当前位置：文档之家› Dust Masses, PAH Abundances, and Starlight Intensities in the SINGS Galaxy Sample

Dust Masses, PAH Abundances, and Starlight Intensities in the SINGS Galaxy Sample

a r

s t

r o

To appear in The Astrophysical Journal

Dust Masses,PAH Abundances,and Starlight Intensities in the SINGS Galaxy Sample B.T.Draine 1,D.A.Dale 2,G.Bendo 3,K.D.Gordon 4,J.D.T.Smith 4,L.Armus 5,C.W.Engelbracht 4,G.Helou 6,R.C.Kennicutt 4,7,A.Li 8,H.Roussel 9,F.Walter 9,D.Calzetti 10,J.Moustakas 4,11,E.J.Murphy 12,G.H.Rieke 4,C.Bot 6,D.J.Hollenbach 13,K.Sheth 6,and H.I.Teplitz 5ABSTRACT Physical dust models are presented for 65galaxies in the SINGS survey that are strongly detected in the four IRAC bands and three MIPS bands.For each galaxy we estimate (1)the total dust mass,(2)the fraction of the dust mass contributed by PAHs,and (3)the intensity of the starlight heating the dust grains.We ?nd that spiral galaxies have dust properties resembling the dust in the local region of the Milky Way,with similar dust-to-gas ratio,and similar PAH abundance.The observed SEDs,including galaxies with SCUBA photometry,can be reproduced by dust models that do not require “cold”(T 10K)dust.The dust-to-gas ratio is observed to be dependent on metallicity.In the interstel-lar media of galaxies with A O ≡12+log 10(O /H)>8.1,grains contain a substantial

fraction of interstellar Mg,Si and Fe.Galaxies with A O<8.1and extended H I en-

velopes in some cases appear to have global dust-to-gas ratios that are low for their

measured oxygen abundance,but the dust-to-gas ratio in the regions where infrared

emission is detected generally appears to be consistent with a substantial fraction of

interstellar Mg,Si,and Fe being contained in dust.The PAH index q PAH–the frac-

tion of the dust mass in the form of PAHs–correlates with metallicity.The nine

galaxies in our sample with A O<8.1have a median q PAH=1.0%,whereas galaxies

with A O>8.1have a median q PAH=3.55%.The derived dust masses favor a value

X CO≈4×1020cm?2(K km s?1)?1for the CO to H2conversion factor.Except for some

starbursting systems(Mrk33,Tolo89,NGC3049),dust in the di?use ISM dominates

the IR power.

Subject headings:ISM:dust,extinction—ISM:general—galaxies:abundances—

galaxies:general—galaxies:ISM—infrared:galaxies

1.Introduction

Interstellar dust a?ects the appearance of galaxies,by attenuating short wavelength radiation from stars and ionized gas,and contributing infrared(IR),far-infrared(FIR),submm,mm,and microwave emission[for a recent review,see Draine(2003)].Dust also is an important agent in the ?uid dynamics,chemistry,heating,cooling,and even ionization balance in some interstellar regions, with a major role in the process of star formation.Despite the importance of dust,determination of the physical properties of interstellar dust grains has been a challenging task–even the overall amount of dust in other galaxies has often been very uncertain.

The SINGS galaxy sample(Kennicutt et al.2003)comprises75galaxies with a wide range of morphological types,all at distances allowing the galaxies to be resolved even at160μm.Ob-servations of this sample with all instruments on Spitzer Space Telescope(Werner et al.2004)are providing a new perspective on the dust abundances and dust properties in a diverse set of galaxies.

For67of the SINGS galaxies we have positive detections in the4bands of the Infrared Array Camera(IRAC;Fazio et al.(2004))and the three bands of the Multiband Imaging Photometer for Spitzer(MIPS;Rieke et al.(2004)),spanning wavelengths from3.6μm to160μm,the wavelength range within which dust radiates most of its power,including the PAH emission features that are prominent in many galaxies;65of these galaxies are used in the present study.For11galaxies we have global?uxes measured with the IRS16μm peak-up?lter.For17of the65galaxies,global 850μm?ux measurements are also available from the SCUBA camera on the JCMT.

The IR emission from dust depends not only on the amount of dust present,but also on the rate at which it is heated by starlight.We develop a technique for estimation of dust masses and starlight intensities in galaxies,and apply it to estimate the total dust mass M dust in each of the65

galaxies in this study.For61galaxies we are also able to estimate a“PAH index”q PAH–de?ned

here to be the mass fraction of the dust that is contributed by polycyclic aromatic hydrocarbon

(PAH)particles containing<103C atoms.In addition,we obtain information on the starlight

intensity distribution–the mean starlight intensity scale factor U ,and the fraction of the dust

heating that takes place in regions of high starlight intensities,including photodissociation regions.

The paper is organized as follows.The sample selection and observational data are summarized

in§2,the physical dust models that are used are described in§3,and the model-?tting procedure

is given in§4.In order to validate the model-?tting procedure,we?rst limit attention to the

subset of SINGS galaxies for which SCUBA data are available(we will refer to these as the SINGS-

SCUBA galaxies).In§5we demonstrate that the dust modeling procedure works well for most

of the SINGS-SCUBA galaxies,and we present dust masses,dust-to-gas mass ratios,PAH index

values,and starlight intensity parameters obtained from these model?ts.For the SINGS-SCUBA

galaxies,our models do not require any contribution from the very cold(<10K)dust that has been

reported by Krugel et al.(1998)for the spiral galaxies NGC6156and NGC6918,or the5–9K

dust that Galliano et al.(2003,2005)reported for low metallicity dwarf galaxies,or the4–6K dust

that Dumke et al.(2004)reported for the edge-on-spiral NGC4631.The global SEDs do not show

evidence for the submillimeter excess seen in the faint outer regions of NGC4631(Bendo et al.

2006b).

Submillimeter measurements are valuable to help constrain the dust models,but are unfor-

tunately not available for most galaxies.In§6we use the SINGS-SCUBA galaxies to develop a

“restricted”?tting procedure that can be applied to galaxies for which submillimeter?uxes are un-

available.For the17galaxies with global850μm?uxes from SCUBA,we show that the restricted

?tting procedure,without employing SCUBA data,recovers dust masses and starlight intensities

that are usually within a factor of two of the values obtained when the SCUBA data are used.

The restricted?tting technique is then applied to the remaining48galaxies to estimate dust

masses and starlight intensities.Dust-to-gas mass ratios for the overall sample are presented in

§7.1,where it is found that some of the SINGS galaxies have very low dust-to-gas ratios,and that the dust-to-gas ratios are correlated with both gas-phase metallicity and galaxy type.The

dust-to-gas ratios depend on the assumed value of X CO,the ratio of H2column density to CO

line intensity;in§9.4we argue that the distribution of derived dust-to-gas ratios supports X CO≈4×1020cm?2(K km s?1)?1.

Values of the PAH index q PAH are estimated for61galaxies in§7.4.Many galaxies are found

to have low values of q PAH,and q PAH is found to be strongly correlated with gas-phase metallicity.

The starlight parameters for the65galaxy sample are presented and discussed in§8.The results

are discussed in§9,and summarized in§10.

2.Data

2.1.IRAC and MIPS

Spitzer Space Telescope was used to observe all75galaxies in the SINGS sample,following the observing strategy described in Kennicutt et al.(2003).The observations in the4IRAC bands(3.6, 4.5,5.7,7.9μm)and3MIPS bands(24,71,160μm)have been reduced following the procedures described in Dale et al.(2005).The extended source aperture corrections found in Reach et al. (2005)were applied to the IRAC data.Global IRAC and MIPS photometry for these galaxies is taken from Dale et al.(2007),which included(usually modest)corrections for aperture size and nonlinearity of the71μm detectors.

Ten of the SINGS galaxies were excluded from the present study:

?NGC584(E4)may be contaminated by a background source,and also has low surface brightness in the MIPS bands compared to the foreground cirrus.

?NGC3034=M82(I0,starburst):Saturation of the bright core of this galaxy precludes global photometry.

?NGC1404(E1):An o?-center IR source contributes a signi?cant fraction of the MIPS?ux, but it is not known whether or not it is a foreground/background object.

?NGC4552(E0)has low surface brightness compared to the foreground cirrus emission,and the MIPS160μm photometry is very uncertain.

?The dwarf galaxies M81dwA and Ho IX are not detected atλ≥5.8μm.

?The dwarf galaxies DDO154and DDO165are only marginally(<3σ)detected at71and 160μm,and M81dwB is a<2σdetection at160μm.

?The dwarf starburst galaxy NGC1377shows strong silicate absorption at9.8μm and18μm (Roussel et al.2006).The objective of the present study is to model the IR spectra using a simple model that assumes the galaxy to be optically-thin atλ>3.5μm;because NGC1377 is clearly not optically thin,it has been removed from the sample.

The sample studied here therefore consists of65galaxies.MIPS71μm photometry for NGC7552 is not usable because of detector saturation,but NGC7552is retained in the sample because it is well-observed at other wavelengths and with other instruments.

Most of the dust mass in galaxies is relatively cool,radiating primarily at wavelengths in the MIPS71μm and160μm bands.Dust grains that are warmer,either because they are in regions with intense starlight,or because they are very small grains immediately following absorption of a stellar photon,may radiate strongly in the MIPS24μm band and shortward.The variety of dust

Fig. 1.—MIPS color-color plot for the65galaxies.The blue shaded area shows the region sampled by the17 galaxies for which global SCUBA?uxes are known(plotted as blue solid symbols)–these only partially cover the color-color space populated by the SINGS sample(green shaded area).Galaxies without SCUBA?uxes are shown in red.Galaxies with relatively extreme?ux ratios are labelled.

conditions found in the SINGS sample is evident from the distribution of the64galaxies in MIPS color-color space,shown in Figure1: νFν 71μm/ νFν 160μm varies by over a factor of10within our sample,and νFν 24μm/ νFν 71μm varies by a factor of8.These variations in MIPS colors presumably re?ect galaxy-to-galaxy di?erences in the intensity of the starlight heating the dust grains,although galaxy-to-galaxy di?erences in dust composition may also play a role.It is evident from the scatter in Figure1that the MIPS24/71color is not simply a function of the71/160color: the MIPS colors cannot be described by a one-parameter sequence of,e.g.,“dust temperature”. Realistic dust models will therefore need to vary at least two parameters to account for the range in observed MIPS colors.

The SINGS sample does not include any powerful AGN,and in all SINGS galaxies the global ?ux in the IRAC3.6μm band is starlight-dominated.Neglecting extinction,we can estimate the “nonstellar”?ux in longer-wavelength bands by subtracting the estimated stellar contribution, assuming a5000K blackbody.For IRAC band4,the IRS16μm Peakup band(see§2.2below)and

the MIPS24μm band,the nonstellar?uxes are:

F nsν 7.9= Fν 7.9?0.260 Fν 3.6,(1)

F nsν 16= Fν 16?0.0693 Fν 3.6,(2)

F nsν 24= Fν 24?0.0326 Fν 3.6.(3) The coe?cients0.260and0.0326in eq.(1)and(3)are close to the values0.232and0.032estimated by Helou et al.(2004).Some stars(e.g.,cool red giants,and AGB stars)have circumstellar dust that is in many cases warm enough to radiate strongly at wavelengths from8-30μm.If such stars are su?ciently numerous,the result will be a“stellar”contribution to the8,16,and24μm?uxes that will be larger than assumed in eq.(1–3).In the absence of extinction at3.6μm,equations (1–3)will therefore overestimate the?ux contributed by interstellar dust.

2.2.IRS16μm

In addition to IRAC and MIPS photometry,nine of the SINGS galaxies have been imaged using the IRS“blue peak-up”detector array,with nominal wavelengthλ=16μm.The IRS blue peak-up observations were taken as part of the IRS instrument calibration program and consist of a grid of peakup images covering the full extent of each galaxy.The reduced images,processed by IRS pipeline version S14,were mosaicked using the MOPEX program(ver.030106)to remove cosmic rays after subtraction of a custom dark image.This custom dark image was created using images taken beyond the visible extent of the galaxy.In some cases,the best dark subtraction was found to require allowing the dark image to vary with time.“Sky”(zodiacal light and Galactic cirrus)contributions were also removed by this custom dark subtraction step.The total16μm?ux was measured using the same methods used for the IRAC and MIPS?uxes(Dale et al.2005).The measured global?uxes were then scaled down by～15%,to account for a recent SSC calibration update(～10%),and the appropriate aperture correction factor(～5%).Fluxes for these11galaxies at16μm and24μm are given in Table1.The?ux density ratio Fν 16/ Fν 24varies considerably among these galaxies,from a low of0.376±0.033for NGC7552to a high of1.21±0.12for NGC3190.

Figure2a shows P16≡ νF nsν 16/( νFν 71+ νFν 160)vs.P24≡ νF nsν 24/( νFν 71+ νFν 160) for the ten galaxies for which we have16,24,71,and160μm photometry,where F nsνis the nonstellar contribution from eq.(1-3).The?ux ratio P16remains essentially constant at P16≈0.112±0.017 while P24varies by almost a factor of3,from0.06to0.18.This suggests that the16μm?ux is not emitted by the same grains as the24μm?ux.In the dust model of Draine&Li(2007, hereafter DL07),a minimum level of24μm emission is produced by single-photon heating of PAHs or ultrasmall grains(with νLν 24/L TIR≈0.03?0.06,depending on q PAH–see Fig.15of DL07), but P24increases as the starlight intensity increases.Figure2a suggests that the16μm emission may be dominated by single-photon heating of PAHs,remaining relatively constant even as P24 rises due to increased starlight heating.This is supported by Figure2b,which shows that the ratio

Fig.2.—(a)P16≡ νF nsν 16/( νFν 71+ νFν 160)versus P24≡ νF nsν 24/( νFν 71+ νFν 160)for the10galaxies imaged with the IRS16μm peak-up?lter for which we also have global MIPS?uxes(NGC7552is excluded).(b) νF nsν 7.9/ νF nsν 16vs P24,Both the ratio of nonstellar16μm emission to total IR power and the ratio of nonstellar 7.9μm emission to nonstellar16μm emission remain constant to within～15%,even as P24varies by a factor of3. of7.9μm emission to16μm emission is nearly constant for this sample,varying by only～±15% over the eight galaxies,consistent with the idea that both are primarily the result of single-photon heating of PAHs.This is consistent with the?nding by F¨o rster Schreiber et al.(2004)that,when averaged over disks of spiral galaxies,the15μm continuum intensity is proportional to the PAH intensity in the5–8μm region.

Table1.Global Fluxes(Jy)in IRS16μm Peak-Up Band

galaxy Fν 16 Fν 24 Fν 16/ Fν 24

Jy Jy

2.3.SCUBA

The dust properties in a galaxy will be best determined if submillimeter photometry is available

to constrain the quantity of cool dust present.SCUBA observations at450μm and/or850μm are

available for26of the65galaxies,1but not all of these are usable in the present study:

1.NGC4254,NGC4579,NGC5194,and NGC6946were scan-mapped,and the data processing

removes an unknown amount of extended emission.Thus global850μm(or450μm)?uxes

are not available for these galaxies.We restrict ourselves to data obtained in“jiggle map”

mode,except for the scan-map observations of NGC5195,for which background subtraction

is thought to be more reliable because of the smaller angular extent of NGC5195.

2.For some galaxies the SCUBA map did not fully cover the region where160μm emission is

detected.Dale et al.(2005)multiplied the observed SCUBA?uxes by a correction factor

based on the fraction of the160μm emission coming from the region mapped by SCUBA.

Because the850μm/160μm?ux ratio may be spatially variable,we choose here to not use

the850μm?ux estimates for galaxies where the corrrection factor exceeds1.6(NGC1097,

NGC4321,NGC4736,and NGC5033).

3.For the Sombrero galaxy,NGC4594,the850μm?ux is dominated by the AGN(Bendo et al.

2006a),and the extranuclear850μm?ux is not reliably measured,so we cannot use the

SCUBA data to constrain the dust model for this galaxy.

We thus have17galaxies where the dust models are constrained by850μm SCUBA data(with

450μm?uxes for3of the17)in addition to IRAC and MIPS data.The global?uxes F obs,b and

1-σuncertainties for each band b are taken from Dale et al.(2007).

The162galaxies for which we have global SCUBA and MIPS photometry are indicated in

Figure1.While the galaxies with SCUBA photometry span a considerable portion of the populated

region in MIPS color-color space,a number of the SINGS galaxies have MIPS colors that are outside

of the range seen among the galaxies for which SCUBA data are available.For example,NGC4725

or NGC5408,with νFν 71μm/ νFν 160μm=0.33and3.1,respectively,fall outside the range0.6–2.4observed for this ratio among the SINGS-SCUBA galaxies.The dust models discussed below

are able to reproduce the IRAC and MIPS?uxes for all of the SINGS galaxies.Galaxies such as

NGC4725or NGC2841,with the lowest values of νFν 71μm/ νFν 160μm,require cooler dust(i.e., lower starlight intensities)than any of the SINGS-SCUBA galaxies.NCG5408,with a very high value of νFν 71μm/ νFν 160μm,requires hotter dust(higher starlight intensities).Submillimeter observations would be of great value to test the predicted submm?uxes from these extreme cases.

2.4.IRAS and ISO

IRAS photometry is obtained from the latest SCANPI data for most SINGS sources,and from HiReS maps for the largest SINGS targets(optical diameters 10′),except in some bands(e.g., no IRAS12μm?ux for NGC0024).A20%calibration uncertainty estimate was applied.In the case of NGC5195(=M51b),the proximity of NCG5194(=M51a)made?ux determination more di?cult,and50%uncertainty estimates were adopted.

Ths IRAS25μm?ux densities are not used,as they are superseded by the MIPS24μm pho-tometry at essentially the same wavelength,but we employ the IRAS12μm,60μm,and100μm photometry in our model-?tting.

When available,we show ISOCAM6.75μm and15μm photometry in the?gures showing the spectral energy distributions(SEDs),but they are not used in the model-?tting.

3.Physical Dust Models

A direct estimate for the dust-to-hydrogen mass ratio M dust/M H in the local Milky Way can be obtained from the di?erence between total interstellar abundances–taken to be equal to current estimates for solar abundances–and observed gas phase abundances in di?use interstellar clouds, where the intensively studied di?use cloud on the line-of-sight toζOph is taken to be representative. Using current estimates of solar abundances,this mass inventory results in M dust/M H≈0.0073 (see Table2).

We will apply(and thereby also test)the dust models developed by Weingartner&Draine (2001a,hereafter WD01)and Li&Draine(2001,hereafter LD01),and updated by DL07.These dust models consist of speci?ed mixtures of carbonaceous grains and amorphous silicate grains,with the smallest carbonaceous grains having the physical properties of polycyclic aromatic hydrocarbon (PAH)particles;the size distributions are chosen to reproduce the observed wavelength-dependent extinction in the local Milky Way,in the Large Magellanic Cloud,and the Small Magellanic Cloud bar region(Weingartner&Draine2001a).Li&Draine(2001,2002)showed that these grain models appeared to be consistent with the observed IR emission from di?use clouds in the Milky Way and the Small Magellanic Cloud.

The DL07dust models used here adopt PAH optical properties that are slightly di?erent from those adopted by LD01.As discussed by DL07,the changes are in part to better conform to recent theoretical estimates for band strengths,and in part to improve agreement with band pro?les determined observationally by Smith et al.(2007).

The PAH emission features at3.3μm,6.2μm,7.7μm,8.6μm,11.3μm,12.0μm,12.7μm,16.4μm, and17μm are prominent in many galaxy spectra,and the dust models considered here include various abundances of PAHs;in each model the PAHs have a wide range of sizes.Because PAH

Table2.Dust Mass per H from Milky Way Abundances X(N X/N H)⊙(ppm)a(N X/N H)gas/(N X/N H)⊙a M X,dust/M H

total0.0073

Table3.Physical Dust Models

A V/N H

j M Model q PAH M dust/M a,b

%mag cm2/H

000.470.01005.3×10?22 2MW3.1

20 1.770.01015.3×10?22

4MW3.1

40 3.190.01025.3×10?22

6MW3.1

60 4.580.01045.3×10?22

8LMC2

05 1.510.003441.2×10?22

10LMC2

a M H≡M(H I+H2)

b M dust/M gas=[M dust/M H]/1.36

emission is mainly the result of single-photon heating,the PAH emission spectrum depends on the size(heat capacity)of the PAH.The prominent6.2μm,7.7μm,and8.6μm emission features are primarily due to PAHs with 103C atoms[see Fig.7of Draine&Li(2007)].Following DL07, we characterize the PAH abundance by a“PAH index”q PAH,de?ned to be the percentage of the total grain mass contributed by PAHs containing less than103C atoms:

q PAH≡M(PAHs with N C<103)

starlight in such regions implies that the dust grains located there radiate only a very small fraction of the total IR power.As will be seen below,an ice-free dust model appears to be satisfactory for modeling the IR emission from normal galaxies.

4.Constraining the Dust Model and Starlight Intensities

In addition to choosing a physical dust mixture(relative numbers of carbonaceous grains and silicate grains of di?erent sizes,including the fraction q PAH of the dust mass that is in PAHs), we must specify the intensity of the radiation that is heating the dust grains.Almost all of the heating of dust grains in a normal galaxy is from absorption of hν<13.6eV photons.In a normal star-forming galaxy a signi?cant(but sub-dominant)fraction of the stellar luminosity may be at hν>13.6eV,but most of these photons end up photoionizing hydrogen or helium rather than being absorbed by dust.The hν<13.6eV recombination radiation–especially Lymanα–may be largely absorbed by dust.However,the total power in ionizing photons is a minor fraction of the total stellar luminosity in a galaxy with a more-or-less steady rate of star formation.Only in galaxies that have undergone an extreme burst of star formation within the last～107yrs will the dust heating be dominated by Lymanαand Lyman continuum radiation.Only in rare cases,e.g., NGC1377(Roussel et al.2006),where the massive stars formed in a starburst are surrounded by dense,dusty H II regions,will the dust grains directly absorb a major fraction of the hν>13.6eV radiation.

The IR emission from dust is relatively insensitive to the detailed spectrum of the hν<13.6eV photons,and the DL07models simply adopt the spectrum of the local interstellar radiation?eld as a reasonable representation for the average spectrum of the interstellar radiation in a normal spiral galaxy.The speci?c energy density of starlight is therefore taken to be

,(5)

uν=U×u(MMP83)

where u(MMP83)

νis the speci?c energy density estimated by Mathis et al.(1983)(hereafter MMP83) for the local Galactic interstellar radiation?eld,and U is a dimensionless scale factor.The intensity of interstellar UV radiation is often characterized by G0,the ratio of the6–13.6eV energy density relative to the value5.288×10?14ergs cm?3for the radiation?eld estimated by Habing(1968). The MMP83ISRF has u(0?13.6eV starlight)=8.65×10?13ergs cm?3,and u(6?13.6eV)= 6.01××10?14ergs cm?3.Thus U=0.88G0.

Dust at di?erent locations in the galaxy will be exposed to di?erent radiation intensities.A physically correct model would specify the locations of the stellar sources and the absorbing dust, and would solve the radiative transfer problem[e.g.,Tu?s et al.(2004)],but this would require many uncertain assumptions about the relative distributions of stars and dust,as well as massive numerical computations.

Following DL07,we suppose that a large fraction of the dust in a galaxy is located in the

di?use interstellar medium,exposed to starlight with an intensity that does not vary much within

the galaxy.This“di?use ISM”dust is idealized as being heated by a single radiation?eld,with

intensity factor U=U min.In addition,DL07suppose that a small fraction of the dust is located

in regions where the radiation?eld is more intense,with a wide range of intensities ranging from

U=U min to U=U max?U min.This would include dust in photodissociation regions,so we refer to this as the“PDR”component,and we use the power-law distribution function used by DL07.

Although this“PDR”component contains only a small fraction of the total dust mass,in some

galaxies it contributes a substantial fraction of the total power radiated by the dust.The models

do not include a component corresponding to cold dust in dark clouds;as discussed in§9.1,such

cold dust appears to account for a minor fraction of the dust mass,and a very small fraction of the

total dust luminosity.Thus,following DL07,we take the dust mass dM dust exposed to radiation

intensities in[U,U+dU]to be a combination of aδfunction and a power-law,

dM dust

U1?α

min?U1?αmax U?αfor U min≤U≤U max,α=1(6)

whereδis the Diracδfunction.This distribution function has?ve parameters:the total dust mass M dust,the fractionγof the dust mass that is associated with the power-law part of the starlight intensity distribution,and3parameters(U min,U max,α)characterizing the distribution of starlight intensities in the high intensity regions.Theδ–function term represents the fraction (1?γ)of the dust that is heated by a general di?use interstellar radiation?eld with approximately uniform intensity～U min.The power-law part of the distribution function,introduced by Dale et al. (2001)and used by Li&Draine(2002),represents the fractionγof the dust mass that is close to OB associations and is exposed to radiation with intensity U>U min;this includes the dust in“photodissociation regions”(PDRs),where radiation intensities can be orders of magnitude higher than the“average”dust grain is exposed to.Equation(6)is a very simplistic description of the distribution of dust grain environments;it neglects the possibility that the dust properties (composition,size distribution)might be variable and correlated with U,and also neglects regional variations in the spectrum of the starlight irradiating the dust.Despite its simplicity,we will see here that eq.(6)appears to capture the essential elements of the distribution of starlight intensities found in galaxies,yielding models with SEDs that approximate what is observed.

Very small particles cool almost completely between photon absorptions,and therefore the shape of the emission spectrum from these grains is almost independent of U.The larger grains, that account for more than half of the total absorption of starlight in the Milky Way,do not cool signi?cantly between photon absorptions,and their temperature depends on the intensity U. The observed FIR emission spectrum is sensitive to the temperature of these larger grains,and therefore allows us to constrain the distribution function for U.While Spitzer Space Telescope provides unprecedented sensitivity to FIR emission,the spectral coverage is somewhat sparse,with

a factor of3gap in wavelength between IRAC7.9μm and the MIPS24μm bands,and a factor of

2.9gap between the MIPS24μm and71μm bands.The IRS“Peak-Up”mode observations can be used for imaging at16μm and26μm,but these observations are not generally available.The large

gaps in wavelength coverage leave considerable uncertainty in the spectral energy distribution at wavelengths between the bands.3Furthermore,the longest wavelength band,at160μm,falls on the short wavelength side of the emission peak for dust temperatures T d (1/6)hc/(160μm)=15K.As a result,Spitzer photometry does not strongly constrain the abundance of dust with temperatures T d 15K.To determine the amount of cool dust,global submillimeter observations are required. Fortunately,such data exist for17of the65galaxies for which we have complete Spitzer photometry (or near-complete in the case of NGC7552),and this subsample will be analyzed?rst,in§5.

We select a model for the IR emission from a galaxy as follows.For each size and composition of dust,we precompute and tabulate the temperature distribution function for the dust grain illuminated by the radiation?eld of eq.(5)for selected values of U(with0.1≤U≤107),using heat capacities,absorption cross sections,and numerical methods described by Draine&Li(2001), LD01,and DL07.Neutral and ionized PAHs are assumed to have di?erent absorption cross sections. The ionized fractionφi(N C)(a function of the number N C of carbon atoms in the PAH)will depend primarily on the ratio U

√

T e/n e as the Milky Way).Our model-?tting procedure assumes that all galaxies have the same shape for the PAH size distribution,the same PAH ionized fraction φi(N C),and the same spectral shape of the illuminating starlight.As a result,our model?ts have ?xed ratios of PAH emission band strengths.Observations do reveal variations in PAH band ratios from one galaxy to the next–for example,L(7.7μm)/L(11.3μm)varies from～4–5to 0.7as we progress from H II-dominated nuclei to AGN-dominated nuclei(Smith et al.2007),and low values of L(7.7μm)/L(11.3μm)are also seen in some AGN-free galactic and extragalactic regions(e.g., Reach et al.2000;Hony et al.2001;Pagani et al.1999)–but most spiral galaxies have global PAH feature ratios that are near-average and characteristic of star-forming regions.

With these temperature distribution functions for the dust,and the dust absorption cross section C abs(λ),we can calculate the time-averaged IR emission for a given grain type and size for each of the discrete values of U considered;we then sum over the grain types and sizes for a dust model j M(see Table3)to?nd the power radiated per unit frequency per unit mass of dust mixture j M exposed to starlight intensity U:

p(0)ν(j M,U)=1

da j M

dT dP(k,a)

3In principle,the IRS instrument can provide6–36μm photometry,and the MIPS SED mode covers55–95μm, but observing time considerations preclude using these observing modes for large areas.

4Following LD01,we assume43%of the dust to be in the“cold neutral medium”(CNM;n e/U≈0.045cm?3, T≈100K),43%to be in the“warm neutral medium”(WNM;n e/U≈0.04cm?3,T≈6000K),and14%to be in the“warm ionized medium”(WIM;n e/U≈0.1cm?3,T≈8000K).The resultingφi(N C)is shown in Fig.7of LD01 and Fig.8of DL07.

M(j M)≡ k da dn k3ρk,(8)

where the sum runs over the di?erent grain types k(amorphous silicate,graphite,PAH0,PAH+) in the DL07dust model,withρk the density of material k,and n k(a)being the number of dust grains of type k per H nucleon,with radii≤a.

We also calculate the speci?c power per unit dust mass

(α?1)

pν(j M,U min,U max,α)≡

4πD2 (1?γ)p(0)ν(j M,U min)+γpν(j M,U min,U max,α) ,(10) where??is the solid angle subtended by the stars.For each(j M,U min,U max,α),we obtain??, M dust,andγby minimizing

χ2≡ b[F obs,b? Fν,model b]2

For the MW dust models,there are e?ectively7adjustable parameters:??,M dust,q PAH(via

j M),γ,U min,U max,andα.However,we will?x one of these parameters from the outset,by setting

α=2.This choice is based on experimentation that indicated that the quality of the?t is not

very sensitive to the precise value ofα,withα≈2providing satisfactory?ts for diverse galaxies.

Therefore we start with6parameters to be adjusted.For the galaxies with SCUBA data,we will

examine the e?ects of varying U max,but we will see in§5.4.2that setting U max=106works well;

therefore,the number of adjustable parameters is,e?ectively,5:??,M dust,q PAH,U min,andγ.

If the number of observed bands is N b,the number of degrees of freedom=(N b?5)where N b ranges from N b=9(e.g.,NGC0024,with4IRAC bands,3MIPS bands,and IRAS60,100μm)to

N b=12(e.g.,NGC3190with4IRAC bands,3MIPS bands,IRS16μm,IRAS12,60,100μm,and

SCUBA850μm).To assess the goodness of?t,we calculateχ2per degree of freedom:

χ2r≡χ2

Fig.3.—(a)SED for the SAap galaxy NGC3190.Rectangles show observed?uxes in the IRAC,MIPS,SCUBA bands,and the IRS16μm band;diamonds show2MASS2.2μm,and IRAS12,60,and100μm,?uxes.Vertical extent of rectangles and diamonds corresponds to±1σrange,and width corresponds to nominal width of band.Solid line shows best-?t model U max=106model,with IRAC,MIPS,IRS16μm,IRAS,and SCUBA data used to constrain the ?t;N b=12for NGC3190.Triangles show model convolved with the IRAC,MIPS,IRS16μm,IRAS,and SCUBA bands.Dot-dashed curves show separate contributions of starlight and emission from dust heated by U=U min (labelled“di?”),and dust heated by U min

The models are generally very successful in?tting the observed SEDs.The SED of NGC3190,

together with a model?t,appears in Figure3a.This is an example where the model(with U min=

2.5,U max=107,γ=1.5×10?3)provides an excellent?t to the observations,withχ2r=0.38.

The inferred dust mass is M dust=107.19M⊙,and the mean starlight intensity is estimated to be

U =2.6.Only a small fractionγ≈0.0015of the dust is in regions with starlight intensities U>U min.Also shown in Figure3a(solid line)is a?t with the upper cuto??xed at U max=106.

The model SED is nearly identical(the solid curve and dash-dot curves coincide in the plot)and

the derived dust mass is unchanged.

Figure3b shows the SED of NGC2798,a galaxy where the dust is considerably warmer than

in NGC3190.The best-?t dust model(U min=8,U max=105,γ=0.09)provides a good?t

(χ2r=0.45)to the observations,but the model with U max=106provides nearly as good a?t

(χ2r=0.46),a derived dust mass di?ering by only0.04dex,and similar q PAH(2.0%vs.2.5%).

The model?ts to NGC2798both have a noticeable“bump”near～33μm,produced by

the warm graphite grains in the DL07model.The small but nonzero conductivity for E c in

graphite5causes the absorption cross section C abs to rise to a broad local maximum near～33μm

(Draine&Lee1984,DL07).When exposed to starlight with U 104,graphite grains produce a broad emission bump peaking in the30–35μm region,depending on U.Unfortunately,the MIPS 24μm and71μm bands straddle this feature,and do not constrain it.Implications of the model 33μm feature are discussed below in§9.3.

Fig.4.—Histograms of M dust/M(H I+H2)for the12galaxies in the sample for which both H I21cm and CO1-0 have been measured,using X CO=4×1020cm?2(K km s?1)?1to estimate M(H2).

5.2.Dust-to-Gas Ratio

If the interstellar abundances of carbon and all heavier elements were proportional to the gas-phase oxygen abundance,and if the same fraction of the major condensible elements(C,O,Mg, Si,Fe)were in solid form as in the Milky Way,then all galaxies would be expected to conform to

M dust

,(13)

(O/H)MW

where(O/H)MW is the oxygen abundance in the local Milky Way,and the factor0.010is from the MW dust models in Table3.

Table4gives the estimated dust mass M dust for the17galaxies.For many of the galaxies there are measurements of21cm emission and CO emission from which the masses of H I and H2

空调自控系统方案设计(江森自控)

沈阳利源轨道交通设备有限公司暖通空调自控系统项目 HVAC暖通空调自控系统技术方案设计书

一. 总体设计方案根据用户对项目要求，并结合沈阳建筑智能化建筑现状，沈阳利源轨道交通装备有限公司暖通空调自控系统项目是屹今为止整个沈阳所有建筑物厂区当中智能化程度要求较高的。沈阳利源轨道交通装备有限公司暖通空调自控系统项目里面分布着大量的暖通空调机电设备。？如何将这些暖通空调机电设备有机的结合起来，达到集中监测和控制，提高设备的无故障时间，给投资者带来明显的经济效益；？如何能够使这些暖通空调机电设备经济的运行，既能够节能，又能满足工作要求，并在运行中尽快的将效益体现出来；？如何提高综合物业管理综合水平，将现代化的的计算机技术应用到管理上提高效率。这是目前业主关心的也是我们设计所侧重的。沈阳利源轨道交通装备有限公司暖通空调楼宇自动化控制系统的监测和控制主要包括下列子系统：冷站系统空调机组系统本暖通空调楼宇自动化控制系统之设计是依据沈阳利源轨道交通设备有限公司暖通空调自控系统项目的设计要求配置的，主体的设计思想是结合招标文件及设计图纸为准。 1.1冷站系统（1）控制设备内容根据项目标书要求，暖通自控系统将会对以下冷站系统设备进行监控：监控设备监控内容冷却水塔（2台）启停控制、运行状态、故障报警、手自动状态。冷却水泵（2台）启停控制、运行状态、故障报警、手

自动状态、水流开关状态；冷却水供回水管路供水温度、回水温度，冷水机组（2台）启停控制、运行状态、故障报警、手自动状态；冷冻水泵（2台）启停控制、运行状态、故障报警、手自动状态、水流开关状态；冷冻水供回水管路供水温度、回水温度、回水流量；分集水器分水器压力、集水器压力、压差旁通阀调节；膨胀水箱高、低液位检测；有关系统的详细点位情况可参照所附的系统监控点表。（2）控制说明本自控系统针对冷站主要监控功能如下：监控内容控制方法冷负荷需求计算根据冷冻水供、回水温度和回水流量测量值，自动计算建筑空调实际所需冷负荷量。机组台数控制根据建筑所需冷负荷自动调整冷水机组运行台数，达到最佳节能目的。独立空调区域负荷计算根据Q=C*M*(T1-T2) T1＝分回水管温度，T2＝分供水总管温度， M＝分回水管回水流量当负荷大于一台机组的15%，则第二台机组运行。机组联锁控制启动：冷却塔蝶阀开启，冷却水蝶阀开启，开冷却水泵，冷冻水蝶阀开启，开冷冻水泵，开冷水机组。停止：停冷水机组，关冷冻泵，关冷冻水蝶阀，关冷却水泵，关冷却水蝶阀，关冷却塔风机、蝶阀。冷却水温度控制根据冷却水温度，自动控制冷却塔风机的启停台数，并且自

最全的全国各大医学院临床专业介绍

一、东北地区黑龙江、吉林、辽宁 1.中国医科大学：中国医科大学虽以“中国”命名，但现在实力更应该被称为“东北医科大学”，是原卫生部部署院校。国家重点学科5个，2012年学科评估临床得分77，参评院校里十名出头，东北第一。一附院排名全国16，皮肤，呼吸，内分泌，放射全国前十，是东北医院里排名最靠前的。盛京医院32，儿外(全国第3)，儿内，妇产，放射全国前十。 2.哈尔滨医科大学：学科评估临床75分，东北第二，可能是全国夏天最凉快的医学院校了，由中国首个获得诺贝尔奖提名的医学家伍连德所建立。国家重点学科两个。国内首家医学院校全球医学教育认证试点性评估单位。一附院排名52，其中神经外科前十，肿瘤医院的肿瘤全国第八。 3.吉林大学白求恩医学院：学科评估74分，原卫生部部署。国家重点学科两个。一附院全国44，神内第七。貌似是被合并拖累的名校，白求恩的知名校友一大堆，全国很多著名的医院里的有名专家都是白求恩毕业的，但现在发展反而成为东北医学院校三巨头最差的，但也因此得到985身份，倒是一种补偿。 4.大连医科大学：在东北经济最好的海滨城市大连，国家重点学科一个，学科评估69，东北第四。一附院情况：博士生应用导师名，卫生部专科医师培训首批试点基地国家药物临床试验基地卫生部“冠心病介入诊疗培训基地”和“心律失常介入诊疗培训基地”卫生部骨科内镜诊疗技术培训基地中华医学会介入治疗推广培训基地中华医学会中华国际医学交流基金会头痛中心欧洲皮肤病性病学会国际视窗交流项目中国中心中华医学会中国医师协会胃肠动力研究中心暨培训基地全国准分子激光手术培训基地全国先天性唇腭裂治疗中心。 5.延边大学医学院：硕士生导师97人，博士生导师4人，学科评估64。附属延边医院有7个硕士点。 6.辽宁医学院：学科评估64，5个联合博士点，7个一级学科硕士点，63个二级学科硕士点。一附院硕士(博)研究生导师146名，国家级冠心病介入培训基地。 7.佳木斯大学：2012学科评估63分。综合大学不好搜具体学院情况，因为基础医学院和附属医院的情况是分开的，学校网站上表示博士点快下来了。 8.北华大学。 9.大连大学医学院。注：综合性大学的医学院，招临床医学硕士院校详细情况比较难搜集，大家可以登录学信网查看。二、西北地区陕西、内蒙古、宁夏、甘肃、青海、新疆 1.第四军医大学：西北老大，没参加2012年临床医学的评估。有研究生院，211。国家重点学科19个(培育4个)，“长江学者奖励计划”特聘教授岗位学科12 个，国家重点实验室1个，全军医学重点建设实验室12个，全军重点建设学科专业领域3个，全军医学专科研究所13个，全军医疗专科(专病)中心19个，全军医学重点实验室12个。西京医院全国第五，消化(1)，整形(3)，麻醉，心外，风湿，皮肤，神外，病理，心血管，耳鼻喉全国前十。唐都第71，胸外第十。 2.西安交通大学医学院：原卫生部部署。2012评估74分。生理学、法医学、泌尿外科和皮肤性病学4个国家重点学科。3个教育部、卫生部重点实验室。一附

医学社会化与社会医学化的相互进程

医学社会化与社会医学化的相互进程随着社会经济的快速发展，人们因此越来越关心自己的健康，因此医学社会化与社会医学化问题越来越受到人们的关注。最为医学生我们应该全面、综合、整体地看待人类的健康和疾病问题，提高我们适应社会医学化要求的综合能力。下面我们从两个方面谈起：社会医学化是指原不属于医学的问题，从疾病或失调的角度，被纳入医学领域处置从而演变成了医学问题的过程。作为一种新的社会控制机制，医学化将某些偏常行为纳入医学治疗的范围，有助于维护社会稳定。随着社会发展，医学化已经扩展和渗透到了人类整个生命历程的各个方面，甚至“是正常的生活事件医学化”。难道科学技术发展了，医疗条件改善了，生活水平提高了，人们这样那样的疾病反而更多了？如果疾病较从前不是少了，而是多了，那么为什么人们的健康水平、人均寿命较从前大幅度提高了？看来，“社会医学化”另有原因。有认识方面的原因。正如人们对自然社会和人自身所知愈少，愈不以为自己无知，从前少听说这病那病，与从前的认识水平有关；如今人们在医学方面的认识深化了，从前尚未认识到的疾病现在认识到了，因此病也多起来了。在这个意义上说，不是病多了，而是病的名堂多了。也有生活本身的原因。随着生活的发展，从前没有的东西现在有了，相应地从前没有的病现在也有了。高楼大厦林立带来了建筑物综合征，信息爆炸带来了信息焦虑综合征，网络兴起才有了网络综合征……从前多少代单传实不多见，如今独生子女整整一代人，因此才会有独生子女就业综合征。所以说是时代的发展导致了这种情况，是人们健康观的转变。健康观，或者说有关健康与疾病的知识，应该是健康社会学研究的起点，但在医学化主导下的健康社会学研究，通常机械地使用了流行病学或社会医学中的个体健康观。这一分支的健康社会学家在讨论社会因素对健康的影响时，其着眼点实际上是社会环境对个体健康的影响，而不是社会的健康。这种“医学化”的视角忽视了健康观的政治经济因素，因而在研究中倾向于采用偏自然科学的卫生统计学和流行病学的方法。虽然这部分健康社会学家也关注生活方式等非医学因素对健康的影响，但是，他们只是简单地把生活方式视为一个个体可以自由选择的健康影响因素，认为健康社会学家的职责就是帮助人们作出正确的选择，采取健康的生活方式;而所谓“健康生活方式”的标准是由掌握健康科学技术的专家制定的，这些专家实际上被主流社会授权对人们的非健康的生活方式，即“越轨”行为进行矫治。医学化取向的健康社会学把这门学科推向了一种应用技术科学的方向，其健康技术主导和对社会生活中的医学化现象认同的态度，使得这门学科出现了远离社会学的趋势。但这些还仅仅是问题的一个方面，更重要的问题在于：什么引导着“生活医学化”的潮流？“生活医学化”，其要害是“化”，即把日常生活的方方面面“化”入医学范畴。那么，是谁推动着这种“化”的进程？当然是“化”的受益者们。首先是制药公司和医疗设备公司，他们因“生活医学化”而拓宽了市场，获得了实惠。其次是有关专家，他们因“生活医学化”而提高了自己的学术地位，增加了收入。再次是媒体，他们因“生活医学化”而吸引了广告客户，丰富了自身内容。为“生活医学化”潮流推波助澜的，还有各种各样的“患者”。媒体上宣传的各种疑难杂症，总有一些人具有或自认为具有其中的某些症状，也总有人自觉不自觉地对号入座，从而患上某种莫须有的疾病，把自己当成需要治疗的患者。这些虚构的病并不是真正的病，却给所谓病人及其家庭带来真正的痛苦。特别是“患者”，不断从一种病痛走向另一种病痛，生活的质量因而大打折扣，天长日久还真的会成为某种疾病的患者。其实即使有某种症状，也不一定非求医问药不可，也许不过是完全能自己处理的日常问题，在以前是不会当成病的。医学社会化则是社会发展的峦然趋势世纪90年代以来，社会发展观逐渐形成。社会发展观就是指在社会系统的协调运行过程中，以人为核心，以人为本，以满足人的需要、实现人的全面发展为目的的进步过程。无数事实已经证明，医学已经社会化。如，在2003年的防范“SARS”战斗中，首先是政府迅速审议和通过了《突发公共卫生事件应急条例草案)》，建立

空调自控技术方案

空调自控系统技术方案第1章. 总体设计说明建筑概况本项目（XXXXX有限公司整体迁扩建项目）位于浙江省杭州市，共有综合车间1及综合仓库、综合车间2、质检研发楼、前处理提取及仓库4个区域。工程设计资料暖通专业图纸采用的主要规范及标准（1）《智能建筑设计标准》（GB/T50314-2006）（2）《智能建筑工程质量验收规范》（GB50339-2003）（3）《民用建筑电气设计规范》（JGJ/T16-2008）（4）《公共建筑节能设计标准》（GB50189-2005）（5）《建筑设计防火规范》（GB50016-2006）（6）《低压配电装置及线路设计规范》（GBJ54-83）（7）《电气工程施工质量验收规范》（GB50303-2002）（8）《采暖、通风与空气调节设计规范》（GBJ19-87）（9）《分散型控制系统工程设计规定》（HG/T20573-95）（10）《低压配电装置及线路设计规范》（GBJ54-83）（11）《低压配电设计规范》（GB50054-95）

第2章. 设计范围空调自控系统冷热源系统、空调机组、新风机组、配套排风机/除尘机、室外温湿度、室内温湿度、室内静压、定风量阀、变风量阀第3章. 系统组成系统主要技术指标 1.本工程空调自控系统设计成一套完整的分布式集散控制系统，通过对厂房的空调机组、新风机组、配套排风机/除尘机组等主要机电设备的集中管理和分散控制，使之达到最佳运行状态，同时收集、记录、保存及管理各系统中重要信息及资料，实现综合自动监测、通讯、控制与管理，达到科学管理、节能管理及综合报警处理的目的，提高建筑物的现代化管理水平。 2.系统采用基于B/S（浏览器/服务器）的网络体系结构，系统网络协议符合国际标准 ISO16484-5(BACnet)。系统为两层网络结构，分别为管理层和控制层，两层网络均具有足够的开放性且应易于扩展，为将来运营和维护中可能发生的变化提供便利。 3.系统由服务器/工作站、网络控制引擎、现场控制器(DDC)等组成。服务器/工作站与网络控制引擎通过管理层网络采用BACnet/IP协议通讯，网络控制引擎作为管理层网络核心设备管理控制层网络并向服务器/工作站发布信息。控制层网络现场控制器通过RS-485现场总线连接到网络控制引擎上，采用BACnet MS/TP 协议与网络控制引擎及其他现场控制器保持紧密联系。传感器及执行器等连接至各现场控制器。 4.系统在控制中心配置服务器及工作站。操作系统支持Windows XP，系统配置打印机用于系统的报警及统计资料的打印。系统仅需在主控工作站上安装系统管理软件，无需在分控工作站上购买和安装特定的软件。 5.为满足管理要求，整个系统还可以让用户设任意多个工作站通过Web以共享方式访问，系统应支持至少5用户同时访问系统。 6.为保持系统稳定安全，系统数据存储不仅仅依赖于工作站电脑，工作站电脑因为故障

全国各医学院校情况速览简介

全国各医学院校情况速览东北地区（黑龙江，吉林，辽宁）： 1，首先是中国医科大学，中国医科大学虽以“中国”命名，但现在实力更应该被称为“东北医科大学”，是原卫生部部署院校。国家重点学科5个，2012年学科评估临床得分77，参评院校里十名出头，东北第一。一附院排名全国16，皮肤，呼吸，内分泌，放射全国前十，是东北医院里排名最靠前的。盛京医院32，儿外（全国第3），儿内，妇产，放射全国前十。2，哈尔滨医科大学，学科评估临床75分，东北第二，可能是全国夏天最凉快的医学院校了，由中国首个获得诺贝尔奖提名的医学家伍连德所建立。国家重点学科两个。国内首家医学院校全球医学教育认证试点性评估单位。一附院排名52，其中神经外科前十，肿瘤医院的肿瘤全国第八。 3，吉林大学白求恩医学院，学科评估74分，原卫生部部署。国家重点学科两个。一附院全国44，神内第七。貌似是被合并拖累的名校，白求恩的知名校友一大堆，全国很多著名的医院里的有名专家都是白求恩毕业的，但现在发展反而成为东北医学院校三巨头最差的，不过也因此得到的985的身份，倒是一种补偿。 4，大连医科大学，在东北经济最好的海滨城市大连，国家重点学科一个，学科评估69，东北第四。一附院情况：博士生应用导师名，卫生部专科医师培训首批试点基地国家药物临床试验基地卫生部“冠心病介入诊疗培训基地”和“心律失常介入诊疗培训基地”卫生部骨科内镜诊疗技术培训基地中华医学会介入治疗推广培训基地中华医学会中华国际医学交流基金会头痛中心欧洲皮肤病性病学会国际视窗交流项目中国中心中华医学会中国医师协会胃肠动力研究中心暨培训基地全国准分子激光手术培训基地全国先天性唇腭裂治疗中心。 5，延边大学医学院，硕士生导师97人，博士生导师4人，学科评估64。附属延边医院有7个硕士点。 6，辽宁医学院，学科评估64，5个联合博士点，7个一级学科硕士点，63个二级学科硕士点。一附院硕士（博）研究生导师146名，国家级冠心病介入培训基地。 7，佳木斯大学，2012学科评估63分。综合大学不好搜具体学院情况，因为基础医学院和附属医院的情况是分开的，学校网站上说博士点快下来了。 8，北华大学。 9，大连大学医学院。 PS:发现越到后边越难搜到详细信息，特别是综合性大学的医学院。不过还好有学信网，至少不会把招临床医学硕士的院校给漏了。二、西北地区（陕西，内蒙古，宁夏，甘肃，青海，新疆） 1，第四军医大学，西北老大，没参加2012年临床医学的评估。有研究生院，211。国家重点学科19个(培育4个)，“长江学者奖励计划”特聘教授岗位学科12 个，国家重点实验室1个，全军医学重点建设实验室12个，全军重点建设学科专业领域3个，全军医学专科研究所13个，全军医疗专科（专病）中心19个，全军医学重点实验室12个。西京医院全国第五，消化（1），整形（3），麻醉，心外，风湿，皮肤，神外，病理，心血管，耳鼻喉全国前十。唐都第71，胸外第十。 2，西安交通大学医学院，原卫生部部署。2012评估74分。生理学、法医学、泌尿外科和皮肤性病学4个国家重点学科。3个教育部、卫生部重点实验室。一附院65。二附院83，多个学科被评为国家重点学科和国家临床重点专科，数量居西北之首，骨外科、消化内科、临床专科护理、地方病科（地方性骨病、心肌病、碘相关及甲状腺疾病）、麻醉科、皮肤科、呼吸内科、耳鼻咽喉头颈外科、急诊医学科、中医科被评为卫生部临床重点专科。 3，新疆医科大学，2012评估临床69分。有2个一级学科博士学位授权点，25个二级学科

医学化学名字英文缩写大全

5-FU 5-氟尿嘧啶 5-HT 5-羟色胺 6-MP 6-巯基嘌呤 A/G 白球蛋白比率 ACD 酸性枸橼酸葡萄糖 ACP 酸性磷酸酶 ACTH 促肾上腺皮质激素 ADH 抗利尿激素 ADP 二磷酸腺苷 AFP 甲（种）胎（儿）蛋白 AHF 抗血友病因子 AKP 碱性磷酸酶 ALL 急性淋巴细胞性白血病 ALS 抗淋巴细胞血清 ALT(GPT) 丙氨酸转氨酶 AMA 抗线粒体抗体 AMI 急性心肌梗塞 AML 急性粒细胞性白血病 AMP 一磷酸腺苷 ANA 抗核抗体 APC 复方阿司匹林 AST(GOT) 天冬氨酸转氨酶 ATN 急性肾小管坏死 ATP 三磷酸腺苷 BCG 卡介苗 BCNU 卡氮芥 BMR 基础代谢率 BP 血压 BSA (1)牛血清白蛋白；(2)体表面积BSP 磺溴酞钠 BT 出血时间 BUN 血尿素氮 BV 血容量 C3 补体3 cAMP 环磷酸腺苷 CAPD 不卧床的持续性腹膜透析CB-1348 苯丁酸氮芥 CBG 皮质类固醇结合球蛋白CCNU 环己亚硝脲 CCU 冠心病监护病室 CEA 癌胚抗原 cGMP 环磷鸟苷 CIC 循环免疫复合物 CIEP 对流免疫电泳

CLL 慢性淋巴细胞性白血病 CML 慢性粒细胞性白血病 CMV 巨细胞病毒 CNS 中枢神经系统 CO2cp 二氧化碳结合力 CoA 辅酶A CO 心输出量 CPBA 竞争性蛋白结合分析 CPC 临床病理讨论会 CPK 肌酸磷酸激酶 cpm 每分钟计数 CSF 脑脊髓液 CT (1)电算机体层摄影；(2)血凝时间CVP 中心静脉压 DIC 播散性血管内凝血 DMSA 二巯基丁二酸 DNase 脱氧核糖核酸酶 DNA 脱氧核糖核酸 DNCB 二硝基氯苯 DOCA 醋酸脱氧皮质酮 dpm 每分钟衰变数 DSA 数字减影血管造影 DSS 登革休克综合征 DTPA 二乙三胺五乙酸 ECG;EKG 心电图 EDTA 乙二胺四乙酸 EEG 脑电图 EHF 流行性出血热 EIA 免疫酶法 ELISA 酶联免疫吸附试验 EMCP 肌电图 ENT 耳鼻咽喉 ERCP 逆行胰胆管造影 ESR 红细胞沉降率 FSH-RH 促卵泡素释放激素 FSH 促卵泡素 FT4I 游离甲状腺素指数 FT4 游离甲状腺素 GABA α-氨基丁酸 GH 生长激素 GTT 葡萄糖耐量试验 HAI;HI 血凝抑制试验 HAV 甲型肝炎病毒 HBcAg 乙型肝炎核心抗原

空调自控系统方案

空调自控系统方案 1概述 (3) 1.1建筑概况.......................................................................................... 错误!未定义书签。 1.2系统概述 (3) 1.2.1节电 (3) 1.2.2节省人力 (3) 1.2.3延长设备的使用寿命 (4) 1.2.4保证建筑及人身安全 (4) 2设计依据 (4) 2.1遵循标准 (4) 3系统设计及设备选型原则 (5) 3.1先进性与适用性 (6) 3.2成熟性 (6) 3.3开放性 (6) 3.4按需集成 (6) 3.5标准化 (6) 3.6可扩展性 (6) 3.7安全性与可靠性 (7) 3.8经济性 (7) 3.9追求最优化的系统设备配置 (7) 3.10保留足够的扩展容量 (7) 4系统监控范围及监控功能说明 (8) 4.1空调机组监控系统.......................................................................... 错误!未定义书签。 4.2排风机监控系统.............................................................................. 错误!未定义书签。 4.3给排水监控系统 (9) 4.4其他系统监控系统 (10) 5HONEYWELL系统解决方案 (10) 5.1概述 (10) 5.2HONEYWELL自控简介 (11)

5.3系统构成 (12) 5.4系统网络结构 (12) 5.5EBI楼宇中央管理系统 (14) 5.5.1概述 (14) 5.5.2EBI系统的特点 (15) 5.5.3操作界面 (16) 5.5.4数据报表 (16) 5.5.5控制算法 (17) 5.5.6实时数据库 (18) 5.5.7报警管理 (18) 5.5.8趋势图 (19) 5.5.9设备界面 (19) 5.5.10EBI系统结构 (21) 5.6E XCEL5000控制系统 (22) 5.6.1Excel5000是一套集散控制系统（TDS） (22) 5.6.2EXCEL 5000是一套开放的计算机网络系统 (23) 5.6.3EXCEL 5000系统保持向上兼容性 (23) 5.6.4Excel5000现场控制器（DDC） (23) 5.6.5带有LONBUS接口的 Excel500控制器 (24) 5.6.6Excel 100控制器 ...................................................................................... 错误!未定义书签。 5.6.7Excel 50 控制器 (26) 5.7末端装置(传感器、执行器等) (27) 5.7.1风门执行器 (27) 5.7.2座式调节型水阀门和执行装置 (28) 5.7.3低限温度装置(防冻开关） (28) 5.7.4继电器 (28) 5.7.5温度传感器 (28) 5.7.6压力传感器 (29) 5.7.7湿度传感器 (29)

地方病防治知识讲座

地方病防治知识宣传资料地方病是指某些在特定地域内经常发生并相对稳定，与地理环境中物理、化学和生物因素密切相关的疾病。地方病是指具有严格的地方性区域特点的一类疾病。全国各省、自治区、直辖市都有不同的地方病发生，地方病主要发生于广大农村、山区、牧区等偏僻地区，病区呈灶状分布。碘缺乏和碘缺乏病一、碘缺乏病及其原因：我们知道,食物是身体内碘的主要来源。如果我们生活环境的土壤含碘少，生长在这种土壤上的植物含碘也少，吃了低碘饲料的各种动物（如羊、牛、狗和兔等），也会碘营养不足。如果我们长期以含碘低的粮食和肉类为食品，就会出现碘营养不足，健康就会或多或少受到影响，所有的人都不能幸免，特别是儿童和妇女。虽然大多数人看上去似乎很“正常”，只有部分人会表现出明显病态-地方性甲状腺肿和地方性克汀病。但实际上，这种“正常”是一种隐藏的病态。科学家把碘缺乏对人身体和智力发育造成的全部不良影响（病态）叫做碘缺乏病。二、碘缺乏的危害碘缺乏严重危害人类健康，碘缺乏病的危害主要有： 1、损害儿童大脑神经发育，表现为不同程度的智力缺陷、学习能力低下，这是碘缺乏最大的危害。 2、地方性甲状腺肿，俗称粗脖根或大脖子病；严重碘缺乏会引发地方性克汀病。表现为聋、哑、呆、傻。 3、导致胎儿死亡、畸形、聋哑或流产、早产。 4、成人体力和劳动能力下降，儿童生长、发育受到影响。 5、碘缺乏病不明显影响牲畜的生长发育、繁殖和生产力，降低肉、蛋、乳等的产量和质量。科学家的研究发现女性比男性更容易受到缺碘的影响。幼儿和青春期少年儿童生长发育较快，体内需要的碘也就多。由于生理的原因，处于青春期的女孩和怀孕的妇女更是需要碘，因此，她们对碘缺乏非常敏感。

21世纪与医学化社会的来临_解读彼得_康拉德_社会的医学化_韩俊红

?(世纪与医学化社会的来临! !!!解读彼得#康拉德(社会的医学化) 韩俊红国外社会学界的医学化(>#206/.0c/%0& )研究兴起于()7@年代的美国(X$#029& ，()7@; &./，()7?;e& $/2，()73)"迄今为止，有关医学化问题的社会学C医学社会学研究已经走过了E@年的历程"关于医学化对于当代社会及社会学理论的现实意义，美国加州大学旧金山分校的克拉克等学者认为，医学化已经成为$?@世纪下半叶西方社会最为深远的社会转型后果之一%(e./$5##%/.F，?@@D:(*();另有加拿大研究者指出，医学化或许是医学社会学研究为社会学理论传统做出的最为重要的贡献(b#"/0&，?@(@:((E)" 作为社会学重要理论概念的$医学化%具有怎样的含义?怎样理解医学化作为一种社会进程?我们应该如何理解医学化及其社会后果?解读美国著名医学社会学家彼得#康拉德(N#%#$e& $/2，()E3 J)的医学化研究思想及其著作，有助于我们寻求上述问题的答案" 一!康拉德医学化研究简介康拉德是美国社会学界医学化研究领域的代表人物"早在()7@年代中期，通过儿童$运动机能亢进%(;H-#$50 #909)这一新型医学标签社会生产过程的个案研究入手，康拉德就步入了医学化研究殿堂(e& $/2，()73)"()7*年，康拉德凭借题为(发现儿童多动症:越轨行为的医学化) (LD03@ :? 3>F?P0A2<@ 70IC 5DA03:.C0%0D <25 M2@ 939:Q07 23@X0C27 9A)一文获得波士顿大学社会学博士学位"这篇博士论文作为美国社会学界关于医学化社会进程开展系统性经验研究的开山之作，曾于()7*年首 !本文曾得益于郇建立博士和诸位审稿编辑的真知灼见，特此致谢"文责自负" )??

常见地方性疾病的诊断及治疗

常见地方性疾病的诊断及治疗(仅供参考) ．仔猪副伤寒又称仔猪沙门氏杆菌病。临床上以出现肠炎和持续下痢为特征。 (1)病原体：猪霍乱沙门氏菌和猪伤寒沙门氏菌，本菌对外界抵抗力较强，常用消毒药物能够很快杀死该菌。 (2)流行特点：冬春季节易发，多发生于4月龄以内的仔猪，病猪带菌猪是主要传染源，可从粪、尿、乳及羊水中排菌。经消化道感染（垫草、饮水、用具）。当饲养管理不当，气候突变，当刺激机体抵抗力下降时，存在体内的病原菌会乘机繁殖，毒力增强而致病。常与猪瘟、气喘病混合感染。 (3)症状：急性型（败血型）：体温升高41～42℃，精神不振，呼吸困难，下痢，耳尖、脚腹下侧，吻端皮肤出现紫红色斑点、淤血，2～4天后病死率升高。慢性型：眼有脓性分泌物，结膜潮红，先拉干粪后下痢，粪便淡黄色、恶臭、皮肤出现弥漫性痴样湿疹，最后衰竭而死。 (4)剖检变化：淋巴结肿大、出血，肝脾肿大，肠壁变厚，盖一层灰粪色或绿色麸色样物质。 (5)治疗：土霉素、卡那霉素、庆大霉素均有疗效。 (6)预防：保持环境干燥卫生，定期消毒。1月龄仔猪口服仔猪副伤寒疫苗，按瓶标签标明的头数，用冷开水稀释，按每头剂疫苗稀释于1～10毫升冷开水中灌服，每头5～10毫升。注射用20％氢氧化铝胶生理盐水稀释，1头1毫升肌肉注射。 2．水肿病猪水肿病是由致病性大肠杆菌引起仔猪的一种肠毒血症。特征为胃壁和头部水肿，共济失调和麻痹。 (1)病原体：溶血性大肠杆菌。 (2)流行特点：多发于春、秋季节，地方性流行。健壮和生长快的仔猪最为常见。传染源为带菌母猪和感染仔猪。由粪便排出病菌，污染饲料和环境，通过消化道感染。 (3)症征：突然发病，沉郁、口吐白沫，体温无明显变化。病猪肌肉震颤，触动时嘶叫，前肢站立不稳，后肢不能站立，步态摇摆。作圆圈运动，病猪体表常见额部、眼睑水肿，四肢下部及两耳尖发紫。 (4)病理变化：病猪胃壁水肿，切开流出清亮的液体，大肠水肿，特别是结肠系膜有透明的胶冻样水肿，肠系膜淋巴结水肿。 (5)治疗：方一：早期选用庆大霉素，每公斤体重用4000单位肌肉注射。方二：20%磺胺嘧啶钠20毫升，维生素C１克，50％葡萄糖50毫升，地塞米松15毫克，混合静注。 3．胃肠炎胃肠炎是猪传染性胃肠炎病毒引起，临床上以呕吐、腹泻为主要特征的高度传染性消化系统疾病。 (1)病原体：胃肠炎病毒，本病毒对光、紫外线、热敏感。 (2)流行特点：以深冬、深秋、早春多见。10日龄以内的仔猪死亡率高。病猪及带菌猪是本病的主要传染源。可以众粪、呕吐物、乳、鼻液和呼出气体中排毒，污染饲料、饮水、空气、用具经消化道和呼吸道感染。 (3)症状：仔猪突然发病，先呕吐，继而腹泻。粪便呈黄色、绿色、灰白色。常有没消化完的凝乳块，并带恶臭味。极度口渴，明显脱水，体重减轻。 (4)病理变化：尸体脱水明显，胃、小肠膨胀，肠壁变薄呈半透明状，肠内充满粪并带有泡沫的液体。

医学人文的内涵及概念.doc

医学人文的内涵及概念近年来，医学人文学、医学人文已成为现代医学领域学术探索和研究的热点。虽然医学人文学和医学人文只有一字之差，但目前从理论上还没有将二者的概念清晰界定开，应用也较为含混。厘清二者的概念、属性以及二者之间区别与联系对医学人文教育及医学人文研究有重要意义。 1医学人文学的内涵及概念医学人文学的出现既不是文人学士的附庸风雅，也不是书斋里的思辨清淡，而是随着现代医学所遭遇的伦理困惑和当代生物医学遭遇到的种种难题，由社会和医学本身为解决上述难题和当前医德医风问题并思考未来医学性质及目的而主动提出的。但是其概念较为含糊，人们常常把它和人文医学作为同义词，相互取代。其实医学人文学一词迄今尚无规范统一的定义，但有一点为学者们都认同，即它是一个学科群而不是一门学科。当代的医学人文学是以生命伦理学为核心的一个学科群，由于直接促成医学人文学的兴起的原因，是发生在医学领域中那些生死两难的问题，生命伦理学首当其冲成为亟待解决的课题。但是，伦理问题不是孤立的，常常与社会、法律相连，因而当代的医学人文学是由医学社会学、医学法学、医学哲学等学科群构成，其核心价值指向是维护人类生命的尊严和人的权利。医学人文学既然是一学科群，那么到底要涉及哪些核心学科？学术界存在一些争论，并没有一致的看法。如湖南医科大学贺达仁将医学人文学划分为6大类4个分支约118门课程，北京大学医史研究中心张大庆则主张医学史、医学哲学、医学伦理和医学法学以及医学社会学作为医学人文学的核心课程。一般来说

目前学术界普遍认为医学人文学的内容应涉及或包括医学伦理学、医学史、医学哲学、医学法学、医学美学、医学社会学、军事医学、医学战创学、医学与文学艺术、医学与宗教等。 2医学人文的内涵及概念相比医学人文学，医学人文的概念更为含糊，一些学者认为医学人文一词不规范、不甚严谨，在应用上与“医学人文学”、“人文医学”等混淆使用。有学者认为医学人文包含了两层意义是指“人道的”医学，强调的是对待他人的善行，如医学研究、临床治疗中的伦理价值。另一层意义则是指人类的终极关怀与人性的提升，如批评人类控制自然的傲慢，承认“医学的限度”；王一方认为医学人文是一种姿态：关注人，注重人的价值，思考人的价值。它也是—种立场，基于一份学术与良知的平衡，一种理性与情感的张力，通过哲学、历史、宗教的反思和批评，文学、艺术的滋润；实现医学目的不断廓清，医学终极价值的永恒追问：那就是“人的医学”，以避免现代、当代生命价值的迷失。杜治政释义，医学人文是医学技术中凝结的对人类生命关爱与尊重的精神，是医疗保健服务以行善为目的宗旨，它涉及医学及保健服务的终极价值目标的定位，因而可以认为医学人文是医学的灵魂。综上所述，医学人文的概念属形而上，也可以说是—个哲学的概念，是探讨医学内在的人文性。由于医学研究探索人的生命规律，是以人为中心的研究领域，这就意味着医学与其他自然科学相比有着极大的特别，就是医学人文的本质特征，这是因为：①生命运动是人体的物质因素、精神因素的双重作用，是主客观的统一。人的心理、意志、情感、性格、意识，乃至人类社会的自我意识、文化等精神要素的运动，是生命运动不可或缺的基本内涵，甚至在某种意义上具有决定因素。生命运动不仅仅是人的

医学生化)

北京医科大2000年生物化学试题 1.名词解释 1.chemical shift 2 .florescence anisotropy 3.spin labelling 4.dichroicratio 5.relaxation time 6.lipidpolymorphism 7.phase separation 8.active oxygen 9.secondary structure 10.sensitized fluorescence 11.adtivc transport 12.ion pump 13.ion channel 14.patch clamp 15.ceii adhesion 16.free radical 17.modeling 18.feedback 19.biocybernetics https://www.doczj.com/doc/2c6243222.html,rmation processing 二.问答题 1.举出一种研究生物膜上脂质分子排列有序程度的方法,栀要说明其原理 2.说明维持蛋白质二级结构的力的特点. 3.栀要说明红外光谱再研究生物分子结构中应用. 4.解释脂双层发生相变的分子机理 5.机体中离子地细胞内、外浓度不同,是什么因素决定的?细胞如何利用这种差别作功? 6.简述影响细胞粘着的因素? 7.细胞内钙浓度增加的主要原因有那些?

8.膜片箱技术的用途是什么?有何优点? 9.什么是线性系统和非现性系统?其主要的不同特征是什么? 10.体内稳态系统主要是靠什么控制环节来保持系统稳态特征的? 北京医科大学1999年招收攻读硕士研究生入学试题：生物化学一单项选择题（每题选一最佳答案，每题一分，共分） 1、成熟红细胞的主要能量来源是 A、碳酸戊糖途径 B、脂肪酸氧化 C、酮体氧化 D、糖有氧氧化 2、体内脱氧核糖核苷酸生成的主要方式是 A、直接由核糖还原 B、由核苷还原 C、由一磷酸核苷还原 D、由二磷酸核苷还原 E、由三磷酸核苷还原 3、胆固醇在体内不能代谢转变为 A、肾上腺皮质激素 B、胆汁酸 C、胆色素 D、维生素D3 E、性激素 4、可合成甲状腺素、儿茶酚胺及黑色素的氨基酸是 A、Trp B、Phe C、Ser D、Tyr E、Thr 5、在正常生理情况下，仅在肝脏合成的物质是 A、糖原 B、血浆蛋白质 C、脂肪酸 D、胆固醇 E、尿素

文档之家