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(完整word版)英文文献及翻译：计算机程序

姓名：刘峻霖班级：通信143班学号：2014101108Computer Language and ProgrammingI. IntroductionProgramming languages, in computer science, are the artificial languages used to write a sequence of instructions (a computer program) that can be run by a computer. Simi lar to natural languages, such as English, programming languages have a vocabulary, grammar, and syntax. However, natural languages are not suited for programming computers because they are ambiguous, meaning that their vocabulary and grammatical structure may be interpreted in multiple ways. The languages used to program computers must have simple logical structures, and the rules for their grammar, spelling, and punctuation must be precise.Programming languages vary greatly in their sophistication and in their degree of versatility. Some programming languages are written to address a particular kind of computing problem or for use on a particular model of computer system. For instance, programming languages such as FORTRAN and COBOL were written to solve certain general types of programming problems—FORTRAN for scientific applications, and COBOL for business applications. Although these languages were designed to address specific categories of computer problems, they are highly portable, meaning that the y may be used to program many types of computers. Other languages, such as machine languages, are designed to be used by one specific model of computer system, or even by one specific computer in certain research applications. The most commonly used progra mming languages are highly portable and can be used to effectively solve diverse types of computing problems. Languages like C, PASCAL and BASIC fall into this category.II. Language TypesProgramming languages can be classified as either low-level languages or high-level languages. Low-level programming languages, or machine languages, are the most basic type of programming languages and can be understood directly by a computer. Machine languages differ depending on the manufacturer and model of computer. High-level languages are programming languages that must first be translated into a machine language before they can be understood and processed by a computer. Examples of high-levellanguages are C, C++, PASCAL, and FORTRAN. Assembly languages are intermediate languages that are very close to machine languages and do not have the level of linguistic sophistication exhibited by other high-level languages, but must still be translated into machine language.1. Machine LanguagesIn machine languages, instructions are written as sequences of 1s and 0s, called bits, that a computer can understand directly. An instruction in machine language generally tells the computer four things: (1) where to find one or two numbers or simple pieces of data in the main computer memory (Random Access Memory, or RAM), (2) a simple operation to perform, such as adding the two numbers together, (3) where in the main memory to put the result of this simple operation, and (4) where to find the next instruction to perform. While all executable programs are eventually read by the computer in machine language, they are not all programmed in machine language. It is extremely difficult to program directly in machine language because the instructions are sequences of 1s and 0s. A typical instruction in a machine language might read 10010 1100 1011 and mean add the contents of storage register A to the contents of storage register B.2. High-Level LanguagesHigh-level languages are relatively sophisticated sets of statements utilizing word s and syntax from human language. They are more similar to normal human languages than assembly or machine languages and are therefore easier to use for writing complicated programs. These programming languages allow larger and more complicated programs to be developed faster. However, high-level languages must be translated into machine language by another program called a compiler before a computer can understand them. For this reason, programs written in a high-level language may take longer to execute and use up more memory than programs written in an assembly language.3. Assembly LanguagesComputer programmers use assembly languages to make machine-language programs easier to write. In an assembly language, each statement corresponds roughly to one machine language instruction. An assembly language statement is composed with the aid of easy to remember commands. The command to add the contents of the storage register A to the contents of storage register B might be written ADD B, A in a typical assembl ylanguage statement. Assembly languages share certain features with machine languages. For instance, it is possible to manipulate specific bits in both assembly and machine languages. Programmers use assemblylanguages when it is important to minimize the time it takes to run a program, because the translation from assembly language to machine language is relatively simple. Assembly languages are also used when some part of the computer has to be controlled directly, such as individual dots on a monitor or the flow of individual characters to a printer.III. Classification of High-Level LanguagesHigh-level languages are commonly classified as procedure-oriented, functional, object-oriented, or logic languages. The most common high-level languages today are procedure-oriented languages. In these languages, one or more related blocks of statements that perform some complete function are grouped together into a program module, or procedure, and given a name such as “procedure A.” If the same sequence of oper ations is needed elsewhere in the program, a simple statement can be used to refer back to the procedure. In essence, a procedure is just amini- program. A large program can be constructed by grouping together procedures that perform different tasks. Procedural languages allow programs to be shorter and easier for the computer to read, but they require the programmer to design each procedure to be general enough to be usedin different situations. Functional languages treat procedures like mathematical functions and allow them to be processed like any other data in a program. This allows a much higher and more rigorous level of program construction. Functional languages also allow variables—symbols for data that can be specified and changed by the user as the program is running—to be given values only once. This simplifies programming by reducing the need to be concerned with the exact order of statement execution, since a variable does not have to be redeclared , or restated, each time it is used in a program statement. Many of the ideas from functional languages have become key parts of many modern procedural languages. Object-oriented languages are outgrowths of functional languages. In object-oriented languages, the code used to write the program and the data processed by the program are grouped together into units called objects. Objects are further grouped into classes, which define the attributes objects must have. A simpleexample of a class is the class Book. Objects within this class might be No vel and Short Story. Objects also have certain functions associated with them, called methods. The computer accesses an object through the use of one of the object’s methods. The method performs some action to the data in the object and returns this value to the computer. Classes of objects can also be further grouped into hierarchies, in which objects of one class can inherit methods from another class. The structure provided in object-oriented languages makes them very useful for complicated programming tasks. Logic languages use logic as their mathematical base. A logic program consists of sets of facts and if-then rules, which specify how one set of facts may be deduced from others, for example: If the statement X is true, then the statement Y is false. In the execution of such a program, an input statement can be logically deduced from other statements in the program. Many artificial intelligence programs are written in such languages.IV. Language Structure and ComponentsProgramming languages use specific types of statements, or instructions, to provide functional structure to the program. A statement in a program is a basic sentence that expresses a simple idea—its purpose is to give the computer a basic instruction. Statements define the types of data allowed, how data are to be manipulated, and the ways that procedures and functions work. Programmers use statements to manipulate common components of programming languages, such as variables and macros (mini-programs within a program). Statements known as data declarations give names and properties to elements of a program called variables. Variables can be assigned different values within the program. The properties variables can have are called types, and they include such things as what possible values might be saved in the variables, how much numerical accuracy is to be used in the values, and how one variable may represent a collection of simpler values in an organized fashion, such as a table or array. In many programming languages, a key data type is a pointer. Variables that are pointers do not themselves have values; instead, they have information that the computer can use to locate some other variable—that is, they point to another variable. An expression is a piece of a statement that describe s a series of computations to be performed on some of the program’s variables, such as X+Y/Z, in which the variables are X, Y, and Z and the computations are addition and division. An assignment statement assigns a variable a value derived fromsome expression, while conditional statements specify expressions to be tested and then used to select which other statements should be executed next.Procedure and function statements define certain blocks of code as procedures or functions that can then be returned to later in the program. These statements also define the kinds of variables and parameters the programmer can choose and the type of value that the code will return when an expression accesses the procedure or function. Many programming languages also permit mini translation programs called macros. Macros translate segments of code that have been written in a language structure defined by the programmer into statements that the programming language understands.V. HistoryProgramming languages date back almost to the invention of the digital computer in the 1940s. The first assembly languages emerged in the late 1950s with the introduction of commercial computers. The first procedural languages were developed in the late 1950s to early 1960s: FORTRAN, created by John Backus, and then COBOL, created by Grace Hopper The first functional language was LISP, written by John McCarthy4 in the late 1950s. Although heavily updated, all three languages are still widely used today. In the late 1960s, the first object-oriented languages, such as SIMULA, emerged. Logic languages became well known in the mid 1970swith the introduction of PROLOG6, a language used to program artificial intelligence software. During the 1970s, procedural languages continued to develop with ALGOL, BASIC, PASCAL, C, and A d a SMALLTALK was a highly influential object-oriented language that led to the merging ofobject- oriented and procedural languages in C++ and more recently in JAVA10. Although pure logic languages have declined in popularity, variations have become vitally important in the form of relational languages for modern databases, such as SQL.计算机程序一、引言计算机程序是指导计算机执行某个功能或功能组合的一套指令。

(完整word版)光学外文文献及翻译

学号2013211033 昆明理工大学专业英语专业光学姓名辜苏导师李重光教授分数导师签字日期2015年5月6日研究生部专业英语考核In digital holography, the recording CCD is placed on the ξ-ηplane in order to register the hologramx ',y 'when the object lies inthe x-y plane. Forthe reconstruction ofthe information ofthe object wave,phase-shifting digital holography includes two steps:(1) getting objectwave on hologram plane, and (2) reconstructing original object wave.2.1 Getting information of object wave on hologram plateDoing phase shifting N-1 times and capturing N holograms. Supposing the interferogram after k- 1 times phase-shifting is]),(cos[),(),(),,(k k b a I δηξφηξηξδηξ-⋅+= （1） Phase detection can apply two kinds of algorithms:synchronous phase detection algorithms [9]and the least squares iterative algorithm [10]. The four-step algorithm in synchronous phase detection algorithm is in common use. The calculation equation is)2/3,,(),,()]2/,,()0,,([2/1),(πηξπηξπηξηξηξiI I iI I E --+=2.2 Reconstructing original object wave by reverse-transform algorithmObject wave from the original object spreads front.The processing has exact and clear description and expression in physics and mathematics. By phase-shifting technique, we have obtained information of the object wave spreading to a certain distance from the original object. Therefore, in order to get the information of the object wave at its initial spreading position, what we need to do is a reverse work.Fig.1 Geometric coordinate of digital holographyexact registering distance.The focusing functions normally applied can be divided into four types: gray and gradient function, frequency-domain function, informatics function and statistics function. Gray evaluation function is easy to calculate and also robust. It can satisfy the demand of common focusing precision. We apply the intensity sum of reconstruction image as the evaluation function:min ),(11==∑∑==M k Nl l k SThe calculation is described in Fig.2. The position occurring the turning point correspondes to the best registration distanced, also equals to the reconstructing distance d '.It should be indicated that if we only need to reconstruct the phase map of the object wave, the registration distance substituted into the calculation equation is permitted having a departure from its true value.4 Spatial resolution of digital holography4.1 Affecting factors of the spatial resolution of digital holographyIt should be considered in three respects: (1) sizes of the object and the registering material, and the direction of the reference beam, (2) resolution of the registering material, and (3) diffraction limitation.For pointx2on the object shown in Fig.3, the limits of spatial frequency are λξθλθθ⎥⎦⎤⎢⎣⎡⎪⎪⎭⎫ ⎝⎛-'-=-=-0211maxmax tan sin sin sin sin z x f R R Fig.2 Determining reconstructing distanceλξθλθθ⎥⎦⎤⎢⎣⎡⎪⎪⎭⎫⎝⎛-'-=-=-211minmintansinsinsinsin zxfRRFrequency range isλξξ⎥⎦⎤⎢⎣⎡⎪⎪⎭⎫⎝⎛-'-⎥⎦⎤⎢⎣⎡⎪⎪⎭⎫⎝⎛-=∆--211211tansintansinzxzxfso the range is unrelated to the reference beam.Considering the resolution of registering material in order to satisfy the sampling theory, phase difference between adjacent points on the recording plate should be less than π, namely resolution of the registration material.cfff=∆η21)(minmaxπ4.2 Expanding the spatial resolution of reconstruction imageExpanding the spatial resolution can be realized at least in three ways: (1) Reducing the registration distance z0 can improve the reconstruction resolution, but it goes with reduction of the reconstruction area at the same ratio.Therefore, this method has its limitation. (2) Increasing the resolution and the imaging size of CCD with expensive price. (3) Applying image-synthesizing technique[11]CCD captures a few of images between which there is small displacement (usually a fraction of the pixel size) vertical to the CCD plane, shown in Fig.4(Schematic of vertical moving is the same).This method has two disadvantages. First, it is unsuitable for dynamic testing and can only be applied in the static image reconstruction. Second, because the pixel size is small (usually 5μm to 10μm) and the displacement should a fraction of this size (for example 2μm), it needs a moving table with high resolution and precision. Also it needs high stability in whole testing.In general, improvement of the spatial resolution of digital reconstruction is Fig.3 Relationship between object and CCDstill a big problem for the application of digital holography.5 Testing resultsFig.5 is the photo of the testing system. The paper does testing on two coins. The pixel size of the CCD is 4.65μm and there are 1 392×1 040 pixels. The firstis one Yuan coin of RMB (525 mm) used for image reconstruction by phase-shifting digital holography. The second is one Jiao coin of RMB (520 mm) for the testing of deformation measurement also by phase-shifting digital holography.5.1 Result of image reconstructionThe dimension of the one Yuancoin is 25 mm. The registrationdistance measured by ruler isabout 385mm. We capture ourphase-shifting holograms andreconstruct the image byphase-shifting digital holography.Fig.6 is the reconstructed image.Fig.7 is the curve of the auto-focusFig.4 Image capturing by moving CCD along horizontal directionFig.5 Photo of the testing systemfunction, from which we determine the real registration distance 370 mm. We can also change the controlling precision, for example 5mm, 0.1 mm,etc., to get more course or precision reconstruction position.5.2 Deformation measurementIn digital holography, the method of measuring deformation measurement differs from the traditional holography. It gets object wave before and after deformation and then subtract their phases to obtain the deformation. The study tested effect of heating deformation on the coin of one Jiao. The results are shown in Fig.8, Where (a) is the interferential signal of the object waves before and after deformation, and (b) is the wrapped phase difference.5.3 Improving the spatial resolutionFor the tested coin, we applied four sub-low-resolution holograms to reconstruct the high-resolution by the image-synthesizing technique. Fig.9 (a) is the reconstructed image by one low-resolution hologram, and (b) is the high-resolution image reconstructed from four low-resolution holograms.Fig.6 Reconstructed image Fig.7 Auto-focus functionFig.8 Heating deformation resultsFig.9 Comparing between the low and high resolution reconstructed image6 SummaryDigital holography can obtain phase and amplitude of the object wave at the same time. Compared to other techniques is a big advantage. Phase-shifting digital holography can realize image reconstruction and deformation with less noise. But it is unsuitable for dynamic testing. Applying the intensity sum of the reconstruction image as the auto-focusing function to evaluate the registering distance is easy, and computation is fast. Its precision is also sufficient. The image-synthesizing technique can improve spatial resolution of digital holography, but its static characteristic reduces its practicability. The limited dimension and too big pixel size are still the main obstacles for widely application of digital holography.外文文献译文：标题：图像重建中的相移数字全息摘要：相移数字全息术被用来研究研究艺术品的内部缺陷。

英文文献整篇翻译

英文文献整篇翻译Title: The Impact of Climate Change on BiodiversityClimate change is a pressing issue that has significant impacts on biodiversity worldwide. Changes in temperature, precipitation patterns, and extreme weather events are altering ecosystems and threatening the survival of many species. The loss of biodiversity not only affects the natural world but also has implications for human societies.One of the major impacts of climate change onbiodiversity is the shifting of habitats. As temperatures rise, many species are forced to move to higher latitudesor elevations in search of suitable conditions. This can disrupt ecosystems and lead to the decline or extinction of species that are unable to adapt to the new conditions.In addition to habitat loss, climate change is also causing changes in the timing of biological events such as flowering, migration, and reproduction. These changes can disrupt the delicate balance of ecosystems and lead to mismatches between species that depend on each other for survival.Furthermore, climate change is exacerbating otherthreats to biodiversity such as habitat destruction, pollution, and overexploitation. The combination of these factors is putting immense pressure on many species and pushing them closer to extinction.It is essential that we take action to mitigate the impacts of climate change on biodiversity. This includes reducing greenhouse gas emissions, protecting and restoring habitats, and implementing conservation measures to safeguard vulnerable species. By addressing the root causes of climate change and protecting biodiversity, we canensure a sustainable future for both the natural world and human societies.气候变化对生物多样性的影响气候变化是一个紧迫的问题，对全球的生物多样性产生重大影响。

【2018最新】英文文献快速中文翻译-优秀word范文 (10页)

本文部分内容来自网络整理，本司不为其真实性负责，如有异议或侵权请及时联系，本司将立即删除！== 本文为word格式，下载后可方便编辑和修改！ ==英文文献快速中文翻译篇一：英文文献小短文(原文加汉语翻译)A fern that hyperaccumulates arsenic(这是题目，百度一下就能找到原文好，原文还有表格，我没有翻译)A hardy, versatile, fast-growing plant helps to remove arsenic from contaminated soilsContamination of soils with arsenic,which is both toxic and carcinogenic, is widespread1. We have discovered that the fern Pteris vittata (brake fern) is extremely efficient in extracting arsenicfrom soils and translocating it into its above-ground biomass. This plant —which, to our knowledge, is the first known arsenic hyperaccumulator as well as the first fern found to function as a hyperaccumulator— has many attributes that recommend it for use in the remediation of arsenic-contaminated soils.We found brake fern growing on a site in Central Florida contaminated with chromated copper arsenate (Fig. 1a). We analysed the fronds of plants growing at the site for total arsenic by graphite furnace atomic absorption spectroscopy. Of 14 plant species studied, only brake fern contained large amounts of arsenic (As;3,280–4,980p.p.m.). We collected additional samples of the plant and soil from the contaminated site (18.8–1,603 p.p.m. As) and from an uncontaminated site (0.47–7.56 p.p.m. As). Brake fern extracted arsenic efficiently from these soils into its fronds: plants growingin the contaminated site contained 1,442–7,526p.p.m. Arsenic and those from the uncontaminated site contained11.8–64.0 p.p.m. These values are much higher than those typical for plants growing in normal soil, which contain less than 3.6 p.p.m. of arsenic3.As well as being tolerant of soils containing as much as 1,500 p.p.m. arsenic, brake fern can take up large amounts of arsenic into its fronds in a short time (Table 1). Arsenic concentration in fernfronds growing in soil spiked with 1,500 p.p.m. Arsenic increasedfrom 29.4 to 15,861 p.p.m. in two weeks. Furthermore, in the same period, ferns growing in soil containing just 6 p.p.m. arsenic accumulated 755 p.p.m. Of arsenic in their fronds, a 126-fold eichment. Arsenic concentrations in brake fern roots were less than 303 p.p.m., whereas those in the fronds reached 7,234 p.p.m.Addition of 100 p.p.m. Arsenic significantly stimulated fern growth, resulting in a 40% increase in biomass compared with the control (data not shown).After 20 weeks of growth, the plant was extracted using a solution of 1:1 methanol:water to speciate arsenic with high-performance liquid chromatography–inductively coupled plasma mass spectrometry. Almostall arsenic was present as relatively toxic inorganic forms, withlittle detectable organoarsenic species4. The concentration of As(III) was greater in the fronds (47–80%) than in the roots (8.3%), indicating that As(V) was converted to As(III) during translocation from roots to fronds.As well as removing arsenic from soils containing different concentrations of arsenic (Table 1), brake fern also removed arsenic from soils containing different arsenic species (Fig. 1c). Again, upto 93% of the arsenic was concentrated in the fronds. Although both FeAsO4 and AlAsO4 are relatively insoluble in soils1, brake fern hyperaccumulated arsenic derived from these compounds into its fronds (136–315 p.p.m.) at levels 3–6 times greater than soil arsenic.Brake fern is mesophytic and is widely cultivated and naturalized in many areas with a mild climate. In the United States, it grows in the southeast and in southern California5. The fern is versatile and hardy, and prefers sunny (unusual for a fern) and alkaline environments (where arsenic is more available). It has considerable biomass, and is fast growing, easy to propagate,and perennial.We believe this is the first report of significant arsenic hyperaccumulationby an unmanipulated plant. Brake fern has great potential toremediate arsenic-contaminated soils cheaply and could also aid studies of arsenic uptake, translocation, speciation, distributionand detoxification in plants. *Soil and Water Science Department, University ofFlorida, Gainesville, Florida 32611-0290, USAe-mail: lqma@?Cooperative Extension Service, University ofGeorgia, Terrell County, PO Box 271, Dawson,Georgia 31742, USA?Department of Chemistry & SoutheastEnvironmental Research Center, FloridaInternational University, Miami, Florida 33199,1. Nriagu, J. O. (ed.) Arsenic in the Environment Part 1: Cycling and Characterization (Wiley, New York, 1994).2. Brooks, R. R. (ed.) Plants that Hyperaccumulate Heavy Metals (Cambridge Univ. Press, 1998).3. Kabata-Pendias, A. & Pendias, H. in Trace Elements in Soils and Plants 203–209 (CRC, Boca Raton, 1991).4. Koch, I., Wang, L., Ollson, C. A., Cullen, W. R. & Reimer, K. J. Envir. Sci. Technol. 34, 22–26 (201X).5. Jones, D. L. Encyclopaedia of Ferns (Lothian, Melbourne, 1987).积累砷的蕨类植物耐寒，多功能，生长快速的植物，有助于从污染土壤去除砷有毒和致癌的土壤砷污染是非常广泛的。

(完整word版)企业偿债能力分析外文文献

外文文献原稿和译文原稿IntroductionAlthough creditors can develop a variety of protective provisions to protect their own interests, but a number of complementary measures are critical to effectively safeguard their interests have to see the company’s solvency. Therefore, to improve a company's solvency Liabilities are on the rise。

On the other hand, the stronger a company’s solvency the easier cash investments required for the project，whose total assets are often relatively low debt ratio，which is the point of the pecking order theory of phase agreement. Similarly，a company's short—term liquidity，the stronger the short-term debt ratio is also lower, long—term solvency，the stronger the long—term debt ratio is also lower 。

Harris et al. Well, Eriotis etc. as well as empirical research and Underperformance found that the solvency （in the quick ratio and interest coverage ratio, respectively, short-term solvency and long—term solvency) to total debt ratio has significant negative correlation。

外文文献及译文模板

原文与译文原文：A More Complete Conceptual Framework for SME FinanceAllen N. Berger Board of Governors of the Federal Reserve SystemGregory F. Udell Kelley School of Business, Indiana University,1. Financial institution structure and lending to SMEsThe research literature provides a considerable amount of evidence on the effects of financial institution structure on SME lending, although as noted above, the findings rarely go beyond the distinction between transactions lending technologies versus relationship lending to parse among the very different transactions technologies. Here, we briefly review the findings with regard to the comparative advantages of large versus small institutions (subsection A), foreign-owned versus domestically-owned institutions (subsection B), state-owned versus privately-owned institutions (subsection C) and market concentration (subsection D).A. Large versus small institutionsThere are a number of reasons why large institutions may have comparative advantages in employing transactions lending technologies which are based on hard information and small institutions may have comparative advantages in using the relationship lending technology which is based on soft information. Large institutions may be able to take advantage of economies of scale in the processing of hard information, but be relatively poor at processing soft information because it is difficult to quantify and transmit through the communication channels of large organizations (e.g., Stein 2002). Under relationship lending, there may be agency problems created within the financial institution because the loan officer that has direct contact over time with the SME is the repository of soft information that cannot be easily communicated to the management or owners of the financial institution. This may give comparative advantages in relationship lending to small institutionswith lower agency costs within the institution because they typically have less separation (if any) between ownership and management and fewer overall layers of management (e.g., Berger and Udell 2002). Finally, it is often argued that large institutions are relatively disadvantaged at relationship lending to SMEs because of organizational diseconomies with also providing transactions loans and other wholesale services to large corporate customers (e.g., Williamson 1967, 1988).The empirical literature on this topic usually does not observe the lending technologies used by large and small institutions, but rather draws conclusions about these technologies from the characteristics of the SME borrowers and contract terms on credits issued to these SMEs by institutions of different sizes. In most cases, the research is based on data from U.S. banks and SMEs. Large institutions are found to lend to larger, older, more financially secure SMEs (e.g., Haynes, Ou, and Berney 1999). It is often argued that these findings are consistent with large institutions lending to relatively transparent and relatively safe borrowers that are more likely to receive t ransactions credits. Large institutions are also found to charge lower interest rates and earn lower yields on SME loan contracts (e.g., Berger, Rosen, and Udell 2003, Berger 2004, Carter, McNulty, and Verbrugge 2004). It is contended that these results may reflect that large institutions lend to safer borrowers and/or employ lending technologies with lower operating costs, which are more likely to be transactions loans. In addition, large institutions are found to have temporally shorter, less exclusive, more impersonal, and longer distance relationships with their SME loan customers (e.g., Berger, Miller, Petersen, Rajan, and Stein forthcoming). These findings are argued to suggest weaker relationships with borrowers for large institutions, which are indicative of transactions loans. Finally, large institutions appear to base their SME credit decisions more on strong financial ratios than on prior relationships (e.g., Cole, Goldberg, and White 2004, Berger, Miller, Petersen, Rajan, and Stein forthcoming). It is argued that both the dependence on strong financial ratios and the non-dependence on prior relationships for large institutions are indicative of the use of transactions lending technologies.We argue that these findings are not as clear-cut in their support of thecomparative advantages by institution size as they might at first seem. For the most part, prior authors appear to treat transactions lending technologies as a collective whole that may be adequately represented by just one of these technologies, financial statement lending. This is not necessarily the case. We agree that the findings that SME credits by large institutions tend to be associated with weaker lending relationships and less often based on prior relationships and are indeed consistent with the predicted comparative disadvantage of large institutions in relationship lending. However, we do not agree with the contentions in the prior literature that greater SME transparency, safer SME borrowers, lower rates and yields, and possible lower operating costs and greater reliance on financial ratios for large institutions provide strong support for the hypothesis that these institutions have comparative advantages in transactions lending technologies. Although greater transparency, safer borrowers, lower rates, lower operating costs, and greater reliance on financial ratios are indicative of the use of the financial statement lending technology, they are not necessarily indicative of the types of loans or borrowers associated with the other transactions lending technologies. That is, these other transactions technologies may not necessarily be used to lend to SMEs that are less opaque or safer than relationship borrowers, may not have lower rates or smaller processing costs than relationship loans, and may not be based on stronger financial ratios than the relationship lending technology.To illustrate, note that two of the transactions lending technologies that are often used by large U.S. banks are not consistent with these characteristics. As indicated above, small business credit scoring appears to be employed by large U.S. banks to lend to SMEs that are relatively opaque and risky, and these loans have relatively high interest rates. As discussed further below, this technology is based largely on the personal credit of the SME owner, rather than on strong financial ratios of the firm. Similarly, as discussed below, the asset-based lending technology employed by many large banks is generally used to lend to relatively opaque and risky borrowers at relatively high interest rates. These loans typically involve relatively high processing costs of monitoring the accounts receivable and inventory pledged as collateral and the primary information is based on the value of the collateral, rather than strongfinancial ratios of the borrower.Moreover, even to the extent that large institutions may be disadvantaged in relationship lending and tend to lend to more transparent SME borrowers on average than small institutions, this does not necessarily imply that a sizeable presence of small institutions is necessary for significant credit availability for opaque SMEs. A limited amount of additional research finds that the local market shares of large and small U.S. banks have relatively little association with SME credit availability in their markets (Jayaratne and Wolken1999, Berger, Rosen, and Udell 2003).One potential hypothesis that may help explain this finding is that large U.S. banks are able to accommodate many opaque SME loan customers with transactions technologies other than financial statement lending, such as small business credit scoring and asset-based lending. That is, large institutions may have more transparent SME borrowers on average than small institutions because they have more financial statement loans to transparent SMEs than small institutions, but these large institutions may also be able to make credit available to significant numbers of opaque SMEs using the other transactions technologies. This hypothesis is difficult to test because the lending technology is usually unobserved.A second hypothesis may also help explain the finding of little association between the market shares of large and small institutions and SME credit availability. Large institutions may be disadvantaged at serving a significant subset of opaque SMEs, but market forces may be efficient in sorting these opaque SMEs to small institutions in the market that serve these borrowers using the relationship lending technology. The empirical evidence on the effects of U.S. bank mergers and acquisitions (M&As) on SME lending provides some support for this second hypothesis, although the lending technologies and the opacity of the borrowers is typically not observed in these studies. The studies find that large institutions reduce their SME lending after M&As, but that other banks in the same local markets appear to respond by increasing their own supplies of SME credit substantially (e.g., Berger, Saunders, Scalise, and Udell 1998, Berger, Goldberg, and White 2001, Averyand Samolyk 2004). As well, new small banks are often created in these markets that provide additional boosts to the local supply of SME credit (Berger, Bonime, Goldberg, and White 2004).The finding that the availability of credit to SMEs does not appear to depend in an important way on the market presence of large versus small institutions in the U.S. does not necessarily apply to other nations because of other differences in the financial institution structures of these nations or lending infrastructures in these nations that limit competition for SME credits. In an international comparison, greater market shares for small banks are found to be associated with higher SME employment, as well as more overall bank lending (Berger, Hasan, and Klapper 2004). These findings hold for both developed and developing nations, hold with controls included for some other aspects of the financial institution structure (e.g., shares of foreign-owned and state-owned banks, bank concentration), and hold with controls for some aspects of the lending infrastructure (e.g., regulation, legal system).B. Foreign-owned versus domestically-owned institutionsFor a number of reasons, foreign-owned institutions may have comparative advantages in transactions lending and domestically-owned institutions may have comparative advantages in relationship lending. Foreign-owned institutions are typically part of large organizations, and so all of the logic discussed above regarding large institutions generally applies to foreign-owned institutions as well. Foreign-owned institutions may also face additional hurdles in relationship lending because they may have particular difficulties in processing and transmitting soft information over greater distances, through more managerial layers, and having to cope with multiple economic, cultural, language, and regulatory environments (e.g., Buch 2003). Moreover, in developing nations, foreign-owned institutions headquartered in developed nations may have additional advantages in transactions lending to some SMEs because of access to better information technologies for collecting and assessing hard information. For example, some foreign-owned institutions use a form of small business credit scoring to lend to SMEs in developing nations based on the SME’s industry.Other institutions provide home-nation training for loan officers stationed in developing nations (Berger,Hasan, and Klapper 2004).There is very little empirical evidence on SME lending by foreign-owned institutions in developed nations, although some research finds that these institutions tend to have a wholesale orientation (e.g., DeYoung and Nolle 1996), and in some cases tend to specialize in serving multinational corporations headquartered in their home nation, presumably using transactions technologies applied to hard information (e.g., Goldberg and Saunders 1981). Some evidence also is consistent with the hypothesis that foreign-owned institutions may have difficulty processing local soft information needed to provide cash management services, although this finding is based on data from multinational corporations (e.g., Berger, Dai, Ongena, and Smith 2003). In most cases, the research on bank efficiency in developed nations suggests that the disadvantages of foreign ownership outweigh the disadvantages on average, although it is not known how much of this is attributable to the lending function (e.g., DeYoung and Nolle 1996, Berger, DeYoung, Genay, and Udell 2000).The empirical findings regarding foreign-owned institutions in developing nations are quite different. Foreign-owned banks usually appear to be more profitable and efficient than domestically-owned banks on average in these nations (e.g., Claessens, Demirguc-Kunt, and Huizinga 2001, Martinez Peria and Mody 2004), although one study finds roughly equal performance after controlling for a number of different types of governance and governance change (Berger, Clarke, Cull, Klapper, and Udell forthcoming). The better performance of foreign-owned banks in developing nations relative to developed nations may be due to the better technology access noted above, or some combination of better access to capital markets, superior ability to diversify risks, or greater managerial experience. There is also evidence on the effects of foreign-owned institutions on SME credit availability in developing nations. In most of the studies, foreign-owned banks individually or larger shares for these banks are associated with greater credit availability for SMEs (e.g., Dages, Goldberg, and Kinney 2000, Clarke, Cull, and Martinez Peria 2002, Beck, Demirguc-Kunt, and Maksimovic 2004, Berger, Hasan, and Klapper 2004, Clarke, Cull, Martinez Peria, and Sanchezforthcoming), although one study finds that foreign-owned banks may have difficulty in supplying SME credit (e.g., Berger, Klapper, and Udell 2001). As above for the U.S. data, the lending technologies are generally unobserved, and there is even less information available about the characteristics of the SME borrowers or contract terms from which to infer these technologies. Although the foreign-owned institutions almost surely use transactions technologies, it is usually not known which among the technologies is employed or the opacity of the borrowers served.C. State-owned versus privately-owned institutionsState-owned institutions may be expected to have comparative advantages in transactions lending and privately-owned institutions may be expected to have comparative advantages in relationship lending simply because state-owned institutions are typically larger. There are also a number of additional arguments with regard to the general ability of state-owned institutions to affect the supply of funds available to creditworthy SMEs through any lending technology. State-owned institutions generally operate with government subsidies and often have mandates to supply additional credit to SMEs or entrepreneurs in general, or to those in specific industries, sectors, or regions. Although in principle, this might be expected to improve funding of creditworthy SMEs, it could have the opposite effect in practice because these institutions may be inefficient due to a lack of market discipline. Much of their funding to SMEs may be to firms that are not creditworthy because of this inefficiency. The credit recipients may also not be creditworthy because the lending mandates do not necessarily require the funding be applied to positive net present value projects, or that the loans be expected to be repaid at market rates. As well some of the funds may be channeled for political purposes, rather than for economically creditworthy ends (e.g., Sapienza forthcoming). State-owned institutions may also provide relatively weak monitoring of borrowers and/or refrain from aggressive collection procedures as part of their mandates to subsidize chosen borrowers or because of the lack of market discipline. In nations with substantial state-owned banking sectors, there may also be significant spillover effects that discourage privately-owned institutions from SME lending due to “crowding out” effects of subsidized loans from state-owned institutions or poor credit cultures that are perpetuatedby the state-owned presence.The empirical findings –which are generally either cross-section studies of many nations or focused on one or a few developing nations –are generally consistent with the negative performance effects of state ownership. Studies of general performance typically find that individual state-owned banks are relatively inefficient and that large shares of state bank ownership are typically associated with unfavorable macroeconomic consequences (e.g., Clarke and Cull 2002, La Porta, Lopez-de-Silanes, and Shleifer 2002, Barth, Caprio, and Levine 2004, Berger, Hasan, and Klapper 2004, Berger, Clarke, Cull, Klapper, and Udell forthcoming). The evidence also generally suggests that less SME credit is available in nations with large market shares for state-owned banks (e.g., Beck, Demirguc-Kunt, and Maksimovic 2004, Berger, Hasan, and Klapper 2004). As well, nonperforming loan rates at state-owned banks tend to be very high, consistent with lending to SMEs with negative net present value loans, weak monitoring of loan customers, and/or lack of aggressive collection procedures (e.g., Hanson 2004, Berger, Clarke, Cull, Klapper, and Udell forthcoming). Consistent with these findings of generally negative consequences of state ownership, studies of the effects of bank privatization in both developed nations (e.g., Verbrugge, Megginson, and Owens 2000, Otchere and Chan 2003) and developing nations (e.g., Clarke, Cull, and Megginson forthcoming) typically find improvements in performance following the elimination of state ownership. Similar to the case for foreign-owned institutions, state-owned institutions likely generally use transactions technologies, but there is little information available on the technologies employed or data from which to infer these technologies.D. Market concentrationGreater market concentration of financial institutions may either reduce or increase the supply of credit available to creditworthy SMEs. Under the traditional structure-conduct-performance (SCP) hypothesis, greater concentration results in reduced credit access through any lending technology. This may occur in several ways as institutions in more concentrated markets may exercise greater market power. These institutions may choose to raise profits through higher interest rates or fees on loans to SMEs; they maychoose to reduce risk or supervisory burden by tightening credit standards for SMEs; and/or they may choose to be less aggressive in finding or serving creditworthy SMEs, taking advantage of a “quiet life” afforded to managers by the market power. Alternatively, institutions in more concentrated markets may increase SME access to credit using one of the lending technologies, relationship lending. Greater concentration may encourage institutions to invest in lending relationships because the SMEs are less likely to find alternative sources of credit in the future. Market power helps the institution enforce a long-term implicit contract in which the borrower receives a subsidized interest rate in the short term, and then compensates the institution by paying a higher-than-competitive rate in a later period (Sharpe 1990, Petersen and Rajan 1995).Although both theories may apply simultaneously, empirical studies have not come to consensus as to which of these may dominate empirically and whether the net supply of SME credit is lower or higher in concentrated markets. Some studies of the SCP hypothesis using U.S. data found that higher concentration is associated with higher SME loan interest rates (e.g., Hannan 1991, Berger, Rosen, and Udell 2003). Although this finding may appear to support the SCP hypothesis, it may also be consistent with the alternative hypothesis of an expansion of relationship lending if relationship loans tend to have higher interest rates on average than transactions loans. Relationship loans do not necessarily have higher average rates, as argued above, but we cannot rule out this possibility. As above for the empirical literatures on large versus small, foreign-owned versus domestically-owned, and state-owned versus privately-owned institutions, much of the difficulty in interpreting the effects of market concentration arises because the lending technologies are generally unobserved.A number of recent studies have looked instead to testing these hypotheses by examining the effects of banking market concentration and other indicators of market power such as regulatory restrictions on competition (part of the lending infrastructure discussed further below) on SMEs and general economic performance. The empirical results are mixed. Some of the studies find unfavorable effects from high banking market concentration andrestrictions on competition (e.g., Jayaratne and Strahan 1998, Black and Strahan 2002, Berger, Hasan, and Klapper 2004), others find favorable effects of bank concentration (e.g., Petersen and Rajan 1995, Cetorelli and Gambera 2001, Zarutskie 2003, Cetorelli 2004, Bonaccorsi di Patti and Dell’Ariccia forthcoming), and still others find the effects may differ with the lending infrastructure or economic environment (e.g., DeYoung, Goldberg, and White 1999, Beck, Demirgüç-Kunt, and Maksimovic 2004).FROM: Prepared for presentation at the World Bank Conference on Small and Medium Enterprises: Overcoming Growth ConstraintsWorld Bank, MC 13-121October 14-15, 2004译文：一个更加完整概念框架的中小企业融资Allen N. Berger 美国联邦储备局Gregory F. Udell 印地安那大学商学院1．金融机构对中小企业贷款和结构这个研究提供了大量的影响金融机构对中小企业贷款质量的证据,如上文提到的,结果几乎超越两者之间的区别与关系型贷款借给技术交易中非常不同的解析交易技术。

英文文献翻译及原文

原文Title: Improved Integral Inequalities for Producets of Convex FunctionsA largely applied inequality for convex functions, due to its geometrical significance, is Hadamard’s inequality (see [3] or [2]) which has generated a wide range of directions forextension and a rich mathematical literature. Below, we recall this inequality, together with its framework.A function [],f a b R ®：, with [],a b R Ì, is said to be convex if whenever[],x a b " [],y a b Î,[]0,1t Î the following inequality holds(1.1) ()()()()()11f tx t y tf x t f y +-?-This definition has its origins in Jensen’s results from [4] and has opened up the mostextended, useful and multi-disciplinary domain of mathematics, namely, convex analysis. Convex curves and convex bodies have appeared in mathematical literature since antiquity and there are many important results related to them. They were known before the analytical foundation of convexity theory, due to the deep geometrical significance and manygeometrical applications related to the convex shapes (see, for example, [1], [5], [7]). One of these results, known as Hadamard’s inequality, which was first published in [3], states that a convex function f satisfies(1.2) Recent inequalities derived from Hadamard’s inequality can be found in Pachpatte’spaper [6] and we recall two of them in the following theorem, because we intend to improve them. Let us suppose that the interval [],a b has the property that 1b a - . Then thefollowing result holds.Theorem 1.1. Let f and g be real-valued, nonnegative and convex functions on [],a b . Then(1.3) ()()()12031(1)(1)2b b a a f tx t y g tx t y dtdydx b a ?-+--蝌()()()()()2,,118b a M a b N a b f x g x dx b a b a 轾+犏?犏--犏臌ò and(1.4) ()()1031122b a a b a b f tx t g tx t dtdx b a 骣骣骣骣++鼢琪琪珑+-+-鼢鼢珑珑鼢鼢珑珑桫桫-桫桫蝌 ()()()122b a f a f b a b f f x dx b a 骣++÷ç＃÷ç÷ç桫-ò()()()()111,,4b a b a f x g x dx M a b N a b b a b a +-轾??臌--òwhere(1.5) ()()()()(),M a b f a g a f b g b =+and(1.6) ()()()()(),N a b f a g b f b g a =+Remark 1.2. The inequalities (1.3) and (1.4) are valid when the length of the interval [],a b does not exceed 1. Unfortunately, this condition is accidentally omitted in [6], but it is implicitly used in the proof of Theorem 1.1.Of course, there are cases when at least one of the two inequalities from the previous theorem is satisfied for 1b a ->, but it is easy to find counterexamples in this case, as follows.Example 1.1. Let us take [][],0,2a b =. The functions []:0,2f R ® and []:0,2g R ® are defined by ()f x x = and ()g x x =. Then it is obvious that (),4M a b =, (),0N a b =. Then, the direct calculus of both sides of (1.3) leads toand, obviously, inequality (1.3) is false.Remark 1.3. Inequality (1.3) is sharp for linear functions defined on []0,1, while inequality (1.4) does not have the same property.In this paper we improve the previous theorem, such that the condition1b a -is eliminated and the derived inequalities are sharp for the whole class of linear functions.()()()1203111(1)(1)26b b a a f tx t y g tx t y dtdydx b a ?-+-=-蝌 ()()()()()2,,1135824b a M a b N a b f x g x dx b a b a 轾+犏+=犏--犏臌ò译文题目：凸函数在积分不等式中的应用由于凸函数的几何意义,Hadamard 不等式在很大程度上影响了不等式凸函数的应用，Hadamard 不等式在丰富的数学文化和广泛的深入研究等条件下形成的，以下,我们回忆一下这些不等式，定义1 函数[],f a b R ®：,并且[],a b R Ì为凸函数,若[],x a b " [],y a b Î,[]0,1t Î,有不等式()()()()()11f tx t y tf x t f y +-?- (1.1)成立，这个由Jensen 提出的定义起源于[4],并且由此发展出对数学和多学科专业领域有用的凸分析，凸曲线和凸面体在很古老的时候就已经出现在了数学领域,有很多重要的成果都和他们有关系，由于许多几何意义和几何应用与凹凸形状有关,认识他们的分析基础是凸性理论，（例如 [1],[5],[7]）其中一个成果是Hadamard 不等式,第一次在[3]出版,阐明了凸函数f 满足()()()122b a f a f b a b f f x dx b a 骣++÷ç＃÷ç÷ç桫-ò (1.2)Pachpatte 不等式理论是由Hadamard 不等式理论推断而来，我们称他们两个为定理因为我们还要优化他们，设区间 [],a b 满足1b a - ,有如下结果定理1.1 设函数f 和g 是定义在非负实数区间[],a b 的凸函数，那么()()()12031(1)(1)2b b a a f tx t y g tx t y dtdydx b a ?-+--蝌 (1.3) ()()()()()2,,118b a M a b N a b f x g x dx b a b a 轾+犏?犏--犏臌ò 和()()1031122b a a b a b f tx t g tx t dtdx b a 骣骣骣骣++鼢琪琪珑+-+-鼢鼢珑珑鼢鼢珑珑桫桫-桫桫蝌 (1.4)()()()()111,,4b a b a f x g x dx M a b N a b b a b a +-轾??臌--ò其中()()()()(),M a b f a g a f b g b =+ (1.5)()()()()(),N a b f a g b f b g a =+ (1.6)注意1.2 当[],a b 中1b a - 的时候,不等式(1，3)和 (1，4)成立,虽然这个条件被忽略,但在证明定理过程中已经被隐含的使用，当然,至少有一两个不等式在以上定理中当1b a ->时成立的,但它很容易找到反例说明在这种情况下,如下令[][],0,2a b =,函数[]:0,2f R ®和[]:0,2g R ®被定义为()f x x =和()g x x =,显然有(),4M a b =,(),0N a b =，带入（1，3）有()()()1203111(1)(1)26b b a a f tx t y g tx t y dtdydx b a ?-+-=-蝌 ()()()()()2,,1135824b a M a b N a b f x g x dx b a b a 轾+犏+=犏--犏臌ò 很显然,不等式(1.3)是错误的，定理1.3 不等式(1.3)是定义在[]0,1上的线性函数,但是不等式(1.4)是不存在这种性质的，本论文将优化早先的定理，比如除去1b a - 条件,并且衍生的不等式满足所有的线性函数，。

外文文献原稿和译文(模板)

北京化工大学北方学院毕业设计（论文）——外文文献原稿和译文（空一行）外文文献原稿和译文（空一行）原□□稿（空一行） IntroductionThe "jumping off" point for this paper is Reengineering the Corporation, by Michael Hammer and James Champy. The paper goes on to review the literature on BPR. It explores the principles and assumptions behind reengineering, looks for commonfactors behind its successes or failures, examines case studies, and presents alternatives to "classical" reengineering theory. The paper pays particular attention to the role of information technology in BPR. In conclusion, the paper offers somespecific recommendations regarding reengineering. Old Wine in New Bottles The concept of reengineering traces its origins back to management theories developedas early as the nineteenth century. The purpose of reengineering is to "make all your processes the best-in-class." Frederick Taylor suggested in the 1880's that managers use process reengineering methods to discover the best processes for performing work, and that these processes be reengineered to optimize productivity. BPR echoes the classical belief that there is one best way to conduct tasks. In Taylor's time, technology did not allow large companies to design processes in across-functional or cross-departmental manner. Specialization was the state-of-theart method to improve efficiency given the technology of the time.（下略）之上之下各留一空行，宋体，三号字，居中，加粗。

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资产重估或减值准备：了解占固定资产在Release 12布赖恩·刘易斯eprentise介绍显著的变化在财务报告的要求已经改变的固定资产核算框架公司。

国际财务报告准则（IFRS）要求的固定资产进行初步按成本入账，但有两种会计模式-成本模式计量的重估模式。

那么，有什么区别，当你应该考虑升值与减值？没有R12带给固定资产哪些重要变化？国际财务报告准则和美国公认会计准则报告的甲骨文®电子商务套件但很显然，美国证券交易委员会（SEC）将不会要求美国公司使用国际财务报告准则在不久的将来，大多数玩家在资本市场倾向于认为它是不可避免的，将国际财务报告准则最终成为美国的财务报告环境的更显著的部分。

这实际上是对发生的程度，超过400基于在美国以外的全球企业都被允许提交美国证券交易所（SEC）的财务报告（10K和10Q -通常被称为年度/季度财务报告）。

为海外谁也不在美国的证券交易委员会提交的公司，国际财务报告准则正在成为金融世界标准报告。

对于谁住在多个资本市场运作的公司，有可能实际上是一个双重报告要求国际财务报告准则和美国公认会计原则（公认会计原则）的财务报表。

与11i版，随后与12版时，Ora cle®电子商务套件（EBS）添加功能让用户生活在两个国际财务报告准则和美国公认会计准则的世界。

这两个报告之间的差异框架是广泛的，但对于本白皮书的目的，我们将专注于固定资产中核算EBS -特别是资产重估或减值。

根据美国公认会计准则，固定资产乃按历史成本，然后以折旧出售或剩余价值。

如果有某些迹象表明固定资产的变现价值造成负面改变，则该资产写下来，损失记录。

这被称为减值。

根据国际财务报告准则，财务报表发行人有权选择成本模式（这是大多数方面的选项类似美国公认会计原则机型）或重估模式（其中有没有下的并行报告美国公认会计原则）。

根据重估模式，固定资产可定期写入，以反映公平市场价值-这是专门美国公认会计原则和美国证券交易委员会的权威所禁止的东西。

本白皮书的平衡都将与美国公认会计原则下，专注于固定资产重估及减值国际财务报告准则。

在此之前潜水深入到这个问题，它通过R12的与固定的新特性列表来运行是非常有用的资产。

在12版的新功能和变更功能的固定资产神谕®电子商务套件（EBS）R12有许多有用的新功能，其中许多以固定发了言资产，包括：•明细分类账会计（SLA）的体系结构- Oracle资产管理系统完全与SLA 集成，允许为一个单一的交易或商业活动的多个会计交涉。

•自动准备成批增加的-默认规则和公共应用程序编程接口（API），这些可以被用来自动地完成质量附加系的制备。

•使用XML Publisher灵活的报告-十三定制新的资产报告。

•自动回滚折旧-回滚可以根据需要对整个资产上选择资产被执行书，它不再需要手动运行。

•增强的功能为能源行业。

•退休和重估，现在除了期间允许的。

这些新增的诸多好处，包括流程的效率，灵活的会计和报告以及行业增强功能。

因收购或资产剥离的角度来看，传统系统从不同的标准转换如美国公认会计准则和国际财务报告准则予以特别处理。

因此，如何在美国公认会计准则和国际财务报告准则相同，在哪里处理固定资产时，他们有什么区别？比较国际财务报告准则和美国公认会计准则的企业合并/固定资产会计下表载列收购后，总结并比较固定资产美国公认会计准则和国际财务报告准则的要求。

美国公认会计原则国际财务报告准则折旧同同重估被禁止宠物/创建重估盈余折旧重估后N / A宠物减值直接写下来写下来，以重估盈余第一，然后直接写出美国公认会计原则是侧重于P＆L（损益）为财务保守的以规则为基础的会计准则使用的实体的所有者（或股东），而国际财务报告准则更多的是侧重一种以原则为基础的会计准则在资产负债表主要用于实体债权人。

美国公认会计准则和国际财务报告准则之间固定资产显著差异的重估，重估领域所有这些盈余，如前所述减值，定义如下：固定资产的重估-一家公司的资产重估考虑到通胀或公允价值变动由于资产购买或收购。

必须有说服力的证据升值。

在值的变化是计入重估盈余（储备）账户。

向下的重估被视为减值。

重估盈余（储备） -该固定资产的价值，由于固定资产重估增加计入重估盈余（储备）。

当如图资产的可变现价值，发生固定资产减值-固定资产减值资产负债表，超过了其实际价值（公允价值）给该公司。

当发生减值，企业必须降低其价值在资产负债表，并承认损失在损益表中。

有没有因为不断变化的情况重估或向上调整值。

这是相似的模式目前在美国公认会计准则的使用。

例子ACME公司购买了价值20万元的建设2008年1月1日。

它使用下面的记录的建设日记帐分录：建筑200,000现金200,000该大楼有20年的使用寿命，并在这个例子中，公司采用直线法折旧。

每年折旧为20万元/ 20年，或者1万美元。

累计折旧截至2010年12月31日，为10,000元* 3或3万元，与账面值20万元减3万元，相当于170000美元。

我们看到，该建筑仍保持其历史成本，并定期折旧，没有其他上升调整值。

如果资产随后被看重的归结于减值，损失计入当期声明为减值损失。

重估模型在重估模式，资产最初以成本入账，但其后其账面值会增加考虑到升值价值。

成本模式和重估模式之间的区别在于，重估模式允许在资产价值向下和向上调整，而成本模型允许只有向下调整，由于减值亏损。

这是目前采用的国际财务报告准则的模型。

例子考虑的Acme公司在成本模型中使用的例子。

假设2010年12月31日，该公司打算切换到重估模型，并进行其估计的公允价值重估运动建设为190,000元（再次，2010年12月31日）。

在当日的账面价值为$ 170,000重估金额为$ 190,000因此是必需的大楼帐户20,000元向上调整。

它是通过记录以下日记帐分录：建筑20,000重估盈余20,000重估盈余升值不被认为是正常的收益，而不是记录在损益表中，而是直接计入称为重估盈余权益账。

重估盈余持有的全部向上重估公司的资产，直到这些资产被出售。

在Acme的有限公司，折旧的情况下，2011年是由剩余使用年限，或190000美元/ 17等于11176美元划分新的账面值。

重估回拨如果重估资产随后被看重的归结于减值损失首先冲减任何余额在重估盈余可用。

如果损失超过同一资产的重估盈余平衡差额计入利润表的减值损失。

例子假设2012年12月31日，公司尖端的重新估值建设再次发现，公允价值应为16万元。

账面值于2012年12月31日，是190000美元减去22352美元2年折旧这相当于167648美元。

账面值由7648美元超过公允价值，因此帐户余额应该由量减少。

我们已经有20,000元在与同一建筑物的重估盈余帐户余额，所以没有减值亏损会在收益表。

日记帐分录为：重估盈余7,648大厦的账户7,648曾经的公允价值是$ 140,000超过公允价值超过账面值会一直27648美元。

在这种情况下，以下日记帐分录将被要求：重估盈余20,000资产减值损失7,648建筑20,000累计减值亏损7,648涨幅建筑价值300,000重估盈余20,000EBS注意事项重估模式在EBS中，您可以重估所有类别的固定资产的书，所有资产类别，或者只是个别资产。

重估在一本书的所有类别或所有资产类别中被认为是“大众重估” -也就是说，你可以重估资产集体。

个别重估资产的影响对资产按资产基础。

如果您选择允许重估，您必须指定您的重估规则-特别是，你是否会允许EBS为“[R] evalue的积累折旧。

如果不重估累计折旧，则Oracle资产转让累计折旧重估储备账。

•输入您要升值类别•进入升值百分比率重估资产。

输入一个正数或负数。

•如果需要覆盖默认的重估规则。

•选择预览（注：必须预览之前，EBS将让你继续）•如果预览后，您需要进行更改，编辑重估规则或百分比。

•发现使用大众交易号码重估的定义。

•选择运行。

Oracle资产管理系统开始一个并发进程执行的重估。

•复查请求完成后的日志文件。

重估个别资产：•输入您希望人民币升值的一个类别，而不是资产编号。

重估功能并不是对固定资产重估根据购买会计规则混乱的一个领域，我们已经遇到过好几次是是否的资产重估功能Oracle的EBS可以用来升值已收购公司的资产。

根据财务会计准则第141（R）和国际财务报告准则第3号业务合并，公司必须重估其资产，以公允价值于收购日期。

这是强制性的必须递交周年所有公司报告与SEC或卷起成美国证券交易委员会报告的公司。

对我们而言，这意味着几乎每个人。

这同样适用于国际财务报告准则报告的公司。

它曾经是，企业可以利用的利益汇集在那里可能只是离开固定资产被收购公司的账目，用于开发成本，累计折旧，并日期在役。

这不再是允许的。

因为根据美国公认会计原则和国际财务报告准则有没有这样的事，作为一个“合并”，总会有一家公司确定为所获取的。

对于这家公司，所有固定资产需要（1）重列，以公允价值之日采集;（2）已在服务之日起经重列至收购日期，以及（3）具有累计折旧归零。

如果一家公司能支持论点，即扣除累计折旧，成本是重大的同公允价值，被收购的公司可能会做，但净值必须迁移到原来的成本领域，累计折旧归零，并在服务日期仍复位至收购日期。

如果公司是重申对公允价值不能使用净额结算方法，然后一些新的公允价值，必须为每个做固定资产。

甲骨文质量重估（OMR）功能将无法为这些类型重估的工作，为下原因：1。

放置在服务之日起必须改变，以业务合并日期- OMR不支持这个。

2。

OMR质量和类别重估将不会容纳扣除累计折旧或装载多个非比例确定的公允价值重述。

3。

个人资产重估是不切实际的大量资产，也不能容纳扣除累计折旧或重新投入使用的日期。