Distance of W3(OH) by VLBI annual parallax measurement
2023年12月英语六级听力原文含翻译第二套
翻译在最终Conversation OneM: Guess what? The worst food I've ever had was in France.W.Really.That'.odd..though.th.Frenc.wer.al.goo.cooks.M.Yes.That'.right..suppos.it'.reall.lik.anywher.else.though.Yo.kno w.som.place.ar.good.Som.bad.Bu.it'.reall.al.ou.ow.fault.W: What do you mean?M.Well.i.wa.th.firs.tim.I'.bee.t.France.Thi.wa.year.ag.whe..wa.a.sc hool..wen.ther.wit.m.parents.friends.fro.m.father'.school.They'.hire..c oac.t.tak.the.t.Switzerland.W: A school trip?M.Right.Mos.o.the.ha.neve.bee.abroa.before.We'.crosse.th.Englis. Channe.a.night.an.w.se.of.throug.France.an.breakfas.tim.arrived.an.t h.coac.drive.ha.arrange.fo.u.t.sto.a.thi.littl.café.Ther.w.al.were.tire.an.hungry.an.the.w.mad.th.grea.discovery.W: What was that?M: Bacon and eggs.W: Fantastic! The real English breakfast.M.Yes.Anyway.w.didn'.kno.an.better.s.w.ha.it.an.ugh...!W: What was it like? Disgusting?M.Oh.i.wa.incredible.The.jus.go..bow.an.pu.som.fa.i.it.An.the.the.pu.som.baco.i.th.fat.brok.a.eg.ove.th.to.an.pu.th.whol.lo.i.th.ove.fo.a bou.te.minutes.W.I.th.oven.You'r.joking.Yo.can'.coo.baco.an.egg.i.th.oven!M.Well.The.mus.hav.don.i.tha.way.I.wa.hot.bu.i.wasn'.cooked.The r.wa.jus.thi.eg.floatin.abou.i.gallon.o.fa.an.ra.bacon.W: Did you actually eat it?M.No.Nobod.did.The.al.wante.t.tur.roun.an.g.home.Yo.know.bac.t. teabag.an.fis.an.chips.Yo.can'.blam.the.really.Anyway.th.nex.nigh.w. wer.al.give.anothe.foreig.speciality.W: What was that?M.Snails.Tha.reall.finishe.the.off.Lovel.holida.tha.was!Questions 1 to 4 are based on the conversation you have just heard.Questio.1.Wha.di.th.woma.thin.o.th.French?Questio.2.Wh.di.th.ma.trave.wit.o.hi.firs.tri.t.Switzerland?Questio.3.Wha.doe.th.ma.sa.abou.th.breakfas.a.th.littl.Frenc.café?Questio.4.Wha.di.th.ma.thin.o.hi.holida.i.France?Conversation TwoM.Yo.sa.you.sho.ha.bee.doin.well.Coul.yo.giv.m.som.ide.o.wha.“doin.well.mean.i.fact.an.figures?W.Well.“doin.well.mean.averagin.￡1,lio.pounds.An.“s.year.w.di.slightl.ove.50,00.an.thi.y ear.w.hop.t.d.mor.tha.60,000.So.that'.goo.i.w.continu.t.rise.M.Now.that'.gros.earnings..assume.Wha.abou.you.expenses?W.Yes.that'.gross.Th.expenses.o.course.g.u.steadily.An.sinc.we'v.move.t.t hi.ne.shop.th.expense.hav.increase.greatly.becaus.it'..muc.bigge.shop.S..coul dn'.sa.exactl.wha.ou.expense.are.The.ar.somethin.i.th.regio.o.si.o.seve.thous merciall.speaking.it'.fairl.low.an.w.tr.t.kee. ou.expense.a.lo.a.w.can.M.An.you.price.ar.muc.lowe.tha.th.sam.good.i.shop.roun.about.Ho.d.th.lo ca.shopkeeper.fee.abou.havin..sho.doin.s.wel.i.thei.midst?W.Perhap..lo.o.the.don'.realiz.ho.wel.w.ar.doing.becaus.w.don'.mak..poin. o.publicizing.Tha.wa..lesso.w.learne.ver.earl.on.W.wer.ver.friendl.wit.al.loca.sh opkeeper.an.w.happene.t.mentio.t..loca.shopkeepe.ho.muc.w.ha.mad.tha.wee k.H.wa.ver.unhapp.an.neve.a.friendl.again.S.w.mak..poin.o.neve.publicizin.th. amoun.o.mone.w.make.Bu.w.ar.o.ver.goo.term.wit.al.th.shops.Non.o.the.hav. plaine.tha.w.ar.puttin.the.ou.o.busines.o.anythin.lik.that..thin.it'..nic.f riendl.relationship.Mayb.i.the.di.kno.wha.w.made.perhap.the.wouldn'.b.s.frien dly.Questions 5 to 8 are based on the conversation you have just heard.Questio.5.Wha.ar.th.speaker.mainl.talkin.about?Questio.6.Wha.doe.th.woma.sa.he.sho.trie.t.do?Questio.7.Wha.d.w.lear.abou.th.good.sol.a.th.woman'.shop?Questio.8.Wh.doesn'.th.woma.wan.t.mak.know.thei.earning.anymore?Passage OneBirds are famous for carrying things around.Some, like homing pigeons, can be trained to deliver messages and packages.Other birds unknowingly carry seeds that cling to them for the ride.Canadian scientists have found a worrisome, new example of the power that birds have to spread stuff around.Way up north in the Canadian Arctic, seabirds are picking up dangerous chemicals in the ocean and delivering them to ponds near where the birds live.Some 10,000 pairs of the birds, called fulmars, a kind of Arctic seabird, make their nests on Devon Island, north of the Arctic Circle.The fulmars travel some 400 kilometers over the sea to find food.When they return home, their droppings end up all around their nesting sites, including in nearby ponds.Previously, scientists noticed pollutants arriving in the Arctic with the wind.Salmon also carry dangerous chemicals as the fish migrate between rivers and the sea.The bodies of fish and other meat-eaters can build up high levels of the chemicals.To test the polluting power of fulmars, researchers collected samples of deposit from 11 ponds on Devon Island.In ponds closest to the colony, the results showed there were far more pollutants than in ponds less affected by the birds.The pollutants in the ponds appear to come from fish that fulmars eat when they're out on the ocean.People who live, hunt, or fish near bird colonies need to be careful, the researchers say.The birds don't mean to cause harm, but the chemicals they carry can cause major problems.Questions 9 to 12 are based on the passage you have just heard.Questio.9.Wha.hav.Canadia.scientist.foun.abou.som.seabirds?Questio.10.Wha.doe.th.speake.sa.abou.th.seabird.calle.fulmars?Questio.11.Wha.di.scientist.previousl.notic.abou.pollutant.i.th.Arctic?Questio.12.Wha.doe.th.speake.war.abou.a.th.en.o.th.talk?Passage TwoIn recent years, the death rate among American centenarians—people who have lived to age 100 or older— has decreased, dropping 14 percent for women and 20 percent for men from 2023 to 2023.The leading causes of death in this age group are also changing.In 2023, the top five causes of death for centenarians were heart disease, stroke, flu, cancer and Alzheimer's disease.But by 2023, the death rate from Alzheimer's disease for this age group had more than doubled—increasing from 3.8 percent to 8.5 percent—making the progressive brain disease the second leading cause of death for centenarians.One reason for the rise in deaths from Alzheimer's disease in this group may be that developing this condition remains possible even after people beat the odds of dying from other diseases such as cancer.People physically fit enough to survive over 100 years ultimately give in to diseases such as Alzheimer's which affects the mind and cognitive function.In other words, it appears that their minds give out before their bodies do.On the other hand, the death rate from flu dropped from 7.4 percent in 2023 to 4.1 percent in 2023.That pushed flu from the third leading cause of death to the fifth.Overall, the total number of centenarians is going up.In 2023, there were 72,197 centenarians, compared to 50,281 in 2023.But because this population is getting larger, the number of deaths in this group is also increasing— 18,434 centenarians died in 2023, whereas 25,914 died in 2023.Questions 13 to 15 are based on the passage you have just heard.Questio.13.Wha.doe.th.speake.sa.abou.th.ris.o.dyin.fo.America.centenari an.i.recen.years?Questio.14.Wha.doe.th.speake.sa.abou.Alzheimer'.disease?Questio.15.Wha.i.characteristi.o.peopl.wh.liv.u.t.10.year.an.beyond?Recording OneOkay.S.let'.ge.started.And to start things off I think what we need to do is consider a definition.I'm going to define what love is but then most of the experiments I'm going to talk about are really focused more on attraction than love.And I'm going to pick a definition from a former colleague, Robert Sternberg, who is now the dean at Tufts University but was here on our faculty at Yale for nearly thirty years.And he has a theory of love that argues that it's made up of three components: intimacy, passion, and commitment, or what is sometimes called decision commitment.And these are relatively straightforward.He argued that you don't have love if you don't have all three of these elements.Intimacy is the feeling of closeness, of connectedness with someone, of bonding.Operationally, you could think of intimacy as you share secrets, you share information with this person that you don't share with anybody else.Okay.That'rmatio.tha.i sn'.share.wit.othe.people.The second element is passion.Passion is the drive that leads to romance.You can think of it as physical attraction.And Sternberg argues that this is a required component of a love relationship.The third element of love in Sternberg's theory is what he calls decision commitment, the decision that one is in a love relationship, the willingness to label it as such, and a commitment to maintain that relationship at least for some period of time.Sternberg would argue it's not love if you don't call it love and if you don't have some desire to maintain the relationship.So if you have all three of these, intimacy, passion and commitment, in Sternberg's theory you have love.Now what's interesting about the theory is what do you have if you only have one out of three or two out of three.What do you have and how is it different if you have a different two out of three?What's interesting about this kind of theorizing is it gives rise to many different combinations that can be quite interesting when you break them down and start to look them carefully.So what I've done is I've taken Sternberg's three elements of love, intimacy, passion and commitment, and I've listed out the different kinds of relationships you would have if you had zero, one, two or three out of the three elements.Questions 16 to 18 are based on the recording you have just heard.Questio.16.Wha.doe.th.speake.sa.abou.mos.o.th.experiment.mentione.i.h i.talk?Questio.17.Wha.doe.Rober.Sternber.argu.abou.love?Questio.18.Wha.questio.doe.th.speake.thin.i.interestin.abou.Sternberg'.th re.element.o.love?Recording TwoHi! I am Elizabeth Hoffler, Master of Social Work.I am a social worker, a lobbyist, and a special assistant to the executive director at the National Association of Social Workers.Today we are going to be talking about becoming a social worker.Social work is the helping profession.Its primary mission is to enhance human well-being and help meet thebasic needs of all people, with a particular focus on those who are vulnerable, oppressed, and living in poverty.We often deal with complex human needs.Social work is different from other professions, because we focus on the person and environment.We deal with the external factors that impact a person's situation and outlook.And we create opportunity for assessment and intervention, to help clients and communities cope effectively with their reality and change that reality when necessary.In thousands of ways social workers help other people, people from every age, every background, across the country.Wherever needed, social workers come to help.The most well-known aspect of the profession is that of a social safety net.We help guide people to critical resources and counsel them on life-changing decisions.There are more than 600,000 professional social workers in the country, and we all either have a bachelor's degree, a master's degree, or a PhD in Social Work.There are more clinically trained social workers than clinically trained psychiatrists, psychologists, and psychiatric nurses combined.Throughout this series you will learn more about the profession, the necessary steps to get a social work degree, the rich history of social work, and the many ways that social workers help others.Later in this series, you will hear from Stacy Collins and Mel Wilson, fellow social workers at the National Association of Social Workers.Stacy is going to walk you through the step-by-step process of becoming a social worker, and Mel will tell you about the range of options you have once you get your social work degree, as well as the high standards of responsibility he social workers must adhere to.The National Association of Social Workers represents nearly 145,000 social workers across the country.Our mission is to promote, protect, and advance the social work profession.We hope you enjoy this series about how you can make a difference by becoming a social worker.Next, we are going to talk about choosing social work.Questions 19 to 22 are based on the recording you have just heard.Questio.19.Wha.doe.th.speake.mainl.tal.about?Questio.20.Wha.d.socia.worker.mainl.do?mon.accordin.t.th.speaker?Questio.22.Wha.i.Me.Wilso.goin.t.tal.abou.i.th.series?Recording ThreeToday, I'd like to talk about what happens when celebrity role models get behind healthy habits, but at the same time, promote junk food.Currently, there's mounting criticism of Michelle Obama's “Let's Move!”campaign, which fights childhood obesity by encouraging youngsters to become more physically active, and has signed on singer Beyoncéand basketball player Shaquille O'Neal, both of whom also endorse sodas, which are a major contributor to the obesity epidemic.Now there's a lot more evidence of how powerful a celebrity— especially a professional athlete— can be in influencing children's behavior.In a report published by the Rudd Center for Food Policy and Obesity at Yale University, researchers studied 100 professional athletes and their endorsement contracts.The team focused on athletes since they are theoretically the best role models for active, healthy lifestyles for children.After sorting the deals by category, they determined that among the 512 brands associated with the athletes, most involved sporting goods, followed closely by food and beverage brands.Sports drinks, which are often high in sugar and calories made up most ofthe food and drink deals, with soft drinks and fast food filling out the remainder.Of the 46 beverages endorsed by professional athletes, 93% relied exclusively on sugar for all of their calories.It's no surprise that high-profile athletes can influence children's eating behaviors, but the scientists were able to quantify how prevalent these endorsements are in the children's environment.Advertisements featuring professional athletes and their endorsed products tend to get impressive exposure on TV, radio, in print and online.And in 2023, the researchers reported that children ages 12 to 17 saw more athlete-endorsed food and beverage brand commercials than adults.One reason any campaign wants a popular celebrity spokesperson is because kids are attracted to them no matter what they are doing.We can't expect kids to turn off that admiration when the same person is selling sugar.At best, kids might be confused.At worst, they'll think the messages about soda are the same as the messages about water, but those two beverages aren't the same.If children are turning to athletes as role models, it's in their best interest if their idols are consistent.Consistent messaging of positive behaviors will show healthier lifestylesfor kids to follow.Questions 23 to 25 are based on the recording you have just heard.Questio.23.Wha.i.th.ai.o.Michell.Obama'.campaign?Questio.24.Wha.doe.researc.fin.abou.advertisement.featurin.professiona. athletes?Questio.25.Wha.doe.th.speake.thin.kids.idol.shoul.do?对话一男: 你猜怎么着？我吃过旳最难吃旳食物是在法国吃旳。
petrel-属性建模
Nugget: Degree of dissimilarity at zero • Vertical
distance.
Basic Statistics
Example of Experimental Variogram calculation Semi-variance for 1 Lag distance Semi-variance for 2 lag distance
- Determine Layer thickness - Determine directions/degree of Anisotropy - Determine correlation/connectedness of facies data
Used as Quality Control to compare data before and after modeling process
Variogram Map
Good for visualizing anisotropy and its direction.
Sample Variogram
Good for finding Major and minor Range horizont
Variogram Map – Theory
EXERCISE A WELL with a string of porosity values in depth steps of 1m: 3, 5, 7, 6, 4, 1, 1, 4. Calculate the variogram values for lags 1, 2, 3, and 4 m respectively. Plot the variogram. Is there a pattern?
Interstitials, Vacancies, and Supersolid Order in Vortex Crystals
D-85747 Garching, Germany David R. Nelson and Daniel S. Fisher Lyman Laboratory of Physics Harvard University Cambridge, Massachusetts 02138
1 = exp − 2 Gi Gj ui (r⊥ , z )uj (r⊥ , z )
(1.1)
by phonons is discussed in Ref. 7. Here, G is a reciprocal lattice vector and u(r⊥ , z ) is the displacement field of a flux lattice with vortices parallel on average to the z direction. Dislocation loops are a topologically distinct excitation which, when they proliferate at a melting transition, drive ρG (T ) to zero and can lead to a hexatic flux liquid with residual bond orientation order [8]. Isolated dislocation loops are far more constrained than their counterparts in crystals of point particles: dislocation loops in fact must lie in a plane spanned by their Burgers vector and the average field direction [9]—see Fig. 1a. Vacancies and interstitials differ even more dramatically from the analogous defects in crystals of point particles. The number of flux lines is conserved, which means that these defects are lines instead of points. The point-like nature of vacancies and interstitials in conventional crystals ensures that they are present in equilibrium at all finite temperatures for entropic reasons [10]. However, because such imperfections have an energy proportional 2
Surface wave higher-mode phase velocity measurements using a roller- coaster-type algorithm
Geophys.J.Int.(2003)155,289–307Surface wave higher-mode phase velocity measurements usinga roller-coaster-type algorithm´Eric Beucler,∗´El´e onore Stutzmann and Jean-Paul MontagnerLaboratoire de sismologie globale,IPGP,4place Jussieu,75252Paris Cedex05,France.E-mail:beucler@ipgp.jussieu.frAccepted2003May20.Received2003January6;in original form2002March14S U M M A R YIn order to solve a highly non-linear problem by introducing the smallest a priori information,we present a new inverse technique called the‘roller coaster’technique and apply it to measuresurface wave mode-branch phase velocities.The fundamental mode and thefirst six overtoneparameter vectors,defined over their own significant frequency ranges,are smoothed averagephase velocity perturbations along the great circle epicentre–station path.These measurementsexplain well both Rayleigh and Love waveforms,within a maximum period range includedbetween40and500s.The main idea of this technique is tofirst determine all possibleconfigurations of the parameter vector,imposing large-scale correlations over the model space,and secondly to explore each of them locally in order to match the short-wavelength variations.Thefinal solution which achieves the minimum misfit of all local optimizations,in the least-squares sense,is then hardly influenced by the reference model.Each mode-branch a posteriorireliability estimate turns out to be a very powerful instrument in assessing the phase velocitymeasurements.Our Rayleigh results for the Vanuatu–California path seem to agree correctlywith previous ones.Key words:inverse problem,seismic tomography,surface waves,waveform analysis.1I N T R O D U C T I O NOver the last two decades,the resolution of global tomographic models has been greatly improved,because of the increase in the amount and the quality of data,and due to more and more sophisticated data processing and inversion schemes(Woodhouse&Dziewonski1984, 1986;Montagner1986;Nataf et al.1986;Giardini et al.1987;Montagner&Tanimoto1990;Tanimoto1990;Zhang&Tanimoto1991; Su et al.1994;Li&Romanowicz1995;Romanowicz1995;Trampert&Woodhouse1995;Laske&Masters1996;Ekstr¨o m et al.1997; Grand et al.1997;van der Hilst et al.1997;Liu&Dziewonski1998;Ekstr¨o m&Dziewonski1998;Laske&Masters1998;M´e gnin& Romanowicz2000;Ritsema&van Heijst2000,among others).These models are derived from surface wave phase velocities and/or body wave traveltimes(or waveforms)and/or free-oscillation splitting measurements.Body wave studies provide high-resolution models but suffer from the inhomogeneous distribution of earthquakes and recording stations,even when considering reflected or diffracted phases.On the other hand,the surface wave fundamental mode is mainly sensitive to the physical properties of the upper mantle.So,the investigation of the transition zone on a global scale,which plays a key role in mantle convection,can only be achieved by using higher-mode surface waves.Afirst attempt at providing a global tomographic model using these waves has been proposed by Stutzmann&Montagner(1994),but with a limited amount of data.More recently,van Heijst&Woodhouse(1999)computed degree-12phase velocity maps of the fundamental mode and the fourfirst overtones for both Love and Rayleigh waves.These data have been combined with body wave traveltimes measurements and free-oscillation splitting measurements,to provide a global tomographic model with a high and uniform resolution over the whole mantle (Ritsema et al.1999;van Heijst et al.1999).The most recent S H model for the whole mantle was proposed by M´e gnin&Romanowicz (2000).This degree-24model results from waveform inversion of body and surface Love waves,including fundamental and higher modes and introducing cross-branch coupling.Extracting information from higher-mode surface waves is a difficult task.The simultaneous arrivals(Fig.3in Section3)and the interference between the different mode-branches make the problem very underdetermined and non-linear.To remove the non-linearity,Cara &L´e vˆe que(1987)and L´e vˆe que et al.(1991)compute the cross-correlogram between the data and monomode synthetic seismograms and ∗Now at:´Ecole Normale Sup´e rieure,24rue Lhomond,75231Paris Cedex05,France.C 2003RAS289290´E.Beucler,´E.Stutzmann and J.-P.Montagnerinvert the amplitude and the phase of thefiltered cross-correlogram.On the other hand,Nolet et al.(1986)and Nolet(1990)use an iterative inverse algorithm tofit the waveform in the time domain and increase the model complexity within the iterations.These two methods provide directly a1-D model corresponding to an average epicentre–station path.They werefirst used‘manually’,which limited the amount of data that could be processed.The exponential increase in the amount of good-quality broad-band data has made necessary the automation of most parts of the data processing and an automatic version of these methods has been proposed by Debayle(1999)for the waveform inversion technique of Cara&L´e vˆe que(1987)and by Lebedev(2000)and Lebedev&Nolet(2003)for the partition waveform inversion.Stutzmann&Montagner(1993)split the inversion into two steps;at each iteration,a least-squares optimization to measure phase velocities is followed by an inversion to determine the1-D S-wave velocity model,in order to gain insight into the factors that control the depth resolution.They retrieve the phase velocity for a set of several seismograms recorded at a single station and originating from earthquakes located in the same area in order to improve the resolution.Another approach has been followed by van Heijst&Woodhouse(1997)who proposed a mode-branch stripping technique based on monomode cross-correlation functions.Phase velocity and amplitude perturbations are determined for the most energetic mode-branch,the waveform of which is then subtracted from the seismogram in order to determine the second most energetic mode-branch phase velocity and amplitude perturbations,and so on.More recently,Y oshizawa&Kennett(2002)used the neighbourhood algorithm(Sambridge1999a,b)to explore the model space in detail and to obtain directly a1-D velocity model which achieves the minimum misfit.It is difficult to compare the efficiency of these methods because they all follow different approaches to taking account of the non-linearity of the problem.Up to now,it has only been possible to compare tomographic results obtained using these different techniques.In this paper,we introduce a new semi-automatic inverse procedure,the‘roller coaster’technique(owing to the shape of the misfit curve displayed in Fig.6b in Section3.4.1),to measure fundamental and overtone phase velocities both for Rayleigh and Love waves.This method can be applied either to a single seismogram or to a set of seismograms recorded at a single station.To deal with the non-linearity of the problem,the roller coaster technique combines the detection of all possible solutions at a large scale(which means solutions of large-wavelength variations of the parameter vector over the model space),and local least-squares inversions close to each of them,in order to match small variations of the model.The purpose of this article is to present an inverse procedure that introduces as little a priori information as possible in a non-linear scheme.So,even using a straightforward phase perturbation theory,we show how this algorithm detects and converges towards the best global misfit model.The roller coaster technique is applied to a path average theory but can be later adapted and used with a more realistic wave propagation theory.One issue of this study is to provide a3-D global model which does not suffer from strong a priori constraints during the inversion and which then can be used in the future as a reference model.We describe hereafter the forward problem and the non-linear inverse approach developed for solving it.An essential asset of this technique is to provide quantitative a posteriori information,in order to assess the accuracy of the phase velocity measurements.Resolution tests on both synthetic and real data are presented for Love and Rayleigh waves.2F O RWA R D P R O B L E MFollowing the normal-mode summation approach,a long-period seismogram can be modelled as the sum of the fundamental mode(n=0) and thefirst higher modes(n≥1),hereafter referred to as FM and HM,respectively.Eigenfrequencies and eigenfunctions are computed for both spheroidal and toroidal modes in a1-D reference model,PREM(Dziewonski&Anderson1981)in our case.Stoneley modes are removed,then the radial order n for the spheroidal modes corresponds to Okal’s classification(Okal1978).In the following,all possible sorts of coupling between toroidal and spheroidal mode-branches(Woodhouse1980;Lognonn´e&Romanowicz1990;Deuss&Woodhouse2001) and off-great-circle propagation effects(Woodhouse&Wong1986;Laske&Masters1996)are neglected.For a given recorded long-period seismogram,the corresponding synthetic seismogram is computed using the formalism defined by Woodhouse&Girnius(1982).In the most general case,the displacement u,corresponding of thefirst surface wave train,in the time domain, can be written asu(r,t)=12π+∞−∞nj=0A j(r,ω)exp[i j(r,ω)]exp(iωt)dω,(1)where r is the source–receiver spatial position,ωis the angular frequency and where A j and j represent the amplitude and the phase of the j th mode-branch,respectively,in the frequency domain.In the following,the recorded and the corresponding synthetic seismogram spectra (computed in PREM)are denoted by(R)and(S),respectively.In the Fourier domain,following Kanamori&Given(1981),a recorded seismogram spectrum can be written asA(R)(r,ω)expi (R)(r,ω)=nj=0B j(r,ω)expij(r,ω)−ωaCj(r,ω),(2)where a is the radius of the Earth, is the epicentral distance(in radians)and C(R)j(r,ω)is the real average phase velocity along the epicentre–station path of the j th mode-branch,which we wish to measure.The term B j(r,ω)includes source amplitude and geometrical spreading, whereas j(r,ω)corresponds to the source phase.The instrumental response is included in both terms and this expression is valid for bothRayleigh and Love waves.The phase shift due to the propagation in the real medium then resides in the term exp[−iωa /C(R)j(r,ω)].C 2003RAS,GJI,155,289–307The roller coaster technique291 Figure1.Illustration of possible2πphase jumps over the whole frequency range(dashed lines)or localized around a given frequency(dotted line).Thereference phase velocity used to compute these three curves is represented as a solid line.Considering that,tofirst order,the effect of a phase perturbation dominates over that of the amplitude perturbation(Li&Tanimoto 1993),and writing the real slowness as a perturbation of the synthetic slowness(computed in the1-D reference model),eq.(2)becomesA(R)(r,ω)expi (R)(r,ω)=nj=0A(S)j(r,ω)expij(r,ω)−ωaC(S)j(ω)−χ,(3) whereχ=ωa1C(R)j(r,ω)−1C(S)j(r,ω).(4) Let us now denote by p j(r,ω),the dimensionless parameter vector of the j th mode-branch defined byp j(r,ω)=C(R)j(r,ω)−C(S)j(ω)Cj(ω).(5)Finally,introducing the synthetic phase (S)j(r,ω),as the sum of the source phase and the phase shift due to the propagation in the reference model,the forward problem can be expressed asd=g(p),A(R)(r,ω)expi (R)(r,ω)=nj=0A(S)j(r,ω)expi(S)j(r,ω)+ωaCj(ω)p j(r,ω).(6)For practical reasons,the results presented in this paper are computed following a forward problem expression based on phase velocity perturbation expanded to third order(eq.A5).When considering an absolute perturbation range lower than10per cent,results are,however, identical to those computed following eq.(6)(see Appendix A).Formally,eq.(6)can be summarized as a linear combination of complex cosines and sines and for this reason,a2πundetermination remains for every solution.For a given parameter p j(r,ω),it is obvious that two other solutions can be found by a2πshift such asp+j(r,ω)=p j(r,ω)+2πC(S)j(ω)ωa and p−j(r,ω)=p j(r,ω)−2πC(S)j(ω)ωa.(7) As an example of this feature,all the phase velocity curves presented in Fig.1satisfy eq.(6).This means that2πphase jumps can occur over the whole frequency range but can also be localized around a given frequency.Such an underdetermination as expressed in eq.(6)and such a non-unicity,in most cases due to the2πphase jumps,are often resolved by imposing some a priori constraints in the inversion.A contrario, the roller coaster technique explores a large range of possible solutions,with the smallest a priori as possible,before choosing the model that achieves the minimum misfit.3D E S C R I P T I O N O F T H E R O L L E R C O A S T E R T E C H N I Q U EThe method presented in this paper is a hybrid approach,combining detection of all possible large-scale solutions(which means solutions of long-wavelength configurations of the parameter vector)and local least-squares optimizations starting from each of these solutions,in order to match the short-wavelength variations of the model space.The different stages of the roller coaster technique are presented in Fig.2and described hereafter.Thefirst three stages are devoted to the reduction of the problem underdetermination,while the non-linearity and the non-unicity are taken into account in the following steps.C 2003RAS,GJI,155,289–307292´E.Beucler,´E.Stutzmann and J.-P.MontagnerStage1Stage2Stage3Stage4using least-squares2phasejumps?Stage5Stage6Figure2.Schematic diagram of the roller coaster technique.See Section3for details.3.1Selection of events,mode-branches and time windowsEvents with epicentral distances larger than55◦and shorter than135◦are selected.Thus,the FM is well separated in time from the HM(Fig.3), and thefirst and the second surface wave trains do not overlap.Since the FM signal amplitude is much larger than the HM amplitude for about 95per cent of earthquakes,each seismogram(real and synthetic)is temporally divided into two different time windows,corresponding to the FM and to the HM parts of the signal.An illustration of this amplitude discrepancy in the time domain is displayed in Fig.3(b)and when focusing on Fig.4(a),the spectrum amplitude of the whole real signal(FM+HM)is largely dominated by the FM one.Eight different pickings defining the four time windows,illustrated in Fig.3(a),are computed using synthetic mode-branch wave trains and are checked manually.For this reason,this method is not completely automated,but this picking step is necessary to assess the data quality and the consistency between recorded and synthetic seismograms.In Appendix B,we show that the phase velocity measurements are not significantly affected by a small change in the time window dimensions.An advantage of this temporal truncation is that,whatever the amplitude of the FM,the HM part of the seismograms can always be treated.Hence,the forward problem is now split into two equations,corresponding to the FM and to the HM parts,respectively.A(R) FM (r,ω)expi (R)FM(r,ω)=A(S)0(r,ω)expi(S)0(r,ω)+ωaC(ω)p0(r,ω)(8)andA(R) HM (r,ω)expi (R)HM(r,ω)=6j=1A(S)j(r,ω)expi(S)j(r,ω)+ωaC(S)j(ω)p j(r,ω).(9)Seismograms(real and synthetic)are bandpassfiltered between40and500s.In this frequency range,only thefirst six overtone phase velocities can be efficiently retrieved.Tests on synthetic seismograms(up to n=15)with various depths and source parameters have shown that the HM for n≥7have negligible amplitudes in the selected time and frequency windows.C 2003RAS,GJI,155,289–307The roller coaster technique293Figure3.(a)Real vertical seismogram(solid line)and its corresponding synthetic computed in PREM(dotted line).The earthquake underlying this waveform occurred on1993September4in Afghanistan(36◦N,70◦E,depth of190km)and was recorded at the CAN GEOSCOPE station(Australia).The epicentral distance is estimated at around11340km.Both waveforms are divided into two time windows corresponding to the higher modes(T1–T2,T5–T6)and to the fundamental mode(T3–T4,T7–T8).(b)The contribution of each synthetic monomode shows the large-amplitude discrepancy and time delay between the fundamental mode and the overtones.The different symbols refer to the spectra displayed in Fig.4.3.2Clustering the eventsFollowing eq.(8),a single seismogram is sufficient to measure the FM phase velocity,whereas for the HM(eq.9)the problem is still highly underdetermined since the different HM group velocities are very close.This can be avoided by a reduction of the number of independent parameters considering mathematical relations between different mode-branch phase velocities.The consequence of such an approach is to impose a strong a priori knowledge on the model space,which may be physically unjustified.Another way to reduce this underdetermination is to increase the amount of independent data while keeping the parameter space dimension constant.Therefore,all sufficiently close events are clustered into small areas,and each individual ray path belonging to the same box is considered to give equivalent results as a common ray path.This latter approach was followed by Stutzmann&Montagner(1993),but with5×5deg2boxes independently of epicentral distance and azimuth values,due to the limited number of data.Here,in order to prevent any bias induced by the clustering of events too far away from one to another,and to be consistent with the smallest wavelength,boxes are computed with a maximum aperture angle of2◦and4◦in the transverse and longitudinal directions,respectively(Fig.5),with respect to the great circle path.The boxes are computed in order to take into account as many different depths and source mechanisms as possible.The FM phase velocity inversion is performed for each path between a station and a box,whereas the HM phase velocities are only measured for the boxes including three or more events.Since only the sixfirst mode-branches spectra are inverted,the maximum number of events per box is set to eight.The use of different events implies average phase velocity measurements along the common ray paths which can be unsuitable for short epicentral distances,but increases the accuracy of the results for the epicentral distances considered.C 2003RAS,GJI,155,289–307294´E.Beucler,´E.Stutzmann and J.-P.MontagnerFigure4.(a)The normalized amplitude spectra of the whole real waveform(solid line)displayed in Fig.3(a).The real FM part of the signal(truncated between T3and T4)is represented as a dotted line and the real HM part(between T1and T2)as a dashed line.(b).The solid line corresponds to the normalized spectrum amplitude of the real signal truncated between T3and T4(Fig.3a).The corresponding synthetic FM is represented as a dotted line and only the frequency range represented by the white circles is selected as being significant.(c)Selection of HM inversion frequency ranges using synthetic significant amplitudes.The solid line corresponds to the real HM signal,picked between T1and T2(Fig.3a).For each mode-branch(dotted lines),only the frequency ranges defined by the symbols(according to Fig.3b)are retained for the inversion.(d)Close up of the sixth synthetic overtone,in order to visualize the presence of lobes and the weak contribution frequency range in the spectrum amplitude.The stars delimit the selected frequency range.3.3Determination of the model space dimensionReal and synthetic amplitude spectra are normalized in order to minimize the effects due to the imprecision of source parameters and of instrumental response determination.As presented in Fig.4,a synthetic mode-branch spectrum is frequently composed by several lobes due to the source mechanism.Between each lobe and also near the frequency range edges due to the bandpassfilter,the amplitude strongly decreases down to zero,and therefore phase velocities are absolutely not constrained at these frequencies.It is around these frequencies that possible local2πphase jumps may occur(Fig.1).Then,we decide to reduce the model space dimension in order to take into account only well-constrained points.For each spectrum,the selection of significant amplitudes,with a thresholdfixed to10per cent of the mean maximum spectra amplitude,defines the inverted frequency range.In the case of several lobes in a synthetic mode-branch amplitude spectrum,only the most energetic one is selected as shown in Figs4(c)and(d).For a given mode-branch,the simultaneous use of different earthquakes implies a discrimination criterion based upon a mean amplitude spectrum of all spectra,which tends to increase the dimensions of the significant frequency range.The normalization and this selection of each mode-branch significant amplitudes is also a way to include surface wave radiation pattern information in the procedure.Changes in source parameters can result in changes in the positions of the lobes in the mode-branch amplitude spectra over the whole frequency range(40–500s).In the future,it will be essential to include these possible biases in the scheme and then to simultaneously invert moment tensor,location and depth.C 2003RAS,GJI,155,289–307The roller coaster technique295Figure5.Geographical distribution of inversion boxes for the SSB GEOSCOPE station case.The enlarged area is defined by the bold square in the inset (South America).Black stars denote epicentres and hatched grey boxes join each inversion group.Each common ray path(grey lines)starts from the barycentre (circles)of all events belonging to the same box.The maximum number of seismograms per box isfixed at eight.3.4Exploration of the model space at very large scaleThe main idea of this stage is to test a large number of phase velocity large-scale perturbations with the view of selecting several starting vectors for local inversions(see Section3.5).The high non-linearity of the problem is mainly due to the possible2πphase jumps.And,even though the previous stage(see Section3.3)prevents the shifts inside a given mode-branch phase velocity curve,2πphase jumps over the whole selected frequency range are still possible.For this reason a classical gradient least-squares optimization(Tarantola&Valette1982a)is inadequate.In a highly non-linear problem,a least-squares inversion only converges towards the best misfit model that is closest to the starting model and the number of iterations cannot change this feature.On the other hand,a complete exploration of all possible configurations in the parameter space is still incompatible with a short computation time procedure.Therefore,an exploration of the model space is performed at very large scale,in order to detect all possible models that globally explain the data set well.3.4.1Fundamental mode caseWhen considering a single mode-branch,the number of parameter vector components is rather small.The FM large-scale exploration can then be more detailed than in the HM case.Considering that,at low frequencies,data are correctly explained by the1-D reference model,the C 2003RAS,GJI,155,289–307296´E.Beucler,´E.Stutzmann and J.-P.MontagnerabFigure6.(a)Five examples of the FM parameter vector configurations during the exploration of the model space at large scale corresponding toαvalues equal to−5,−,0,+2.5and+5per cent.The selected points for which the phase velocity is measured(see Section3.3)are ordered into parameter vector components according to increasing frequency values.Thefirst indices then correspond to the low-frequency components(LF)and the last ones to the high-frequency(HF) components.Varying the exploration factorα,different perturbation shapes are then modelled and the misfit between data and the image of the corresponding vector is measured(represented in thefigure below).(b)The misfit in the FM case,symbolized by+,is the expression of the difference between data and the image of the tested model(referred to as pα)through the g function(eq.8).Theαvalues are expressed as a percentage with respect to the PREM.As an example,thefive stars correspond to the misfit values of thefive models represented in thefigure above.The circles represent the bestαvalues and the corresponding vectors are then considered as possible starting models for the next stage.dimensionless phase velocity perturbation(referred to as pα)can be modelled as shown in thefive examples displayed in Fig.6(a).Basically, the low-frequency component perturbations are smaller than the high-frequency ones.However,if such an assumption cannot be made,the simplest way to explore the model space is then byfixing an equalαperturbation value for all the components.The main idea is to impose strong correlations between all the components in order to estimate how high the non-linearity is.Varyingαenables one to compute different parameter vectors and solving eq.(8)to measure the distance between data and the image of a given model through the g function,integrated over the whole selected frequency range.Considering that only small perturbations can be retrieved,the exploration range is limited between−5and+5per cent,using an increment step of0.1per cent.The result of such an exploration is displayed in Fig.6(b)and clearly illustrates the high non-linearity and non-unicity of the problem.In a weakly non-linear problem,the misfit curve(referred to as||d−g(pα)||)should exhibit only one minimum.This would indicate that,whatever the value of the starting model,a gradient algorithm always converges towards the samefinal model,the solution is then unique.In our case,Fig.6(b)shows that,when choosing the reference model(i.e.α=0per cent)as the starting model,a gradient least-squares optimization converges to the nearest best-fitting solution(corresponding to the third circle),and could never reach the global best-fitting model(in this example representedC 2003RAS,GJI,155,289–307The roller coaster technique 297by the fourth circle).Therefore,in order not to a priori limit the inversion result around a given model,all minima of the mis fit curve (Fig.6b)are detected and the corresponding vectors are considered as possible starting models for local optimizations (see Section 3.5).3.4.2Higher-mode caseThe introduction of several mode-branches simultaneously is much more dif ficult to treat and it becomes rapidly infeasible to explore the model space as accurately as performed for the FM.However,a similar approach is followed.In order to preserve a low computation time procedure,the increment step of αis fixed at 1per cent.The different parameter vectors are computed as previously explained in Section3.4.1(the shape of each mode-branch subvector is the same as the examples displayed in Fig.6a).In order to take into account any possible in fluence of one mode-branch on another,all combinations are tested systematically.Three different explorations of the model space are performed within three different research ranges:[−4.5to +1.5per cent],[−3to +3per cent]and [−1.5to +4.5per cent].For each of them,76possibilities of the parameter vector are modelled and the mis fit between data and the image of the tested vector through the g function is computed.This approach is almost equivalent to performing a complete exploration in the range [−4.5to +4.5per cent],using a step of 0.5per cent,but less time consuming.Finally,all mis fit curve minima are detected and,according to a state of null information concerning relations between each mode-branch phase velocities,all the corresponding vectors are retained as possible starting models.Thus,any association between each starting model subvectors is allowed.3.5Matching the short-wavelength variations of the modelIn this section,algorithms,notation and comments are identical for both FM and HM.Only the main ideas of the least-squares criterion are outlined.A complete description of this approach is given by Tarantola &Valette (1982a,b)and by Tarantola (1987).Some typical features related to the frequency/period duality are also detailed.3.5.1The gradient least-squares algorithmThe main assumption which leads us to use such an optimization is to consider that starting from the large-scale parameter vector (see Section 3.4),the non-linearity of the problem is largely reduced.Hence,to infer the model space from the data space,a gradient least-squares algorithm is performed (Tarantola &Valette 1982a).The expression of the model (or parameter)at the k th iteration is given by p k =p 0+C p ·G T k −1· C d +G k −1·C p ·G T k −1−1· d −g (p k −1)+G k −1·(p k −1−p 0) ,(10)where C p and C d are the a priori covariance operators on parameters and data,respectively,p 0the starting model,and where G k −1=∂g (p k −1)/∂p k −1is the matrix of partial derivatives of the g function established in eqs (8)and (9).The indices related to p are now expressing the iteration rank and no longer the mode-branch radial order.De fining the k th image of the mis fit function byS (p k )=12[g (p k )−d ]T ·C −1d ·[g (p k )−d ]+(p k −p 0)T ·C −1p ·(p k −p 0) ,(11)the maximum-likelihood point is de fined by the minimum of S (p ).Minimizing the mis fit function is then equivalent to finding the best compromise between decreasing the distance between the data vector and the image of the parameter vector through the g function,in the data space on one hand (first part of eq.11),and not increasing the distance between the starting and the k th model on the other hand (second part of eq.11),following the covariances de fined in the a priori operators on the data and the parameters.3.5.2A priori data covariance operatorThe a priori covariance operator on data,referred to as C d ,includes data errors and also all effects that cannot be modelled by the g function de fined in eq.(8)and (9).The only way to really measure each data error and then to compute realistic covariances in the data space,would be to obtain exactly the corresponding seismogram in which the signal due to the seismic event is removed.Hence,errors over the data space are impossible to determine correctly.In order to introduce as little a priori information as possible,the C d matrix is computed with a constant value of 0.04(including data and theory uncertainties)for the diagonal elements and zero for the off-diagonal elements.In other words,this choice means that the phase velocity perturbations are expected to explain at least 80per cent of the recorded signal.3.5.3A priori parameter covariance operatorIn the model space,the a priori covariance operator on parameters,referred to as C p ,controls possible variations between the model vector components for a given iteration k (eq.10),and also between the starting and the k th model (eq.11).Considering that the phase velocity perturbation between two adjoining components (which are ordered according to increasing frequency values)of a given mode-branch do not vary too rapidly,C p is a non-diagonal matrix.This a priori information reduces the number of independent components and then induces smoothed phase velocity perturbation curves.A typical behaviour of our problem resides in the way the parameter space is discretized.In the matrix domain,the distance between two adjoining components is always the same,whereas,as the model space is not evenly spaced C 2003RAS,GJI ,155,289–307。
OSHA现场作业手册说明书
DIRECTIVE NUMBER: CPL 02-00-150 EFFECTIVE DATE: April 22, 2011 SUBJECT: Field Operations Manual (FOM)ABSTRACTPurpose: This instruction cancels and replaces OSHA Instruction CPL 02-00-148,Field Operations Manual (FOM), issued November 9, 2009, whichreplaced the September 26, 1994 Instruction that implemented the FieldInspection Reference Manual (FIRM). The FOM is a revision of OSHA’senforcement policies and procedures manual that provides the field officesa reference document for identifying the responsibilities associated withthe majority of their inspection duties. This Instruction also cancels OSHAInstruction FAP 01-00-003 Federal Agency Safety and Health Programs,May 17, 1996 and Chapter 13 of OSHA Instruction CPL 02-00-045,Revised Field Operations Manual, June 15, 1989.Scope: OSHA-wide.References: Title 29 Code of Federal Regulations §1903.6, Advance Notice ofInspections; 29 Code of Federal Regulations §1903.14, Policy RegardingEmployee Rescue Activities; 29 Code of Federal Regulations §1903.19,Abatement Verification; 29 Code of Federal Regulations §1904.39,Reporting Fatalities and Multiple Hospitalizations to OSHA; and Housingfor Agricultural Workers: Final Rule, Federal Register, March 4, 1980 (45FR 14180).Cancellations: OSHA Instruction CPL 02-00-148, Field Operations Manual, November9, 2009.OSHA Instruction FAP 01-00-003, Federal Agency Safety and HealthPrograms, May 17, 1996.Chapter 13 of OSHA Instruction CPL 02-00-045, Revised FieldOperations Manual, June 15, 1989.State Impact: Notice of Intent and Adoption required. See paragraph VI.Action Offices: National, Regional, and Area OfficesOriginating Office: Directorate of Enforcement Programs Contact: Directorate of Enforcement ProgramsOffice of General Industry Enforcement200 Constitution Avenue, NW, N3 119Washington, DC 20210202-693-1850By and Under the Authority ofDavid Michaels, PhD, MPHAssistant SecretaryExecutive SummaryThis instruction cancels and replaces OSHA Instruction CPL 02-00-148, Field Operations Manual (FOM), issued November 9, 2009. The one remaining part of the prior Field Operations Manual, the chapter on Disclosure, will be added at a later date. This Instruction also cancels OSHA Instruction FAP 01-00-003 Federal Agency Safety and Health Programs, May 17, 1996 and Chapter 13 of OSHA Instruction CPL 02-00-045, Revised Field Operations Manual, June 15, 1989. This Instruction constitutes OSHA’s general enforcement policies and procedures manual for use by the field offices in conducting inspections, issuing citations and proposing penalties.Significant Changes∙A new Table of Contents for the entire FOM is added.∙ A new References section for the entire FOM is added∙ A new Cancellations section for the entire FOM is added.∙Adds a Maritime Industry Sector to Section III of Chapter 10, Industry Sectors.∙Revises sections referring to the Enhanced Enforcement Program (EEP) replacing the information with the Severe Violator Enforcement Program (SVEP).∙Adds Chapter 13, Federal Agency Field Activities.∙Cancels OSHA Instruction FAP 01-00-003, Federal Agency Safety and Health Programs, May 17, 1996.DisclaimerThis manual is intended to provide instruction regarding some of the internal operations of the Occupational Safety and Health Administration (OSHA), and is solely for the benefit of the Government. No duties, rights, or benefits, substantive or procedural, are created or implied by this manual. The contents of this manual are not enforceable by any person or entity against the Department of Labor or the United States. Statements which reflect current Occupational Safety and Health Review Commission or court precedents do not necessarily indicate acquiescence with those precedents.Table of ContentsCHAPTER 1INTRODUCTIONI.PURPOSE. ........................................................................................................... 1-1 II.SCOPE. ................................................................................................................ 1-1 III.REFERENCES .................................................................................................... 1-1 IV.CANCELLATIONS............................................................................................. 1-8 V. ACTION INFORMATION ................................................................................. 1-8A.R ESPONSIBLE O FFICE.......................................................................................................................................... 1-8B.A CTION O FFICES. .................................................................................................................... 1-8C. I NFORMATION O FFICES............................................................................................................ 1-8 VI. STATE IMPACT. ................................................................................................ 1-8 VII.SIGNIFICANT CHANGES. ............................................................................... 1-9 VIII.BACKGROUND. ................................................................................................. 1-9 IX. DEFINITIONS AND TERMINOLOGY. ........................................................ 1-10A.T HE A CT................................................................................................................................................................. 1-10B. C OMPLIANCE S AFETY AND H EALTH O FFICER (CSHO). ...........................................................1-10B.H E/S HE AND H IS/H ERS ..................................................................................................................................... 1-10C.P ROFESSIONAL J UDGMENT............................................................................................................................... 1-10E. W ORKPLACE AND W ORKSITE ......................................................................................................................... 1-10CHAPTER 2PROGRAM PLANNINGI.INTRODUCTION ............................................................................................... 2-1 II.AREA OFFICE RESPONSIBILITIES. .............................................................. 2-1A.P ROVIDING A SSISTANCE TO S MALL E MPLOYERS. ...................................................................................... 2-1B.A REA O FFICE O UTREACH P ROGRAM. ............................................................................................................. 2-1C. R ESPONDING TO R EQUESTS FOR A SSISTANCE. ............................................................................................ 2-2 III. OSHA COOPERATIVE PROGRAMS OVERVIEW. ...................................... 2-2A.V OLUNTARY P ROTECTION P ROGRAM (VPP). ........................................................................... 2-2B.O NSITE C ONSULTATION P ROGRAM. ................................................................................................................ 2-2C.S TRATEGIC P ARTNERSHIPS................................................................................................................................. 2-3D.A LLIANCE P ROGRAM ........................................................................................................................................... 2-3 IV. ENFORCEMENT PROGRAM SCHEDULING. ................................................ 2-4A.G ENERAL ................................................................................................................................................................. 2-4B.I NSPECTION P RIORITY C RITERIA. ..................................................................................................................... 2-4C.E FFECT OF C ONTEST ............................................................................................................................................ 2-5D.E NFORCEMENT E XEMPTIONS AND L IMITATIONS. ....................................................................................... 2-6E.P REEMPTION BY A NOTHER F EDERAL A GENCY ........................................................................................... 2-6F.U NITED S TATES P OSTAL S ERVICE. .................................................................................................................. 2-7G.H OME-B ASED W ORKSITES. ................................................................................................................................ 2-8H.I NSPECTION/I NVESTIGATION T YPES. ............................................................................................................... 2-8 V.UNPROGRAMMED ACTIVITY – HAZARD EVALUATION AND INSPECTION SCHEDULING ............................................................................ 2-9 VI.PROGRAMMED INSPECTIONS. ................................................................... 2-10A.S ITE-S PECIFIC T ARGETING (SST) P ROGRAM. ............................................................................................. 2-10B.S CHEDULING FOR C ONSTRUCTION I NSPECTIONS. ..................................................................................... 2-10C.S CHEDULING FOR M ARITIME I NSPECTIONS. ............................................................................. 2-11D.S PECIAL E MPHASIS P ROGRAMS (SEP S). ................................................................................... 2-12E.N ATIONAL E MPHASIS P ROGRAMS (NEP S) ............................................................................... 2-13F.L OCAL E MPHASIS P ROGRAMS (LEP S) AND R EGIONAL E MPHASIS P ROGRAMS (REP S) ............ 2-13G.O THER S PECIAL P ROGRAMS. ............................................................................................................................ 2-13H.I NSPECTION S CHEDULING AND I NTERFACE WITH C OOPERATIVE P ROGRAM P ARTICIPANTS ....... 2-13CHAPTER 3INSPECTION PROCEDURESI.INSPECTION PREPARATION. .......................................................................... 3-1 II.INSPECTION PLANNING. .................................................................................. 3-1A.R EVIEW OF I NSPECTION H ISTORY .................................................................................................................... 3-1B.R EVIEW OF C OOPERATIVE P ROGRAM P ARTICIPATION .............................................................................. 3-1C.OSHA D ATA I NITIATIVE (ODI) D ATA R EVIEW .......................................................................................... 3-2D.S AFETY AND H EALTH I SSUES R ELATING TO CSHO S.................................................................. 3-2E.A DVANCE N OTICE. ................................................................................................................................................ 3-3F.P RE-I NSPECTION C OMPULSORY P ROCESS ...................................................................................................... 3-5G.P ERSONAL S ECURITY C LEARANCE. ................................................................................................................. 3-5H.E XPERT A SSISTANCE. ........................................................................................................................................... 3-5 III. INSPECTION SCOPE. ......................................................................................... 3-6A.C OMPREHENSIVE ................................................................................................................................................... 3-6B.P ARTIAL. ................................................................................................................................................................... 3-6 IV. CONDUCT OF INSPECTION .............................................................................. 3-6A.T IME OF I NSPECTION............................................................................................................................................. 3-6B.P RESENTING C REDENTIALS. ............................................................................................................................... 3-6C.R EFUSAL TO P ERMIT I NSPECTION AND I NTERFERENCE ............................................................................. 3-7D.E MPLOYEE P ARTICIPATION. ............................................................................................................................... 3-9E.R ELEASE FOR E NTRY ............................................................................................................................................ 3-9F.B ANKRUPT OR O UT OF B USINESS. .................................................................................................................... 3-9G.E MPLOYEE R ESPONSIBILITIES. ................................................................................................. 3-10H.S TRIKE OR L ABOR D ISPUTE ............................................................................................................................. 3-10I. V ARIANCES. .......................................................................................................................................................... 3-11 V. OPENING CONFERENCE. ................................................................................ 3-11A.G ENERAL ................................................................................................................................................................ 3-11B.R EVIEW OF A PPROPRIATION A CT E XEMPTIONS AND L IMITATION. ..................................................... 3-13C.R EVIEW S CREENING FOR P ROCESS S AFETY M ANAGEMENT (PSM) C OVERAGE............................. 3-13D.R EVIEW OF V OLUNTARY C OMPLIANCE P ROGRAMS. ................................................................................ 3-14E.D ISRUPTIVE C ONDUCT. ...................................................................................................................................... 3-15F.C LASSIFIED A REAS ............................................................................................................................................. 3-16VI. REVIEW OF RECORDS. ................................................................................... 3-16A.I NJURY AND I LLNESS R ECORDS...................................................................................................................... 3-16B.R ECORDING C RITERIA. ...................................................................................................................................... 3-18C. R ECORDKEEPING D EFICIENCIES. .................................................................................................................. 3-18 VII. WALKAROUND INSPECTION. ....................................................................... 3-19A.W ALKAROUND R EPRESENTATIVES ............................................................................................................... 3-19B.E VALUATION OF S AFETY AND H EALTH M ANAGEMENT S YSTEM. ....................................................... 3-20C.R ECORD A LL F ACTS P ERTINENT TO A V IOLATION. ................................................................................. 3-20D.T ESTIFYING IN H EARINGS ................................................................................................................................ 3-21E.T RADE S ECRETS. ................................................................................................................................................. 3-21F.C OLLECTING S AMPLES. ..................................................................................................................................... 3-22G.P HOTOGRAPHS AND V IDEOTAPES.................................................................................................................. 3-22H.V IOLATIONS OF O THER L AWS. ....................................................................................................................... 3-23I.I NTERVIEWS OF N ON-M ANAGERIAL E MPLOYEES .................................................................................... 3-23J.M ULTI-E MPLOYER W ORKSITES ..................................................................................................................... 3-27 K.A DMINISTRATIVE S UBPOENA.......................................................................................................................... 3-27 L.E MPLOYER A BATEMENT A SSISTANCE. ........................................................................................................ 3-27 VIII. CLOSING CONFERENCE. .............................................................................. 3-28A.P ARTICIPANTS. ..................................................................................................................................................... 3-28B.D ISCUSSION I TEMS. ............................................................................................................................................ 3-28C.A DVICE TO A TTENDEES .................................................................................................................................... 3-29D.P ENALTIES............................................................................................................................................................. 3-30E.F EASIBLE A DMINISTRATIVE, W ORK P RACTICE AND E NGINEERING C ONTROLS. ............................ 3-30F.R EDUCING E MPLOYEE E XPOSURE. ................................................................................................................ 3-32G.A BATEMENT V ERIFICATION. ........................................................................................................................... 3-32H.E MPLOYEE D ISCRIMINATION .......................................................................................................................... 3-33 IX. SPECIAL INSPECTION PROCEDURES. ...................................................... 3-33A.F OLLOW-UP AND M ONITORING I NSPECTIONS............................................................................................ 3-33B.C ONSTRUCTION I NSPECTIONS ......................................................................................................................... 3-34C. F EDERAL A GENCY I NSPECTIONS. ................................................................................................................. 3-35CHAPTER 4VIOLATIONSI. BASIS OF VIOLATIONS ..................................................................................... 4-1A.S TANDARDS AND R EGULATIONS. .................................................................................................................... 4-1B.E MPLOYEE E XPOSURE. ........................................................................................................................................ 4-3C.R EGULATORY R EQUIREMENTS. ........................................................................................................................ 4-6D.H AZARD C OMMUNICATION. .............................................................................................................................. 4-6E. E MPLOYER/E MPLOYEE R ESPONSIBILITIES ................................................................................................... 4-6 II. SERIOUS VIOLATIONS. .................................................................................... 4-8A.S ECTION 17(K). ......................................................................................................................... 4-8B.E STABLISHING S ERIOUS V IOLATIONS ............................................................................................................ 4-8C. F OUR S TEPS TO BE D OCUMENTED. ................................................................................................................... 4-8 III. GENERAL DUTY REQUIREMENTS ............................................................. 4-14A.E VALUATION OF G ENERAL D UTY R EQUIREMENTS ................................................................................. 4-14B.E LEMENTS OF A G ENERAL D UTY R EQUIREMENT V IOLATION.............................................................. 4-14C. U SE OF THE G ENERAL D UTY C LAUSE ........................................................................................................ 4-23D.L IMITATIONS OF U SE OF THE G ENERAL D UTY C LAUSE. ..............................................................E.C LASSIFICATION OF V IOLATIONS C ITED U NDER THE G ENERAL D UTY C LAUSE. ..................F. P ROCEDURES FOR I MPLEMENTATION OF S ECTION 5(A)(1) E NFORCEMENT ............................ 4-25 4-27 4-27IV.OTHER-THAN-SERIOUS VIOLATIONS ............................................... 4-28 V.WILLFUL VIOLATIONS. ......................................................................... 4-28A.I NTENTIONAL D ISREGARD V IOLATIONS. ..........................................................................................4-28B.P LAIN I NDIFFERENCE V IOLATIONS. ...................................................................................................4-29 VI. CRIMINAL/WILLFUL VIOLATIONS. ................................................... 4-30A.A REA D IRECTOR C OORDINATION ....................................................................................................... 4-31B.C RITERIA FOR I NVESTIGATING P OSSIBLE C RIMINAL/W ILLFUL V IOLATIONS ........................ 4-31C. W ILLFUL V IOLATIONS R ELATED TO A F ATALITY .......................................................................... 4-32 VII. REPEATED VIOLATIONS. ...................................................................... 4-32A.F EDERAL AND S TATE P LAN V IOLATIONS. ........................................................................................4-32B.I DENTICAL S TANDARDS. .......................................................................................................................4-32C.D IFFERENT S TANDARDS. .......................................................................................................................4-33D.O BTAINING I NSPECTION H ISTORY. .....................................................................................................4-33E.T IME L IMITATIONS..................................................................................................................................4-34F.R EPEATED V. F AILURE TO A BATE....................................................................................................... 4-34G. A REA D IRECTOR R ESPONSIBILITIES. .............................................................................. 4-35 VIII. DE MINIMIS CONDITIONS. ................................................................... 4-36A.C RITERIA ................................................................................................................................................... 4-36B.P ROFESSIONAL J UDGMENT. ..................................................................................................................4-37C. A REA D IRECTOR R ESPONSIBILITIES. .............................................................................. 4-37 IX. CITING IN THE ALTERNATIVE ............................................................ 4-37 X. COMBINING AND GROUPING VIOLATIONS. ................................... 4-37A.C OMBINING. ..............................................................................................................................................4-37B.G ROUPING. ................................................................................................................................................4-38C. W HEN N OT TO G ROUP OR C OMBINE. ................................................................................................4-38 XI. HEALTH STANDARD VIOLATIONS ....................................................... 4-39A.C ITATION OF V ENTILATION S TANDARDS ......................................................................................... 4-39B.V IOLATIONS OF THE N OISE S TANDARD. ...........................................................................................4-40 XII. VIOLATIONS OF THE RESPIRATORY PROTECTION STANDARD(§1910.134). ....................................................................................................... XIII. VIOLATIONS OF AIR CONTAMINANT STANDARDS (§1910.1000) ... 4-43 4-43A.R EQUIREMENTS UNDER THE STANDARD: .................................................................................................. 4-43B.C LASSIFICATION OF V IOLATIONS OF A IR C ONTAMINANT S TANDARDS. ......................................... 4-43 XIV. CITING IMPROPER PERSONAL HYGIENE PRACTICES. ................... 4-45A.I NGESTION H AZARDS. .................................................................................................................................... 4-45B.A BSORPTION H AZARDS. ................................................................................................................................ 4-46C.W IPE S AMPLING. ............................................................................................................................................. 4-46D.C ITATION P OLICY ............................................................................................................................................ 4-46 XV. BIOLOGICAL MONITORING. ...................................................................... 4-47CHAPTER 5CASE FILE PREPARATION AND DOCUMENTATIONI.INTRODUCTION ............................................................................................... 5-1 II.INSPECTION CONDUCTED, CITATIONS BEING ISSUED. .................... 5-1A.OSHA-1 ................................................................................................................................... 5-1B.OSHA-1A. ............................................................................................................................... 5-1C. OSHA-1B. ................................................................................................................................ 5-2 III.INSPECTION CONDUCTED BUT NO CITATIONS ISSUED .................... 5-5 IV.NO INSPECTION ............................................................................................... 5-5 V. HEALTH INSPECTIONS. ................................................................................. 5-6A.D OCUMENT P OTENTIAL E XPOSURE. ............................................................................................................... 5-6B.E MPLOYER’S O CCUPATIONAL S AFETY AND H EALTH S YSTEM. ............................................................. 5-6 VI. AFFIRMATIVE DEFENSES............................................................................. 5-8A.B URDEN OF P ROOF. .............................................................................................................................................. 5-8B.E XPLANATIONS. ..................................................................................................................................................... 5-8 VII. INTERVIEW STATEMENTS. ........................................................................ 5-10A.G ENERALLY. ......................................................................................................................................................... 5-10B.CSHO S SHALL OBTAIN WRITTEN STATEMENTS WHEN: .......................................................................... 5-10C.L ANGUAGE AND W ORDING OF S TATEMENT. ............................................................................................. 5-11D.R EFUSAL TO S IGN S TATEMENT ...................................................................................................................... 5-11E.V IDEO AND A UDIOTAPED S TATEMENTS. ..................................................................................................... 5-11F.A DMINISTRATIVE D EPOSITIONS. .............................................................................................5-11 VIII. PAPERWORK AND WRITTEN PROGRAM REQUIREMENTS. .......... 5-12 IX.GUIDELINES FOR CASE FILE DOCUMENTATION FOR USE WITH VIDEOTAPES AND AUDIOTAPES .............................................................. 5-12 X.CASE FILE ACTIVITY DIARY SHEET. ..................................................... 5-12 XI. CITATIONS. ..................................................................................................... 5-12A.S TATUTE OF L IMITATIONS. .............................................................................................................................. 5-13B.I SSUING C ITATIONS. ........................................................................................................................................... 5-13C.A MENDING/W ITHDRAWING C ITATIONS AND N OTIFICATION OF P ENALTIES. .................................. 5-13D.P ROCEDURES FOR A MENDING OR W ITHDRAWING C ITATIONS ............................................................ 5-14 XII. INSPECTION RECORDS. ............................................................................... 5-15A.G ENERALLY. ......................................................................................................................................................... 5-15B.R ELEASE OF I NSPECTION I NFORMATION ..................................................................................................... 5-15C. C LASSIFIED AND T RADE S ECRET I NFORMATION ...................................................................................... 5-16。
利用脉泽研究银河系的旋臂结构与运动学-科学技术处-南京大学
附件4：2017年度国家科技奖推荐公示内容一、项目名称：中文名：利用脉泽研究银河系的旋臂结构与运动学英文名：Study on the Spiral Arm Structure and Kinematics of the Milky Way with Maser Astrometry二、推荐单位意见：银河系结构和运动是当代天体物理中最具有挑战意义的研究课题之一。
项目组经过十多年的努力工作，在解决银河系大小和旋臂结构等天体物理难题方面取得突破性的进展。
项目组在国际上首先提出用甚长基线干涉仪(VLBI)测量甲醇脉泽的三角视差和自行，研究银河系旋臂结构和运动学性质这一开创性的学术观点。
并首次通过技术创新使射电天体测量精度达到10个微角秒，天体距离测量可达到3万光年，比传统的光学天文视差测量精度高了2个量级。
项目组在3个科学发现点：1.首次精确测量银河系英仙臂的距离；2.发现并精确测定银河系本地臂的形态和运动学性质；3.发现甲醇脉泽是银河系旋臂最好的示踪天体上具有原创性，使直接测量银河系旋臂结构成为现实。
项目获得了国内外同行和专家的高度评价，认为项目组的工作“开创了天文学三角视差测量银河系内遥远天体距离的新纪元”和银河系结构研究领域的“里程碑”。
项目引发了国际天文学界利用三角视差测量天体距离的热潮，大大推动了银河系结构的研究和射电天体测量学科的发展。
项目的多项科学发现都具有原创性，具有重大科学价值，并得到了国内外天文学届的公认。
推荐该项目为国家自然科学奖二等奖。
三、项目简介：银河系结构可能是天文学中持续时间最长，但至今仍未解决的重大问题之一。
有关银河系结构的文字记载，最早可追溯到古希腊大哲学家及天文学家亚里士多德(公元前384--322年)的卓著《气象学》。
2000多年来，天文学家苦苦追寻，仍未清晰地勾画出银河系的结构。
近20年来，项目组成员潜心研究，利用一种新的技术和方法直接测量银河系结构，对绘制银河系的真实面貌做出了开创性的工作。
An interior-point method for large-scale l1-regularized logistic regression. Journal of Mac
where Prob(b|x) is the conditional probability of b, given x ∈ R n . The logistic model has parameters v ∈ R (the intercept) and w ∈ Rn (the weight vector). When w = 0, wT x + v = 0 defines the neutral hyperplane in feature space, on which the conditional probability of each outcome is 1/2. On the shifted parallel hyperplane wT x + v = 1, which is a distance 1/ w 2 from the neutral hyperplane,
1. Introduction
In this section we describe the basic logistic regression problem, the 2 - and 1 -regularized versions, and the regularization path. We set out our notation, and review existing methods and literature. Finally, we give an outline of this paper. 1.1 Logistic Regression Let x ∈ Rn denote a vector of explanatory or feature variables, and b ∈ {−1, +1} denote the associated binary output or outcome. The logistic model has the form Prob(b|x) = exp b(wT x + v) 1 = , 1 + exp (−b(wT x + v)) 1 + exp (b(wT x + v))
交通流
Network impacts of a road capacity reduction:Empirical analysisand model predictionsDavid Watling a ,⇑,David Milne a ,Stephen Clark baInstitute for Transport Studies,University of Leeds,Woodhouse Lane,Leeds LS29JT,UK b Leeds City Council,Leonardo Building,2Rossington Street,Leeds LS28HD,UKa r t i c l e i n f o Article history:Received 24May 2010Received in revised form 15July 2011Accepted 7September 2011Keywords:Traffic assignment Network models Equilibrium Route choice Day-to-day variabilitya b s t r a c tIn spite of their widespread use in policy design and evaluation,relatively little evidencehas been reported on how well traffic equilibrium models predict real network impacts.Here we present what we believe to be the first paper that together analyses the explicitimpacts on observed route choice of an actual network intervention and compares thiswith the before-and-after predictions of a network equilibrium model.The analysis isbased on the findings of an empirical study of the travel time and route choice impactsof a road capacity reduction.Time-stamped,partial licence plates were recorded across aseries of locations,over a period of days both with and without the capacity reduction,and the data were ‘matched’between locations using special-purpose statistical methods.Hypothesis tests were used to identify statistically significant changes in travel times androute choice,between the periods of days with and without the capacity reduction.A trafficnetwork equilibrium model was then independently applied to the same scenarios,and itspredictions compared with the empirical findings.From a comparison of route choice pat-terns,a particularly influential spatial effect was revealed of the parameter specifying therelative values of distance and travel time assumed in the generalised cost equations.When this parameter was ‘fitted’to the data without the capacity reduction,the networkmodel broadly predicted the route choice impacts of the capacity reduction,but with othervalues it was seen to perform poorly.The paper concludes by discussing the wider practicaland research implications of the study’s findings.Ó2011Elsevier Ltd.All rights reserved.1.IntroductionIt is well known that altering the localised characteristics of a road network,such as a planned change in road capacity,will tend to have both direct and indirect effects.The direct effects are imparted on the road itself,in terms of how it can deal with a given demand flow entering the link,with an impact on travel times to traverse the link at a given demand flow level.The indirect effects arise due to drivers changing their travel decisions,such as choice of route,in response to the altered travel times.There are many practical circumstances in which it is desirable to forecast these direct and indirect impacts in the context of a systematic change in road capacity.For example,in the case of proposed road widening or junction improvements,there is typically a need to justify econom-ically the required investment in terms of the benefits that will likely accrue.There are also several examples in which it is relevant to examine the impacts of road capacity reduction .For example,if one proposes to reallocate road space between alternative modes,such as increased bus and cycle lane provision or a pedestrianisation scheme,then typically a range of alternative designs exist which may differ in their ability to accommodate efficiently the new traffic and routing patterns.0965-8564/$-see front matter Ó2011Elsevier Ltd.All rights reserved.doi:10.1016/j.tra.2011.09.010⇑Corresponding author.Tel.:+441133436612;fax:+441133435334.E-mail address:d.p.watling@ (D.Watling).168 D.Watling et al./Transportation Research Part A46(2012)167–189Through mathematical modelling,the alternative designs may be tested in a simulated environment and the most efficient selected for implementation.Even after a particular design is selected,mathematical models may be used to adjust signal timings to optimise the use of the transport system.Road capacity may also be affected periodically by maintenance to essential services(e.g.water,electricity)or to the road itself,and often this can lead to restricted access over a period of days and weeks.In such cases,planning authorities may use modelling to devise suitable diversionary advice for drivers,and to plan any temporary changes to traffic signals or priorities.Berdica(2002)and Taylor et al.(2006)suggest more of a pro-ac-tive approach,proposing that models should be used to test networks for potential vulnerability,before any reduction mate-rialises,identifying links which if reduced in capacity over an extended period1would have a substantial impact on system performance.There are therefore practical requirements for a suitable network model of travel time and route choice impacts of capac-ity changes.The dominant method that has emerged for this purpose over the last decades is clearly the network equilibrium approach,as proposed by Beckmann et al.(1956)and developed in several directions since.The basis of using this approach is the proposition of what are believed to be‘rational’models of behaviour and other system components(e.g.link perfor-mance functions),with site-specific data used to tailor such models to particular case studies.Cross-sectional forecasts of network performance at specific road capacity states may then be made,such that at the time of any‘snapshot’forecast, drivers’route choices are in some kind of individually-optimum state.In this state,drivers cannot improve their route selec-tion by a unilateral change of route,at the snapshot travel time levels.The accepted practice is to‘validate’such models on a case-by-case basis,by ensuring that the model—when supplied with a particular set of parameters,input network data and input origin–destination demand data—reproduces current mea-sured mean link trafficflows and mean journey times,on a sample of links,to some degree of accuracy(see for example,the practical guidelines in TMIP(1997)and Highways Agency(2002)).This kind of aggregate level,cross-sectional validation to existing conditions persists across a range of network modelling paradigms,ranging from static and dynamic equilibrium (Florian and Nguyen,1976;Leonard and Tough,1979;Stephenson and Teply,1984;Matzoros et al.,1987;Janson et al., 1986;Janson,1991)to micro-simulation approaches(Laird et al.,1999;Ben-Akiva et al.,2000;Keenan,2005).While such an approach is plausible,it leaves many questions unanswered,and we would particularly highlight two: 1.The process of calibration and validation of a network equilibrium model may typically occur in a cycle.That is to say,having initially calibrated a model using the base data sources,if the subsequent validation reveals substantial discrep-ancies in some part of the network,it is then natural to adjust the model parameters(including perhaps even the OD matrix elements)until the model outputs better reflect the validation data.2In this process,then,we allow the adjustment of potentially a large number of network parameters and input data in order to replicate the validation data,yet these data themselves are highly aggregate,existing only at the link level.To be clear here,we are talking about a level of coarseness even greater than that in aggregate choice models,since we cannot even infer from link-level data the aggregate shares on alternative routes or OD movements.The question that arises is then:how many different combinations of parameters and input data values might lead to a similar link-level validation,and even if we knew the answer to this question,how might we choose between these alternative combinations?In practice,this issue is typically neglected,meaning that the‘valida-tion’is a rather weak test of the model.2.Since the data are cross-sectional in time(i.e.the aim is to reproduce current base conditions in equilibrium),then in spiteof the large efforts required in data collection,no empirical evidence is routinely collected regarding the model’s main purpose,namely its ability to predict changes in behaviour and network performance under changes to the network/ demand.This issue is exacerbated by the aggregation concerns in point1:the‘ambiguity’in choosing appropriate param-eter values to satisfy the aggregate,link-level,base validation strengthens the need to independently verify that,with the selected parameter values,the model responds reliably to changes.Although such problems–offitting equilibrium models to cross-sectional data–have long been recognised by practitioners and academics(see,e.g.,Goodwin,1998), the approach described above remains the state-of-practice.Having identified these two problems,how might we go about addressing them?One approach to thefirst problem would be to return to the underlying formulation of the network model,and instead require a model definition that permits analysis by statistical inference techniques(see for example,Nakayama et al.,2009).In this way,we may potentially exploit more information in the variability of the link-level data,with well-defined notions(such as maximum likelihood)allowing a systematic basis for selection between alternative parameter value combinations.However,this approach is still using rather limited data and it is natural not just to question the model but also the data that we use to calibrate and validate it.Yet this is not altogether straightforward to resolve.As Mahmassani and Jou(2000) remarked:‘A major difficulty...is obtaining observations of actual trip-maker behaviour,at the desired level of richness, simultaneously with measurements of prevailing conditions’.For this reason,several authors have turned to simulated gaming environments and/or stated preference techniques to elicit information on drivers’route choice behaviour(e.g. 1Clearly,more sporadic and less predictable reductions in capacity may also occur,such as in the case of breakdowns and accidents,and environmental factors such as severe weather,floods or landslides(see for example,Iida,1999),but the responses to such cases are outside the scope of the present paper. 2Some authors have suggested more systematic,bi-level type optimization processes for thisfitting process(e.g.Xu et al.,2004),but this has no material effect on the essential points above.D.Watling et al./Transportation Research Part A46(2012)167–189169 Mahmassani and Herman,1990;Iida et al.,1992;Khattak et al.,1993;Vaughn et al.,1995;Wardman et al.,1997;Jou,2001; Chen et al.,2001).This provides potentially rich information for calibrating complex behavioural models,but has the obvious limitation that it is based on imagined rather than real route choice situations.Aside from its common focus on hypothetical decision situations,this latter body of work also signifies a subtle change of emphasis in the treatment of the overall network calibration problem.Rather than viewing the network equilibrium calibra-tion process as a whole,the focus is on particular components of the model;in the cases above,the focus is on that compo-nent concerned with how drivers make route decisions.If we are prepared to make such a component-wise analysis,then certainly there exists abundant empirical evidence in the literature,with a history across a number of decades of research into issues such as the factors affecting drivers’route choice(e.g.Wachs,1967;Huchingson et al.,1977;Abu-Eisheh and Mannering,1987;Duffell and Kalombaris,1988;Antonisse et al.,1989;Bekhor et al.,2002;Liu et al.,2004),the nature of travel time variability(e.g.Smeed and Jeffcoate,1971;Montgomery and May,1987;May et al.,1989;McLeod et al., 1993),and the factors affecting trafficflow variability(Bonsall et al.,1984;Huff and Hanson,1986;Ribeiro,1994;Rakha and Van Aerde,1995;Fox et al.,1998).While these works provide useful evidence for the network equilibrium calibration problem,they do not provide a frame-work in which we can judge the overall‘fit’of a particular network model in the light of uncertainty,ambient variation and systematic changes in network attributes,be they related to the OD demand,the route choice process,travel times or the network data.Moreover,such data does nothing to address the second point made above,namely the question of how to validate the model forecasts under systematic changes to its inputs.The studies of Mannering et al.(1994)and Emmerink et al.(1996)are distinctive in this context in that they address some of the empirical concerns expressed in the context of travel information impacts,but their work stops at the stage of the empirical analysis,without a link being made to net-work prediction models.The focus of the present paper therefore is both to present thefindings of an empirical study and to link this empirical evidence to network forecasting models.More recently,Zhu et al.(2010)analysed several sources of data for evidence of the traffic and behavioural impacts of the I-35W bridge collapse in Minneapolis.Most pertinent to the present paper is their location-specific analysis of linkflows at 24locations;by computing the root mean square difference inflows between successive weeks,and comparing the trend for 2006with that for2007(the latter with the bridge collapse),they observed an apparent transient impact of the bridge col-lapse.They also showed there was no statistically-significant evidence of a difference in the pattern offlows in the period September–November2007(a period starting6weeks after the bridge collapse),when compared with the corresponding period in2006.They suggested that this was indicative of the length of a‘re-equilibration process’in a conceptual sense, though did not explicitly compare their empiricalfindings with those of a network equilibrium model.The structure of the remainder of the paper is as follows.In Section2we describe the process of selecting the real-life problem to analyse,together with the details and rationale behind the survey design.Following this,Section3describes the statistical techniques used to extract information on travel times and routing patterns from the survey data.Statistical inference is then considered in Section4,with the aim of detecting statistically significant explanatory factors.In Section5 comparisons are made between the observed network data and those predicted by a network equilibrium model.Finally,in Section6the conclusions of the study are highlighted,and recommendations made for both practice and future research.2.Experimental designThe ultimate objective of the study was to compare actual data with the output of a traffic network equilibrium model, specifically in terms of how well the equilibrium model was able to correctly forecast the impact of a systematic change ap-plied to the network.While a wealth of surveillance data on linkflows and travel times is routinely collected by many local and national agencies,we did not believe that such data would be sufficiently informative for our purposes.The reason is that while such data can often be disaggregated down to small time step resolutions,the data remains aggregate in terms of what it informs about driver response,since it does not provide the opportunity to explicitly trace vehicles(even in aggre-gate form)across more than one location.This has the effect that observed differences in linkflows might be attributed to many potential causes:it is especially difficult to separate out,say,ambient daily variation in the trip demand matrix from systematic changes in route choice,since both may give rise to similar impacts on observed linkflow patterns across re-corded sites.While methods do exist for reconstructing OD and network route patterns from observed link data(e.g.Yang et al.,1994),these are typically based on the premise of a valid network equilibrium model:in this case then,the data would not be able to give independent information on the validity of the network equilibrium approach.For these reasons it was decided to design and implement a purpose-built survey.However,it would not be efficient to extensively monitor a network in order to wait for something to happen,and therefore we required advance notification of some planned intervention.For this reason we chose to study the impact of urban maintenance work affecting the roads,which UK local government authorities organise on an annual basis as part of their‘Local Transport Plan’.The city council of York,a historic city in the north of England,agreed to inform us of their plans and to assist in the subsequent data collection exercise.Based on the interventions planned by York CC,the list of candidate studies was narrowed by considering factors such as its propensity to induce significant re-routing and its impact on the peak periods.Effectively the motivation here was to identify interventions that were likely to have a large impact on delays,since route choice impacts would then likely be more significant and more easily distinguished from ambient variability.This was notably at odds with the objectives of York CC,170 D.Watling et al./Transportation Research Part A46(2012)167–189in that they wished to minimise disruption,and so where possible York CC planned interventions to take place at times of day and of the year where impacts were minimised;therefore our own requirement greatly reduced the candidate set of studies to monitor.A further consideration in study selection was its timing in the year for scheduling before/after surveys so to avoid confounding effects of known significant‘seasonal’demand changes,e.g.the impact of the change between school semesters and holidays.A further consideration was York’s role as a major tourist attraction,which is also known to have a seasonal trend.However,the impact on car traffic is relatively small due to the strong promotion of public trans-port and restrictions on car travel and parking in the historic centre.We felt that we further mitigated such impacts by sub-sequently choosing to survey in the morning peak,at a time before most tourist attractions are open.Aside from the question of which intervention to survey was the issue of what data to collect.Within the resources of the project,we considered several options.We rejected stated preference survey methods as,although they provide a link to personal/socio-economic drivers,we wanted to compare actual behaviour with a network model;if the stated preference data conflicted with the network model,it would not be clear which we should question most.For revealed preference data, options considered included(i)self-completion diaries(Mahmassani and Jou,2000),(ii)automatic tracking through GPS(Jan et al.,2000;Quiroga et al.,2000;Taylor et al.,2000),and(iii)licence plate surveys(Schaefer,1988).Regarding self-comple-tion surveys,from our own interview experiments with self-completion questionnaires it was evident that travellersfind it relatively difficult to recall and describe complex choice options such as a route through an urban network,giving the po-tential for significant errors to be introduced.The automatic tracking option was believed to be the most attractive in this respect,in its potential to accurately map a given individual’s journey,but the negative side would be the potential sample size,as we would need to purchase/hire and distribute the devices;even with a large budget,it is not straightforward to identify in advance the target users,nor to guarantee their cooperation.Licence plate surveys,it was believed,offered the potential for compromise between sample size and data resolution: while we could not track routes to the same resolution as GPS,by judicious location of surveyors we had the opportunity to track vehicles across more than one location,thus providing route-like information.With time-stamped licence plates, the matched data would also provide journey time information.The negative side of this approach is the well-known poten-tial for significant recording errors if large sample rates are required.Our aim was to avoid this by recording only partial licence plates,and employing statistical methods to remove the impact of‘spurious matches’,i.e.where two different vehi-cles with the same partial licence plate occur at different locations.Moreover,extensive simulation experiments(Watling,1994)had previously shown that these latter statistical methods were effective in recovering the underlying movements and travel times,even if only a relatively small part of the licence plate were recorded,in spite of giving a large potential for spurious matching.We believed that such an approach reduced the opportunity for recorder error to such a level to suggest that a100%sample rate of vehicles passing may be feasible.This was tested in a pilot study conducted by the project team,with dictaphones used to record a100%sample of time-stamped, partial licence plates.Independent,duplicate observers were employed at the same location to compare error rates;the same study was also conducted with full licence plates.The study indicated that100%surveys with dictaphones would be feasible in moderate trafficflow,but only if partial licence plate data were used in order to control observation errors; for higherflow rates or to obtain full number plate data,video surveys should be considered.Other important practical les-sons learned from the pilot included the need for clarity in terms of vehicle types to survey(e.g.whether to include motor-cycles and taxis),and of the phonetic alphabet used by surveyors to avoid transcription ambiguities.Based on the twin considerations above of planned interventions and survey approach,several candidate studies were identified.For a candidate study,detailed design issues involved identifying:likely affected movements and alternative routes(using local knowledge of York CC,together with an existing network model of the city),in order to determine the number and location of survey sites;feasible viewpoints,based on site visits;the timing of surveys,e.g.visibility issues in the dark,winter evening peak period;the peak duration from automatic trafficflow data;and specific survey days,in view of public/school holidays.Our budget led us to survey the majority of licence plate sites manually(partial plates by audio-tape or,in lowflows,pen and paper),with video surveys limited to a small number of high-flow sites.From this combination of techniques,100%sampling rate was feasible at each site.Surveys took place in the morning peak due both to visibility considerations and to minimise conflicts with tourist/special event traffic.From automatic traffic count data it was decided to survey the period7:45–9:15as the main morning peak period.This design process led to the identification of two studies:2.1.Lendal Bridge study(Fig.1)Lendal Bridge,a critical part of York’s inner ring road,was scheduled to be closed for maintenance from September2000 for a duration of several weeks.To avoid school holidays,the‘before’surveys were scheduled for June and early September.It was decided to focus on investigating a significant southwest-to-northeast movement of traffic,the river providing a natural barrier which suggested surveying the six river crossing points(C,J,H,K,L,M in Fig.1).In total,13locations were identified for survey,in an attempt to capture traffic on both sides of the river as well as a crossing.2.2.Fishergate study(Fig.2)The partial closure(capacity reduction)of the street known as Fishergate,again part of York’s inner ring road,was scheduled for July2001to allow repairs to a collapsed sewer.Survey locations were chosen in order to intercept clockwiseFig.1.Intervention and survey locations for Lendal Bridge study.around the inner ring road,this being the direction of the partial closure.A particular aim wasFulford Road(site E in Fig.2),the main radial affected,with F and K monitoring local diversion I,J to capture wider-area diversion.studies,the plan was to survey the selected locations in the morning peak over a period of approximately covering the three periods before,during and after the intervention,with the days selected so holidays or special events.Fig.2.Intervention and survey locations for Fishergate study.In the Lendal Bridge study,while the‘before’surveys proceeded as planned,the bridge’s actualfirst day of closure on Sep-tember11th2000also marked the beginning of the UK fuel protests(BBC,2000a;Lyons and Chaterjee,2002).Trafficflows were considerably affected by the scarcity of fuel,with congestion extremely low in thefirst week of closure,to the extent that any changes could not be attributed to the bridge closure;neither had our design anticipated how to survey the impacts of the fuel shortages.We thus re-arranged our surveys to monitor more closely the planned re-opening of the bridge.Unfor-tunately these surveys were hampered by a second unanticipated event,namely the wettest autumn in the UK for270years and the highest level offlooding in York since records began(BBC,2000b).Theflooding closed much of the centre of York to road traffic,including our study area,as the roads were impassable,and therefore we abandoned the planned‘after’surveys. As a result of these events,the useable data we had(not affected by the fuel protests orflooding)consisted offive‘before’days and one‘during’day.In the Fishergate study,fortunately no extreme events occurred,allowing six‘before’and seven‘during’days to be sur-veyed,together with one additional day in the‘during’period when the works were temporarily removed.However,the works over-ran into the long summer school holidays,when it is well-known that there is a substantial seasonal effect of much lowerflows and congestion levels.We did not believe it possible to meaningfully isolate the impact of the link fully re-opening while controlling for such an effect,and so our plans for‘after re-opening’surveys were abandoned.3.Estimation of vehicle movements and travel timesThe data resulting from the surveys described in Section2is in the form of(for each day and each study)a set of time-stamped,partial licence plates,observed at a number of locations across the network.Since the data include only partial plates,they cannot simply be matched across observation points to yield reliable estimates of vehicle movements,since there is ambiguity in whether the same partial plate observed at different locations was truly caused by the same vehicle. Indeed,since the observed system is‘open’—in the sense that not all points of entry,exit,generation and attraction are mon-itored—the question is not just which of several potential matches to accept,but also whether there is any match at all.That is to say,an apparent match between data at two observation points could be caused by two separate vehicles that passed no other observation point.Thefirst stage of analysis therefore applied a series of specially-designed statistical techniques to reconstruct the vehicle movements and point-to-point travel time distributions from the observed data,allowing for all such ambiguities in the data.Although the detailed derivations of each method are not given here,since they may be found in the references provided,it is necessary to understand some of the characteristics of each method in order to interpret the results subsequently provided.Furthermore,since some of the basic techniques required modification relative to the published descriptions,then in order to explain these adaptations it is necessary to understand some of the theoretical basis.3.1.Graphical method for estimating point-to-point travel time distributionsThe preliminary technique applied to each data set was the graphical method described in Watling and Maher(1988).This method is derived for analysing partial registration plate data for unidirectional movement between a pair of observation stations(referred to as an‘origin’and a‘destination’).Thus in the data study here,it must be independently applied to given pairs of observation stations,without regard for the interdependencies between observation station pairs.On the other hand, it makes no assumption that the system is‘closed’;there may be vehicles that pass the origin that do not pass the destina-tion,and vice versa.While limited in considering only two-point surveys,the attraction of the graphical technique is that it is a non-parametric method,with no assumptions made about the arrival time distributions at the observation points(they may be non-uniform in particular),and no assumptions made about the journey time probability density.It is therefore very suitable as afirst means of investigative analysis for such data.The method begins by forming all pairs of possible matches in the data,of which some will be genuine matches(the pair of observations were due to a single vehicle)and the remainder spurious matches.Thus, for example,if there are three origin observations and two destination observations of a particular partial registration num-ber,then six possible matches may be formed,of which clearly no more than two can be genuine(and possibly only one or zero are genuine).A scatter plot may then be drawn for each possible match of the observation time at the origin versus that at the destination.The characteristic pattern of such a plot is as that shown in Fig.4a,with a dense‘line’of points(which will primarily be the genuine matches)superimposed upon a scatter of points over the whole region(which will primarily be the spurious matches).If we were to assume uniform arrival rates at the observation stations,then the spurious matches would be uniformly distributed over this plot;however,we shall avoid making such a restrictive assumption.The method begins by making a coarse estimate of the total number of genuine matches across the whole of this plot.As part of this analysis we then assume knowledge of,for any randomly selected vehicle,the probabilities:h k¼Prðvehicle is of the k th type of partial registration plateÞðk¼1;2;...;mÞwhereX m k¼1h k¼1172 D.Watling et al./Transportation Research Part A46(2012)167–189。
EPOCH-II高流量输出单元I说明书
EPOCH-II ®High-Current Output UnitI 1000 VA of high current I Rugged, portable test setIUp to 187 Amperes maximum outputEPOCH-IIHigh-Current Output UnitDESCRIPTIONThe EPOCH-II ®is a high-current output unit designed to be controlled by the PULSAR ®in combination with the High-Current Interface Module to produce a rugged,portable high-current, high-volt/ampere test set. The EPOCH-II also is designed to be controlled by the EPOCH-10®Relay T est Set.PULSAR/EPOCH-II or EPOCH-10/EPOCH-II combination uses microprocessor-based, digitally synthesized sine wave generators and solid-state regulated power amplifiers to provide sinusoidal voltage and current outputs with precise control of the phase-angle relationships.These combinations will produce accurate test results even with a fluctuating power source or when testing nonlinear or highly saturable relays.An optional IEEE-488 GPIB interface transforms the EPOCH-10/EPOCH-II combination into a programmable automatic test system when used with an externalcontroller or computer. Amplitude and/or phase angle can be set to desired values, step changed, ramped, or pulsed to new values.APPLICATIONSPULSAR/EPOCH-II or EPOCH-10/EPOCH-II combination is designed to test both complex protective relays which require phase-shifting capability and simpler relays,including all overcurrent relays.The table above lists the different types of relays by device numbers, and the different combinations of a PULSAR or EPOCH-10s and an EPOCH-II required to test them.FEATURES AND BENEFITSI Output current source has a 5-minute duty cycle rating of 1000 volt-amperes.IFour output ranges at 0.01 ampere and two output ranges at 0.1 ampere are provided.IT ough steel, sealed enclosure provides a high shock and vibration resistance.ICompletely compatible with PULSAR via the High-Current Interface Module and the EPOCH-10 units.Device No.Relay TypesSpecifyOne EPOCH-II and PULSAR with High-Current Interface Module or one EPOCH-10One EPOCH-II and PULSAR with Interface Module or two EPOCH-10sInstantaneous Overcurrent up to 187 A at 1000 VADirectional Overcurrent up to 187 A at 1000 VA All of the above plus. . .Differential Distance (open-delta)50678721One EPOCH-II and PULSAR with Interface Modules or three EPOCH-10sDistance (wye)21Ground DirectionalOvercurrent up to 187 A at 1000 VA67NOvercurrent up to 187 A at 1000 VA 51 1981EPOCH-II High-Current Output UnitSPECIFICATIONSInputInput Voltage (specify one)115 V ±10%, 50/60 Hz, 30 A (at full rated output)OR230 V ±10%, 50/60 Hz, 20 AOutputOutput CurrentT o provide a variety of test circuit impedances, six output taps with two ranges are provided.High Range2.00 to 10.00 A at 100 V max3.00 to 15.00 A at 66.6 V max8.00 to 40.00 A at 25 V max10.00 to 50.00 A at 20 V max20.00 to 100.0 A at 10 V max34.00 to 170.0 A at 5.9 V maxOutput Power:1000 VALow Range2.00 to 10.00 A at 50 V max3.00 to 1 5.00 A at 33.3 V max8.00 to 40.00 A at 12.5 V max10.00 to 50.00 A at 10 V max20.00 to 100.0 A at 5 V max34.00 to 170.0 A at 2.95 V maxOutput Power:500 VAAccuracyT ypical:±0.5% of settingMaximum:±1.0% of settingAlarm will indicate when amplitude, phase angle, or waveform is in error.ResolutionFour ranges:0.01 AT wo ranges:0.l ADuty CycleFive minutes at full rated VA output. Fifteen minutes recovery time.Overrange CapabilityThe EPOCH-II has an overrange capability of +10% for each tap with a maximum output current of 187 A on the 170 A tap. DistortionLess than 1% typical, 3% max.Output of EPOCH-10/EPOCH-II CombinationFrequencyI Synchronized to input power sourceI60 Hz crystal-controlledI50 Hz crystal-controlled AccuracyI Synchronized, tracks input frequencyI±0.006 Hz for 60-Hz crystal control (±001%)I±0.005 Hz for 50-Hz crystal control (±0.01%)Output of PULSAR and Interface Module Connected to EPOCH-II The High-Current Interface Module provides a variable frequency signal to the Epoch-II High-Current Output Unit.Output frequency is continuously displayed for each channel with large, high-intensity LEDs with the following ranges:5.000 to 99.999 Hz100.01 to 999.99 HzFrequency Accuracy:±10 ppm at 23°C, ±2°C)Current Phase Angle ControlAngle is adjusted on the EPOCH-10 control unit by 4-digit, pushbutton control with large LED display of setting.Range:0.0 to 359.9°Resolution:0.1°Accuracy:less than ±0.3°typical, ±1.0°maxControl SectionThe control unit for the EPOCH-II high-current section is PULSAR (with the High-Current Interface Module), an EPOCH-I or EPOCH-10. Thus, the excellent operating and control features of PULSAR and the EPOCH-10 are used to control the EPOCH-II.Note:When the EPOCH-II is in use, the current output of the EPOCH-10 control unit is inoperative. All EPOCH-10s can control an EPOCH-II high-current section. When the high-current section of the EPOCH-II is not needed, the EPOCH-10 can be used independently or slaved together with other EPOCH units. ProtectionThe input line circuit is breaker-protected. The dc power supply is overcurrent-protected. In addition, overvoltage protection is provided on the input line circuit.The power amplifiers are forced-air cooled and are protected by thermal-overload sensors.Audio and visual alarms on the PULSAR and EPOCH-10 control units indicate whenever the current or potential outputs are overloaded.TemperatureOperating32 to 122°F (0 to 50°C)Reduced duty cycle above 113°F (45°C)Storage–13 to +158°F (–25°to +70°C)Dimensions7.6 H x 19.75 W x 21.6 D in.(193 H x 502 W x 549 D mm)Weight115 lb (52.3 kg)EPOCH-II with EPOCH-10 control unitEPOCH-II High-Current Output UnitUKArchcliffe Road Dover CT17 9EN EnglandT +44 (0) 1304 502101 F +44 (0) 1304 207342UNITED STATES4271 Bronze Way DallasTX75237-1017 USAT 800 723 2861 (USA only)T +1 214 330 3203F +1 214 337 3038OTHER TECHNICAL SALES OFFICESValley Forge USA, Toronto CANADA,Mumbai INDIA, Trappes FRANCE,Sydney AUSTRALIA, Madrid SPAINand the Kingdom of BAHRAIN.Registered to ISO 9001:2000 Reg no. Q 09290Registered to ISO 14001 Reg no. EMS 61597EPOCH_II_DS_en_V10The word ‘Megger’ is a registeredtrademark。
Exact Solutions of the Generalized Equal Width Wave Equation
(u )2 dξ = k2 , as ξ −→ +∞ ,
(13)
By substituting (14) into (13) and using the relation (11), we obtain the analytical expression of the following important square integral,
2
Derivation of the Exact Solutions
We concentrate on finding an exact solitary wave solution of the form u(x, t) = u(x − x0 − Ct) . (3)
This corresponds to a traveling-wave propagating with steady celerity C . We are interested in solutions depending only on the moving coordinate ξ = x − x0 − Ct as, u(x, t) = u(x − x0 − Ct) ≡ u(ξ ) . (4) Substituting into (2), the function u(ξ ) satisfies a third order nonlinear ordinary differential equation (ODE), −Cu + aup u − δu + µCu =0, (5)
Abstract. The equal width wave (EW) equation is a model partial differential equation for the simulation of one-dimensional wave propagation in nonlinear media with dispersion processes. The EW-Burgers equation models the propagation of nonlinear and dispersive waves with certain dissipative effects. In this work, we derive exact solitary wave solutions for the general form of the EW equation and the generalized EW-Burgers equation with nonlinear terms of any order. We also derive analytical expressions of three invariants of motion for solitary wave solutions of the generalized EW equation.
江苏省常州市2023-2024学年高二下学期教育学会学业水平监测期末考英语试卷
江苏省常州市2023-2024学年高二下学期教育学会学业水平监测期末考英语试卷一、听力选择题1．Who cleans the man’s home?A．A cleaner.B．The man himself.C．The man’s sister. 2．What time does the museum open on Saturdays?A．At 8:30 a. m.B．At 9:00 a. m.C．At 10:00 a. m.3．What was wrong with the package?A．There was no note on it.B．It was sent to the wrong apartment.C．The woman’s mother took it by mistake.4．What does the man suggest the woman do?A．Get more exercise.B．Get plenty of sleep.C．Be careful with her diet.5．What are the speakers mainly discussing?A．The schoolwork.B．A trip around Asia.C．A world news report.听下面一段较长对话，回答以下小题。
6．Where is the conversation probably taking place?A．At a party.B．In a medical lab.C．At a staff meeting. 7．What is the main problem with the self-driving cars?A．They sometimes can't avoid blocks.B．They can't follow the maps all the time.C．They can't work together with human brains.听下面一段较长对话，回答以下小题。
(完整word版)大学体验英语(第三版)课文原文及翻译
Frog Story 蛙的故事A couple of odd things have happened lately. 最近发生了几桩怪事儿.I have a log cabin in those woods of Northern Wisconsin. I built it by hand and also added a greenh ouse to the front of it. It is a joy to live in。
In fact, I work out of my home doing audio production an d environmental work。
As a tool of that trade I have a computer and a studio。
我在北威斯康星州的树林中有一座小木屋.是我亲手搭建的，前面还有一间花房.住在里面相当惬意。
实际上我是在户外做音频制作和环境方面的工作——作为干这一行的工具，我还装备了一间带电脑的工作室。
I also have a tree frog that has taken up residence in my studio. 还有一只树蛙也在我的工作室中住了下来。
How odd， I thought， last November when I first noticed him sitting atop my sound—board over my computer.I figured that he（and I say he，though I really don't have a clue if she is a he or vice versa） would be more comfortable in the green house。
So I put him in the greenhouse. Back he came. And stayed。
tpo40三篇托福阅读TOEFL原文译文题目答案译文背景知识
tpo40三篇托福阅读TOEFL原文译文题目答案译文背景知识阅读-1 (2)原文 (2)译文 (5)题目 (8)答案 (17)背景知识 (17)阅读-2 (20)原文 (20)译文 (23)题目 (25)答案 (35)背景知识 (35)阅读-3 (38)原文 (38)译文 (41)题目 (44)答案 (53)背景知识 (54)阅读-1原文Ancient Athens①One of the most important changes in Greece during the period from 800 B.C. to 500 B.C. was the rise of the polis, or city-state, and each polis developed a system of government that was appropriate to its circumstances. The problems that were faced and solved in Athens were the sharing of political power between the established aristocracy and the emerging other classes, and the adjustment of aristocratic ways of life to the ways of life of the new polis. It was the harmonious blending of all of these elements that was to produce the classical culture of Athens.②Entering the polis age, Athens had the traditional institutions of other Greek protodemocratic states: an assembly of adult males, an aristocratic council, and annually elected officials. Within this traditional framework the Athenians, between 600 B.C. and 450 B.C., evolved what Greeks regarded as a fully fledged democratic constitution, though the right to vote was given to fewer groups of people than is seen in modern times.③The first steps toward change were taken by Solon in 594 B.C., when he broke the aristocracy's stranglehold on elected offices by establishing wealth rather than birth as the basis of office holding, abolishing the economic obligations of ordinary Athenians to the aristocracy, and allowing the assembly (of which all citizens were equal members) to overrule the decisions of local courts in certain cases. The strength of the Athenian aristocracy was further weakened during the rest of the century by the rise of a type of government known as a tyranny, which is a form of interim rule by a popular strongman (not rule by a ruthless dictator as the modern use of the term suggests to us). The Peisistratids, as the succession of tyrants were called (after the founder of the dynasty, Peisistratos), strengthened Athenian central administration at the expense of the aristocracy by appointing judges throughout the region, producing Athens’ first national coinage, and adding and embellishing festivals that tended to focus attention on Athens rather than on local villages of the surrounding region. By the end of the century, the time was ripe for more change: the tyrants were driven out, and in 508 B.C. a new reformer, Cleisthenes, gave final form to the developments reducing aristocratic control already under way.④Cleisthenes' principal contribution to the creation of democracy at Athens was to complete the long process of weakening family and clanstructures, especially among the aristocrats, and to set in their place locality-based corporations called demes, which became the point of entry for all civic and most religious life in Athens. Out of the demes were created 10 artificial tribes of roughly equal population. From the demes, by either election or selection, came 500 members of a new council, 6,000 jurors for the courts, 10 generals, and hundreds of commissioners. The assembly was sovereign in all matters but in practice delegated its power to subordinate bodies such as the council, which prepared the agenda for the meetings of the assembly, and courts, which took care of most judicial matters. Various committees acted as an executive branch, implementing policies of the assembly and supervising, for instance, the food and water supplies and public buildings. This wide-scale participation by the citizenry in the government distinguished the democratic form of the Athenian polis from other less liberal forms.⑤The effect of Cleisthenes’ reforms was to establish the superiority of the Athenian community as a whole over local institutions without destroying them. National politics rather than local or deme politics became the focal point. At the same time, entry into national politics began at the deme level and gave local loyalty a new focus: Athens itself. Over the next two centuries the implications of Cleisthenes’ reforms were fully exploited.⑥During the fifth century B.C. the council of 500 was extremely influential in shaping policy. In the next century, however, it was the mature assembly that took on decision-making responsibility. By any measure other than that of the aristocrats, who had been upstaged by the supposedly inferior "people", the Athenian democracy was a stunning success. Never before, or since, have so many people been involved in the serious business of self-governance. It was precisely this opportunity to participate in public life that provided a stimulus for the brilliant unfolding of classical Greek culture.译文古雅典①在公元前800年到公元前500年期间，希腊最重要的变化之一是城邦的崛起，并且每个城邦都发展了适合其情况的政府体系。
David Hilbert - Mathematical Problems
Mathematical ProblemsLecture delivered before the International Congress ofMathematicians at Paris in 1900By Professor David Hilbert1Who of us would not be glad to lift the veil behind which the future lies hidden; to cast a glance at the next advances of our science and at the secrets of its development during future centuries? What particular goals will there be toward which the leading mathematical spirits of coming generations will strive? What new methods and new facts in the wide and rich field of mathematical thought will the new centuries disclose?History teaches the continuity of the development of science. We know that every age has its own problems, which the following age either solves or casts aside as profitless and replaces by new ones. If we would obtain an idea of the probable development of mathematical knowledge in the immediate future, we must let the unsettled questions pass before our minds and look over the problems which the science of today sets and whose solution we expect from the future. To such a review of problems the present day, lying at the meeting of the centuries, seems to me well adapted. For the close of a great epoch not only invites us to look back into the past but also directs our thoughts to the unknown future. The deep significance of certain problems for the advance of mathematical science in general and the important role which they play in the work of the individual investigator are not to be denied. As long as a branch of science offers an abundance of problems, so long is it alive; a lack of problems foreshadows extinction or the cessation of independent development. Just as every human undertaking pursues certain objects, so also mathematical research requires its problems. It is by the solution of problems that the investigator tests the temper of his steel; he finds new methods and new outlooks, and gains a wider and freer horizon.It is difficult and often impossible to judge the value of a problem correctly in advance; for the final award depends upon the gain which science obtains from the problem. Nevertheless we can ask whether there are general criteria which mark a good mathematical problem. An old French mathematician said: "A mathematical theory is not to be considered complete until you have made it so clear that you can explain it to the first man whom you meet on the street." This clearness and ease of comprehension, here insisted on for a mathematical theory, I should still more demand for a mathematical problem if it is to be perfect; for what is clear and easily comprehended attracts, the complicated repels us.Moreover a mathematical problem should be difficult in order to entice us, yet not completely inaccessible, lest it mock at our efforts. It should be to us a guide post on the mazy paths to hidden truths, and ultimately a reminder of our pleasure in the successful solution.The mathematicians of past centuries were accustomed to devote themselves to the solution of difficult particular problems with passionate zeal. They knew the value of difficult problems. I remind you only of the "problem of the line of quickest descent," proposed by John Bernoulli. Experience teaches, explains Bernoulli in the public announcement of this problem, that lofty minds are led to strive for the advance of science by nothing more than by laying before them difficult and at the same time useful problems, and he therefore hopes to earn the thanks of the mathematical world by following the example of men like Mersenne, Pascal, Fermat, Viviani and others and laying before the distinguished analysts of his time a problem by which, as a touchstone, they may test the value of their methods and measure their strength. The calculus of variations owes its origin to this problem of Bernoulli and to similar problems.Fermat had asserted, as is well known, that the diophantine equationx n + y n = z n(x, y and z integers) is unsolvable—except in certain self evident cases. The attempt to prove this impossibility offers a striking example of the inspiring effect which such a very special and apparently unimportant problem may have upon science. For Kummer, incited by Fermat's problem, was led to the introduction of ideal numbers and to the discovery of the law of the unique decomposition of the numbers of a circular field into ideal prime factors—a law which today, in its generalization to any algebraic field by Dedekind and Kronecker, stands at the center of the modern theory of numbers and whose significance extends far beyond the boundaries of number theory into the realm of algebra and the theory of functions.To speak of a very different region of research, I remind you of the problem of three bodies. The fruitful methods and the far-reaching principles which Poincaré has brought into celestial mechanics and which are today recognized and applied in practical astronomy are due to the circumstance that he undertook to treat anew that difficult problem and to approach nearer a solution.The two last mentioned problems—that of Fermat and the problem of the three bodies—seem to us almost like opposite poles—the former a free invention of pure reason, belonging to the region of abstract number theory, the latter forced upon us by astronomy and necessary to an understanding of the simplest fundamental phenomena of nature.But it often happens also that the same special problem finds application in the most unlike branches of mathematical knowledge. So, for example, the problem of the shortest line plays a chief and historically important part in the foundations of geometry, in the theory of curved lines and surfaces, in mechanics and in the calculus of variations. And how convincingly has F. Klein, in his work on the icosahedron, pictured the significance which attaches to the problem of the regular polyhedra in elementary geometry, in group theory, in the theory of equations and in that of linear differential equations.In order to throw light on the importance of certain problems, I may also refer to Weierstrass, who spokeof it as his happy fortune that he found at the outset of his scientific career a problem so important as Jacobi's problem of inversion on which to work.Having now recalled to mind the general importance of problems in mathematics, let us turn to the question from what sources this science derives its problems. Surely the first and oldest problems in every branch of mathematics spring from experience and are suggested by the world of external phenomena. Even the rules of calculation with integers must have been discovered in this fashion in a lower stage of human civilization, just as the child of today learns the application of these laws by empirical methods. The same is true of the first problems of geometry, the problems bequeathed us by antiquity, such as the duplication of the cube, the squaring of the circle; also the oldest problems in the theory of the solution of numerical equations, in the theory of curves and the differential and integral calculus, in the calculus of variations, the theory of Fourier series and the theory of potential—to say nothing of the further abundance of problems properly belonging to mechanics, astronomy and physics. But, in the further development of a branch of mathematics, the human mind, encouraged by the success of its solutions, becomes conscious of its independence. It evolves from itself alone, often without appreciable influence from without, by means of logical combination, generalization, specialization, by separating and collecting ideas in fortunate ways, new and fruitful problems, and appears then itself as the real questioner. Thus arose the problem of prime numbers and the other problems of number theory, Galois's theory of equations, the theory of algebraic invariants, the theory of abelian and automorphic functions; indeed almost all the nicer questions of modern arithmetic and function theory arise in this way.In the meantime, while the creative power of pure reason is at work, the outer world again comes into play, forces upon us new questions from actual experience, opens up new branches of mathematics, and while we seek to conquer these new fields of knowledge for the realm of pure thought, we often find the answers to old unsolved problems and thus at the same time advance most successfully the old theories. And it seems to me that the numerous and surprising analogies and that apparently prearranged harmony which the mathematician so often perceives in the questions, methods and ideas of the various branches of his science, have their origin in this ever-recurring interplay between thought and experience.It remains to discuss briefly what general requirements may be justly laid down for the solution of a mathematical problem. I should say first of all, this: that it shall be possible to establish the correctness of the solution by means of a finite number of steps based upon a finite number of hypotheses which are implied in the statement of the problem and which must always be exactly formulated. This requirement of logical deduction by means of a finite number of processes is simply the requirement of rigor in reasoning. Indeed the requirement of rigor, which has become proverbial in mathematics, corresponds to a universal philosophical necessity of our understanding; and, on the other hand, only by satisfying this requirement do the thought content and the suggestiveness of the problem attain their full effect. A new problem, especially when it comes from the world of outer experience, is like a young twig, which thrives and bears fruit only when it is grafted carefully and in accordance with strict horticultural rules upon the old stem, the established achievements of our mathematical science.Besides it is an error to believe that rigor in the proof is the enemy of simplicity. On the contrary we find it confirmed by numerous examples that the rigorous method is at the same time the simpler and the more easily comprehended. The very effort for rigor forces us to find out simpler methods of proof. It also frequently leads the way to methods which are more capable of development than the old methods of less rigor. Thus the theory of algebraic curves experienced a considerable simplification and attained greater unity by means of the more rigorous function-theoretical methods and the consistent introduction of transcendental devices. Further, the proof that the power series permits the application of the four elementary arithmetical operations as well as the term by term differentiation and integration, and the recognition of the utility of the power series depending upon this proof contributed materially to the simplification of all analysis, particularly of the theory of elimination and the theory of differential equations, and also of the existence proofs demanded in those theories. But the most striking example for my statement is the calculus of variations. The treatment of the first and second variations of definite integrals required in part extremely complicated calculations, and the processes applied by the old mathematicians had not the needful rigor. Weierstrass showed us the way to a new and sure foundation of the calculus of variations. By the examples of the simple and double integral I will show briefly, at the close of my lecture, how this way leads at once to a surprising simplification of the calculus of variations. For in the demonstration of the necessary and sufficient criteria for the occurrence of a maximum and minimum, the calculation of the second variation and in part, indeed, the wearisome reasoning connected with the first variation may be completely dispensed with—to say nothing of the advance which is involved in the removal of the restriction to variations for which the differential coefficients of the function vary but slightly.While insisting on rigor in the proof as a requirement for a perfect solution of a problem, I should like, on the other hand, to oppose the opinion that only the concepts of analysis, or even those of arithmetic alone, are susceptible of a fully rigorous treatment. This opinion, occasionally advocated by eminent men, I consider entirely erroneous. Such a one-sided interpretation of the requirement of rigor would soon lead to the ignoring of all concepts arising from geometry, mechanics and physics, to a stoppage of the flow of new material from the outside world, and finally, indeed, as a last consequence, to the rejection of the ideas of the continuum and of the irrational number. But what an important nerve, vital to mathematical science, would be cut by the extirpation of geometry and mathematical physics! On the contrary I think that wherever, from the side of the theory of knowledge or in geometry, or from the theories of natural or physical science, mathematical ideas come up, the problem arises for mathematical science to investigate the principles underlying these ideas and so to establish them upon a simple and complete system of axioms, that the exactness of the new ideas and their applicability to deduction shall be in no respect inferior to those of the old arithmetical concepts.To new concepts correspond, necessarily, new signs. These we choose in such a way that they remind us of the phenomena which were the occasion for the formation of the new concepts. So the geometrical figures are signs or mnemonic symbols of space intuition and are used as such by all mathematicians. Who does not always use along with the double inequality a > b > c the picture of three points following one another on a straight line as the geometrical picture of the idea "between"? Who does not make use of drawings of segments and rectangles enclosed in one another, when it is required to prove with perfect rigor a difficult theorem on the continuity of functions or the existence of points of condensation? Whocould dispense with the figure of the triangle, the circle with its center, or with the cross of three perpendicular axes? Or who would give up the representation of the vector field, or the picture of a family of curves or surfaces with its envelope which plays so important a part in differential geometry, in the theory of differential equations, in the foundation of the calculus of variations and in other purely mathematical sciences?The arithmetical symbols are written diagrams and the geometrical figures are graphic formulas; and no mathematician could spare these graphic formulas, any more than in calculation the insertion and removal of parentheses or the use of other analytical signs.The use of geometrical signs as a means of strict proof presupposes the exact knowledge and complete mastery of the axioms which underlie those figures; and in order that these geometrical figures may be incorporated in the general treasure of mathematical signs, there is necessary a rigorous axiomatic investigation of their conceptual content. Just as in adding two numbers, one must place the digits under each other in the right order, so that only the rules of calculation, i. e., the axioms of arithmetic, determine the correct use of the digits, so the use of geometrical signs is determined by the axioms of geometrical concepts and their combinations.The agreement between geometrical and arithmetical thought is shown also in that we do not habitually follow the chain of reasoning back to the axioms in arithmetical, any more than in geometrical discussions. On the contrary we apply, especially in first attacking a problem, a rapid, unconscious, not absolutely sure combination, trusting to a certain arithmetical feeling for the behavior of the arithmetical symbols, which we could dispense with as little in arithmetic as with the geometrical imagination in geometry. As an example of an arithmetical theory operating rigorously with geometrical ideas and signs, I may mention Minkowski's work, Die Geometrie der Zahlen.2Some remarks upon the difficulties which mathematical problems may offer, and the means of surmounting them, may be in place here.If we do not succeed in solving a mathematical problem, the reason frequently consists in our failure to recognize the more general standpoint from which the problem before us appears only as a single link in a chain of related problems. After finding this standpoint, not only is this problem frequently more accessible to our investigation, but at the same time we come into possession of a method which is applicable also to related problems. The introduction of complex paths of integration by Cauchy and of the notion of the IDEALS in number theory by Kummer may serve as examples. This way for finding general methods is certainly the most practicable and the most certain; for he who seeks for methods without having a definite problem in mind seeks for the most part in vain.In dealing with mathematical problems, specialization plays, as I believe, a still more important part than generalization. Perhaps in most cases where we seek in vain the answer to a question, the cause of the failure lies in the fact that problems simpler and easier than the one in hand have been either not at all or incompletely solved. All depends, then, on finding out these easier problems, and on solving them bymeans of devices as perfect as possible and of concepts capable of generalization. This rule is one of the most important levers for overcoming mathematical difficulties and it seems to me that it is used almost always, though perhaps unconsciously.Occasionally it happens that we seek the solution under insufficient hypotheses or in an incorrect sense, and for this reason do not succeed. The problem then arises: to show the impossibility of the solution under the given hypotheses, or in the sense contemplated. Such proofs of impossibility were effected by the ancients, for instance when they showed that the ratio of the hypotenuse to the side of an isosceles right triangle is irrational. In later mathematics, the question as to the impossibility of certain solutions plays a preeminent part, and we perceive in this way that old and difficult problems, such as the proof of the axiom of parallels, the squaring of the circle, or the solution of equations of the fifth degree by radicals have finally found fully satisfactory and rigorous solutions, although in another sense than that originally intended. It is probably this important fact along with other philosophical reasons that gives rise to the conviction (which every mathematician shares, but which no one has as yet supported by a proof) that every definite mathematical problem must necessarily be susceptible of an exact settlement, either in the form of an actual answer to the question asked, or by the proof of the impossibility of its solution and therewith the necessary failure of all attempts. Take any definite unsolved problem, such as the question as to the irrationality of the Euler-Mascheroni constant C, or the existence of an infinite number of prime numbers of the form 2n + 1. However unapproachable these problems may seem to us and however helpless we stand before them, we have, nevertheless, the firm conviction that their solution must follow by a finite number of purely logical processes.Is this axiom of the solvability of every problem a peculiarity characteristic of mathematical thought alone, or is it possibly a general law inherent in the nature of the mind, that all questions which it asks must be answerable? For in other sciences also one meets old problems which have been settled in a manner most satisfactory and most useful to science by the proof of their impossibility. I instance the problem of perpetual motion. After seeking in vain for the construction of a perpetual motion machine, the relations were investigated which must subsist between the forces of nature if such a machine is to be impossible;3 and this inverted question led to the discovery of the law of the conservation of energy, which, again, explained the impossibility of perpetual motion in the sense originally intended.This conviction of the solvability of every mathematical problem is a powerful incentive to the worker. We hear within us the perpetual call: There is the problem. Seek its solution. You can find it by pure reason, for in mathematics there is no ignorabimus.The supply of problems in mathematics is inexhaustible, and as soon as one problem is solved numerous others come forth in its place. Permit me in the following, tentatively as it were, to mention particular definite problems, drawn from various branches of mathematics, from the discussion of which an advancement of science may be expected.Let us look at the principles of analysis and geometry. The most suggestive and notable achievements of the last century in this field are, as it seems to me, the arithmetical formulation of the concept of thecontinuum in the works of Cauchy, Bolzano and Cantor, and the discovery of non-euclidean geometry by Gauss, Bolyai, and Lobachevsky. I therefore first direct your attention to some problems belonging to these fields.1. Cantor's problem of the cardinal number of the continuumTwo systems, i. e, two assemblages of ordinary real numbers or points, are said to be (according to Cantor) equivalent or of equal cardinal number, if they can be brought into a relation to one another such that to every number of the one assemblage corresponds one and only one definite number of the other. The investigations of Cantor on such assemblages of points suggest a very plausible theorem, which nevertheless, in spite of the most strenuous efforts, no one has succeeded in proving. This is the theorem:Every system of infinitely many real numbers, i. e., every assemblage of numbers (or points), is either equivalent to the assemblage of natural integers, 1, 2, 3,... or to the assemblage of all real numbers and therefore to the continuum, that is, to the points of a line; as regards equivalence there are, therefore, only two assemblages of numbers, the countable assemblage and the continuum.From this theorem it would follow at once that the continuum has the next cardinal number beyond that of the countable assemblage; the proof of this theorem would, therefore, form a new bridge between the countable assemblage and the continuum.Let me mention another very remarkable statement of Cantor's which stands in the closest connection with the theorem mentioned and which, perhaps, offers the key to its proof. Any system of real numbers is said to be ordered, if for every two numbers of the system it is determined which one is the earlier and which the later, and if at the same time this determination is of such a kind that, if a is before b and b is before c, then a always comes before c. The natural arrangement of numbers of a system is defined to be that in which the smaller precedes the larger. But there are, as is easily seen infinitely many other ways in which the numbers of a system may be arranged.If we think of a definite arrangement of numbers and select from them a particular system of these numbers, a so-called partial system or assemblage, this partial system will also prove to be ordered. Now Cantor considers a particular kind of ordered assemblage which he designates as a well ordered assemblage and which is characterized in this way, that not only in the assemblage itself but also in every partial assemblage there exists a first number. The system of integers 1, 2, 3, ... in their natural order is evidently a well ordered assemblage. On the other hand the system of all real numbers, i. e., the continuum in its natural order, is evidently not well ordered. For, if we think of the points of a segment of a straight line, with its initial point excluded, as our partial assemblage, it will have no first element.The question now arises whether the totality of all numbers may not be arranged in another manner so that every partial assemblage may have a first element, i. e., whether the continuum cannot be consideredas a well ordered assemblage—a question which Cantor thinks must be answered in the affirmative. It appears to me most desirable to obtain a direct proof of this remarkable statement of Cantor's, perhaps by actually giving an arrangement of numbers such that in every partial system a first number can be pointed out.2. The compatibility of the arithmetical axiomsWhen we are engaged in investigating the foundations of a science, we must set up a system of axioms which contains an exact and complete description of the relations subsisting between the elementary ideas of that science. The axioms so set up are at the same time the definitions of those elementary ideas; and no statement within the realm of the science whose foundation we are testing is held to be correct unless it can be derived from those axioms by means of a finite number of logical steps. Upon closer consideration the question arises: Whether, in any way, certain statements of single axioms depend upon one another, and whether the axioms may not therefore contain certain parts in common, which must be isolated if one wishes to arrive at a system of axioms that shall be altogether independent of one another. But above all I wish to designate the following as the most important among the numerous questions which can be asked with regard to the axioms: To prove that they are not contradictory, that is, that a definite number of logical steps based upon them can never lead to contradictory results.In geometry, the proof of the compatibility of the axioms can be effected by constructing a suitable field of numbers, such that analogous relations between the numbers of this field correspond to the geometrical axioms. Any contradiction in the deductions from the geometrical axioms must thereupon be recognizable in the arithmetic of this field of numbers. In this way the desired proof for the compatibility of the geometrical axioms is made to depend upon the theorem of the compatibility of the arithmetical axioms.On the other hand a direct method is needed for the proof of the compatibility of the arithmetical axioms. The axioms of arithmetic are essentially nothing else than the known rules of calculation, with the addition of the axiom of continuity. I recently collected them4 and in so doing replaced the axiom of continuity by two simpler axioms, namely, the well-known axiom of Archimedes, and a new axiom essentially as follows: that numbers form a system of things which is capable of no further extension, as long as all the other axioms hold (axiom of completeness). I am convinced that it must be possible to find a direct proof for the compatibility of the arithmetical axioms, by means of a careful study and suitable modification of the known methods of reasoning in the theory of irrational numbers.To show the significance of the problem from another point of view, I add the following observation: If contradictory attributes be assigned to a concept, I say, that mathematically the concept does not exist. So, for example, a real number whose square is -l does not exist mathematically. But if it can be proved that the attributes assigned to the concept can never lead to a contradiction by the application of a finite number of logical processes, I say that the mathematical existence of the concept (for example, of a number or a function which satisfies certain conditions) is thereby proved. In the case before us, wherewe are concerned with the axioms of real numbers in arithmetic, the proof of the compatibility of the axioms is at the same time the proof of the mathematical existence of the complete system of real numbers or of the continuum. Indeed, when the proof for the compatibility of the axioms shall be fully accomplished, the doubts which have been expressed occasionally as to the existence of the complete system of real numbers will become totally groundless. The totality of real numbers, i. e., the continuum according to the point of view just indicated, is not the totality of all possible series in decimal fractions, or of all possible laws according to which the elements of a fundamental sequence may proceed. It is rather a system of things whose mutual relations are governed by the axioms set up and for which all propositions, and only those, are true which can be derived from the axioms by a finite number of logical processes. In my opinion, the concept of the continuum is strictly logically tenable in this sense only. It seems to me, indeed, that this corresponds best also to what experience and intuition tell us. The concept of the continuum or even that of the system of all functions exists, then, in exactly the same sense as the system of integral, rational numbers, for example, or as Cantor's higher classes of numbers and cardinal numbers. For I am convinced that the existence of the latter, just as that of the continuum, can be proved in the sense I have described; unlike the system of all cardinal numbers or of all Cantor s alephs, for which, as may be shown, a system of axioms, compatible in my sense, cannot be set up. Either of these systems is, therefore, according to my terminology, mathematically non-existent.From the field of the foundations of geometry I should like to mention the following problem:3. The equality of two volumes of two tetrahedra of equal bases and equal altitudesIn two letters to Gerling, Gauss5 expresses his regret that certain theorems of solid geometry depend upon the method of exhaustion, i. e., in modern phraseology, upon the axiom of continuity (or upon the axiom of Archimedes). Gauss mentions in particular the theorem of Euclid, that triangular pyramids of equal altitudes are to each other as their bases. Now the analogous problem in the plane has been solved.6 Gerling also succeeded in proving the equality of volume of symmetrical polyhedra by dividing them into congruent parts. Nevertheless, it seems to me probable that a general proof of this kind for the theorem of Euclid just mentioned is impossible, and it should be our task to give a rigorous proof of its impossibility. This would be obtained, as soon as we succeeded in specifying two tetrahedra of equal bases and equal altitudes which can in no way be split up into congruent tetrahedra, and which cannot be combined with congruent tetrahedra to form two polyhedra which themselves could be split up into congruent tetrahedra.74. Problem of the straight line as the shortest distance between two pointsAnother problem relating to the foundations of geometry is this: If from among the axioms necessary to。
河北省2024-2025学年高三上学期9月月考英语试题
河北省2024-2025学年高三上学期9月月考英语试题一、听力选择题1．What will the man probably do next?A．Make a cake.B．Take part in a race.C．Stop at the supermarket. 2．What does the man advise the woman to do?A．Take a few risks.B．Watch out for potential dangers.C．Avoid harming the natural system.3．What does the man intend to do?A．Buy a house.B．Expand his house.C．Advertise his house. 4．What are the speakers talking about?A．Drink orders.B．Items on the menu.C．Their favorite fruit. 5．Who is Elle most likely to be?A．Elena’s sister.B．John’s daughter.C．John’s elder sister.听下面一段较长对话，回答以下小题。
6．What do we know about Rob Brown?A．He will graduate next year.B．He takes an interest in cooking.C．He’s dissatisfied with Stacy’s service.7．What problem does Stacy find out?A．Rob clicked the wrong birth date.B．Rob selected the wrong year for his class.C．Rob didn’t know how to register for the course.听下面一段较长对话，回答以下小题。
distance
distanceDistance is a concept that plays a significant role in several fields, including mathematics, physics, and everyday life. It refers to the measurement of space between two points or objects. Distance is one of the fundamental quantities that help us understand and describe the world around us. In this document, we will explore the various aspects of distance and how it is relevant in different domains.In mathematics, distance is defined as the length of the shortest path between two points. It can be measured in one, two, or three dimensions. In one dimension, distance is simply the absolute value of the difference between two points on a number line. For example, the distance between points -5 and 3 is 8 units. In two or three dimensions, distance is calculated using the Pythagorean theorem. This theorem states that the square of the distance between two points is equal to the sum of the squares of the differences in their coordinates. This formula allows us to calculate distances in two-dimensional planes or three-dimensional spaces.In physics, distance is a crucial concept for describing the motion of objects. It is closely related to the concept of displacement, which is the change in position of an object.Distance measures the total path traveled by an object, regardless of the direction. On the other hand, displacement measures the straight-line distance between the initial and final positions. For example, if an object travels 10 meters north and then returns 10 meters south, its displacement is zero, but its total distance is 20 meters. Understanding the difference between distance and displacement is important for accurately describing and analyzing the motion of objects.In everyday life, distance is a common measurement that we use to describe the space between objects or locations. It helps us determine the length of a journey, the spacing between objects in a room, or the proximity of one location to another. Distance is often measured using standard units such as meters, kilometers, miles, or feet. These units allow us to have a common language when discussing distances and enable us to make accurate comparisons.One practical application of distance measurement is in navigation systems, such as GPS (Global Positioning System). These systems use satellite signals to determine the distance between a user's location and a desired destination. By calculating the distance, the GPS device can provide the user with accurate directions and estimated travel times.Distance is also relevant in the study of geography. Geographers use distance to measure the size and shape of regions, determine the proximity of natural resources, and analyze the relationship between different geographic features. They use tools like maps, GIS (Geographic Information System), and remote sensing technologies to measure and analyze distances accurately.In addition to physical distance, there is also the concept of psychological or emotional distance. This refers to the perceived separation between individuals in terms of their thoughts, feelings, and relationships. Psychological distance can vary depending on factors such as familiarity, cultural background, and personal experiences. Understanding and managing psychological distance is crucial for effective communication, empathy, and building relationships.In conclusion, distance is a fundamental concept that is relevant in various fields and aspects of life. Whether it is measuring physical space, analyzing motion, navigating through spaces, or understanding human relationships, distance plays a vital role in our everyday lives. By understanding and quantifying distance, we can better comprehend the world around us and make informed decisions based on this knowledge.。
- 1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。
a r X i v :a s t r o -p h /0409343v 1 14 S e p 2004Proceedings of the 7th European VLBI Network SymposiumBachiller,R.Colomer,F.,Desmurs,J.F.,de Vicente,P.(eds.)October 12th-152004,Toledo,SpainDistance of W3(OH)by VLBI annual parallax measurementK.Hachisuka 1,A.Brunthaler 2,1,Y.Hagiwara 3,K.M.Menten 1,H.Imai 4,M.Miyoshi 5,and T.Sasao 61Max-Planck-Institut f¨u r Radioastronomie,Auf dem H¨u gel 69,53121Bonn,Germany 2Joint Institute for VLBI in Europe,Postbus 2,7990AA Dwingeloo,The Netherlands 3ASTRON,Westerbork Observatory,P.O.Box 2,7990AA Dwingeloo,The Netherlands 4Department of Physics,Kagoshima University,Kagoshima 890-0065,Japan 5National Astronomical Observatory,Mitaka,Tokyo 181-8588,Japan6Department of Space Survey and Information Technology,Ajou University,Suwon,442-749,Republic of KoreaAbstract.The most powerful tool for measuring distances within our Galaxy is the annual parallax.We carried out phase-referencing VLBI observations of H 2O masers in the star forming region W3(OH)with respect to the extragalactic continuum source ICRF 0244+624to measure their absolute proper motions.The measured annualparallax is 0.484±0.004milli-arcseconds which corresponds to a distance of 2.07+0.01−0.02kpc from the sun.This distance is consistent with photometric and kinematic distances from previous observations.1.IntroductionThe annual parallax is the most powerful tool for the de-termination of distances to objects in our Galaxy.The Hipparcos satellite successfully measured the distances to many stars in the Solar neighborhood.Those results contributed to various field of modern astronomy (e.g.Perryman et al.1995).However,annual parallax measure-ments for far-away sources with kpc distances using single telescopes are impossible,since the value of the annual parallax is very small,e.g.,1milli arcsecond (mas)at a distance of 1kilopersecs (kpc).In fact,the Hipparcos satellite only determined the distances of stars within 200pc from the Sun.On the other hand,Very Long Baseline Interferometry (VLBI)provides the highest resolution in astronomy.In phase-referencing VLBI,the position of a target source is measured relative to a nearby positional reference source (see e.g.Beasley &Conway 1995;Ros 2003).The fea-sibility of annual parallax measurements with VLBI has been demonstrated by Brisken et al.(2002)who measured annual parallaxes of pulsars in the Galaxy and by van Langevelde et al.(2000)and Vlemmings et al.(2002)who measured distances of Galactic OH masers associated with late type stars.Their results indicate that VLBI astrom-etry can measure distances of up to a few kpc.Hence,a large part of the Milky Way can be accessed by VLBI.This enables us to understand the Galactic structure and dynamics by VLBI astrometry since many maser sources exist in the whole Galaxy (e.g.Wouterloot et al.1993)and are high brightness VLBI targets.As our first step into this field of study,we ob-served H 2O masers in the Galactic star forming region W3(OH)and,alternately,the close-by extragalactic con-tinuum source J0244+624with phase-referencing VLBI.Here we report the result of an annual parallax measure-ment of H 2O maser features in W3(OH).2.Observation and data reduction 2.1.Observed sourcesWe selected W3(OH)as our target source since it is one of the strongest Galactic H 2O maser sources.Located in the Perseus arm,W3(OH)was thought to have a distance of about 2.3kpc from the Sun (Georgelin &Georgelin 1976;Humphreys 1978).Relative proper motions of H 2O masers in W3(OH)have been measured before with VLBI (Alcolea et al.1992).These masers move in a bipolar out-flow,originating in the so-called Turner-Welch (TW)ob-ject,which is thought to be a high or intermediate-mass protostar (e.g.,Reid et al.1995;Wyrowski et al.1999).We used ICRF 0244+624as a phase-reference source.Its angular separation from W3(OH)is 2.17degrees.Since this source is extragalactic with a redshift of 0.0438(Margon &Kwitter 1978),its own proper motion is negli-gible.It is also very strong and compact at lower frequen-cies (Fey &Charlot.2000).Thus,it is very useful as a phase-reference source.2.2.VLBA multi-epoch observationsSeven epochs of observations were made over the course of 16months (Table 1).Time separations were from two to four months.Each observation was carried out during 4hours including calibrator observations.NRAO150was observed for 5minutes every 44minutes for delay and bandpass calibration.W3(OH)and ICRF 0244+624were observed with fast anntena-switching phase-referencing mode and at high elevation.The typical elevation varied from 46to 62degrees.The switching cycle was 40sec-onds at all epochs,typical on-source time was 7seconds for W3(OH)and ICRF 0244+624,respectively.All observations were made with the ten station NRAO VLBA1.Two antennas(KP and LA)did not observe in thefirst epoch because of heavy snow,one anntena(PT) wasflagged in the third and seventh epoch since most of the data was lost because of system troubles.Also,SC was flagged in all epochs,since it produced no useful data.All Data were recorded using the VLBA recorder with two base-band channels(BBCs)and a bandwidth of16MHz. Data correlation was made with1024spectral channels in each BBC with an integration time of2seconds.The re-sulting velocity spacing of each spectral channel was0.224 km s−1at22.24GHz.Table1.Summary of the VLBA observations.2001/01/2801:11:00–05:13:00(UT)72001/05/1218:20:00–22:20:00(UT)92001/07/1214:20:00–18:20:00(UT)82001/08/2511:27:00–15:27:00(UT)92001/10/2307:35:00–11:35:00(UT)92002/01/1202:16:00–06:16:00(UT)92002/05/0618:44:00–22:44:00(UT)71The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities,Inc.tions.It is difficult to exactly trace the same maser feature since H2O masers are highly time variable and their abso-lute proper motions relative to the extragalactic reference source were non-linear because of the effect of the paral-lax.3.Results3.1.Reference source:ICRF0244+624The extragalactic continuum source ICRF0244+624was detected in all epochs.The peakflux densities were always over0.9Jy/beam,which is strong enough for a excellent phase calibration.The structure of this source was com-pact and unresolved like in previous VLBI observations at lower frequencies.Positions of the peak between all epochs werefluctuating within±10µas from the map origin.The standard deviations of the peak position were6.5µas in right ascension and7.6µas in declination,which we take as the uncertainty of the reference position.3.2.Galactic H2O maser source:W3(OH)H2O masers in W3(OH)were detected in all epochs.The peakflux densities were from a few hundred mJy to one thousand Jy.The masers were distributed over an area of 2.5”×0.5”(Figure1)which is consistent with previous VLBI observations(Alcolea et al.1992).Figure1contains only the15maser features that were detected in at least 5epochs.These features are listed in Table2.The maser features were usually detected in2to7adjacent velocity channels.There were additionally many other short lived H2O maser features.The typical formal position error of each H2O maser spot was10µas in right ascension and20µas in decli-nation.Figure2shows the absolute proper motion of the maser feature2in Table2.This proper motion is the sum of the inner motion in W3(OH),the annual parallax,the Galactic rotation,Solar motion and probably a peculiar motion of W3(OH)which might differ from the Galactic rotation.All motions except the annual parallax are lin-ear motions.Also,these motions are equal for all maser features except the inner motion.Decoffset(mas)RA offset (mas)−200−100100−2500−2000−1500−1000−500200Fig.1.Spatial distribution of H2O maser features in W3(OH).The open square shows that the H2O maser fea-ture was detected over5epochs.Table2.List of detected maser features.The columnsgive the name,number of channels with emission used inthe modelfit,number of epochs,position offset from thephase center atfirst detected epoch and LSR velocity.147–4.99–5.6–48.6247–9.6833.4–49.0336–7.7233.3–48.6425–5.6232.9–50.1535–13.7049.2–49.4626–21.6863.2–49.0735–19.5462.2–48.8846–38.1697.9–49.4977–144.50–144.3–51.11045–653.6492.1–52.61126–646.0790.2–51.51245–653.2792.3–51.91336–662.8695.0–54.71457–2045.84–133.4–45.21556–2231.2884.1–62.8,∆πiwhere πi and ∆πi are the parallax and its error from fit i and ¯πis the parallax from the combined fit.2468101214012345NRiFig.4.Histogram of parameter R i (see text)for the indi-vidual fits and the expectation from a Gaussian distribu-tion of errors (dashed line).A histogram of this parameter R i is shown in Figure 4together with the expectation for a Gaussian distribution of parallaxes.It can be clearly seen that the data is in good agreement with a Gaussian distribution.Hence,the fitting results are dominated by statistical and not by systematic errors.An annual parallax for W3(OH)of 0.484±0.004kpccorresponds to a distance of 2.07+0.01−0.02kpc.Georgelin &Georgelin (1976)estimated a kinematic distance of 2.3kpc for W3(OH)and Humphreys (1978)estimated a pho-tometric distance of 2.2kpc to the OB association near W3(OH).4.ConclusionWe estimated an annual parallax of 0.484±0.004mas for W3(OH)from the absolute proper motions of associated H 2O maser features.This corresponds to a distance of2.07+0.01−0.02kpc and is consistent with past determinations.The absolute proper motion is the sum of the annual parallax and a linear component.The linear component includes the inner motion of each maser feature,which can be estimated independently from the motion relative to a reference maser feature.After subtracting the inner motions,all maser components will have the same proper motions.The linear part of these motions can be deter-mined from maser features which are detected in more than five epochs.Thus,we can decrease the number of free parameters by fixing the linear component.Then we can also use components which are detectable in less than 5epochs.This has the potential to increase the accuracy of the annual parallax even further.We will also get the total proper motion of W3(OH)from this observation and this will help to constrain models of the Galactic rotation.This will be the subject of an upcoming paper.There are other H 2O of other maser sources withclose-by positional reference sources in the Galaxy.Thus,it is possible to determine the distance of other maser sources with phase-referencing VLBI astrometric observa-tions with similar accuracy to the case of the H 2O masers in W3(OH).We are planning an extensive program to use parallax and proper motion measurements to constrain Galactic structure and rotation.Acknowledgements.We are grateful to Dr.Mark Reid for very helpful discussions.ReferencesAlcolea,J.,Menten,K.M.,Moran,J.M.,&Reid,M.J.1992,in Astrophysical Masers,ed.A.W.Clegg &G.E.Nedoluha (Heidelberg:Springer),225Beasley,A.J.,&Conway,J.E.1995,Very Long BaselineInterferometry and the VLBA,ed.J. A.Zensus,P.J.Diamond,&P.J.Napier (San Francisco:ASP),ASP Conf.Ser.,82,328Brisken,W.F.,Benson,J.M.&Goss,W.M.,2002,Ape,571,906Brunthaler, A.,Reid,M.J.&Falcke,H.,2003,astro-ph/0309575Fey,A.L.&Charlot,P.2000,ApJS,128,17Georgelin,Y.M.,&Georgelin,Y.P.1976,A&A,49,57Margon,B.&Kwitter,K.B.1978,Apj,224,L43Perryman,M.A.C.,Lindegren,L.,Kovalevsky,J.,et al.1995,A&A,304,69Reid,M.J.,Argon,A.L.,Masson,C.R.,et al.1995,ApJ,238,443Ros,E.2003,astro-ph/0308265van Langevelde,H.J.,Vlemmings,W.,Diamond,P.J.,et al.2000,A&A,357,945Vlemmings,W.,van Langevelde,H.J.,Diamond,P.J.,et al.2003,A&A,407,213Wouterloot,J.G.A.,Brand,J.,&Fiegle,K.1993,A&AS,98,589Wyrowski,F.,Schilke,P.,Walmsley,C.M.,&Menten,K.M.1999,ApJ,514,L43。