Peak picking:•Click the button in the upper toolbar, and the Tab bar of the active data window will be replaced by a following toolbar•Define peak picking regions: Note: the active button is highlighted in green: Define peak picking range: Change peak picking range: delete all peak picking regionsWhen the button is green, put the cursor at the upper-left cornerof a peak picking range, then left-click-hold and drag the cursor tothe low-right corner of the range. You can use this button tomodify the peak picking range.•Other buttons in the toolbar: Define peaks manually: Define peaks semi-automatically: Delete all peaks: Save the peak region and peak list and return: Return, discarding any changes8.How to process a 2D NMR spectruma.Fourier transform:•Type xfb in the command lineb.Phase correction:•Click phase correction button in upper toolbar•The Tab bar of the active data window will be replaced by afollowing toolbar•Right-click and choose add in the popup menu to select threepeaks at different parts the spectrum•Click the button to display rows of selected peaks underphase row mode•Perform phase correction by click-holding the button andto make all peaks in three rows in absorption mode•Click the button to execute, save and return•Click the button to display columns of selected peaks underphase column mode•Perform phase correction by click-holding the button andto make all peaks in three rows in absorption mode•Click the button to execute, save and return•Other buttons in the tool bar: show next or previous row/column: arrange row/column horizontally or vertically orvertically in a split window•Click the button to return from 2D phase modec.2D chemical shift calibration•Click the button in the upper toolbar, and the Tab bar of theactive data window will be replaced by the following toolbar•Left-click at the reference peak in the data window, the dialogbox will appear•Enter the F2 and F1 chemical shifts you want to assign to thereference peak•Click ok9.How to display multiple 1D /2D spectraa.Click the button in the upper toolbar, and the Tab bar of the active datawindow will be replaced by a following toolbarb.Add a dataset:•Enter re and specify the additional dataset•OR left-click-hold the dataset in the browser and drag it into thedata window•OR right-click the dataset in the browser and choose Displayfrom the popup menuc.Select/deselect the datasets•The browser is split in two parts and in the lower part you canclick one dataset to select it•OR click in the corresponding area in the data window•Click the button to deselect all the datasetsd.Remove a dataset:•Select a dataset you want to remove as step c•Click the button to remove ite.Other buttons:: Toggle between superimposed and stacked display: Switch on/off display of datapaths and scaling factors: Show the difference between the first and the sum of the otherdatasets: Show the sum of all datasets in the multiple display window10.How to perform multiplet analysis?a.Perform Peak-picking as Procedure 7(f) (you might need use manual peak-picking button to pick all peaks)b.In Menu bar, click Analysis → Structure Analysis → Multiplet Definition[mana]c.The Tab bar of the active data window will be replaced by the following toolbard.Automatically define multiplet•Click the button in toolbar to define multiplet in whole sweep width automatically•Click the button in toolbar; left-click-hold mouse and drag to define the region, multiplet in this region will be definedautomatically.e.Manually define multiplet•Click the button in the toolbar•Put red cursor line on a peak and left-click to select, repeat to select other peaks, then right-click and select Define Multipletin the popup menu•Click the button in the toolbar to couple existing multiplets¾Left-click to select each multiplet¾Right-click and select Define Multiplet in the popupmenu¾The coupling constants will be listed in the up-rightcorner of the window¾Click the button in the toolbar, the resulting reportwill show in popup windowf.Click the button in the toolbar, and save multiplet assignment and returnTOPSPIN PLOT EDITOR INSTRUCTIONS1.How to use TOPSPIN PLOT EDITOR to plot a spectrum?2.How to plot several 1D spectra in stack mode in Topspin Plot Editor?3.How to export a spectrum as PDF or PNG or EMF format file so you caninsert it to your report/thesis?1.How to use TOPSPIN Plot Editor to plot a spectruma.Type Layout in the command line to select the desired layout by clicking down-arrow button of LAYOUT box , then type plot in the command line andTOPSPIN Plot Editor will startb.OR File→Print, and select Print with layout-start Plot Editor in the popupwindowIn the required parameters, select the desired layout by clicking down-arrowbutton in LAYOUT box. After clicking OK button, the TOPSPIN Plot Editorwill startThe layout can be specified by using one of the following abbreviations:+: the standard layout directory: ../topspin/plot/layout~: the user home directory#: current processed data directoryc.Preview the current plot layout and plot (Click File→ Print)d.Modify the plot layoutMove, resize and delete an object (spectrum, title, parameter or logo):•Mark an object by clicking the button and then clicking the object•Click-hold the object and move the mouse to move the object•Click-hold one of the green markers and move the mouse to resize the object•Click the button in command bar to delete the objectModify the spectrum•Mark the spectrum object and click the button in the command bar•Mark the spectrum object and click the button in the command barUnder Linux, all parts (Graph, 1D spectrum. DataSet and Basic) are shown simultaneouslyIf the spectrum is a 2D spectrum, the popup window isModify parameters and title•Right-click the object and choose corresponding buttons in the popup menu to modify the object2.How to plot several 1D spectra in stack mode in Topspin Plot Editora.Click the button in the command bar, click Edit button in the popupData Set Selector window. The Portfolio Editor window will pop upb.In Portfolio Editor window, choose right Directory and User, all datasets willshow up.c.Choose the first spectrum by clicking the respective entries in the sections Name,Expno and Procno. Then click the Append button.d.Repeat step c for the rest of spectra, then click Apply back to Data Set Selectorwindow, click OKe.In TOPSPIN Plot Editor, click File → New to open a new layoutf.Click the button, click-hold left mouse button and drag in the layout areag.Mark the spectrum by click the button, then click button incommand bar. The popup window ish.Click Stacked menu bar, fill the box. In Spectra Offset box, the first number isoffset of X-axes, and the second number is offset of Y-axes. By adjusting thesetwo offsets, you will get the desired layout3.How to export a spectrum as PDF or PNG or EMF format file so you can insert it toyour report/thesis?a.From Topspin Plot Editor• A spectrum is appeared in the Plot Editor with desired layout•Click File → Export•In the box of Save as type, you can choose the type you want,and put filename in box of File name, then click Save buttonb.From Topspin (Note: No PDF type is available)• A spectrum is appeared in the data area•Click File → Export•Put filename in the File name box with extension•Click Export button。

RC1 反应热计的用户指南说明书

A paper from theRC User Forum USA, Hilton Head, 1996.IntroductionRecent papers1,2,3 by this author have discussed, primarily, use of an integrated batch chemical syn-thesis process development and modeling system first installed at the Arkansas Eastman site in 1992. The integrated system consists of METTLER TOLEDO’s RC1 reaction calorimeter, ASI’s ReactIR/Probe system and BatchCAD, LTD’s RE-ACTION and RATE simulation and modeling soft-ware. The most recent paper3 included information regarding specific computer assisted batch reactor systems, assembled at the Arkansas Eastman and Tennessee Eastman sites along with the integrated system. If unlimited funds were available, use of the well-developed capabilities of the RC1 in all laboratory phases of batch synthesis process devel-opment would be desirable. However, many batch process development and evaluation tasks can be performed satisfactorily by (less expensive) reactor systems other than the RC1.Capabilities of Lab-scale, Computer Assisted Batch Reactor Systems developed recently by Tennessee Eastman’s Organic Chemicals Division (TEOC) TEOC personnel have assembled a series of com-puter assisted batch reactor systems that are con-trolled through Camile TG hardware and software. The purpose of the systems is to provide process development chemists with stirred tank batch reac-tor systems that have capabilities for mimicking plant-scale temperature profiles, reagent addition rates and mixing conditions. These systems have most of the capabilities that the RC1 has except for reaction calorimetry. In some ways, Camile-basedU SE OF A UTOMATED B ATCHL ABORATORY R EACTORS YSTEMS OTHER THAN THERC1 IN P ROCESSD EVELOPMENT AND S CALE-UPby James T. Leach, Eastman Chemical CompanyI ncreasing pressures for efficient and effective use of scarce resources and ever shorter times to mar-ket for new products provide a great deal of incentive for exploration of uses of low cost automated batch laboratory reactor systems and related commercial software packages. This paper discusses some of the batch process development/scale-up tasks which have been undertaken successfully using relatively low cost computer assisted laboratory reactor system assembled by Tennessee Eastman’s Or-ganic Chemicals Division personnel. Among the tasks are: (1) repetitive execution of synthesis processes, (2) mixing scale-up/scale-down studies, (3) crystallization process development and evaluation studies, and (4) development of kinetic models for use in plant-scale simulation studies (when reactor systems were used with ASI’s ReactIR/Probe system and BatchCAD, Ltd.’s REACTION and RATE software). Various desk top computer based software packages which facilitate tasks such as process optimization, statistical design and evaluation of experiments, estimation of materials properties and estimation of heats of reaction are listed. Also given is a discussion showing how the RC1 and low cost batch reactor systems can be used together to provide sufficient information, for many types of batch process systems, to facili-tate process development and scale-up without the use of intermediate pilot plant facilities.Keywords: RC1, ReactIR, BatchCad, Scale-up, batch reactor, kinetic, RATE, REACTION, Camile, process optimization.systems are more open and flexible than the RC1 and are more capable of controlling complex set-ups than is the RC1 system. Some of the features of Camile controlled laboratory systems used by TEOC personnel are:plex, automated recipe sequencingavailable.e of thermostats that control jacket tem-peratures in the range of –20 to 200°C andreactor temperatures in the range of –5 to170°C.plex temperature ramping capability.4.Jacket temperature control or reactor tempera-ture control modes.5.Open architecture to facilitate design andcontrol of custom built systems to suit a widevariety of needs (incorporating a large num-ber of digital I/O’s, analog inputs and analogoutputs).6.Event and data logging.7.Dynamic Data Exchange to spreadsheets orMicrosoft3 applications.8.pH control systems.9.Dosing of liquid reagents from digital balancesmunication with digital balances forpurposes such as recording weight of distillatecollected.11.Alarms, timers, etc.Applications1.Precision replication of synthesis processes –process capability studies.2.Process optimization studies changing onlydesired variables.3.Solubility studies.4.Crystallization studies.5.Continuous determination of reaction mixtureviscosity.6.Mixing simulation studies, matching stirrertip speed or power per unit volume with thatof large reactor.ed with ReactIR to perform kinetic model-ing studies – recording of concentration/temperature/time information simultaneously.ed as distillation control system.9.Indication of tendency of desired reaction toexhibit exothermic behavior.10.Training of plant operations personnel whennew processes are transferred to the productionplant. Operators observe process propertiesand mixing through walls of glass reactors.11.In conjunction with batch modeling/simula-tion software and heat of reaction and proper-ties estimation software, computer assistedlab reactors are used to assist developmentchemists in building and testing batch processmodels. In most cases this type of experimen-tation is used by TEOC personnel instead ofpilot plant experimentation.Pilot Plant Experimentation –Do I really need it?This topic was discussed in considerable detail in a previous paper3. The overall conclusions of the pa-per can be summarized as follows: (1) When the predominant factor in batch process scale-up is heat transfer, intermediate pilot plant experimenta-tion can be foregone because, in most cases, heat transfer on scale-up is very predictable when ap-propriate process modeling work has been per-formed during the developmental phases. (2) In cases where mass transfer is the predominant fac-tor in determining some property of the product as a process result, intermediate scale experimenta-tion may be useful.Appropriate modeling work is that which provides dynamic material balance and heat balance infor-mation for the process under consideration for any specific stirred tank reactor vessel available (prior to transfer of the process to plant-scale equipment). Also, appropriate modeling work will provide a sound basis for design of equipment specifically suited to the process heat transfer and mixing re-quirements. Among the inputs required for appro-priate process modeling work are: (1) a kinetic model for the chemical synthesis process under study, (2) accurate values (measured or estimated) for process heat(s) of reaction, (3) heat capacity of the reaction mixture as functions of composition and temperature, (4) reaction mixture heat transfer coefficients (or materials properties that can be used to estimate them), and (5) heat transfer capa-bilities of specific plant-scale stirred tank reactor systems to be used for the process.Mixing studies – Scale-up and scale-downFor general purpose mixing in stirred tank reactor systems, two mixing rules4 often are applied in try-ing to approximate the mixing in a small reactor that will be realized in a much larger reactor.1.Assuming geometric similarity (similar stirrerdesign, similar baffling, and similar diameter of stirrer to diameter of tank ratio), match theperipheral speed of the stirrer in the smallsystem to that of the stirrer in the large system.This is easily done if one knows the diameter of the large stirrer and the rpm at which it will be turning as well as the diameter and rpm of the stirrer in the lab reactor.2.Match the power/volume in the small system tothat expected in the large system.A Case StudySuppose the firm wishes to perform an occasional batch synthesis of a compound we shall call «R-Acetol» by the route 1.Compound C can react further to form compound E as is shown in route 2.In order to find conditions which will maximize the formation of C while minimizing the formation of E, using a minimal number of laboratory experi-ments, it is beneficial to develop a complete kinetic model which describes how the rates of both reac-tions vary as functions of time, concentrations of reactants, and reaction mixture temperature. ExperimentalThe ReactIR and a Camile-controlled, jacketed, stirred-tank, batch reactor system were used to per-form a synthesis experiment using a variation of this reaction sequence. Reaction mixture spectra were collected and reaction mixture temperature was recorded during the course of the reaction. The following procedure was used:1.A background spectrum was obtained with theDicomp probe in place in the empty reactorsystem.Route 1Route 2Acetic Acid Solventwith catalystR-AcetolCat.A B C DE+2.A weighed quantity of solvent, acetic acid,was charged to the reactor vessel (which was under jacket temperature control). At thispoint, a ReactIR Reaction Sequence wasinitiated and reaction mixture temperaturelogging was begun.3.A weighed quantity of component A wascharged to the reactor vessel. Sufficient timewas allowed for this component to dissolvebefore proceeding to the next step.4.A weighed quantity of component B, aceticanhydride, was charged to the reactor vessel.5.Catalyst was charged to the reactor vessel.6.The mixture then began to react, exhibiting amild exotherm. The reaction was allowed to go to completion.7.Several spectra obtained during the course ofthe reaction were examined to find features that would facilitate simple quantitative analyses for individual components in the reaction mixture.In order to obtain maximal benefit from use of the ReactIR, it was desirable to use it as astand-alone analytical device, if possible. Thisstrategy would avoid dependence on samplingthe reaction mixture for analysis by calibration methods. It also would avoid having to enlistthe aid of other personnel and equipment tocomplete the task of development of a kineticmodel for the chemical synthesis sequence.8.A table of reaction mixture component concen-trations, time and temperature data was devel-oped using the QuantIR software with subse-quent merging of the quantitative profile output, in a Microsoft Excel spreadsheet, with thereaction mixture temperature logged by theCamile system.9.The table produced in Step 8. was imported intoBatchCAD, LTD’s, RATE software for develop-ment of a complete kinetic model with subse-quent fitting of the model parameters to theexperimental data.10.The kinetic model was used in BatchCAD,LTD’s REACTION software to find optimumconditions for conducting this synthesis so that conversion of A to C was a maximum value.That is, process optimization was performedusing only one synthesis experiment.Now that I have an optimized laboratory procedure, how do I go about scaling it up to 2000-gallon size?Heat transfer, mixing and material balance on scale-up – The synthesis will be conducted in a 2000-gallon, glass-lined, Pfaudler vessel, equipped with a retreat curve stirrer. The reactor will be cooled with –10°C glycol/water coolant and will be heated with 90 psig steam. The maximum reaction mixture viscosity observed during laboratory ex-perimentation was 0.018 Pa-s or 0.018 kg/m·s. Upon calculating the minimum expected Reynolds number for the system (78900) and examining the power curve4 associated with the reactor system, it can be seen that the reactor will be operating in the turbulent mixing regime. Therefore, the reaction mixture can be considered «well mixed». Heat transfer and dynamic material balances in the 2000-gallon vessel can be simulated with reasonable ac-curacy with the help of BatchCAD, LTD’s REAC-TION software. REACTION uses the Seider-Tate5 correlation for estimating the reaction mixture heat transfer coefficient along with the kinetic model de-veloped using the ReactIR and laboratory reactor. The heats of reaction for the two reactions under study were estimated using NIST6 software. Mate-rials properties were found in AICHE’s DIPPR7 database.Synthesis Process Optimization The utility of integrated process model develop-ment is apparent when one compares the labor and elapsed time required to perform process opti-mizations by computer simulation to the require-ments of optimization performed using brute force experimentation, or even statistically de-signed experiments. After a complete synthesis process model has been built, one can perform computer simulation studies to predict effects of changing important process variables, in a plant-scale operation, such as reagent addition rates, temperature profiles, stoichiometry, residence time, etc. within a few days. Simplex Optimiza-tion software can provide a systematic procedure to assist process development personnel in deter-mining the optimum conditions under which their synthesis processes should be conducted in plant-scale equipment.Testing of the Proposed Pecipe under Expected Plant Conditions (model validation) A Camile-controlled model reactor system can be programmed to replicate the temperature profile and/or reagent addition rates predicted for the 2000-gallon scale system. Also, the stirrer system can be set to model mixing in the large reactor. The synthesis then can be conducted, using predicted conditions, with the reaction mixture being quenched and analyzed to verify that the expected yield of component C will be realized. If expected process results are not realized, then additional study will be required to determine the cause of the discrepancy between predicted and observed re-sults prior to proceeding with scale-up. This type of experimentation helps to minimize occurrences unpleasant surprises when processes are trans-ferred from the laboratory to the production plant. Summary and Conclusions Many of the tasks required to build and validate batch synthesis process models can be performed with laboratory-scale, computer assisted, stirred-tank reactors such as those described in this paper. All of the software required for batch synthesis process model building and simulation studies can reside in the desktop computer used to control the laboratory reactor. Thus, the laboratory investigator is not bound to expensive computer network hard-ware and/or software. Experiences of this author show that appropriate process modeling, simula-tion studies, and validation experimentation can provide, in an efficient, expedient manner, assur-ances that desired process results will be forthcom-ing upon transfer of laboratory processes to plant-scale equipment.Note: Work results reported in this paper and opin-ions expressed herein are those of the author and do not constitute endorsement by any Eastman Chemical Company organization of any of the hardware or software mentioned, nor do they con-stitute warranty of such items for fitness for any particular use.Literature Cited:1.Leach, J.T., The Role of Reaction Calorimetry in De-velopment and Use of Predictive Models of BatchOrganic Synthesis Processes, paper presented at the1992 USA Mettler RC1 User Forum, San Antonio,Texas, Oct. 5,1992.2.Leach, J.T., Ruggeri, S., Russell, R., and Younger, D.,Scale-up Techniques used at Arkansas Eastman, Pro-ceedings of the First International Conference onScale-up of Chemical Processes, Brighton, England, Sept. 1994.3.L each, J.T., Use of Laboratory Experimentation/BatchProcess Modeling, in Lieu of Pilot Plant Experiments, to Facilitate Scale-up – When is this Strategy Benefi-cial? Paper presented at the Spring AICHE Confer-ence in New Orleans, February 28, 1996; «Experi-mental Strategies for Pilot Plants» Session, No 138 4.Bisio, A. and Kabel, R.L. Scale-up of Chem. Pro-cesses, John Wiley & Sons, New York, 1985, pp 313, 325.5.Seider, E.N. and Tate, G.E., Ind. Eng. Chem.,281429 (1946).6.NIST Standard Reference Database 25, National In-stitute of Standards and Technology, Gaithersburg,MD 208997.DIPPR Project 801 Data Base, American Institute ofChemical engineers’ Design Institute for PhysicalProperty Data (DIPPR).8.Simplex Optimization is a trademark ofWindowChem Software, Inc.REACTION Operating Manual, BatchCAD, Ltd., New Castle upon Tyne, UKRC1 is a trademark of Mettler-Toledo GmbH, CH-8603 Schwerzenbach, Switzerland.REACTION is a trademark of BatchCAD, Ltd., New Castle upon Tyne, UK.RATE is a trademark of BatchCAD, Ltd.ReactIR, Dicomp and QuantIR are trademarks of ASI Applied Systems, Inc., Millersville, MD 21108.Camile and Camile TG are trademarks of Sagian, Inc., Midland, MI.Microsoft, Windows and EXCEL are trademarks of Microsoft Corporation, USA.James T. LeachEastman Chemical CompanyKingsport, Tennessee 37662, USAThis lecture was held at the 8th RC User Forum in Hilton Head Island, South Carolina, USA, in October 1996. Mettler-Toledo GmbH,CH-8603 Schwerzenbach.Layout by Christian Rellstab.。

Origin of the Bathochromic Shift of Astaxanthin i

INTRODUCTION β-Crustacyanin (β-Cr) counts among the most studied carotenoproteins owing to its unique and intriguing optical properties.1−6 It is the basic building block of the pigment protein complex α-crustacyanin (α-Cr), which is responsible for the coloration of lobsters and other blue-black crustaceans. Xray crystallography investigations have revealed that β-Cr binds two astaxanthin (AXT) molecules at a minimum intermolecular distance of 7 Å.2 Upon binding to the protein, the absorption maximum shifts from 480 to 490 nm for the carotenoids in solution to ∼580 nm, corresponding to a bathochromic shift of 4000 cm−1(Figure 1).1 In nature, β-Crs aggregate into an octamer named α-Cr, which has absorption shifted even further to 630 nm. A number of theoretical and experimental studies have addressed the issue of the bathochromic shift in β-Cr and the mechanism of coloration of the crustaceans.1−6 However, biochemical and some quantum chemical investigations favor distinctly diﬀerent explanations for the shift. The proposed mechanisms can be divided into three groups. The ﬁrst mechanism is the resonance coupling between the two AXT molecules in β-Cr. The coupling is mediated by large transition dipole moment of the carotenoids as well as by the