Interaction Between Structural Changes in Machine Translation
语言学名词解释
一、名词解释1.Diachronic历时的It refers to say of the study of developing of language and languages over time.研究语言随时间发展变化的方法。
2.Arbitrariness任意性Saussure first refers to the fact that the forms of linguistic signs bear no natural relationship to their meaning.任意性是指语言符号的形式与所表达的意义之间没有天然或逻辑的联系。
It is refers to absence of any physical correspondence between linguistic signals and the entities to which they refer.任意性是指语言符号和这些符号所指的实体间不存在任何物质的联系。
3.Parole言语It refers to the concrete utterances of a speaker.指语言在实际使用中的实现。
4.Creativity创造性By creativity we mean language is resourceful because of its duality and its recursiveness, which enables human beings to produce and understand an infinitely large number of sentences including the sentences that were never heard before.创造性是指语言具有能产型，因为语言有双重性和递归性,也就是说话者能够结合各个语言单位形成无尽的句子，其中很多句子是以前没有的或者没有听说过的。
岩土工程中英文对照外文翻译文献
中英文对照外文翻译(文档含英文原文和中文翻译)原文:Safety Assurance for Challenging Geotechnical Civil Engineering Constructions in Urban AreasAbstractSafety is the most important aspect during design, construction and service time of any structure, especially for challenging projects like high-rise buildings and tunnels in urban areas. A high level design considering the soil-structure interaction, based on a qualified soil investigation is required for a safe and optimised design. Dueto the complexity of geotechnical constructions the safety assurance guaranteed by the 4-eye-principle is essential. The 4-eye-principle consists of an independent peer review by publicly certified experts combined with the observational method. The paper presents the fundamental aspects of safety assurance by the 4-eye-principle. The application is explained on several examples, as deep excavations, complex foundation systems for high-rise buildings and tunnel constructions in urban areas. The experiences made in the planning, design and construction phases are explained and for new inner urban projects recommendations are given.Key words: Natural Asset; Financial Value; Neural Network1.IntroductionA safety design and construction of challenging projects in urban areas is based on the following main aspects:Qualified experts for planning, design and construction;Interaction between architects, structural engineers and geotechnical engineers;Adequate soil investigation;Design of deep foundation systems using the FiniteElement-Method (FEM) in combination with enhanced in-situ load tests for calibrating the soil parameters used in the numerical simulations;Quality assurance by an independent peer review process and the observational method (4-eye-principle).These facts will be explained by large construction projects which are located in difficult soil and groundwater conditions.2.The 4-Eye-PrincipleThe basis for safety assurance is the 4-eye-principle. This 4-eye-principle is a process of an independent peer review as shown in Figure 1. It consists of 3 parts. The investor, the experts for planning and design and the construction company belong to the first division. Planning and design are done accordingto the requirements of the investor and all relevant documents to obtain the building permission are prepared. The building authorities are the second part and are responsible for the buildingpermission which is given to the investor. The thirddivision consists of the publicly certified experts.They are appointed by the building authorities but work as independent experts. They are responsible for the technical supervision of the planning, design and the construction.In order to achieve the license as a publicly certified expert for geotechnical engineering by the building authorities intensive studies of geotechnical engineering in university and large experiences in geotechnical engineering with special knowledge about the soil-structure interaction have to be proven.The independent peer review by publicly certified experts for geotechnical engineering makes sure that all information including the results of the soil investigation consisting of labor field tests and the boundary conditions defined for the geotechnical design are complete and correct.In the case of a defect or collapse the publicly certified expert for geotechnical engineering can be involved as an independent expert to find out the reasons for the defect or damage and to develop a concept for stabilization and reconstruction [1].For all difficult projects an independent peer review is essential for the successful realization of the project.3.Observational MethodThe observational method is practical to projects with difficult boundary conditions for verification of the design during the construction time and, if necessary, during service time. For example in the European Standard Eurocode 7 (EC 7) the effect and the boundary conditions of the observational method are defined.The application of the observational method is recommended for the following types of construction projects [2]:very complicated/complex projects;projects with a distinctive soil-structure-interaction,e.g. mixed shallow and deep foundations, retaining walls for deep excavations, Combined Pile-Raft Foundations (CPRFs);projects with a high and variable water pressure;complex interaction situations consisting of ground,excavation and neighbouring buildings and structures;projects with pore-water pressures reducing the stability;projects on slopes.The observational method is always a combination of the common geotechnical investigations before and during the construction phase together with the theoretical modeling and a plan of contingency actions(Figure 2). Only monitoring to ensure the stability and the service ability of the structure is not sufficient and,according to the standardization, not permitted for this purpose. Overall the observational method is an institutionalized controlling instrument to verify the soil and rock mechanical modeling [3,4].The identification of all potential failure mechanismsis essential for defining the measure concept. The concept has to be designed in that way that all these mechanisms can be observed. The measurements need to beof an adequate accuracy to allow the identification ocritical tendencies. The required accuracy as well as the boundary values need to be identified within the design phase of the observational method . Contingency actions needs to be planned in the design phase of the observational method and depend on the ductility of the systems.The observational method must not be seen as a potential alternative for a comprehensive soil investigation campaign. A comprehensive soil investigation campaignis in any way of essential importance. Additionally the observational method is a tool of quality assurance and allows the verification of the parameters and calculations applied in the design phase. The observational method helps to achieve an economic and save construction [5].4.In-Situ Load TestOn project and site related soil investigations with coredrillings and laboratory tests the soil parameters are determined. Laboratory tests are important and essential for the initial definition of soil mechanical properties of the soil layer, but usually not sufficient for an entire and realistic capture of the complex conditions, caused by theinteraction of subsoil and construction [6].In order to reliably determine the ultimate bearing capacity of piles, load tests need to be carried out [7]. Forpile load tests often very high counter weights or strong anchor systems are necessary. By using the Osterberg method high loads can be reached without install inganchors or counter weights. Hydraulic jacks induce the load in the pile using the pile itself partly as abutment.The results of the field tests allow a calibration of the numerical simulations.The principle scheme of pile load tests is shown in Figure 3.5.Examples for Engineering Practice5.1. Classic Pile Foundation for a High-Rise Building in Frankfurt Clay and LimestoneIn the downtown of Frankfurt am Main, Germany, on aconstruction site of 17,400 m2 the high-rise buildingproject “PalaisQuartier” has been realized (Figure 4). The construction was finished in 2010.The complex consists of several structures with a total of 180,000 m2 floor space, there of 60,000 m2 underground (Figure 5). The project includes the historic building “Thurn-und Taxis-Palais” whose facade has been preserved (Unit A). The office building (Unit B),which is the highest building of the project with a height of 136 m has 34 floors each with a floor space of 1340 m2. The hotel building (Unit C) has a height of 99 m with 24 upper floors. The retail area (Unit D)runs along the total length of the eastern part of the site and consists of eight upper floors with a total height of 43 m.The underground parking garage with five floors spans across the complete project area. With an 8 m high first sublevel, partially with mezzanine floor, and four more sub-levels the foundation depth results to 22 m below ground level. There by excavation bottom is at 80m above sea level (msl). A total of 302 foundation piles(diameter up to 1.86 m, length up to 27 m) reach down to depths of 53.2 m to 70.1 m. above sea level depending on the structural requirements.The pile head of the 543 retaining wall piles (diameter1.5 m, length up to 38 m)were located between 94.1 m and 99.6 m above sea level, the pile base was between 59.8 m and 73.4 m above sea level depending on the structural requirements. As shown in the sectional view(Figure 6), the upper part of the piles is in the Frankfurt Clay and the base of the piles is set in the rocky Frankfurt Limestone.Regarding the large number of piles and the high pile loads a pile load test has been carried out for optimization of the classic pile foundation. Osterberg-Cells(O-Cells) have been installed in two levels in order to assess the influence of pile shaft grouting on the limit skin friction of the piles in the Frankfurt Limestone(Figure 6). The test pile with a total length of 12.9 m and a diameter of 1.68 m consist of three segments and has been installed in the Frankfurt Limestone layer 31.7 m below ground level. The upper pile segment above the upper cell level and the middle pile segment between the two cell levels can be tested independently. In the first phase of the test the upper part was loaded by using the middle and the lower part as abutment. A limit of 24 MN could be reached (Figure 7). The upper segment was lifted about 1.5 cm, the settlement of the middle and lower part was 1.0 cm. The mobilized shaft friction was about 830 kN/m2.Subsequently the upper pile segment was uncoupled by discharging the upper cell level. In the second test phase the middle pile segment was loaded by using the lower segment as abutment. The limit load of the middle segment with shaft grouting was 27.5 MN (Figure 7).The skin friction was 1040 kN/m2, this means 24% higher than without shaft grouting. Based on the results of the pile load test using O-Cells the majority of the 290 foundation piles were made by applying shaft grouting. Due to pile load test the total length of was reduced significantly.5.2. CPRF for a High-Rise Building in Clay MarlIn the scope of the project Mirax Plaza in Kiev, Ukraine,2 high-rise buildings, each of them 192 m (46 storeys)high, a shopping and entertainment mall and an underground parking are under construction (Figure 8). The area of the project is about 294,000 m2 and cuts a 30 m high natural slope.The geotechnical investigations have been executed 70m deep. The soil conditions at the construction site are as follows: fill to a depth of 2 m to 3mquaternary silty sand and sandy silt with a thickness of 5 m to 10 m tertiary silt and sand (Charkow and Poltaw formation) with a thickness of 0 m to 24 m tertiary clayey silt and clay marl of the Kiev and But schak formation with a thickness of about 20 m tertiary fine sand of the But schak formation up to the investigation depthThe ground water level is in a depth of about 2 m below the ground surface. The soil conditions and a cross section of the project are shown in Figure 9.For verification of the shaft and base resistance of the deep foundation elements and for calibration of the numerical simulations pile load tests have been carried out on the construction yard. The piles had a diameter of 0.82 m and a length of about 10 m to 44 m. Using the results of the load tests the back analysis for verification of the FEM simulations was done. The soil properties in accordance with the results of the back analysis were partly 3 times higher than indicated in the geotechnical report. Figure 10 shows the results of the load test No. 2 and the numerical back analysis. Measurement and calculation show a good accordance.The obtained results of the pile load tests and of the executed back analysis were applied in 3-dimensionalFEM-simulations of the foundation for Tower A, taking advantage of the symmetry of the footprint of the building. The overall load of the Tower A is about 2200 MN and the area of the foundation about 2000 m2 (Figure11).The foundation design considers a CPRF with 64 barrettes with 33 m length and a cross section of 2.8 m × 0.8m. The raft of 3 m thickness is located in Kiev Clay Marl at about 10 m depth below the ground surface. The barrettes are penetrating the layer of Kiev Clay Marl reaching the Butschak Sands.The calculated loads on the barrettes were in the range of 22.1 MN to 44.5 MN. The load on the outer barrettes was about 41.2 MN to 44.5 MN which significantly exceeds the loads on the inner barrettes with the maximum value of 30.7 MN. This behavior is typical for a CPRF.The outer deep foundation elements take more loads because of their higher stiffness due to the higher volume of the activated soil. The CPRF coefficient is 0.88 =CPRF . Maximum settlements of about 12 cm werecalculated due to the settlement-relevant load of 85% of the total design load. The pressure under the foundation raft is calculated in the most areas not exceeding 200 kN/m2, at the raft edge the pressure reaches 400 kN/m2.The calculated base pressure of the outer barrettes has anaverage of 5100 kN/m2 and for inner barrettes an average of 4130 kN/m2. The mobilized shaft resistance increases with the depth reaching 180 kN/m2 for outer barrettes and 150 kN/m2 for inner barrettes.During the construction of Mirax Plaza the observational method according to EC 7 is applied. Especially the distribution of the loads between the barrettes and the raft is monitored. For this reason 3 earth pressure devices were installed under the raft and 2 barrettes (most loaded outer barrette and average loaded inner barrette) were instrumented over the length.In the scope of the project Mirax Plaza the new allowable shaft resistance and base resistance were defined for typical soil layers in Kiev. This unique experience will be used for the skyscrapers of new generation in Ukraine.The CPRF of the high-rise building project MiraxPlaza represents the first authorized CPRF in the Ukraine. Using the advanced optimization approaches and taking advantage of the positive effect of CPRF the number of barrettes could be reduced from 120 barrettes with 40 mlength to 64 barrettes with 33 m length. The foundation optimization leads to considerable decrease of the utilized resources (cement, aggregates, water, energy etc.)and cost savings of about 3.3 Million US$.译文:安全保证岩土公民发起挑战工程建设在城市地区摘要安全是最重要的方面在设计、施工和服务时间的任何结构,特别是对具有挑战性的项目,如高层建筑和隧道在城市地区。
Fluid-Structure Interaction and Dynamics
Fluid-Structure Interaction and Dynamics Fluid-structure interaction (FSI) and dynamics are critical aspects of engineering and physics that play a significant role in various fields such as aerospace, civil engineering, biomechanics, and more. The interaction betweenfluid flow and solid structures can lead to complex and often unpredictable behavior, making it a challenging yet fascinating area of study. One of the key problems in FSI and dynamics is the accurate prediction and analysis of the behavior of structures under the influence of fluid forces. This is particularly important in the design and operation of aircraft, ships, bridges, and other engineering systems where the interaction between the structure and the surrounding fluid can have a significant impact on performance and safety. Understanding the dynamic response of structures to fluid forces is crucial for ensuring structural integrity and stability under various operating conditions. From a fluid mechanics perspective, FSI and dynamics involve the study of howfluid flow affects the behavior of solid structures and vice versa. Theinteraction between the fluid and the structure can lead to phenomena such as vortex shedding, flow-induced vibrations, and aeroelastic instabilities, which can have detrimental effects on the performance and safety of engineering systems. Therefore, it is essential to develop accurate computational models and simulation techniques to predict and analyze these complex interactions. In the field of computational fluid dynamics (CFD) and structural analysis, researchers and engineers are constantly striving to improve the accuracy and efficiency of FSI simulations. High-fidelity simulations of FSI and dynamics require sophisticated numerical methods, such as finite element analysis (FEA), computational fluid dynamics (CFD), and coupled FSI solvers, to capture the intricate interactions between the fluid and the structure. These simulations can provide valuable insights into the behavior of complex engineering systems and help in optimizing their design and performance. Moreover, experimental testing and validation play a crucial role in advancing our understanding of FSI and dynamics. Physicaltesting of scaled models in wind tunnels, water tanks, and other experimental facilities can provide valuable data for validating computational models and gaining insights into the complex behavior of fluid-structure interactions.Experimental testing is also essential for understanding real-world phenomena such as flutter, buffeting, and vortex-induced vibrations, which can have significant implications for the design and operation of engineering systems. In conclusion, fluid-structure interaction and dynamics are multifaceted areas of study that require a multidisciplinary approach, combining expertise in fluid mechanics, structural analysis, computational modeling, and experimental testing. The accurate prediction and analysis of FSI phenomena are crucial for the design and operation of engineering systems, and ongoing research and development in this field are essential for advancing our understanding of complex fluid-structure interactions. As we continue to push the boundaries of engineering and physics, the study of FSI and dynamics will remain a captivating and challenging area of research with far-reaching implications for various industries and applications.。
Structural_Change_in_a_Multi-Sector_Model_of_Growth
Structural Change in a Multi-Sector Modelof GrowthL Rachel Ngai Christopher A Pissarides∗November2004(this revision,May2006,forthcoming in theAmerican Economic Review)AbstractWe study a multi-sector model of growth with differences in TFP growth rates across sectors and derive sufficient conditions for thecoexistence of structural change,characterized by sectoral labor re-allocation,and balanced aggregate growth.The conditions are weakrestrictions on the utility and production functions.Along the bal-anced growth path,labor employed in the production of consump-tion goods gradually moves to the sector with the lowest TFP growthrate,until in the limit it is the only sector with nontrivial employ-ment of this kind.The employment shares of intermediate and cap-ital goods remain constant during the reallocation process.(JELO41,O14,E29)Economic growth takes place at uneven rates across different sectors of the economy.This paper has two objectives related to this fact:(a)to derive the implications of different sectoral total factor productivity(TFP) growth rates for structural change,the name given to the shifts in industrial∗Ngai:Centre for Economic Performance,London School of Economics and CEPR (e-mail:l.ngai@).Pissarides:Centre for Economic Performance,London School of Economics,CEPR and IZA(e-mail:c.pissarides@).We have benefited from comments received at several presentations(the CEPR ESSIM2004meetings,the SED 2004annual conference,the NBER2004Summer Institute,the2004Canadian Macro-economic Study Group and several universities),and from Fernando Alvarez,Francesco Caselli,Antonio Ciccone,Nobu Kiyotaki,Robert Lucas,Nick Oulton,Danny Quah, Sergio Rebelo,Robert Shimer,Nancy Stokey,Richard Rogerson,Jaume Ventura and two anonymous referees.Funding from the CEP,a designated ESRC Research Centre, is acknowledged.employment shares that take place over long periods of time,and(b)to show that even with ongoing structural change,the economy’s aggregate ratios can be constant.We refer to the latter as aggregate balanced growth. The restrictions needed to yield structural change consistent with the facts and aggregate balanced growth are weak restrictions on functional forms that are frequently imposed by macroeconomists in related contexts.We obtain our results in a baseline model of many consumption goods and a single capital good,supplied by a sector that we label manufacturing. Our baseline results are consistent with the existence of intermediate goods and many capital goods under some reasonable restrictions.Production functions in our model are identical in all sectors except for their rates of TFP growth and each sector produces a differentiated good that enters a constant elasticity of substitution(CES)utility function.We show that a low(below one)elasticity of substitution acrossfinal goods leads to shifts of employment shares to sectors with low TFP growth.In the limit the employment share used to produce consumption goods vanishes from all sectors except for the one with the smallest TFP growth rate,but the employment shares used to produce capital goods and intermediate goods converge to non-trivial stationary values.If the utility function in addition has unit inter-temporal elasticity of substitution,during structural change the aggregate capital-output ratio is constant and the aggregate economy is on a balanced growth path.Our results contrast with the results of Cristina Echevarria(1997),John Laitner(2000),Francesco Caselli and Wilbur Coleman II(2001)and Dou-glas Gollin,Stephen Parente and Richard Rogerson(2002)who derived structural change in a two-or three-sector economy with non-homothetic preferences.Our results also contrast with the results of Piyabha Kongsamut, Sergio Rebelo and Danyang Xie(2001)and Reto Foellmi and Josef Zweimuller (2005),who derived simultaneous constant aggregate growth and struc-tural change.Kongsamut et al.(2001)obtain their results by imposing a restriction that maps some of the parameters of their Stone-Geary utility function onto the parameters of the production functions,abandoning one of the most useful conventions of modern macroeconomics,the complete in-dependence of preferences and technologies.Foellmi and Zweimuller(2005) obtain their results by assuming endogenous growth driven by the intro-duction of new goods into a hierarchic utility function.Our restrictions are quantitative restrictions on a conventional CES utility function that main-tains the independence of the parameters of preferences and technologies.Our results confirm William J Baumol’s(1967)claims about structural change.Baumol divided the economy into two sectors,a“progressive”one that uses new technology and a“stagnant”one that uses labor as the only input.He then claimed that the production costs and prices of the stagnant sector should rise indefinitely,a process known as“Baumol’s cost disease,”and labor should move in the direction of the stagnant sector.1 In the more recent empirical literature two competing explanations (which can coexist)have been put forward for structural change.Our ex-planation,which is sometimes termed“technological”because it attributes structural change to different rates of sectoral TFP growth,and a utility-based explanation,which requires different income elasticities for different goods and can yield structural change even with equal TFP growth in all sectors.Baumol,Sue Anne Batey Blackman and Edward N.Wolff(1985) provide empirical evidence at the2-digit industry level,consistent with our model.Irving B.Kravis,Alan W.Heston and Robert Summers(1983)also present evidence that favors the technological explanation,at least when the comparison is between manufacturing and services.Two features of their data that are satisfied by the technological explanation proposed in this paper are(a)relative prices reflect differences in TFP growth rates and(b)real consumption shares vary a lot less over time than nominal consumption shares.2Our model is also consistent with the observed pos-itive correlation between employment growth and relative price inflation across two-digit sectors3and with historical OECD evidence presented by Simon Kuznets(1966)and Angus Maddison(1980)for one-digit sectors.41Baumol controversially also claimed that as more weight is shifted to the stagnant sector,the economy’s growth rate will be on a declining trend and eventually converge to zero.This claim contrasts with ourfinding that the economy is on a balanced-growth path.We get our result because we include capital in our analysis,ironically left out of the analysis by Baumol(1967,p.417)“primarily for ease of exposition...that is [in]essential to the argument”.2See Rodney E.Falvey and Norman Gemmell(1996)for an update of some of their results.Falvey and Gemmellfind a unit income elasticity and a small(negative)price elasticity for services in a cross-section of countries,consistent with our results.3These correlations are shown in the working paper version of this paper,L.Rachel Ngai and Christopher A.Pissarides(2004).4Kuznets(1966)documented structural change for13OECD countries and the USSR between1800and1960and Maddison(1980)documented the same pattern for16OECD countries from1870to1987.They both found a pattern with the same general features as the predictions that we obtain when the ranking of the average historical TFP growth rates is agriculture followed by manufacturing followed by services.Section1describes our model of growth with many sectors and sec-tions2and3respectively derive the conditions for structural change and balanced aggregate growth.In sections4and5we study two extensions of our baseline model,one where consumption goods can also be used as intermediate inputs and one where there are many capital goods.The Appendix discusses the implications of one more extension,differences in capital intensities across sectors,and contains proofs of the main results.1An economy with many sectorsThe baseline economy consists of an arbitrary number of m sectors.Sectors i=1,...,m−1produce only consumption goods.The last sector,which is denoted by m and labeled manufacturing,produces both afinal consump-tion good and the economy’s capital stock.We derive the equilibrium as the solution to a social planning problem.The objective function isU=Z∞0e−ρt v(c1,..,c m)dt,(1) whereρ>0,c i≥0are per-capita consumption levels and the instanta-neous utility function v(.)is concave and satisfies the Inada conditions. The constraints of the problem are as follows.The labor force is exogenous and growing at rateνand the aggregate capital stock is endogenous and defines the state of the economy.Sectoral allocations are controls that satisfyP m i=1n i=1;P m i=1n i k i=k,(2)where n i≥0is the employment share and k i≥0is the capital-labor ratio in sector i,and k≥0is the aggregate capital-labor ratio.There is free mobility for both factors.All production in sectors i=1,...,m−1is consumed but in sector m production may be either consumed or invested.Therefore:c i=F i(n i k i,n i)∀i=m(3)˙k=F m(nk m,n m)−c m−(δ+ν)k(4)mwhereδ>0is the depreciation rate.Production function F i(.,.)has constant return to scale,positive and diminishing returns to inputs,and satisfies the Inada conditions.The social planner chooses the allocation of factors n i and k i across m sectors through a set of static e fficiency conditions,v i /v m =F m K /F i K =F m N /F i N ∀i.(5)The allocation of output to consumption and capital is chosen through a dynamic e fficiency condition,−˙v m /v m =F m K −(δ+ρ+ν).(6)where F i Nand F i K are the marginal products of labor and capital in sector i.5By (5),the rates of return to capital and labor are equal across sectors.In order to focus on the implications of di fferent rates of TFP growth across sectors we assume production functions are identical in all sectors except for their rates of TFP growth:F i =A i F (n i k i ,n i );˙A i /A i =γi ;∀i,(7)With these production functions,we show in the Appendix that static e fficiency and the resource constraints (2)implyk i =k ;p i /p m =v i /v m =A m /A i ;∀i,(8)where p i is the price of good i in the decentralized economy.The utility function has constant elasticities both across goods and over time:v (c 1,...,c m )=φ(.)1−θ−11−θ;φ(.)=³P m i =1ωi c (ε−1)/εi´ε/(ε−1)(9)where θ,ε,ωi >0and Σωi =1.Of course,if θ=1,v (.)=ln φ(.)and if ε=1,ln φ(.)=P m i =1ωi ln c i .In the decentralized economy demand functions have constant price elasticity −εand unit income elasticity.With this utility function,(8)yields:p i c i m m =µωi m ¶εµA m i ¶1−ε≡x i ∀i.(10)The new variable x i is the ratio of consumption expenditure on good i to consumption expenditure on the manufacturing good and will prove useful in the subsequent analysis.The intuition behind this formula is in terms 5The corresponding transversality condition is lim t −→∞k exp ³−R t 0(F m k −δ−ν)dτ´=0.of price elasticities,given that all goods have unit income elasticity.The ratio of consumption expenditures is a weighted average of the ratio of the weights of each good in the utility function and of their relative prices.A higher price ratio p i/p m raises the ratio of expenditure on good i to good m by one minus their common price elasticity.We also define aggregate consumption expenditure and output per capita in terms of manufacturing:c≡P m i=1p i p m c i;y≡P m i=1p i p m F i(11) Using static efficiency we derive:c=c m X;y=A m F(k,1)(12)where X≡P m i=1x i.2Structural changeWe define structural change as the state in which at least some of the labor shares are changing over time,i.e.,˙n i=0for at least some i.We derive in the Appendix(Lemma A2)the employment shares:x iµc¶∀i=m,(13)n i=x mµc¶+µ1−c¶.(14)n m=Thefirst term in the right side of(14)parallels the term in(13)and so represents the employment needed to satisfy the consumption demand for the manufacturing good.The second bracketed term is equal to the sav-ings rate and represents the manufacturing employment needed to satisfy investment demand.Conditions(13)and(14)drive our structural change results.To see the intuition behind them,note that by aggregation over all i,we obtain that in our economy the employment share used to produce consumption goods is equal to c/y,and the employment share used to produce capital goods is 1−c/y.Conditions(13)and(14)state that the same holds for each sector i.From(10)and(12),the consumption expenditure share of each sector is p i c i/p m c=x i/X.So the employment share of consumption good i is the consumption share of good i multiplied by the employment share of totalconsumption.Equivalently,the employment share of consumption good i is the average propensity to consume good i:n i=p i c i/p m y.Condition(13)has the important implication that the growth rate of two sectors’relative employment depends only on the difference between the sectors’TFP growth rates and the elasticity of substitution betweengoods:˙n in i−˙n jn j=(1−ε)¡γj−γi¢∀i,j=m.(15)But(8)implies that the growth rate of relative prices is:˙p i p i−˙p jp j=γj−γi∀i(16)and so,˙n in i−˙n jn j=(1−ε)µ˙p i p i−˙p j p j¶∀i,j=m(17)Proposition1The rate of change of the relative price of good i to good j is equal to the difference between the TFP growth rates of sector j and sector i.In sectors producing only consumption goods,relative employment shares grow in proportion to relative prices,with the factor of proportionality given by one minus the elasticity of substitution between goods.6The dynamics of the individual employment shares satisfy:˙n i n i =c˙/yc/y+(1−ε)(¯γ−γi);∀i=m(18)˙n mn m="c˙/y c/y+(1−ε)(¯γ−γm)#(c/y)(x m/X)n m(19)+Ã−c˙/y1−c/y!µ1−c/y n m¶where¯γ≡P m i=1(x i/X)γi is a weighted average of TFP growth rates,with the weight given by each good’s consumption share.Equation(18)gives the growth rate in the employment share of each consumption good as a linear function of its own TFP growth rate.The intercept and slope of this function are common across sectors but although the slope is a constant,the intercept is in general a function of time because both c/y and¯γare in general functions of time.Manufacturing,however, does not conform to this rule,because its employment share is a weighted 6All derivations and proofs,unless trivial,are collected in the Appendix.average of two components,one for the production of the consumption good,which conforms to the rule,and one for the production of capital goods,which behaves differently.The properties of structural change follow immediately from(18)and (19).Considerfirst the case of equality in sectoral TFP growth rates,i.e., letγi=γm∀i.Our economy in this case is one of balanced TFP growth, with relative prices remaining constant but with many differentiated goods. Because of the constancy of relative prices all consumption goods can be aggregated into one,so we effectively have a two-sector economy,one sector producing consumption goods and one producing capital goods.Structural change can still take place in this economy but only between the aggregate of the consumption sectors and the capital sector,and only if c/y changes over time.If c/y is increasing over time,the investment rate is falling and labor is moving out of the manufacturing sector and into the consumption sectors.Conversely,if c/y is falling over time labor is moving out of the consumption sectors and into manufacturing.In both cases,however,the relative employment shares in consumption sectors are constant.If c/y is constant over time,structural change requiresε=1and differ-ent rates of sectoral TFP growth rates.It follows immediately from(16), (18)and(19)that if c˙/y=0,ε=1implies constant employment shares but changing prices.With constant employment shares faster-growing sec-tors produce relatively more output over time.Price changes in this case are such that consumption demands exactly match all the output changes due to the different TFP growth rates.But ifε=1,prices still change as before but consumption demands are either too inelastic(in the case ε<1)to match all the output change,or are too elastic(ε>1)to be satisfied merely by the change in output due to TFP growth.So ifε<1 employment has to move into the slow-growing sectors and ifε>1it has to move into the fast-growing sectors.Proposition2Ifγi=γm∀i=m,a necessary and sufficient condition for structural change is˙c/c=˙y/y.The structural change in this case is between the aggregate of consumption sectors and the manufacturing sector.If˙c/c=˙y/y,necessary and sufficient conditions for structural change areε=1and∃i∈{1,..,m−1}s.t.γi=γm.The structural change in this case is between all sector pairs with different TFP growth rates.Ifε<1 employment moves from the sector with the higher TFP growth rate to the sector with the lower TFP growth rate;conversely ifε>1.Proposition2forε<1confirms the structural change facts identified by Baumol et al.(1985).When demand is price inelastic,the sectors with the low productivity growth rate attract a bigger share of labor,despite the rise in their price.From the static efficiency results in(8)and(12) wefind that the nominal output shares(defined as p i F i/p m y)are equal to the employment shares in all sectors,and by(10)the nominal consumption shares are given by x i/X,so the results obtained for employment shares also hold for nominal consumption and output shares.But real consumption growth satisfies˙c i/c i−˙c j/c j=ε¡γi−γj¢;∀i,j,(20) an expression also satisfied by real output shares∀i,j=m.A comparison of(15)with(20)reveals that a smallεcan reconcile the small changes in the relative real consumption shares with the large changes in relative nominal consumption shares found by Kravis et al. (1983).The authors concluded that theirfinding is evidence in favor of the technological explanation of structural change.More recently Daniel E. Sichel(1997)found the same pattern for relative output shares,and Falvey and Gemmell(1996)found that the real consumption share of services(a sector with low TFP growth rate)falls very gradually with income,both of which are consistent with our model whenε<1.3Aggregate growthWe now study the aggregate growth path of this economy,with the objec-tive offinding a sufficient set of conditions that satisfy structural change as derived in the preceding section,and in addition satisfy Kaldor’s stylized facts of aggregate growth.Recall that for the analysis of structural change we imposed a Hicks-neutral technology.It is well-known that with this type of technology,the economy can be on a steady state only if the production function is Cobb-Douglas.We therefore let F(n i k i,n i)=kαi n i,α∈(0,1).7 With TFP in each sector growing at some rateγi,the aggregate economy will also grow at some rate related to theγi s.The following Proposition derives the evolution of the aggregate economy:7Daron Acemoglu and Veronica Guerrieri(2005)examined the implications of dif-ferent capital intensities for economic growth and structural change.They show that capital deepening can cause both structural change and unbalanced growth.We exam-ine in the Appendix the implications of different capital shares and afixed factor for our model.Proposition 3Given any initial k (0),the equilibrium of the aggregate economy is a path for the pair {c,k }that satis fies the following two dif-ferential equations:˙k =A m k α−1−c −(δ+ν),(21)θ˙c c=(θ−1)(γm −¯γ)+αA m k α−1−(δ+ρ+ν).(22)We de fine an aggregate balanced growth path such that aggregate out-put,consumption and capital grow at the same rate.It follows from Propo-sition 3that a necessary condition for the existence of an aggregate bal-anced growth path is that the expression (θ−1)(γm −¯γ)be a constant.To show this,let:(θ−1)(γm −¯γ)≡ψconstant.(23)De fine aggregate consumption and the capital-labor ratio in terms of e ffi-ciency units,c e ≡cA −1/(1−α)m and k e ≡kA −1/(1−α)m and let g m ≡γm /(1−α),the rate of labor-augmenting technological growth in the capital-producing sector.The dynamic equations (21)and (22)become˙c e /c e =£αk α−1e +ψ−(δ+ν+ρ)¤/θ−g m (24)˙k e =k αe−c e −(g m +δ+ν)k e .(25)Equations (24)and (25)parallel the two di fferential equations in the con-trol and state of the one-sector Ramsey economy,making the aggregate equilibrium of our many-sector economy identical to the equilibrium of the one-sector Ramsey economy when ψ=0,and trivially di fferent from it otherwise.Both models have a saddlepath equilibrium and stationary so-lutions ³ˆc e ,ˆke ´that imply balanced growth in the three aggregates.The capital-labor ratio is growing at the rate of growth of labor-augmenting technological progress in the sector that produces capital goods,g m .Ag-gregate consumption and output de flated by the price of manufacturing goods are also growing at the same rate.Proposition 2and the requirement that ψbe constant yield the impor-tant Proposition:Proposition 4Necessary and su fficient conditions for the existence of an aggregate balanced growth path with structural change are:θ=1,ε=1;and ∃i ∈{1,..,m −1}s.t.γi =γm .Recalling the definition of¯γfollowing equation(19),Proposition3im-plies that the contribution of each consumption sector i to aggregate equi-librium is through its weight x i in¯γ.Because each x i depends on the sector’srelative TFP level,the weights here are functions of time.So¯γcannot beconstant during structural change and the only way thatψcan be constantis throughθ=1,which yieldsψ=0.In this case our aggregate economyin c and k becomes formally identical to the one-sector Ramsey economywith growth rateγm.There are two other conditions that give a constantψand so yield balanced aggregate growth:γi=γm∀i orε=1.But as Proposition2demonstrates neither condition permits structural change onthe balanced growth path,where c/y is constant.Proposition4requires the utility function to be logarithmic in the con-sumption compositeφ,which implies an intertemporal elasticity of substi-tution equal to one,but be non-logarithmic across goods,which is neededto yield non-unit price elasticities.A noteworthy implication of Proposi-tion4is that balanced aggregate growth does not require constant ratesof growth of TFP in any sector other than manufacturing.Because bothcapital and labor are perfectly mobile across sectors,changes in the TFPgrowth rates of consumption-producing sectors are reflected in immediateprice changes and reallocations of capital and labor across sectors,withouteffect on the aggregate growth path.To give intuition for the logarithmic intertemporal utility function werecall that balanced aggregate growth requires that aggregate consumptionbe a constant fraction of aggregate wealth.With our homothetic utilityfunction this can be satisfied either when the interest rate is constant orwhen consumption is independent of the interest rate.The relevant interestrate here is the rate of return to capital in consumption units,which isgiven by the net marginal product of capital,αy/k−δ,minus the changein the relative price of the consumption composite,γm−¯γ.The latter is not constant during structural change.In the caseε<1,¯γis falling over time(see Lemma A3in the Appendix for proof),and so the real interest rate is also falling,and converging toαy/k−δ.With a non-constant interest rate the consumption-wealth ratio is constant only if consumption is independent of the interest rate,which requires a logarithmic utility function.88After re-examining the evidence,Robert Barro and Xavier Sala-i-Martin(2004,p.13)concluded,consistent with our model,“it seems likely that Kaldor’s hypothesis of a roughly stable real rate of return should be replaced by a tendency for returns to fallUnder the condition of Proposition4there is a steady-state character-ized by aggregate balanced growth,in the sense that in this steady state the aggregate ratios are constant.In order to achieve this balance,the aggregates c and y are divided by manufacturing price,to conform to the aggregate k.If some other price index is used as deflator,the rate of growth of the aggregates is constant only if the rate of growth of the price index is constant,but of course the aggregate ratios are still constant.The pub-lished aggregate series studied by macroeconomists usually use an average price as deflator which does not havefixed weights.If the price index used to deflate national statistics is some˜p,the published real aggregate income is y/˜p.If the weights used to construct˜p are the sector shares,˜p changes during structural change.But because sector shares do not change rapidly over time,visually there is virtually nothing to distinguish the“stylized fact”of constant growth in reported per capita GDP with another“styl-ized fact”of constant growth in our per capita output measure.9 Next,we summarize the dynamics of employment shares along the ag-gregate balanced growth path.Proposition5Let sector l denote the sector with the smallest TFP growth rate whenε<1or the sector with the biggest TFP growth rate whenε>1. On the aggregate balanced growth path,n l increases monotonically.Employ-ment in the other sectors is either hump-shaped or declines monotonically. Asymptotically,the economy converges to an economy withn∗m=ˆσ=αµδ+ν+g mδ+ν+ρ+g m¶;n∗l=1−ˆσwhereˆσis the savings rate along the aggregate balanced growth path.Proposition5follows immediately from(18)-(19)and Lemma A3.Con-sider the caseε<1,the one forε>1following by a corresponding ar-gument.Forε<1,sector i expands if and only if its TFP growth rate is smaller than¯γ,and contracts if and only if its growth rate exceeds it. But ifε<1,the weighted average¯γis decreasing over time(see Lemma A3in the Appendix).Therefore,the set of expanding sectors is shrinking over some range as an economy develops.”In our model it is converging from above to a positive value.9Nicholas Kaldor(1961,p.178)spoke of a“steady trend rate”of growth in the“ag-gregate volume of production.”In Ngai and Pissarides(2004,Fig.4)we plot our series of per capita real incomes and the published chain-weighted series for the United States since1929,and show that they are virtually indistinguishable from each other.over time,as more sectors’TFP growth rates exceed¯γ.This feature of the model implies that sectors with TFP growth rates below the initial¯γexhibit a hump-shaped employment share,an implication that we believe is unique to our model.These employment sharesfirst rise but once¯γdrops down to their ownγi they fall.10In contrast to each sector’s employment share,once the economy is on the aggregate balanced growth path output and consumption in each consumption sector grow according to˙F i=˙Aii+α˙ki+˙n ii=εγi+αg m+(1−ε)¯γ.(26)Ifε61the rate of growth of consumption and output in each sector is positive(providedγi≥0),and so sectors never vanish,even though their employment shares in the limit may vanish.Ifε>1the rate of growth of output may be negative in some low-growth sectors,and since by Lemma A3¯γis rising over time in this case,their rate of growth remains indefinitely negative until they vanish.Finally,we examine briefly the implications ofθ=1.Whenθ=1 balanced aggregate growth cannot coexist with structural change,because the termψ=(θ−1)(γm−¯γ)in the Euler condition(24)is a function of time.But as shown in the Appendix Lemma A3,¯γis monotonic.As t→∞,ψconverges to the constant(θ−1)(γm−γl),whereγl is the TFP growth rate in the limiting sector(the slowest or fastest growing consumption sector depending on whetherε<or>1).Therefore,the economy withθ=1converges to an asymptotic steady state with the same growth rate as the economy withθ=1.What characterizes the dynamic path of the aggregate economy when θ=1?By differentiation and using Lemma A3,we obtain˙ψ=(θ−1)(1−ε)P m i=1(x i/X)(γi−¯γ)2(27) which is of second-order compared with the growth in employment shares in(15),given that theγs are usually small numbers centered around0.02. Therefore,the rate of growth of the economy during the adjustment to the asymptotic steady state withθ=1is very close to the constant growth 10Maddison(1980,p.48)in his study of historical OECD data found a“shallow bell shape”for manufacturing employment for each of the16OECD countries,which can be reproduced by our model if the manufacturing TFP growth rate takes values between the TFP growth rates of agriculture and services.。
细胞程序性死亡
细胞凋亡一词来源于希腊语, 原指树叶或花的自然凋落。
由英、美三位科学家在1972年首次提出,于2002年获得诺贝尔医学奖。
细胞凋亡是指机体在一定生理、病理条件下为维持内环境稳定, 通过基因控制而使细胞主动有序的死亡, 表现一系列形态和生化方面的特征。
细胞凋亡是细胞正常的死亡,它涉及一系列基因的激活、表达以及调控等作用,不造成炎症和自体的损伤, 是细胞为了更好地适应生存环境而主动争取的死亡过程。
因这一死亡过程严格受到程序的控制, 又称细胞程序性死亡（Progammed cell death，PCD）【1】。
一．环境因子与PCD1 病原体与植物PCD植物受病原物(真菌、细菌和病毒)感染时往往会发生过敏性细胞死亡，即过敏反应（hypersensitive response，HR）：一方面死亡细胞可以将入侵寄主体内的病原病原微生物限制在感染点周围，阻止其进一步扩展而实现局部抗病性；另一方面也可进一步激活植物抗病防卫的相关信号通路，使植物获得对此后入侵的多种类型病原物的系统抗病性[2]。
现有研究结果表明，植物HR 中的细胞死亡往往表现出PCD 的典型特征。
例如，Wakabayashi 等[3]发现，生菜感染细菌后，细胞线粒体会增大，出现类似动物PCD 的症状，细胞质内空泡化增加，使细胞丧失功能。
Olszak等[4]用细菌侵染拟南芥突变体acdll 后发现，拟南芥AtFMO基因蛋白的表达既可以激活细胞的防御系统，又可以促进细胞发生PCD 现象，但并不是细胞发生PCD 现象所必需的。
2 低氧与植物PCD由于淹水或水培中微生物和植物根的呼吸，降低了植物根际氧的浓度而出现了低氧或无氧状态，导致根部细胞发生PCD现象。
He 等[5]研究表明，Ca2+和蛋白质磷酸化与植物通气组织的形成有关：在正常供氧条件下Ca2+通道抑制剂和蛋白质磷酸酯酶抑制剂都能促进玉米根中细胞的死亡，而在低氧的根中Ca2+螯合物EGTA 和蛋白激酶抑制剂都能防止细胞死亡。
叶绿素对叶黄素生物可给率的影响
黄千千，陈丽君，李韵唱，等. 叶绿素对叶黄素生物可给率的影响[J]. 食品工业科技，2024，45（5）：108−117. doi:10.13386/j.issn1002-0306.2023070007HUANG Qianqian, CHEN Lijun, LI Yunchang, et al. Effect of Chlorophylls on the Bioaccessibility of Lutein[J]. Science and Technology of Food Industry, 2024, 45(5): 108−117. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023070007· 研究与探讨 ·叶绿素对叶黄素生物可给率的影响黄千千1,2，陈丽君1,2，李韵唱1,2，陈雪寒1,2，陈乾睿1,2，王元楷1,2，蔡 甜3,4，陈科伟1,2,4,5,6,*（1.西南大学食品科学学院，重庆 400715；2.西南大学食品科学与工程国家级实验教学示范中心，重庆 400715；3.西南大学化学化工学院，重庆 400715；4.西南大学中匈食品科学合作中心，重庆 400715；5.川渝共建特色食品重庆市重点实验室，重庆 400715；6.农业农村部农产品贮藏保鲜质量安全风险评估实验室（重庆），重庆 400715）摘 要：叶黄素具有多种生理活性，它在人体内不能合成，只能从外界获取，但叶黄素因其脂溶性的特点导致生物可给率低，如何高效补充叶黄素成为研究热点。
叶绿素常与叶黄素共同出现在人类饮食中，且二者均为脂溶性物质，会产生一定的相互作用。
因此研究膳食叶绿素及其结构变化对叶黄素生物可给率的影响具有重要意义。
通过制备膳食中常见的8种不同结构的叶绿素（叶绿素a 和b 、脱镁叶绿素a 和b 、脱植基叶绿素a 和b 、脱镁叶绿酸a 和b ），采用体外静态消化模型和胶束化实验研究它们对叶黄素生物可给率的影响，并测定叶黄素和叶绿素形成的混合胶束粒径和电位的变化。
Fluid-Structure Interaction
Fluid-Structure Interaction Fluid-structure interaction (FSI) is a complex and fascinating phenomenon that occurs when the motion of a fluid affects the behavior of a nearby structure, and vice versa. This interaction has significant implications in various engineering and scientific fields, including aerospace, civil engineering, biomechanics, and oceanography. Understanding and effectively managing FSI is crucial for the design and performance of numerous systems and structures. In this response, we will explore the multifaceted nature of FSI, considering its impact, challenges, and potential solutions from different perspectives. From an engineering standpoint, FSI presents both opportunities and challenges. On one hand, harnessing FSI can lead to innovative designs and improved performance in a wide range of applications. For example, in aerospace engineering, FSI considerations arecritical for optimizing the aerodynamic performance of aircraft and spacecraft. By accounting for the interaction between the airflow and the structural components, engineers can develop more efficient and stable designs. Similarly, in civil engineering, understanding FSI is essential for designing resilient structuresthat can withstand the forces exerted by wind, water, or seismic events. By integrating FSI analysis into the design process, engineers can enhance the safety and longevity of infrastructure. However, managing FSI also poses significant challenges. The complex and nonlinear nature of fluid-structure interactions makes accurate prediction and analysis difficult. Engineers and researchers oftengrapple with the intricacies of FSI, including turbulence, boundary layer effects, and structural deformation. These challenges are further compounded in scenarios involving multiphysics phenomena, such as the interaction between fluid flow, heat transfer, and structural dynamics. As a result, there is a pressing need for advanced computational tools, experimental techniques, and theoretical models to improve our understanding and control of FSI. In the realm of scientific research, FSI serves as a rich area of exploration, offering insights into fundamental principles of fluid dynamics and structural mechanics. From studying the biomechanics of human physiology to investigating the behavior of marine ecosystems, FSI phenomena are pervasive in the natural world. For instance, in cardiovascular research, understanding the interaction between blood flow andarterial walls is crucial for diagnosing and treating vascular diseases. By simulating FSI scenarios, scientists can gain a deeper understanding of physiological processes and develop new medical interventions. Moreover, FSI plays a pivotal role in the study of ocean dynamics and environmental phenomena. The interaction between ocean currents, waves, and coastal structures has profound implications for coastal erosion, offshore engineering, and marine ecology. By examining FSI in these contexts, researchers can contribute to the sustainable management of coastal resources and the protection of vulnerable ecosystems. Furthermore, the insights gained from studying FSI in natural systems can inspire innovative solutions for engineering challenges, leading to the development ofbio-inspired designs and technologies. In addressing the complexities of FSI, interdisciplinary collaboration is essential. Engineers, physicists, mathematicians, and computer scientists must work together to develop comprehensive approaches for analyzing and simulating FSI phenomena. Byintegrating expertise from diverse fields, researchers can leverage advanced computational methods, such as finite element analysis, computational fluid dynamics, and coupled multiphysics simulations, to tackle FSI challenges. Furthermore, experimental validation and data-driven approaches are critical for refining FSI models and ensuring their accuracy in real-world scenarios. In conclusion, fluid-structure interaction is a multifaceted and significant aspect of engineering and scientific research. While it presents opportunities for innovation and discovery, it also poses formidable challenges that demand concerted efforts from the research community. By embracing a holistic and collaborative approach, we can advance our understanding of FSI, develop robust computational tools, and unlock new possibilities for designing resilient and efficient systems. Ultimately, the exploration of FSI holds great promise for addressing real-world problems and shaping the future of engineering and science.。
交互作用和二次效应结构方程
SEM of Latent Interaction and Quadratic Effects潜变量交互作用和二次效应结构方程Herbert W. MarshOxford UniversityZhonglin WenSouth China Normal UniversityHong Kong Examinations AuthorityKit-Tai HauThe Chinese University of Hong Kong AERA Extended Course ◦San Francisco ◦April 7 & 8, 2006 ◦Structural Equation Modeling: A Second CourseLatent Interaction --Marsh, Wen, Hau 2Latent Interaction --提要传统方法显变量（方差分析，回归分析）潜变量（因子得分, 2SLS, 多组SEM）约束方法的演变约束方法、部分约束方法和无约束方法非正态分布：方法的稳健性乘积指标的类型二次效应其他方法（如QML，2SMM）总结Latent Interaction --交互作用例子教育心理：教学方法与学生个性对教学效果发展心理：年龄与某个给定的变量对因变量期望值理论：期望与价值对动机自我概念：自我概念分量与对该分量的重视程度对整体自尊Latent Interaction --二次效应二次效应的例子作业量增加，学业成绩提高，但到达一定作业量后反而降低开始时，压力的增加会提高成绩，但压力太大成绩反而下降低水平上的焦虑有利于表现，但高水平的焦虑却相反自我概念随儿童年龄而降低，少年时期最低，青年初期有所提高先降后升，二次效应是非线性效应最简单的例子强大的二次效应会给人有交互效应的错觉Latent Interaction --交互效应传统分析方法显变量的交互效应分析方法，(X 1, X 2) 对结果(Y )当X 1, X 2是类别变量，方差分析（ANOVA ）当X 1, X 2是连续变量，回归分析当X 2类别变量, X 1是连续变量, 对X 2的不同类别，做Y 对X 1的回归分析，比较回归系数。
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Satoshi KINOSHITA Research and Development Center Toshiba Corporation K o m u k a i - T o s h i b a - c h o 1, S a i w a i - k u , Kawasaki, 210 Japan John I'HILLIPS Jun-ichi TSUJII C e n t r e h)r C o m t ) u t a t i o n a l L i n g u i s t i c s UMIST P . O . B o x 88, M a n c h e s t e r , M60 1QD, U.K.
2
Formalism
We use a simple formalism, representing a sentence as a network of semantic dependencies. The basic units of the formMism are indices, properlies, and reIstwna. A logical form consists of an unordered net of Ierms; each term is either a property predicated of an it~dex, or ~t relation between two indices. The written notation depicts properties and relations as unary and binary functors, respectively, and indices as theiL" arguments, i.e. within brackets. A logical form representing ' J o h n saw M a r y ' might be e : john(j) & see(el & m a r y ( n 0 & tense(e,past) & subj(e,j) & obj(e,m) This representation in simplified particularly in t h a t
I managed to painl my house quickly: m : me(me) & manage(m) & tense(m,past) & subj(m,me) & obj(m,p) & paint(p) & obj(p,h) & of(h,me) & house(h) & qniek(q) & subj(q,p) Mary looked at the brightly painted house: l : mary(m) & look(l) & tense(l,past) & subj(l,m) & at(l,h) & bright(b) & subj(b,p) & paint(p) & obj(p,h) & house(h) Mary's house was painted:
p : mary(m) & of(h,rn) & house(h) & paint(p) & tense(p,past) & obj(p,h) Figure 1: Examples of Logical Forms
to be combined properly to produce translation. Because of the declarative nature of translation exampies, EBMT inevitably encounters the same complexitics of combining translation units in declarative representation o.~ I,BMT does. tLescarch in LBMT[1][2][3][ll][12][13] has revealed that dittieulties in tim declarative representation of bi-lingual knowledge stem mainly from the treatment of idiosyncratic structural changes caused by lexieal items, and interactions of such idiosyncratic structural changes when they co-exist in single sentences. These type of structural changes also cause problems when they are combined with general or ordinary linguistic phenomena soeh as coordination. A formal framework to cope with these m a t t e r s is essential in other aPl)roaches, such as EBMT, as in LBMT, if the translation is produced in a compositional way. In this paper, we discuss problems caused by such interaction, and give solutions in our logic-based transfer framework[8]. Our transfer model views the transfer process as deduction; it produces the target linguistic description without changing the source description. This giw:s a clear contrast to the conventional tree-traasducer model, which gradually tranSforms the source description, and is therefore hard to control. Because of the logic oriented nature of our framework, it can also be extended easily to cope with the other local issue of MT such as the integration of knowledge-based processing with translation[4].
Actxs DECOLING-92, NANTES,23-28 Ao~r 1992
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I'~oc. ov COLING-92, NANTES, AUG. 23-28, 1992
the man who Mary saw: the man who saw Mary:
x : man(x) & mary(m) & see(el & t . . . . . (e,past) & subj(e,m) & obj(e,x) x : man(x) & nrary(m) & see(el & tense(e,past) & subj(e,x) & obj(e,m)
Abstract
This paper discusses coml)lex structural changes during transfer within a non-destructive transfer framework. Though the description of each individual structural change is not difficult, special provision must be made when they are combined, because interaction between them sometimes causes unexpected problems. Transfer of coordinate structures is also discussed a.q this sometimes necessitates a structural change and interacts with other structural changes in a problematic way.
1
Introductiห้องสมุดไป่ตู้n
Several focal issues have emerged in machine trans lation (MT) research as the result of recent intensive studies in the field. T h a t is, • Declarative Frameworks for expressing Bi-lingual Knowledge • Integration of Knowledge-based Processing and Contextual Processing with the Translation p r o cess • Effective Exploitation of Domain/'l~xt TypeSpecificity (or Sublauguageness) in MT and Discovery Processes for such Specifieities Though new frameworks of MT such as Statisticsbased MT (SBMT), F,xample-bascd MT (F, BMT), Analogy-based MT (ABMT), Knowledge-based MT (KBMT) etc. look radically difihrent from conventional liuguisties-based MT (LIIMT) anch as Transfer-based MT, they address role or two of the above focal issues and ignore the rest[7][10]. In particular, the new paradigms of MT tend to ignore t.he first issue ie. declarative representation of bi-lingual knowledge and the complexities involved in the process of combining units of bi-liagual knowledge. It is our contention that any MT system, whichever paradigm it belongs to, has to store a set of translation-equivalent units for a pair of languages and combine these to produce larger units of translation. In EBMT, for example, a set of translation examples has to be stored and several of them have