Model of the W3(OH) environment based on data for both maser and 'quasi-thermal' methanol l

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Model_Based_Inversion_of_Dynamic_Range_Compression

Model-Based Inversion of Dynamic Range CompressionStanislaw Gorlow,Student Member,IEEE,and Joshua D.Reiss,Member,IEEEAbstract—In this work it is shown how a dynamic nonlinear time-variant operator,such as a dynamic range compressor,can be inverted using an explicit signal model.By knowing the model parameters that were used for compression one is able to recover the original uncompressed signal from a“broadcast”signal with high numerical accuracy and very low computational complexity.A compressor-decompressor scheme is worked out and described in detail.The approach is evaluated on real-world audio material with great success.Index Terms—Dynamic range compression,inversion, model-based,reverse audio engineering.I.I NTRODUCTIONS OUND or audio engineering is an established discipline employed in many areas that are part of our everyday life without us taking notice of it.But not many know how the audio was produced.If we take sound recording and reproduction or broadcasting as an example,we may imagine that a prerecorded signal from an acoustic source is altered by an audio engineer in such a way that it corresponds to certain criteria when played back.The number of these criteria may be large and usually depends on the context.In general,the said alteration of the input signal is a sequence of numerous forward transformations, the reversibility of which is of little or no interest.But what if one wished to do exactly this,that is to reverse the transfor-mation chain,and what is more,in a systematic and repeatable manner?The research objective of reverse audio engineering is twofold:to identify the transformation parameters given the input and the output signals,as in[1],and to regain the input signal that goes with the output signal given the transformation parameters.In both cases,an explicit signal model is manda-tory.The latter case might seem trivial,but only if the applied transformation is linear and orthogonal and as such perfectly invertible.Yet the forward transform is often neither linear nor invertible.This is the case for dynamic range compressionManuscript received December05,2012;revised February28,2013; accepted February28,2013.Date of publication March15,2013;date of current version March29,2013.This work was supported in part by the “Agence Nationale de la Recherche”within the scope of the DReaM project (ANR-09-CORD-006)as well as the laboratory with which theﬁrst author is afﬁliated as part of the“mobilitéjuniors”program.The associate editor coordinating the review of this manuscript and approving it for publication was Prof.Woon-Seng Gan.S.Gorlow is with the Computer Science Research Laboratory of Bordeaux (LaBRI),CNRS,Bordeaux1University,33405Talence Cedex,France(e-mail: stanislaw.gorlow@labri.fr).J.D.Reiss is with the Centre for Digital Music(C4DM),Queen Mary,Uni-versity of London,London E14NS,U.K.(e-mail:josh.reiss@). Digital Object Identiﬁer10.1109/TASL.2013.2253099(DRC),which is commonly described by a dynamic nonlinear time-variant system.The classical linear time-invariant(LTI) system theory does not apply here,so a tailored solution to the problem at hand must be found instead.At this point,we also like to highlight the fact that neither V olterra nor Wiener model approaches[2]–[4]offer a solution,and neither do describing functions[5],[6].These are useful tools when identifying a time-invariant or a slowly varying nonlinear system or ana-lyzing the limit cycle behavior of a feedback system with a static nonlinearity.A method to invert dynamics compression is described in[7], but it requires an instantaneous gain value to be transmitted for each sample of the compressed signal.To provide a means to control the data rate,the gain signal is subsampled and also en-tropy coded.This approach is highly inefﬁcient as it does not rely on a gain model and is extremely generic.On the other hand,transmitting the uncompressed signal in conjunction with a few typical compression parameters like threshold,ratio,attack,and release would require a much smaller capacity and yield the best possible signal quality with regard to any thinkable measure.A more realistic scenario is when the uncompressed signal is not available on the consumer side.This is usually the case for studio music recordings and broadcast material where the listener is offered a signal that is meant to sound“good”to everyone.However,the loudness war [8]has resulted in over-compressed audio material.Over-com-pression makes a song lose its artistic features like excitingness or liveliness and desensitizes the ear thanks to a louder volume. There is a need to restore the original signal’s dynamic range and to experience audio free of compression.In addition to the normalization of the program’s loudness level,the Dolby solution[9],[10]also includes dynamic range expansion.The expansion parameters that help reproduce the original program’s dynamic range are tuned on the broadcaster side and transmitted as metadata together with the broadcast signal.This is a very convenient solution for broadcasters,not least because the metadata is quite compact.Dynamic range ex-pansion is yet another forward transformation rather than a true inversion.Evidently,none of the previous approaches satisfy the re-verse engineering objective of this work.The goal of the present work,hence,is to invert dynamic range compression,which is a vital element not only in broadcasting but also in mastering. The paper is organized as follows.Section II provides a brief introduction to dynamic range compression and presents the compressor model upon which our considerations are based. The data model,the formulation of the problem,and the pur-sued approach are described next in Section III.The inversion1558-7916/$31.00©2013IEEEFig.1.Basic broadband compressor model(feed forward).is discussed in detail in Section IV.Section V illustrates how an integral step of the inversion procedure,namely the search for the zero-crossing of a non-linear function,can be solved in an iterative manner by means of linearization.Some other com-pressor features are discussed in Section VI.The complete al-gorithm is given in the form of pseudocode in Section VII and its performance is evaluated for different compressor settings in Section VIII.Conclusions are drawn in Section IX,where some directions for future work are mentioned.II.D YNAMIC R ANGE C OMPRESSIONDynamic range compression or simply“compression”is a sound processing technique that attenuates loud sounds and/or ampliﬁes quiet sounds,which in consequence leads to a reduc-tion of an audio signal’s dynamic range.The latter is deﬁned as the difference between the loudest and quietest sound mea-sured in decibel.In the following,we will use the word“com-pression”having“downward”compression in mind,though the discussed approach is likewise applicable to“upward”compres-sion.Downward compressing means attenuating sounds above a certain threshold while leaving sounds below the threshold unchanged.A sound engineer might use a compressor to reduce the dynamic range of source material for purposes of aesthetics, intelligibility,recording or broadcast limitations.Fig.1illustrates the basic compressor model from([11],ch.2)amended by a switchable RMS/peak detector in the side chain making it compatible with the compressor/limiter model from ([12],p.106).We will hereafter restrict our considerations to this basic model,as the purpose of the present work is to demon-strate a general approach rather than a solution to a speciﬁc problem.First,the input signal is split and a copy is sent to the side chain.The detector then calculates the magnitude or level of the sidechain signal using the root mean square(RMS)or peak as a measure for how loud a sound is([12],p.107). The detector’s temporal behavior is controlled by the attack and release parameters.The sound level is compared with the threshold level and,for the case it exceeds the threshold,a scale factor is calculated which corresponds to the ratio of input level to output level.The knee parameter determines how quick the compression ratio is reached.At the end of the side chain,the scale factor is fed to a smoothingﬁlter that yields the gain.The response of theﬁlter is controlled by another set of attack and re-lease parameters.Finally,the gain control applies the smoothed gain to the input signal and adds aﬁxed amount of makeup gain to bring the output signal to a desired level.Such a broad-band compressor operates on the input signal’s full bandwidth, treating all frequencies from zero through the highest frequency equally.A detailed overview of all sidechain controls of a basic gain computer is given in([11],ch.3),e.g.,III.D ATA M ODEL,P ROBLEM F ORMULATION,ANDP ROPOSED S OLUTIONA.Data Model and Problem FormulationThe employed data model is based on the compressor from Fig.1.The following simpliﬁcations are additionally made:the knee parameter(“hard”knee)and the makeup gain(ﬁxed at 0dB)are ignored.The compressor is deﬁned as a single-input single-output(SISO)system,that is both the input and the output are single-channel signals.What follows is a description of each block by means of a dedicated function.The RMS/peak detector as well as the gain computer build upon aﬁrst-order(one-pole)lowpassﬁlter.The sound level or envelope of the input signal is obtained by(1)where represents an RMS detector,and a peak detector.The non-zero smoothing factor,may take on different values,or,depending on whether the detector is in the attack or release phase.The condition for the level detector to enter the attack phase and to choose over is(2)A formula that converts a time constant into a smoothing factor is given in([12],p.109),so e.g.,where is the sampling frequency.The static nonlinearity in the gain computer is usually modeled in the logarithmic domain as a continuous piecewise linear function:(3) where is the slope,,and is the threshold in decibel.The slope is further derived from the de-sired compression ratio according to(4)Equation(3)is equivalently expressed in the linear domain as(5) where,and is the linear scale factor beforeﬁltering.The smoothed gain is then calculated as the exponentially-weighted moving average,(6) where the decision for the gain computer to choose the attack smoothing factor instead of is subject to(7) The output signal isﬁnally obtained by multiplying the above gain with the input signal:(8) Due to the fact that the gain is strictly positive,,it follows that(9) where sgn is the signum or sign function.In consequence,it is convenient to factorize the input signal as a product of the sign and the modulus according to(10)The problem at hand is formulated in the following manner: Given the compressed signal and the model parameters recover the modulus of the original signal from based on.For a more intuitive use,the smoothing factors and may be replaced by the time constants and.The meaning of each parameter is listed below.The threshold in dBThe compression ratio dB:dBThe detector type(RMS or peak)The attack time of the envelopeﬁlter in msThe release time of the envelopeﬁlter in msThe attack time of the gainﬁlter in msThe release time of the gainﬁlter in msB.Proposed SolutionThe output of the side chain,that is the gain of,given ,and,may be written as(11) In(11),denotes a nonlinear dynamic operator that maps the modulus of the input signal onto a sequence of instanta-neous gain values according to the compressor model rep-resented ing(11),(8)can be solved for yieldingsubject to invertibility of.In order to solve the above equa-tion one requires the knowledge of,which is unavailable. However,since is a function of,we can express as a function of one independent variable,and in that manner we obtain an equation with a single unknown:(12) where represents the entire compressor.If is invertible, i.e.,bijective for all can be obtained from by(13) And yet,since is unknown,the condition for applying decompression must be predicted from,and ,and therefore needs the condition for toggling between the attack and release phases.Depending on the quality of the prediction,the recovered modulus may differ somewhat at transition points from the original modulus,so that in the end(14)In the next section it is shown how such an inverse compressor or decompressor is derived.IV.I NVERSION OF D YNAMIC R ANGE C OMPRESSIONA.Characteristic FunctionFor simplicity,we choose the instantaneous envelope value instead of as the independent variable in(12).The relation between the two items is given by(1).From(6)and(8), when(15)(16) From(1),(17) or equivalently(note that by deﬁnition)(18) Moreover,(18)has a unique solution if and also are in-vertible.Moving the expression on the left-hand side over to the right-hand side,we may deﬁne(19) which shall be termed the characteristic function.The root or zero-crossing of hence represents the sought-after enve-lope value.Once is found(see Section V),the current values of,and are updated as per(20) and the decompressed sample is then calculated as(21)B.Attack-Release Phase Toggle1)Envelope Smoothing:In case a peak detector is in use, takes on two different values.The condition for the attack phase is then given by(2)and is equivalent to(22) Assuming that the past value of is known at time,what is needed to be done is to express the unknown in terms of such that the above equation still holds true.If is rather small,,or equivalently if is sufﬁciently large,ms at44.1-kHz sampling,the term in(15)is negligible,so it approximates(15)as(23) Solving(23)for and plugging the result into(22),we obtain(24) If(24)holds true,the detector is assumed to be in the attack phase.2)Gain Smoothing:Just like the peak detector,the gain smoothingﬁlter may be in either the attack or release phase. The necessary condition for the attack phase in(7)may also be formulated as(25) But since the current envelope value is unknown,we need to substitute in the above inequality by something that is known.With this in mind,(15)is rewritten as(26) Provided that,and due to the fact that ,the expression in square brackets in(26)is smaller than one,and thus during attack(27) Substituting by using(20), and solving(27)for results in(28) If in(25)is substituted by the expression on the right-hand side of(28),(25)still holds true,so the following sufﬁcient condition is used to predict the attack phase of the gainﬁlter:(29) Note that the values of all variables are known whenever(29)is evaluated.C.Envelope PredictorAn instantaneous estimate of the envelope value is re-quired not only to predict when compression is active,formally according to(5),but also to initialize the iterative search algorithm in Section V.Resorting once more to(15)itcan be noted that in the opposite case where, and so(30) The sound level of the input signal at time is therefore(31) which must be greater than the threshold for compression to set in,whereas and are selected based on(24)and(29), respectively.D.Error AnalysisConsider being estimated from according to(32) The normalized error is then(33)(34) As during attack andduring release,respectively.The instantaneous gain can also be expressed as(35) where is the runtime in ing(35)in(34),the mag-nitude of the error is given by(36)(37) For,(36)becomes(38) whereas for,(37)converges to inﬁnity:(39) So,the error is smaller for large or short.The smallest possible error is for,which then again depends on the current and the previous value of.The error accumulatesifFig.2.Graphical illustration for the iterative search for the zero-crossing.with.The difference between consecutive-values is signal dependent.The signal envelopeﬂuctuates less and is thus smoother for smaller or longer.is also more stable when the compression ratio is low.Foris perfectly constant.The threshold has a negative impact on error propagation.The lower the more the error depends on ,since more samples are compressed with different-values. The RMS detector stabilizes the envelope more than the peak detector,which also reduces the error.Furthermore,since usu-ally,the error due to is smaller during release whereas the error due to is smaller during attack.Finally,the error is expected to be larger at transition points between quiet to loud signal passages.The above error may cause a decision in favor of a wrong smoothing factor in(24),like instead of e.g.,The decision error from(24)then propagates to(29).Given that ,the error due to(32)is accentuated by(24)with the consequence that(29)is less reliable than(24).The total error in(29)thus scales with.In regard to(31),re-liability of the envelope’s estimate is subject to validity of(24) and(29).A better estimate is obtained when the sound level de-tector and the gainﬁlter are both in either the attack or release phase.Here too,the estimation error increases withand also with.V.N UMERICAL S OLUTION OF THE C HARACTERISTIC F UNCTION An approximate solution to the characteristic function can be found,e.g.,by means of linearization.The estimate from(31) may moreover serve as a starting point for an iterative search of an optimum:The criterion for optimality is further chosen as the deviation of the characteristic function from zero,initialized to(40) Thereupon,(19)may be approximated at a given point using the equation of a straight line,,where is the slope and is the-intercept.The zero-crossing is characterized by the equation(41)as shown in Fig.2.The new estimate of the optimal is found as(42) If is less optimal than,the iteration is stopped and is theﬁnal estimate.The iteration is also stopped if is smaller than some.In the latter case,has the optimal value with respect to the chosen criterion.Otherwise,is set to and is set to after every step and the procedure is repeated until has converged to a more optimal value.The proposed method is a special form of the secant method with a single initial value.VI.G ENERAL R EMARKSA.Stereo LinkingWhen dealing with stereo signals,one might want to apply the same amount of gain reduction to both channels to prevent image shifting.This is achieved through stereo linking.One way is to calculate the required amount of gain reduction for each channel independently and then apply the larger amount to both channels.The question which arises in this context is which of the two channels was the gain derived from.To give an answer resolving the dilemma of ambiguity,one solution would be to signal which of the channels carries the applied gain.One could then decompress the marked sample and use its gain for the other channel.Although very simple to implement, this approach provokes an additional data rate of44.1kbps at44.1-kHz sampling.A rate-efﬁcient alternative that comes witha higher computational cost is realized in the following way. First,one decompresses both the left and the right channel in-dependently and in so doing one obtains two estimates and,where subscript shall denote the left channel and subscript the right channel,respectively.In a second step,one calculates the compressed values of and and selects the channel for which holds true.In aﬁnal step,one updates the remaining variables using the gain of the selected channel.B.LookaheadA compressor with a look-ahead function,i.e.,with a delay in the main signal path as in([12],p.106),uses past input samples as weighted output samples.Now that some future input sam-ples are required to invert the process—which are unavailable, the inversion is rendered impossible.and must thus be in sync for the approach to be applied.C.Clipping and LimitingAnother point worth mentioning is that“hard”clipping and “brick-wall”limiting are special cases of compression with the attack time set to zero and the compression ratio set to. The static nonlinearity in that particular case is a one-to-many mapping,which by deﬁnition is noninvertible.VII.T HE A LGORITHMThe complete algorithm is divided into three parts,each of them given as pseudocode below.Algorithm1out-lines the compressor that corresponds to the model from Sections II–III.Algorithm2illustrates the decompressor de-scribed in Section IV,and the iterative search from Section V isﬁnally summarized in Algorithm3.The parameter repre-sents the sampling frequency in kHz.function C OMPfor doif thenelseend ifif thenelseend ifif thenelseend ifend forreturnend functionVIII.P ERFORMANCE E VALUATIONA.Performance MetricsTo evaluate the inverse approach,the following quantities are measured:the root-mean-square error(RMSE),(43) given in decibel relative to full scale(dBFS),the perceptual sim-ilarity between the original and decompressed signal,and the execution time of the decompressor relative to real time(RT). Furthermore,we present the percentage of compressed samples, the mean number of iterations until convergence per compressed sample,the error rate of the attack-release toggle for the gainsmoothingﬁlter,andﬁnally the error rate of the envelope pre-dictor.The perceptual similarity is assessed by PEMO-Q[13], Algorithm2The decompressorfunction D ECOMPfor doif thenelseend ifif thenelseend ifif thenC HARFZEROelseend ifend forreturnend functionAlgorithm3The iterative search for the zero-crossingfunction C HARFZEROrepeatif thenreturnend ifuntilreturnend function [14]with as metric.The simulations are run in MATLAB on an Intel Core i5-520M CPU.putational ResultsFig.3shows the inverse output signal for a synthetic input signal using an RMS detector.The inverse signal is obtained from the compressed signal with an error of dBFS.It is visually indistinguishable from the original signal.Due to the fact that the signal envelope is con-stant most of the time,the error is noticeable only around tran-sition points—which are few.The decompressor’s performance is further evaluated for some commercial compressor presets. The used audio material consists of12items covering speech, sung voice,music,and jingles.All items are normalized to LKFS[15].The-value in the break condition of Algorithm3 is set to.A detailed overview of compressor settings and performanceﬁgures is given in Tables I–II.The presented results suggest that the decompressed signal is perceptually in-distinguishable from the original—the-value isﬂawless. This was also conﬁrmed by the authors through informal lis-tening tests.As can be seen from Table II,the largest inversion error is associated with setting E and the smallest with setting B.For allﬁve settings,the error is larger when an RMS detector is in use.This is partly due to the fact that has a stronger curvature in comparison to.By deﬁning the distance in (40)as,it is possible to attain a smaller error for an RMS detector at the cost of a slightly longer runtime.In most cases,the envelope predictor works more reliably as compared to the toggle switch between attack and release.It can also be observed that the choice of time constants seems to have little impact on decompressor’s accuracy.The major parameters that affect the decompressor’s performance are and,while the threshold is evidently the predominant one:the RMSE strongly correlates with the threshold level.Figs.4–5show the inversion error as a function of various time constants.These are in the range of typical attack and re-lease times for a limiter(peak)or compressor(RMS)([12],pp. 109–110).It can be observed that the inversion accuracy de-pends on the release time of the peak detector and not so much on its attack time for both the envelope and the gainﬁlter,see Figs.4,5(b).For the envelopeﬁlter,all error curves exhibit a local dip around a release time of0.5s.The error increases steeply below that bound but moderately with larger values.In the proximity of5s,the error converges to dBFS.With regard to the gainﬁlter,the error behaves in a reverse manner. The curves in Fig.5(b)exhibit a local peak around0.5s with a value of180dBFS.It can further be observed in Fig.4(a) that the curve for ms has a dip where is close to1ms,i.e.,where is minimal.This is also true for Fig.4(c)and(d):the lowest error is where the attack and release times are identical.As a general rule,the error that is due to the attack-release switch is smaller for the gainﬁlter in Fig.5. Looking at Fig.6one can see that the error decreases with threshold and increases with compression ratio.At a ratio of 10:1and beyond,the RMSE scales almost exclusively with the threshold.The lower the threshold,the stronger the error prop-agates between decompressed samples,which leads to a largerFig.3.An illustrative example using an RMS amplitude detector with set to 5ms,a threshold ofdBFS (dashed line in the upper right corner),acom-pression ratio of 4:1,and set to 1.6ms for attack and 17ms for release,respectively.TheRMSE is dBFS.TABLE IS ELECTED C OMPRESSOR S ETTINGSTABLE IIP ERFORMANCE F IGURES O BTAINED FOR V ARIOUS A UDIO M ATERIAL (12I TEMS )RMSE value.The RMS detector further augments the error be-cause it stabilizes the envelope more than the peak de-tector.Clearly,the threshold level has the highest impact on the decompressor’s accuracy.IX.C ONCLUSION AND O UTLOOKThis work examines the problem of ﬁnding an inverse to a nonlinear dynamic operator such as a digital compressor.The proposed approach is characterized by the fact that it uses an explicit signal model to solve the problem.To ﬁnd the “dry”or uncompressed signal with high accuracy,it is suf ﬁcient to know the model parameters.The parameters can e.g.,be sent together with the “wet”or compressed signal in the form of metadata as is the case with Dolby V olume and ReplayGain [16].A new bit-stream format is not mandatory,since many digital audio stan-dards,like WA V or MP3,provide means to tag the audio con-Fig.4.RMSE as a function of typical attack and release times using a peak (upper row)or an RMS amplitude detector (lower row).In the left column,the attack time of the envelope ﬁlter is varied while the release time is held constant.The right column shows the reverse case.The time constants of the gain ﬁlter are ﬁxed at zero.In all four cases,threshold and ratio are ﬁxed at 32dBFS and 4:1,respectively.Fig.5.RMSE as a function of typical attack and release times using a peak (upper row)or an RMS amplitude detector (lower row).In the left column,the attack time of the gain ﬁlter is varied while the release time is held constant.The right column shows the reverse case.The time constants of the envelope ﬁlter are ﬁxed at zero.In all four cases,threshold and ratio are ﬁxed at 32dBFS and 4:1,respectively.tent with “ancillary”data.With the help of the metadata,one can then reverse the compression applied after mixing or be-fore broadcast.This allows the end user to have control over the amount of compression,which may be preferred because the sound engineer has no control over the playback environ-ment or the listener’s individual taste.When the compressor parameters are unavailable,they can possibly be estimated from the compressed signal.This mayFig.6.RMSE as a function of threshold relative to the signal’s average loudness level(left column)and compression ratio(right column)using a peak(upper row)or an RMS amplitude detector(lower row).The time constants are:ms,ms,and s.thus be a direction for future work.Another direction would be to apply the approach to more sophisticated models that include a“soft”knee,parallel and multiband compression,or perform gain smoothing in the logarithmic domain,see[11],[12],[17], [18]and references therein.In conclusion,we want to draw the reader’s attention to the fact that the presentedﬁgures suggest that the decompressor is realtime capable which can pave the way for exciting new applications.One such application could be the restoration of dynamics in over-compressed audio or else the accentuation of transient components,see[19]–[21],by an adaptively tuned decompressor that has no prior knowledge of the compressor parameters.A CKNOWLEDGMENTThis work was carried out in part at the Centre for Digital Music(C4DM),Queen Mary,University of London.R EFERENCES[1]D.Barchiesi and J.Reiss,“Reverse engineering of a mix,”J.AudioEng.Soc.,vol.58,pp.563–576,2010.[2]T.Ogunfunmi,Adaptive Nonlinear System Identiﬁcation:The Volterraand Wiener Model Approaches.New York,NY,USA:Springer Sci-ence+Business Media,2007,ch.3.[3]Y.Avargel and I.Cohen,“Adaptive nonlinear system identiﬁcationin the short-time Fourier transform domain,”IEEE Trans.SignalProcess.,vol.57,no.10,pp.3891–3904,Oct.2009.[4]Y.Avargel and I.Cohen,“Modeling and identiﬁcation of nonlinear sys-tems in the short-time Fourier transform domain,”IEEE Trans.SignalProcess.,vol.58,no.1,pp.291–304,Jan.2010.[5]A.Gelb and W.E.Vander Velde,Multiple-Input Describing Functionsand Nonlinear System Design.New York,NY,USA:McGraw-Hill,1968,ch.1.[6]P.W.J.M.Nuij,O.H.Bosgra,and M.Steinbuch,“Higher-order sinu-soidal input describing functions for the analysis of non-linear systems with harmonic responses,”Mech.Syst.Signal Process.,vol.20,pp.1883–1904,2006.[7]chaise and L.Daudet,“Inverting dynamics compression withminimal side information,”in Proc.DAFx,2008,pp.1–6.[8]E.Vickers,“The loudness war:Background,speculation and recom-mendations,”in Proc.AES Conv.129,Nov.2010.[9]Dolby Digital and Dolby V olume Provide a Comprehensive LoudnessSolution,Dolby Laboratories,2007.[10]Broadcast Loudness Issues:The Comprehensive Dolby Approach,Dolby Laboratories,2011.[11]R.Jeffs,S.Holden,and D.Bohn,Dynamics processor—Technology&Application Tips,Rane Corporation,2005.[12]U.Zölzer,DAFX:Digital Audio Effects,2nd ed.Chichester,WestSussex,U.K.:Wiley,2011,ch.4,The Atrium,Southern Gate,PO19 8SQ.[13]R.Huber and B.Kollmeier,“PEMO-Q—A new method for objectiveaudio quality assessment using a model of auditory perception,”IEEE Trans.Audio Speech Lang.Process.,vol.14,no.6,pp.1902–1911, Nov.2006.[14]HörTech gGmbH,PEMO-Q[Online].Available:http://www.ho-ertech.de/web_en/produkte/pemo-q.shtml,version1.3[15]ITU-R,Algorithms to Measure Audio Programme Loudness and True-Peak Audio Level,Mar.2011,rec.ITU-R BS.1770-2.[16]Hydrogenaudio,ReplayGain[Online].Available:http://wiki.hydroge-/index.php?title=ReplayGain,Feb.2013[17]J.C.Schmidt and J.C.Rutledge,“Multichannel dynamic range com-pression for music signals,”in Proc.IEEE ICASSP,1996,vol.2,pp.1013–1016.[18]D.Giannoulis,M.Massberg,and J.D.Reiss,“Digital dynamic rangecompressor design—A tutorial and analysis,”J.Audio Eng.Soc.,vol.60,pp.399–408,2012.[19]M.M.Goodwin and C.Avendano,“Frequency-domain algorithms foraudio signal enhancement based on transient modiﬁcation,”J.Audio Eng.Soc.,vol.54,pp.827–840,2006.[20]M.Walsh,E.Stein,and J.-M.Jot,“Adaptive dynamics enhancement,”in Proc.AES Conv.130,May2011.[21]M.Zaunschirm,J.D.Reiss,and A.Klapuri,“A sub-band approachto modiﬁcation of musical transients,”Comput.Music J.,vol.36,pp.23–36,2012.。

【精品】生态系统服务模型

生态系统服务模型1.2.8生态系统服务评估模型（ecosystem services model）生态系统服务及其价值评估已成为了生态学和生态经济学研究的热点（Daily, 1997; Costanza et al., 1997; De Groot et al., 2002）。

国外生态系统服务功能价值的评估研究可以追溯到1925年比利时的Drumarx首次以对野生生物游憩的费用支出作为野生生物的经济价值。

1941年，美国的Dafdon首次用费用支出法核算出森林和野生生物的经济价值。

1947年，美国的Flotting提出可根据旅行费用计算出其消费者剩余，并以消费者剩余作为游憩区的游憩价值;1959年，美国的Clawson修改旅行费用评估法;1964年，J. L. Knetch再次修改并完善了旅行费用评估法。

同年，美国的Davis在研究湎因州森林的游憩价值时，首次提出并运用了条件价值法的报价技术。

1972年，日本林业厅估算了全日本森林提供的生态功能价值。

1973年，Nordhau和Tobin提出用“经济福利准则”修改国民生产总值，由此引发了对环境资源进行估算的国际关注，许多学者先后提出多种方案来估算环境资源的价值（刘玉龙等，2005）。

1991年国际科学联合会环境委员会召开了讨论如何开展生物多样性的定量研究的会议，促进了生物多样性的研究及其价值评估方法的发展。

1993年联合国有关机构止式出版了《综合环境与经济核算手册》临时版本(简称SEEA)，对此前各国环境与经济综合核算的研究成果进行了较全面总结，并提供了环境与经济核算的总体思路与框架以及一些生态价值的核算方法(张建国,杨建洲.福建森林综合效益计算与评价[J].生态经济，1994,(5):1-6.)。

1997年Costanza等人对全球主要类型的生态系统服务功能的价值进行了评估，揭开了生态系统服务功能价值研究的序幕。

1997年，由Gretch Daily等人编著的《生态系统服务功能》一书，系统地阐述了生态系统服务功能的内容与评价方法，同时还分析了不同地区森林、湿地、海岸等生态系统服务功能价值评价的近20个实例(Daily G C. Natures Science: Societal Dependence on Natural Ecosystems[M]. Washington D C: Island Press,1997.)，具有较高的学术价值。

Mavenpom.xml详解

Mavenpom.xml详解⼀、pom 简介POM 是项⽬对象模型 (Project Object Model) 的简称, XML 格式,名称为 pom.xml ,它是 Maven 项⽬的核⼼配置⽂件,该⽂件⽤于管理源代码、配置⽂件、开发者的信息和⾓⾊、问题追踪系统、组织信息、项⽬授权、项⽬的url、项⽬的依赖关系等等.事实上,在 Maven 的世界中,⼀个项⽬可以什么都没有,甚⾄没有代码,但是必须包含 pom.xml ⽂件.并且⼀个 Maven 项⽬有且只有⼀个 pom.xml ⽂件,该⽂件必须在项⽬的根⽬录下.⼆、pom.xml 完整结构<project xmlns="/POM/4.0.0"xmlns:xsi="/2001/XMLSchema-instance"xsi:schemaLocation="/POM/4.0.0/xsd/maven-4.0.0.xsd"><modelVersion>4.0.0</modelVersion><groupId>...</groupId><artifactId>...</artifactId><version>...</version><packaging>...</packaging><dependencies>...</dependencies><parent>...</parent><dependencyManagement>...</dependencyManagement><modules>...</modules><properties>...</properties><build>...</build><reporting>...</reporting><name>...</name><description>...</description><url>...</url><inceptionYear>...</inceptionYear><licenses>...</licenses><organization>...</organization><developers>...</developers><contributors>...</contributors><issueManagement>...</issueManagement><ciManagement>...</ciManagement><mailingLists>...</mailingLists><scm>...</scm><prerequisites>...</prerequisites><repositories>...</repositories><pluginRepositories>...</pluginRepositories><distributionManagement>...</distributionManagement><profiles>...</profiles></project>我们这⾥就选择⼀些⽐较常⽤的配置来说三、pom 常⽤配置1、坐标坐标是⼀个项⽬的唯⼀标识符,可以通过坐标准确的定位到某⼀个具体的项⽬.有了坐标进⾏定位之后,如果其它的 Maven 项⽬想使⽤该项⽬⽣成的 jar 包,只需要通过坐标引⼊依赖即可Maven 坐标是通过 groupId、artifactId、version 来共同定位的.groupId: 组织 Id ,表⽰当前模块所⾪属的项⽬.起名规范：⼀级域名(com、org).⼆级域名(公司名称).项⽬名称artifactId: 模块 Id, 表⽰⼀个项⽬中的某个模块,例如商城项⽬⾥⾯的订单模块、⽤户模块、商品模块...等等version：当前的版本为什么坐标需要三个元素才能定位呢?⽐如你⾃⼰的项⽬中需要使⽤某⼀个 jar 包,那么怎么找到这个 jar 包呢?这个时候你就需要使⽤ groupId 来定位这个 jar 包是属于哪个公司的哪个项⽬,定位到了项⽬之后呢,你还需要使⽤ artifactId 定位到该项⽬的具体模块,因为⼀个项⽬可以有很多的模块,定位到了具体模块之后呢,还需要使⽤ version 来定位具体的版本号,因为⼀个模块可以进⾏迭代,如果不指定具体的版本号也就⽆法准确的定位,这个类似于地理⾥⾯只有通过东经和北纬才能准确定位⼀个地理位置⼀样.<groupId>com.xiaomaomao.springAnalyse</groupId><artifactId>spring-ioc</artifactId><version>1.0-SNAPSHOT</version>2、全局变量 propertiesproperties: 全局属性,⼀般情况下⽤于定义全局的 jar 包版本.仅仅是定义全局变量,不起其他作⽤.应⽤场景:在实际项⽬中如果我们使⽤同⼀个公司的 jar 包, jar 包的版本号最好是保持⼀致,因为有时候 jar 包版本不⼀致的情况下,有可能会出现不同版本之间发⽣不兼容的错误, 我们这⾥就以 spring 为例,下⾯的这些依赖当中 spring-context、spring-webmvc 都是属于 spring 的 jar 包,并且它们的版本号都是 4.3.11.RELEASE,突然有⼀天,项⽬经理兴奋的告诉我,spring 推出了 5.0 版本,功能很强⼤,我们要升级版本,那么这个时候你就只能挨个的找到 spring 相关的依赖,⼀个⼀个的把它们升级到 5.0 版本,我们这⾥仅仅只有两个 spring 相关的依赖,改起来⽐较快,可是如果你的项⽬⾥⾯使⽤了⼏⼗个,甚⾄上百个 spring 的依赖呢?这个时候你挨个挨个的去替换,⼯作量⽐较⼤,并且还有可能⼀不留神改错了,好不容易改完了,也没有改错,终于可以休息⼀下了,这个时候项⽬经理那个糟⽼头⼦⼜来了,他告诉你 spring 5.0 有版本缺陷,我们还是改回原来的 4.3.11.RELEASE 版本吧,我想此时你是奔溃的,你就只能挨个挨个的将 spring 的依赖 jar 包⼀个⼀个的还原,好了,还原了,也改好了,终于没事了,你冷不丁的冒出⼀个念头,万⼀项⽬经理⼜要我切换成其它的版本,⼯作量太⼤了,有没有什么⽐较好的办法呢?答案是有的,我们就可以通过 properties 标签来统⼀管理 jar 包的版本<dependencies><dependency><groupId>org.springframework</groupId><artifactId>spring-context</artifactId><version>4.3.11.RELEASE</version></dependency><dependency><groupId>org.springframework</groupId><artifactId>spring-webmvc</artifactId><version>4.3.11.RELEASE</version></dependency><dependency><groupId>junit</groupId><artifactId>junit</artifactId><version>4.11</version><scope>test</scope></dependency><dependency><groupId>javax.servlet</groupId><artifactId>javax.servlet-api</artifactId><version>4.0.0</version><scope>provided</scope></dependency></dependencies>在 <properties> 标签中定义⼀类 jar 包的版本,引⼊依赖的时候通过 ${标签名} 的⽅式来控制版本<properties><spring-version>4.3.11.RELEASE</spring-version><junit-version>4.11</junit-version><javax.servlet-version>4.0.0</javax.servlet-version></properties><dependencies><dependency><groupId>org.springframework</groupId><artifactId>spring-context</artifactId><version>${spring-version}</version></dependency><dependency><groupId>org.springframework</groupId><artifactId>spring-webmvc</artifactId><version>${spring-version}</version></dependency><dependency><groupId>junit</groupId><artifactId>junit</artifactId><version>${junit-version}</version><scope>test</scope></dependency><dependency><groupId>javax.servlet</groupId><artifactId>javax.servlet-api</artifactId><version>${javax.servlet-version}</version><scope>provided</scope></dependency></dependencies>如果以后想统⼀切换 spring、junit 等 jar 包的版本,我们只需要在 properties 标签中切换就可以了,再也不⽤去依赖中挨个挨个的替换 jar 包的版本了3、dependencydependency 标签统⼀的定义在 dependencies 标签中,它代表的意思是我们可以通过该标签引⼊我们需要的相关 jar 包3.1、如何查找⼀个 jar 包的地址?Maven 依赖官⽹:3.1.1、进⼊官⽹,查找需要的 jar 包3.1.2、选择 jar 包版本3.1.3、复制依赖到项⽬ pom.xml 中3.2、如何查看引⼊的依赖4、依赖的 scope 作⽤域依赖的 scope 标签表⽰的意思是依赖的使⽤范围(也就是这个 jar 包在什么范围内是可以使⽤的),scope 的取值有 compile、test、provided、runtime、system 4.1、compile该依赖可以在整个项⽬中使⽤(是指代码范围, main ⽬录和 test ⽬录下都能使⽤这个依赖),参与打包部署.是 scope 的默认值.典型的例如: commons f ileupload 例如:我们修改 spring 核⼼依赖 spring-context 的 scope 为 test<dependency><groupId>org.springframework</groupId><artifactId>spring-context</artifactId><version>${spring-version}</version><scope>test</scope></dependency>在 main ⽬录下使⽤就出现了报错在 test ⽬录下使⽤就是正常的4.2、test该依赖只能在测试代码中使⽤(是指代码范围,只能在 test ⽬录下使⽤这个依赖),不参与打包部署.典型的例如: junit4.3、provided该依赖编写源代码时需要使⽤,因为当我们使⽤ Servlet 的时候,如果不添加 javax.servlet-api 依赖,就⽆法使⽤⾥⾯相关的 API,如果使⽤了编译就会报错,provided 不参与打包部署.只是在编写源码的时候使⽤,为什么不参与打包部署呢?因为我们的项⽬打包部署到服务器的时候,服务器会为我们提供 javax.servlet-api ,这⾥以 tomcat 为例,找到 tomcat 的安装⽬录,打开⾥⾯的 lib ⽬录,在 tomcat 容器启动的时候会为我们提供 servlet-api.jar ,那么我们项⽬中的 pom.xml 中就不需要再提供 servlet-api 这个依赖了4.4、runtime该依赖编写代码时不需要,运⾏时需要,参与打包部署.典型的例如数据库驱动 mysql-connector-java<dependency><groupId>mysql</groupId><artifactId>mysql-connector-java</artifactId><version>8.0.20</version></dependency>为什么编写代码时不需要呢？jvm 运⾏期的时候通过反射加载数据库驱动,完成例如注册驱动、获取连接、获取 PrepareStatement 对象等,我们编写代码的时候只是在编译期间,根本不会使⽤到数据库驱动,项⽬最终打包部署的时候也是需要数据驱动的,否则你⽆法连接数据库和操作 Sql 语句.4.5、system表⽰使⽤本地系统路径下的 jar 包,需要和 systemPath 配合使⽤,典型的例如 Oracle 数据库驱动: ojdbc.jar ,它是未授权 Maven 中央仓库的(刚刚去 Maven 中央仓库发现有,但是我们就假设它没有被Maven 中央仓库录⼊)有些 jar 包可能因为授权的问题或者是⼀些个⼈的 jar 包,这些 jar 包不会被 Maven 中央仓库录⼊,这个时候如果我们想在项⽬中使⽤这些 jar 包的话,我们可以先将 jar 包下载先来,然后可以在 pom.xml 中配置指向本地某个 jar 包的路径,引⼊相关的 jar 包对主程序是否有效对测试程序是否有效是否参与打包是否参与部署典型例⼦compile 是是是是spring-context test 否是否否junit provided 是是否否servlet-api 、jsp-api runtime 否否是是mysql-connector-java system -----引⼊ Oracle 驱动之后就可以使⽤了,没有出现报错其实吧,我觉得如果某些 jar 包 Maven 中央仓库没有录⼊,我们可以将需要的 jar 包下载下来,然后上传到私服中,通过左边从私服中下载就可以了.这⾥总结⼀下 scope 依赖范围4.6、远程仓库 repositoriesrepositories:⽤来配置当前⼯程使⽤的远程仓库依赖查找顺序:本地仓库--->当前⼯程 pom.xml 中配置的远程仓库--->⽤户级别的 settings.xml 中配置的远程仓库----> 全局 settings.xml 中配置的远程仓库---->Maven 中央仓库应⽤场景：如果有些 jar 包在 Maven 中央仓库没有,但是在其他仓库(例如:阿⾥仓库、spring 仓库、mybatis 仓库)⾥是有这个 jar 包的,例如 spring 新发布了⼀个版本,由于是刚发⾏的版本,性能不太稳定,这个时候Maven 中央仓库⼀般不会将这些 jar 包录⼊,但是你就是想⽤ spring 最新的版本,那么可以在 pom.xml 中通过配置 repositories 从指定的某公司官⽅仓库来获取相应的 jar 包<repositories><repository><id>spring_repo</id><name>Private Repository</name><url>http://repo.spring.io/milestone</url><layout>default</layout><releases><enabled>true</enabled><updatePolicy>always</updatePolicy><checksumPolicy>warn</checksumPolicy></releases><snapshots><enabled>true</enabled><updatePolicy>always</updatePolicy></snapshots></repository><repository><id>alimaven</id><name>aliyun maven</name><url>/nexus/content/groups/public/</url></repository></repositories>4.7、插件 plugins插件,就是⼀种⼯具.常见的如:清理插件 maven c lean p lugin ,编译插件 maven c ompile p lugin插件和依赖的区别:插件是⼯具,偏向于开发环境.和项⽬功能、源码、打包好的 jar 包没有任何关系.插件和依赖的关系,类似于 IDEA ⼯具和上线的 jar 包.Maven 的核⼼⽂件很⼩,主要的任务都是由插件来完成.定位到：%本地仓库%\org\apache\maven\plugins ,可以看到⼀些下载好的插件4.7.1、插件的⽬标 (Plugin Goals)⼀个插件通常可以完成多个任务,每⼀个任务就叫做插件的⼀个⽬标.如执⾏ mvn install 命令时,调⽤的插件和执⾏的插件⽬标如下4.7.2、将插件绑定到⽣命周期Maven 的⽣命周期是抽象的,实际需要插件来完成任务,这⼀过程是通过将插件的⽬标 (goal) 绑定到⽣命周期的具体阶段 (phase) 来完成的.例如将 maven-compiler-plugin 插件的 compile ⽬标绑定到 default ⽣命周期的 compile 阶段,完成项⽬的源代码编译.Maven 对⼀些⽣命周期的阶段（phase）默认绑定了插件⽬标,因为不同的项⽬有 jar、war、pom 等不同的打包⽅式,因此对应的有不同的绑定关系,其中针对 default ⽣命周期的 jar 包打包⽅式的绑定关系如下第⼆列中,冒号后⾯即是绑定的插件⽬标,冒号前⾯是插件的前缀(prefix),是配置和使⽤插件的⼀种简化⽅式.4.7.3、⾃定义绑定⽤户可以根据需要将任何插件⽬标绑定到任何⽣命周期的阶段, 例如将 maven-source-plugin 的 jar-no-fork ⽬标绑定到 default ⽣命周期的 package 阶段, 这样,以后在执⾏ mvn package 命令打包项⽬时,在 package 阶段之后会执⾏源代码打包,⽣成如 ehcache-core-2.5.0-sources.jar 形式的源码包.<build><plugins><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-source-plugin</artifactId><version>2.2.1</version><executions><execution><id>attach-source</id><phase>package</phase><goals><goal>jar-no-fork</goal></goals></execution></executions></plugin></plugins>……</build>4.7.4、pom.xml 中配置插件<build><plugins><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-clean-plugin</artifactId><version>3.0.0</version></plugin><plugin><groupId>org.apache.tomcat.maven</groupId><artifactId>tomcat7-maven-plugin</artifactId><version>2.2</version><configuration><path>/xiaomaomao</path><port>8888</port></configuration></plugin></plugins></build>这⾥有个很奇怪的现象,我使⽤ IDEA 帮我创建 Web 项⽬, IDEA ⾃动帮我下载了插件,其中 maven-clean-plugin 插件的版本是 3.1.0 ,我这⾥把插件的版本替换成了 3.0.0然后看⼀下我们加⼊的 maven-tomcat 插件五、超级 pom当我们利⽤ IDEA 为我们创建⼯程的时候,我们没有进⾏任何配置,为什么能下载各种插件呢?这是由于存在超级 pom 的原因,所有的 Maven 项⽬都要继承超级 pom,⾥⾯有 Maven 默认的⼀些配置超级 pom 存放位置: Maven 的安装⽬录\bin\maven-model-builder-3.6.0.jar\org\apache\maven\model\pom-4.0.0.xml解压开 maven-model-builder-3.6.0.jar 这个压缩包,⾥⾯有两个⽬录在 org/apache/maven/model/ ⽬录下有⼀个 pom-4.0.0.xml ,这个 pom 就是超级 pom ,例如⾥⾯就配置了相关的仓库信息。

2025届高中英语一轮话题复习(教师版)：主题三人与自然语境33 自然科学研究成果

主题对接教材北师大版选择性必修第三册Unit 9Human biologyⅠ.阅读单词——会意1．phenomenon n．现象2．lung n．肺3．atom n．原子4．camel n．骆驼5．cattle n．牛6．goat n．山羊7．gene n．基因8．ape n．猿9．inferior adj.低级别的，下级的；差的，次的10．bacteria n．细菌11．zone n．地区，地带12．artificially ad v.人为地，人工地13．clue n．线索，提示14．arbitrary adj.任意的15．intake n．摄入量，摄取量16．embryo n．胚；胚胎；萌芽时期17．hatch v t.& v i.孵出；孵化18．ethical adj.伦理的；合乎道德的19．organ n．器官20．curse n．祸端，祸根；诅咒；咒语Ⅱ.重点单词——记形1．twin n．双胞胎中的一个2．forever ad v.永远；长久地3．mere adj.仅仅，只不过4．breakthrough n．突破，重大进展5．bother v t.打扰v i.操心n．烦扰6．trial n．试验；审判，审理7．symptom n．症状；征兆，征候8．crucial adj.至关重要的，关键性的9．bound adj.很有可能，肯定会10．private adj.私有的，自用的；私营的，民营的11．infer v t.(inferred；inferred)推断，推定12．widespread adj.分布广的，广泛流传的13．outbreak n．(战争或疾病)爆发，突然发生14．underline v t.强调，使突出；在……之下画线15．clone v t.克隆，使无性繁殖n．克隆动物或植物，无性繁殖的个体16．pose v t.造成，引起，产生(问题、危险、困难等) n．(为画像、拍照等而摆的)姿势，姿态17．scan v t.(scanned；scanned)细看；浏览；扫描检查(物体或身体部位等)；(机器或计算机程序)扫描18．abuse v t.滥用，妄用；虐待n．滥用；虐待Ⅲ.拓展单词——悉变1．wholly ad v.完全地→whole adj.完整的；全部的2．differ v i.不同；相异→different adj.不同的→difference n．不同；差异3．estimate v t.& n．估计，估算→estimation n．估计；估算；判断4．capable adj.有能力的；有才干的→capability n．(完成困难事情的)能力，才能→incapable adj.无能力的；不能胜任的5．calculate v t.计算，核算→calculation n．计算→calculator n．计算器6．edit v i.& v t.编辑，编校；剪辑，剪接→editor n．编辑；主编→edition n．版(本) 7．innovate v i.& v t.革新，创新，改革→innovation n．创新；改革8．compare v t.& v i.比较，相比，比作n．比较→comparison n．比较9．contain v t.包含，容纳；控制→container n．容器；集装箱10．regulation n．规则；规章；法规→regulate v t.调节；管理11．identical adj.完全相同的，同一的→identity n．身份；同一性；一致12．classify v t.将……分类；把……归入一类→classification n．归类，分类，分级13．accumulate v i.(数量)逐渐增加v t.积攒→accumulation n．积累，堆积；堆积物，堆积量14．object v i.反对；不赞成n．物体；对象→objection n．不赞成；反对；异议→objective adj.客观的；无偏见的n．目标15．oppose v t.反对；反抗→opposed adj.反对的；对立的→opposition n．反对16．blessing n．福气，幸运→bless v．祝福；使有幸……→blessed adj.神圣的；幸福的17．treat v t.治疗；对待→treatment n．治疗；疗法；对待方式18．bury v t.埋葬，安葬；埋藏→burial n．埋葬，葬礼19．physicist n．物理学家→physical adj.身体的；物质的；物理(学)的；根据自然规律的→physically ad v.肉体地，身体上地；依据自然规律，根本上1．provoke v t.激起，引起2．primate n．灵长目动物3．betterment n．(个人社会和经济地位的)改良，改善，提高4．reproductive adj.繁殖的，生殖的5．constitution n．体质；身体素质；宪法；章程6．impulse n．(神经)冲动；(电)脉冲7．corresponding adj.相应的；对应的8．skyrocket v．激增；猛涨9．commercialize v．使商业化；利用……牟利10．compulsory adj.必须做的；义务的；强迫的；强制的Ⅳ.背核心短语1．die of死于……2．suffer from遭受……3．be bound to必定4．according to根据5．a form of...一种……形式6．have the potential to do sth有潜能做某事7．a number of许多，大量的8．be devoted to致力于……9．be buried in埋头于/专心于……10．apply to适用于；应用于11．identify...as...确认……是……12．differ from sb/sth in...在……方面与某人/某物不同13．suspect sb of (doing) sth 怀疑某人(做)某事；怀疑某人有罪14．get through用完，耗尽；接通；(设法)处理；完成；度过，熬过15．depend on/upon 取决于16．carry out履行；执行Ⅴ.悟经典句式1．that 引导表语从句The advantage is that if there is a new illness some of these animals may die，but others will survive and pass on the ability to resist that disease to the next generation.其优点是如果出现某种新的疾病，这类动物中的一些可能会死掉，而另一些却能存活下来，并把抵抗这种疾病的能力传给下一代。

高中英语人教版(2019)选择性必修第三册Unit3 Environmental Protect

the world.
10
We all share a great responsibility to protect the environment, without which we could not survive. However, the amount and scale of environmental issues may seem too much for ordinary people. But with hard work and determination, anyone can achieve great things.
One such person is Yin Yuzhen. At a young age, Yin moved to Inner Mongolia to live with her husband in the desert. She felt very lonely. To improve the tough environment and cheer herself up, Yin began planting trees to take land back from the desert. “I would rather die of tiredness from fighting the sand than be buried by it !” she said.
4
Ben Drake, an export on air pollution, is being interviewed on the radio. He said that smog was a severe problem _in__th_e__e_a_rl_y_2_0_t_h_century in Britain. At that time, Britain was experiencing a boom in _i_n_d_u_s_tr_y_. Factories and homes _u_se_d__lo_t_s_o_f_c_o_a_l_, which created smog. He also mentioned the heavy smog in London __w_a_s_p_a_r_ti_c_u_l_a_rl_y_b_a_d__a_n_d_c_a_u_s_e_d _o_v_e_r_4_0_0_0__d_e_a_th_s_ in 1952. Later the UK government restricted _b_u_rn__in_g __c_o_a_l_in homes and forced factories to__m__o_v_e_a_w__a_y_f_ro_m___ci_t_y_c_e_n_te_r_s_. As smog is harmful to everyone, the expert advised us to __re_p_l_a_c_e_c_o_a_l_ _w__it_h_c_l_e_a_n_e_r_f_o_rm__s_o_f_e_n_e_r_g_y_, use ___n_e_w__e_n_e_r_g_y_-e_f_fi_c_ie_n_t__ve_h_i_c_le_s___, and further develop _g_r_e_e_n_t_e_c_h_n_o_lo_g_y__.

人教版(2019)选择性必修第三册Unit 3 Environmental Protection大单

人教版（2019）选择性必修第三册Unit 3 Environmental Protection大单元整体学习学程设计高二英语大单元整体学习学程设计Unit3 Environmental Protection——Make environmental proposals班级：____小组：____姓名：____单元概述【单元内容】The theme of this unit is human and nature, whose topic is Environmental Protection. Just as Mohandas K. Gandhi said, “Earth provides enough to satisfy every man’s needs, but not every man’s greed.", in this unit you will be aware of the impacts of human activities on the environment, explore diverse environmental problems, work out the causes, impact and measures of some serious environmental problems in order to solve them. Moreover, you are hoped to put the measures you learned into practice in your daily life, and try to live a harmonious life with nature.【课标要求】核心素养课标要求语言能力语言知识词汇能正确使用与“环境保护”主题相关的词和词块来理解和表达。

语法能够理解并正确运用直接引语和间接引语的转换规则，能根据不同语境将陈述句、一般疑问句、特殊疑问句和祈使句形式的直接引语转述为间接引语，提升语言表达的丰富性。

Structural reliability calculation based on JC method

Structural reliability calculation based on JC methodWang Chang-longSchool of civil engineering Hebei University of EngineeringHandan, ChinaWangchanglong11@Abstract —In order to make a set of complete theoretical calculation methods of structure design on crest spillway of face rockfill dam, proposed from view of the mechanical point 㧘according to stability analysis of chute bottom slab for crest spillway of face rockfill dam, obtained the anti-slide stable performance function, used computer program of JC method to calculate structural reliability. Applications showed the theoretical design method can further improve the structure design theory of crest spillway of face rockfill dam, it can achieve the better and credible calculating results, provide the reference for future engineering applications.Keywords- rockfill dam; spillway;structure design; JC method; reliabilityI. I NTRODUCTIONBuilding the spillway of reservoirs in the steep mountainscross-strait, mountain strong and no suitable pass area, it is high cost. So it was innovation to build spillway on the top of dam. The construction method of vibrating rolling concrete was used since the 1960's, dam deformation significantly reduced, it has been become impossible to build spillway on the top of dam. If normal or non-normal spillway was directly arranged on the top of the dam, it had a series of advantages of simplified hub layout , low ost and convenient construction. So the research was been wide range attention by engineering. At present, there are some successful example overflow concrete face rockfill dam was built ,such as Crotty in Australia [1], Xinjiang’s Yushugou in China. But up to now ,structure design of face rockfill dam’s spillway is no a set of complete theory. It is necessary to further research on the theoretical method of structure design. The paper based on the mechanical point, analyzed the theory structure design on crest spillway of face rockfill dam, obtained performance function of anti-slide stability floor, used computer program of JC method totheoretical design method that can achieve the better and credible calculating results. II.A NTI -SLIDE STABILITY ANALYSIS OF CHUTE BOTTOMSLABSchematic diagram and slab stress diagram of bottom sliding instability are respectivelyshown Figure 1and Figure 2. Let0,0=≤¦¦y xF F,03=¦G M by Figure 1 andFigure 2, then0cos sin 21313214321≤+−−−+++++++αα䯵䯴䯵䯴F F F N G G G W W W W T (1)sin cos 21132143212=+−−++++++−+Δαα䯵䯴䯵䯴F F N G G G W W W W N F p (2))()2sin 2()2sin 2()32cos 2()2cos 2(2cos 2)(()2cos 2()cos 22(21113221′′−+′++′+++″+′+++′+′+++++++′++++l l lF l F l a s lW l a s l W l a s l W W a s l l G l a s G δδδδαδαααααα (3) ″+′=111W W W , ′1W is filling material’s weight ofrectangular part on the dam of level-resistance floor top,2009 IITA International Conference on Services Science, Management and Engineeringl bh r W t ′=′1,″1W is filling material’s weight of triangularpart on the dam of level-resistance floor top,2121l bty r W t ′=″α; 2W is chute floor’s weight on the damof level-resistance floor top, δαb l r W c cos 2′=; 3W iswater weight of floor top, h b l r W αcos 03′=; 4W is waterweight of floor top, h lb r W 04=; h lb r W 04=; 1G isbuttress dead weight; 2G is dead weight of level-resistance floor,δ′′++=b l a s r G c )(2;3G is floor dead weight,δlb r G c =3; T is flow drag force, 31220hv n l r T =; p F Δ isfluctuating pressure, lb r v F p 022905.0±=Δ; 1N is supportingforce of the dam filler to level-resistance floor, 2N is supporting force of the cushion to floor; 321F F F 䯸䯸 isrespectively the friction of upper and lower surface and damfiller, the cushion and floor, f G W W W F ′+++=䯵䯴13211,f G W W W F ′+++=䯵䯴13211,f N F ′=12,f N F 23=.l ′and δ′is respectively length and thickness of level-resistance floor, ,l b,δis respectively length, width and thickness of floor; a is buttress bottom long ˄determined by the construction norms ˅; s is the distance between the edgeof buttress and the upper end plate (determined by the construction norms)˗ is the average water depth of top plate. h ′is average height of buttress on the level-resistance floor (determined by the construction norms). h is maximum water depth;˗,c r ,0r t r is respectively concrete bulk density,water bulk density and dam filler bulk density,3m t˗n isfloor roughness; v is maximum velocity ˗f ˈf ′isrespectgively the friction coefficient of upper and lower surface and dam filler, the cushion and floor, value range is [0.6,0.8], the paper checks 0.6 [2,3,4]. Conclusion that by the type (1) and (3).cos cos sin 11321132143212≤′−′+++−−+++++++−αααf N f G W W W N G G G W W W W f N T 䯵䯴䯵䯴 (4))cos sin (sin )(cos )(1132132143212=−′+−′++++++++++=ΔN f F f G W W W G G G W W W W N p αααα(5)»»»»»»»»»»»»¼º««««««««««««¬ª+−′+++′′+′+++++′+−−+++−′+++++−−−+++″+′×′+=Δ)sin 2cos 2()32cos 2(2cos 2)((2cos 2)2cos 2()cos 222cos 2(2)cos 2)((214132131221321111αδαδααδαδααδαδαf W l a s l W l a s l W W W T f G s a l G f l a s l G fF a s l C G W W W W l C N p(6) Where αδααδαδcos 2sin 2sin 2cos 221f f l f f l f C −′−′++′′=a s lf f f f f lC +++′−−′′+′=ααδαδδαcos 2sin 2cos 22sin 22 safety factor of Anti-slide stabilityαααsin cos sin 32143212113䯵䯴䯵䯴G G G W W W W T F F N F K ++++++++++=(7)III. C OMPUTER PROGRAME OF STRUCTURAL RELIABILITYCALCULATION BASED ON JC METHODThe programe used LabVIEW languages. LabVIEW itself is software development environment of relatively complete function, but it was designed for replacing normal BASIC or C languages. LabVIEW is program languages that is not just software development environment [5]. As languages to write application programs, LabVIEW possess all the characteristics of language expect programming in different ways, so it was also called G language.It is a normal programming language to apply on any programming task and the expansion of the generic library. G language concludes commonly used program debugging tools,such as permit setting breakpoints, single-step debugging, probe data andthe implementation process was dynamic display. It is the greatest difference on programming ways between G language and traditional high-level programming language. Text programming was used by normal high-level programming language, while the way was used by the G graphical programming language. The programme has good visibility, the modular programming was better reflected and debugging easier. Program diagram is shown Figure 3 [6].Figure 3. Program diagram.IV. C ASE STUDY [7]Crotty dam height is 83m ˈmaximum flow is 245m 3/s ˈspillway width is 12.2m ˈchute slope is 1:1.5ˈmaximum velocity is 30m/s ˈthe largest single-wide follow 20m 3/s/m, floor size of length, width, thicknessness is respectively 12m, 12m and 0.5m ˈlevel-resistance floor length is 10m,width 0.3m, the width is same with floor, caculating reliability of chute bottom slab.The anti-slide stability performance function is3120027.08.599.9564.2696.238.179.39832.0555.0hv t h r kh kt krkm m nf Z −−−−+++++=The variables value of performance function was shown in Table 1.TABLE I.V ARIABLES VALUE OF PERFORMANCE FUNCTION variable n fmkr t h vdistribution typeextreme value Ilognormal extreme value I lognormal normalnormalnormalnormalmean -116.826 0.6 487.687 0.6 2.1 2.4 0.7 30 standarddeviation-58.413 0.12 243.841 0.12 0.042 0.048 0.035 6We can know the reliable indexes 4749.2=βof floorfrom the calculation results was shown procedures on the front panel ˈtransformed into reliabilityis was ()%87.99=Φβ. China's building structure design had provided uniform standards for the buildings that was only in the static load such as reliable index value shown in Table 2.Figure 4. Schematic diagram of calculation results. TABLE II. S PECIFIED VALUE OF TARGET RELIABILITY INDEXdmage typegrade of securityI˄important˅ II˄general˅III(secondary)ductility 3.7 3.2 2.7brittle 4.2 3.7 3.2If the buildings are under the dynamic load and static load combination, its target reliability index is small than value of the above provisions, generally between 1-2. So the floor can meet the stable requirement.V.C ONCLUSIONSAccording to the above theoretical analysis and calculation, we can draw the following conclusions.The design method of structural reliability is an applicable method, JC method is one of the effective ways to realize the design method.LabVIEW language achieve modular programming, and process all the cycle data as form displayed on the front panel, that is intuitive and convenient.From the above results can be seen, only by experience to determine the spillway of face rockfill dam size is not enough. From the reliability calculation of case study, a reliable index of the floor has been beyond the scope of stability requirements, showed that the floor was not the optimal form.To get the best floor forms, need for further structural analysis.R EFERENCES[1]S.Y. Li, “Crotty CFRD dam spillway body design and operation ofmonitoring,” Express water resources & hysripower information, vol.20, pp.17-20, Aug. 1999.[2]Shi Kebin, Huo Hongli, Bai Junwen, “Stability analysis of the chutebottom slab with the horizontal anti-slide slab for the crest spillway of rockfill dam,” Water power, vol.31, pp. 23-25, Sep. 2005.[3]Zhou Feng, Shi Kebin, Li Yujian, “Stability analysis of the chutebottom slab with anchorage of crest spillway of rockfill dam,” Water power, vol.33, pp. 32-34, June 2007.[4]Wu Shiwei, Structural reliability analysis,Nanjing: Hohai universitypress, 2002.[5] Li Jixiang, Xie Guihua, Liu Jianjun, “Improvement and application ofthe JC method in calculating structural reliability,” Journal of Hunan university of science & technolog, vol.20, pp. 33-36, Sep. 2005.[6] Huo Hongli, Shi Kebin, “A new computer program of JC method forcomputation of structure reliability,” Water resources and hydropower engineering, vol.36, pp. 41-43, March 2005.[7] Tao Li, “Computer program of calculating structure reliability with JCmethod,” Journal of water resources and architectural engineering, vol.6, pp. 32-34, June 2008.。

The Heuristic Model

This study
Simultaneously minimizes cost and environmental impact
Notebook EOL process as an example
A HEURISTIC MODEL

Heuristic means “find” or “discover”. non-quantitative “soft” method. To use the input of trained professions. To build a database of possible outcomes. Useful in this scenario.

What they can learned from the model? Reach the final aim: Use the model(heuristic approach ,Compromise programming, Pareto Efficiency) looking for the best EOL recycling processes maximize benefit and minimize environmental impact.
Introduction
End-of-life Products (EOL)
WEEE
EWRB & EWRA
Administrative Measures
Global Electrical and electronic product producers Most economical EOL process Smallest environmental load

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a r Xiv:as tr o-ph/49188v18Se p24Model of the W3(OH)environment based on data for both maser and ‘quasi-thermal’methanol lines Andrei M.Sobolev Ural State University,Russia Edmund C.Sutton University of Illinois at Urbana-Champaign,USA Dinah M.Cragg Monash University,Australia Peter D.Godfrey Monash University,Australia April 15,2004Abstract.In studies of the environment of massive young stellar objects,recent progress in both observations and theory allows a uniﬁed treatment of data for maser and ‘quasi-thermal’lines.Interferometric maser images provide information on the distribution and kinematics of masing gas on small spatial scales.Observations of multiple masing transitions provide constraints on the physical parameters.Interferometric data on ‘quasi-thermal’molecular lines permits an investigation of the overall distribution and kinematics of the molecular gas in the vicinity of young stellar objects,including those which are deeply ing multiple transitions of diﬀerent molecules,one can obtain good constraints on the physical and chemical bining these data enables the construction of uniﬁed models,which take into account spatial scales diﬀering by orders of magnitude.Here we present such a combined analysis of the environment around the ultra-compact HII region in W3(OH).This includes the structure of the methanol masing region,physical structure of the near vicinity of W3(OH),detection of new masers in the large-scale shock front and embedded sources in the vicinity of the TW young stellar object.Keywords:radiolines –ISM:molecules 1.Possibility of combined analysis of data on maser and‘quasi-thermal’linesModern studies of the kinematical,physical and chemical status of star forming regions are largely based on the information delivered by emission in molecular lines.Diﬀerent molecular transitions have diﬀer-ent excitation temperatures,as a result of the radiative and collisional population exchange between quantum levels.In the stationary case these take the form of pumping cycles (see,e.g.,Sobolev and Deguchi,1994).Excitation states of molecular transitions are mostly character-ized by positive excitation temperatures and,hence,the optical depths c 2008Kluwer Academic Publishers.Printed in the Netherlands.2 A.M.Sobolev et al.of the corresponding lines are mostly positive.Such lines are called ‘quasi-thermal’and trace the whole extent of the suﬃciently dense and warm environment of the massive young stellar object where the corresponding molecule is abundant.Under speciﬁc conditions,in some regions of a molecular cloud the pump cycles can lead to extreme overheating of some quantum transi-tions and their excitation temperatures might become negative(see, e.g.,Sobolev and Deguchi,1994).In this case the optical depth of the corresponding line becomes negative and emission from material which is more distant from the observer is ampliﬁed at the transition frequency instead of being hidden.Such extreme deviation from the local thermodynamic equilibrium(LTE)is called a maser and often leads to extremely bright lines arising from compact areas which can be substantially smaller in size than the region where the maser is formed(see,e.g.,Sobolev et al.,1998).At present,combined analysis of the data in both types of lines(i.e., maser and‘quasi-thermal’)is uncommon.The main reason is that the spatial resolutions used in the maser research(rather small fractions of an arcsecond,down to microarcseconds)and in the‘quasi-thermal’line research(arcseconds and tens of arcseconds)are greatly diﬀerent.From the time of its discovery,maser emission has provided very important information on the nature and kinematics of associated ob-jects.Despite this,the structure of the masing regions themselves is rather unclear;these are the regions where maser ampliﬁcation may develop along particular lines of sight due to the existence of pop-ulation inversion.For example,current models of maser excitation meet great diﬃculties in trying to produce extremely bright masers in regions matching the sizes of the tiny maser hot spots which are determined interferometrically.At the same time there are indications that the masing regions have extensions much greater than these spot sizes.Indeed,analysis of multi-transitional observations of a masing molecule such as methanol(CH3OH)shows that the sizes of the masing regions can be comparable to those of the associated molecular cores (see,e.g.,Sobolev,1993,Slysh et al.,1999).There are indications that strong masers also form in rather extended regions.Firstly,VLBI ob-servations show that the strongest H2O and CH3OH masers have a ‘core-extended halo’structure(see,e.g.,Gwinn,1994,Minier et al., 2002).Secondly,absorption lines are detected with the100-m tele-scope that correspond to transitions which are considerably overcooled only under conditions where the masing transitions are strongly in-verted(Menten et al.,1986).One such line was observed with the VLA(Wilson et al.,1991).So,modern interferometry in some casesModel of W3(OH)environment3 can provide the basis for combined analysis of data in both maser and ‘quasi-thermal’types of lines.In this paper we analyse the data on methanol lines obtained with the BIMA interferometer.In theﬁrst section we show that the masing region can beﬁlled with numerous optically elongated structures which are responsible for producing maser spikes and accompanying pedestal proﬁles.Analysis of the data provides estimates of the physical param-eters of the masing gas.In the second section we show that combined analysis of the data on the maser and‘quasi-thermal’methanol lines re-veals the physical structure of the vicinity of the W3(OH)ultracompact HII region.It is also shown that the size of the masing region exceeds that of maser hot spot sizes by orders of magnitude.In the third section we provide evidence that analysis of the‘quasi-thermal’line data may indicate the presence of previously unknown masing objects to the south-west of W3(OH),which are to be studied by interferometrical means.In turn,the data on the H2O masers around the TW object to the east of W3(OH)show the presence of molecular material which can be detected in‘quasi-thermal’line emission.2.Analysis of the methanol line emission and absorption atW3(OH)The BIMA interferometer was used to observe24methanol lines in 3mm and1mm wavelength ranges toward W3(OH)with a spectral resolution better than1.2km/s.Details of the observations are de-scribed in(Sutton et al.,2004).This source is a prototypical class II methanol maser source.Emission in9transitions which were pre-dicted to mase under certain conditions(Sobolev et al.,1997)was de-tected(Sutton et al.,2001).Some lines display pronounced narrow maser spike and pedestal proﬁles while others show the pedestal com-ponent alone.Analysis of this data on newly discovered masers and maser candidate lines has brought considerable improvement to the model of the masing region in front of W3(OH).It was shown that maser action takes place in hot(about150K), dense(2×106cm−3),methanol-rich gas in front of the UCHII region, pumped by infrared radiation from warm dust.The observed variety of maser line proﬁles andﬂux ratios can be explained if the maser spike emission from W3(OH)arises in the region where maser ampliﬁcation is moderate and directional,whereas for the pedestal emission the maser action is weaker and directed less strongly towards the observer.This can be a result of the geometry of the maser region containing some regions greatly elongated along the line of sight and others elongated4 A.M.Sobolev et al.in diﬀerent directions.The model predicted strong absorption in6 methanol lines with frequencies84.52121,85.56807,94.54181,95.16952, 105.06376,and109.15321GHz.The six lines which were predicted to show absorption in the masing region show double peaked proﬁles.These are not consistent with two emission components atﬁxed velocities,but,rather,can be wellﬁtted with a superposition of2gaussians corresponding to common emitting and absorbing regions(seeﬁgure1).Excitation analysis in the way described in(Sutton et al.,2001)has shown that the depths of the ab-sorptions are well in accord with the model predictions.Figure2shows that emission in the maps of absorbing lines at the maser velocities comes from a diﬀerent spatial position than does the bulk of emission in maser lines.That means that the size of the masing region is compa-rable to the total spread of the6.7GHz class II methanol maser spots. Modelling of the methanol lines in the way described in(Sutton et al., 2001and Sutton et al.,2004)is consistent with the hypothesis that 2methanol-rich regions are situated in front of the ultracompact HII region(UCHII)in W3(OH):theﬁrst being a rather hot(greater than 200K)and dense(greater than108cm−3)methanol emitting region with angular size slightly exceeding that of the UCHII,and the second region producing the strong masers and absorptions.The latter has a size of order1arcsecond,which is about3orders of magnitude greater than that of the6.7GHz maser spots,and corresponds to the total extent of the region where the strong class II methanol masers are distributed.So,BIMA observations have shown that the methanol maser region in W3(OH)has a size of a few by1016cm,and provided estimates of the physical parameters on the basis of combined analysis of the masing and quasi-thermally excited lines.3.How‘quasi-thermal’line observations help reveal masersand vice versaSutton et al.(2004)showed that BIMA observations reveal the presence of extended features to the south-west of W3(OH)which are traced by the methanol line emission(see also lower panels inﬁg.2).Methanol is a chemical tracer of shocked regions,and analysis of the spatial structure of its emission in regions of massive star formation can lead to the discovery of extremely young stellar objects displaying maser emission (Sobolev and Strelnitskii,1982).Indeed,Sutton et al.(2004)found2 objects which are most pronounced in the Class I methanol maser lines. Excitation analysis carried out in this paper shows that these lines are most probably weak masers,which can be conﬁrmed by interferometricModel of W3(OH)environment5Figure1.BIMA spectra of6methanol lines which were predicted to absorb in the methanol masing region.Fits with2gaussians corresponding to common emitting (V LSR=−44.9km/s)and absorbing(V LSR=−44.6km/s)regions are shown.The line proﬁles are not consistent with two emission components atﬁxed velocities. This suggests that there is an absorbing region situated closer to the observer.So, it is likely that we see absorption against the line emitting background.6 A.M.Sobolev et al.Figure2.BIMA maps of W3(OH)in the methanol lines.The upper row of channel maps corresponds to the line at84.5GHz which shows strong absorption in the model(Sutton et al.,2001)and displays an absorption dip in the spectrum shown inﬁgure1.It is seen that no emission comes from the northern part of the source in the central and right panels corresponding to velocities of the dip.The middle row shows maps of the111.3GHz line which is transparent in the model and shows an uneven pedestal proﬁle.It is seen that emission comes from both northern and southern parts of the source at all line velocities.The lower row of panels shows maps of the107.0GHz line which is observed as a bright maser and behaves accordingly in the model.It is seen that emission in the central and right panels mostly comes from the northern part of the source where the methanol masing region described in the text is situated.Contour levels are0.4,0.8,1.2,1.6,2,4,6,8,and10Jy/beam. Interferometer beams are shown in the lower left corners of the leftmost panels. measurements with higher spatial resolution.This can be done with the forthcoming CARMA facility or with the VLA in counterpart lines of the same methanol line series.In turn,data on the maser emission of water around the TW young stellar object situated about6”to the east of W3(OH)shows the pres-ence of molecular material situated on both sides of the TW object with an almost equal angular separation of about1”.The nature of the ma-terial in the immediate vicinity of the TW object is unclear and can be explained in terms of the jet and edge-on disk(Shchekinov and Sobolev, 2004).Water masers are produced under very special conditions and can display great deviations from the systemic velocity of the source, i.e.,they might not reveal bulk motions of matter.So,observations of ‘quasi-thermal’molecular emission in the TW vicinity with appropriate angular resolution are very important to clarify the situation and,inModel of W3(OH)environment7 any case,help promote understanding of important processes related to the earliest stages of massive star formation.The existence of molecular material situated1”to the west of TW was clearly shown by inter-ferometry of red-shifted highly excited‘quasi-thermal’line emission (Wyrowski et al.,1997)and a compact continuum source was found at this position(Wyrowski et al.,1999).However,highly excited lines and the continuum did not indicate the presence of molecular material to the east of the TW object where the strongest water masers reside.In the paper by Sutton et al.(2004)it is shown that the TW object is surrounded by a dense envelope of molecular gas.This surrounding gas obscures the source interiors.However,Doppler shifted internal objects can display themselves in the line wings.We have searched for such emission in the wings of the strong low excitation lines of the methanol line quartet at96.7GHz.Because the lines are blended,we examined the blue wing of the96.74458GHz line and the red wing of the96.73939GHz line.Results of the search are shown inﬁgure3.We found the source to the west of TW in the red wing emission and found evidence of the existence of the blue-shifted methanol emission from the water maser site situated about1”east of TW.The later fact is also interesting from the chemical point of view because it shows that the water masers are formed in the methanol abundant region.So,masers have prompted the detection of‘quasi-thermal’line emission which can provide a clue for elucidating the nature of one of the most intriguing objects of early massive star formation.4.ConclusionsThis paper provides an example of how combined analysis of the inter-ferometry data on the maser and‘quasi-thermal’lines helps to elucidate the structural,physical and chemical status of the regions of massive star formation.Data on sets of both maser and‘quasi-thermal’lines allows estimates of the temperature,density,molecular abundances and source extensions and shapes.Weﬁnd that the numerous methanol transitions form a good basis for such types of studies both from the point of view of their high diagnostic capacity and because relevant lines are rather easy to observe with existing and forthcoming ra-dioastronomical facilities.We have also shown that information on ‘quasi-thermal’lines can reveal the existence of masing objects while the masers can prompt the detection of molecular material emitting in ‘quasi-thermal’lines.8 A.M.Sobolev et al.GHz.The cross marks the position of the TW object.The upper row of panels shows emission in the blue wing of the96.74458GHz line and the leftmost upper panel displays embedded material situated about1”east of the TW.The lower row of panels corresponds to the red wing of the96.73939GHz line and displays the embedded source to the west of the TW.The interferometer beam is shown in the lower left corner of the leftmost upper panel.AcknowledgementsAMS was supported by grants from 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