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The Economics of Microfinance-chapter 1
The Economics of Microfi nanceBeatriz Armendáriz and Jonathan MorduchThe MIT PressCambridge, MassachusettsLondon, EnglandSecond Edition© 2010 Massachusetts Institute of TechnologyAll rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher.For information about special quantity discounts, please email special_sales@mitpress. .This book was set in Palatino by Toppan Best-set Premedia Limited.Printed and bound in the United States of America.Library of Congress Cataloging-in-Publication DataArmendáriz, Beatriz.The economics of microfinance / Beatriz Armendáriz and Jonathan Morduch.—2nd ed.p. cm.Includes bibliographical references and index.ISBN 978-0-262-01410-6 (hardcover : alk. paper)—ISBN 978-0-262-51398-2 (pbk. : alk. paper) 1. Microfinance. I. Morduch, Jonathan. II. Title.HG178.3.A76 2010332—dc22200903476010 9 8 7 6 5 4 3 2 11 1.1 IntroductionIn March 1978, seven years after Bangladesh won its war for indepen-dence, a small group of young men joined together to make a secret pledge. They vowed to create a new and dynamic organization dedi-cated to fi ghting rural poverty. Some saw Bangladesh’s plight as hope-less, as the country struggled in a world increasingly divided between haves and have-nots. Thirty years later, however, the organization started by the young men serves nearly six million villagers in Bangladesh and is celebrated by global business leaders. The Associa-tion for Social Advancement (now best known by its acronym, ASA) targets Bangladesh’s poorest villagers, many of them women, offering tools to create better lives. ASA found success by applying fundamen-tal lessons from economics and management, coupled with important (and not obvious) new insights. In the process, ASA is expanding fi nancial markets and creating fresh ways to think about business strat-egies, economics, and social change.1The hurdles have been high and ASA’s leaders have had to rethink their plans more than once. While ASA started with a commitment to fomenting political transformation, its course shifted radically. Today ASA is squarely a bank for the poor, headquartered in a new offi ce tower in Bangladesh’s capital. In this, ASA stands as part of a global “microfi nance” movement dedicated to expanding access to small-scale loans, savings accounts, insurance, and broader fi nancial services in poor and low-income communities. Their bet is that access to microfi -nance can offer powerful ways for the poor to unlock their productive potential by growing small businesses. Increasingly, the focus is also on helping customers save for the future and create more stable lives. InRethinking Banking2 Chapter1doing so, ASA and institutions like it are challenging decades ofthinking about markets and social policy in low-income communities.ASA’s customers borrow on average around $120 per loan, andrepay the loans over the better part of a year. Traditional commercialbanks avoid this population. First, the loans are so small that profitsare typically hard to find, and, second, lending seems risky since theborrowers are too poor to offer much in the way of collateral. But atthe end of 2008 ASA reported loan recovery rates of 99.6 percent, andtheir reported revenues have fully covered costs in every year since1993.For many observers, microfinance is nothing short of a revolution ora paradigm shift (Robinson 2001). Innovators are profi led in leadingnewspapers and business magazines (in December 2007, ASA toppedForbes magazine’s global ranking of microfinance providers), andthe 2006 Nobel Peace Prize, awarded to the microfi nance pioneersMuhammad Yunus and Grameen Bank, signals the ways in whichmicrofinance has shaken up the world of international development.One of the most striking elements is that the pioneering models grewout o f e xperiments i n l ow-income c ountries l ike B olivia a nd B angladesh—rather than from adaptations of standard banking models in richercountries.Entrepreneurs, academics, social activists, and development expertsfrom around the world have been attracted by the lessons about retailbanking through microfinance, as well as by the promise that bankslike ASA hold for getting much-needed resources to underserved pop-ulations.2 Scores of doctoral dissertations, master’s theses, and aca-demic studies have now been written on microfinance. Some focus onthe nontraditional contracts used to compensate for risks and to addressinformation problems faced by the microlenders. Others focus onmicrofinance as a way to better understand the nature of markets inlow-income economies—with possible lessons for how to supply insur-ance, water, and electricity through markets rather than throughinefficient state-owned companies. Still others focus on the ways thatmicrofinance promises to reduce poverty, fight gender inequality, andstrengthen communities. This book provides a critical guide to someof the most important new ideas.The ideas give reasons for hope. Banks and NGOs like ASA areflourishing at a time when the effectiveness of foreign aid to ease theburdens of the world’s poor faces fundamental questions (e.g., Boone1996; Easterly 2006). Governments around the world routinely faceRethinking Banking 3criticism for at times being corrupt, bloated, and uninterested in reform. Against this background, banks and NGOs like ASA offer the promise of innovative, cost-effective paths to poverty reduction and social change.ASA is not the only microlender flourishing in rural Bangladesh. ASA’s leadership could learn from the experiences of Grameen Bank and from BRAC (formerly the Bangladesh Rural Advancement Com-mittee). When we looked at the fi gures at the end of 2003, Grameen claimed 3.1 million members, BRAC claimed 3.9 million, and ASA claimed 2.3 million, nearly all of whom had been written off by com-mercial banks as being “unbankable.” Just four years later, at the end of 2007, the 3 biggest microlenders in Bangladesh claimed over 20 million customers: Grameen counted 7.4 million members, BRAC counted another 7.4 million, and ASA counted 5.4 million.3 Even accounting for the fact that people may belong to more than one micro-lending program at a time, both the absolute and relative fi gures show the potential for rapid growth and scale.The institutions anchor a movement that is global and growing. Microfinance programs have created new opportunities in contexts as diverse as villages along the Amazon, inner-city Los Angeles, the Paris outskirts, and war-ravaged Bosnia. Programs are well-established in Bolivia, Bangladesh, and Indonesia, and momentum is gaining in Mexico and India. Table 1.1 shows the results of a survey conducted by the Microcredit Summit Campaign. By the end of 2007, the campaign had reports of 154.8 million microfinance clients served worldwide by over 3,350 microfinance institutions. Of these clients, 106.6 million were reported as being in the bottom half of those living below their nation’s poverty line or were living in households earning under $1 per day per person (defined as “the poorest”; Daley-Harris 2009). Between 1997 and 2007, the numbers grew on average by about 30 percent per year, and the movement’s leaders expect continued expansion as credit unions, commercial banks, and others enter the market.Microfinance presents a series of exciting possibilities for extending markets, reducing poverty, and fostering social change. But it also presents a series of puzzles, many of which have not yet been widely discussed. One aim of this book is to describe the innovations that have created the movement. Another aim is to address and clarify the puzzles, debates, and assumptions that guide discussions but that are too often overlooked. Debates include whether the poorest are best4 Chapter 1served by loans or by better ways to save, whether subsidies are a help or a hindrance, whether providing credit without training and other complements is enough, and which aspects of lending mechanisms have driven successful performances. Many of the insights from the microfinance experience can be seen fruitfully through the lens of recent innovations in economics (especially the economics of informa-tion, contract theory, and behavioral economics). Other microfinance insights point to areas where new research is needed, especially around possibilities and constraints for saving by the poor and for estimating social impacts.Another aim of the book is to tackle the myths that have made their way into conversations on microfinance. The first myth is that microfinance is essentially about providing loans. In chapter 6 we show that providing better ways for low-income households to save and insure can be as important. But we take issue with the argument that, for the poorest, saving is more important. The second myth is that the secret to the high repayment rates on loans is tied closely to the use of the group lending contracts made famous by Bangladesh’s Grameen Bank and Bolivia’s BancoSol. (Grameen’s original approach is described in section 1.4 and in chapter 4.) Group lending has indeed been a critical innovation, but we note emerging tensions,Table 1.1Growth of microfi nance coverage as reported to the Microcredit Summit Campaign, 1997–2007End of year Total number ofinstitutionsTotal number of clients reached (millions)Number of “poorest” clients reported (millions)1997 65516.59.01998 70518.710.71999 96421.813.020001,47738.221.620012,03357.329.520022,33467.841.620032,57781.355.020042,81499.772.720053,056135.296.220063,244138.796.220073,352154.8106.6Source : Daley-Harris 2009.Rethinking Banking 5and in chapter 5 we describe a series of innovations in contracts and banking practices that go beyond group lending. We believe that the future of microfinance lies with these less-heralded innovations—including the focus on female customers (discussed in greater detail in chapter 7) and the improved management practices described in chapter 11.The third myth is that microfinance has a clear record of social impacts and has been shown to be a major tool for poverty reduction and gender empowerment. We believe that microfinance can make a real difference in the lives of those served (otherwise we would not have written this book), but microfinance is neither a panacea nor a magic bullet, and it cannot be expected to work everywhere or for everyone. Relatively few rigorous studies of impacts have been com-pleted, and the evidence on statistical impacts has been mixed so far. There is not yet a widely acclaimed study that robustly shows strong impacts, but many studies suggest the possibility. Better impact studies can help resolve debates, and we review recent results using random-ized control trials. Chapter 9 describes approaches and challenges to be confronted in pushing ahead.The final myth is that most microlenders today are both serving the poor and making profits. We show in chapters 8 and 10 that profitability has been elusive for many institutions, and we describe why good banking practices matter—and how subsidies can be deployed strategi-cally to move microfinance forward.Unlike most discussions of microfinance oriented toward practitio-ners, we do not begin by describing new microfinance institutions.4 We will have much to say about recent innovations later, but our approach begins instead with the nature of poverty and the markets and institutions that currently serve poor households. By beginning with households, communities, and markets, we develop analytical tools and insights that can then be used to think about the new institu-tions, as well as to think about directions that go beyond current approaches.1.2 Why Doesn’t Capital Naturally Flow to the Poor?From the viewpoint of basic economics, the need for microfinance is somewhat surprising. One of the first lessons in introductory econom-ics is the principle of diminishing marginal returns to capital, which says that enterprises with relatively little capital should be able to earn6 Chapter 1higher returns to their investments than enterprises with a great deal of capital. Poorer enterprises should thus be able to pay banks higher interest rates than richer enterprises. Money should flow from rich depositors to poor entrepreneurs.The “diminishing returns principle” is derived from the assumed concavity of production functions, as illustrated in figure 1.1. Concav-ity is a product of the plausible assumption that when an enterprise invests more (i.e., uses more capital), it should expect to produce more output, but each additional unit of capital will bring smaller and smaller incremental (“marginal”) gains. When a tailor buys his first $100 sewing machine, production can rise quickly relative to the output when using only a needle and thread. The next $100 investment, say for a set of electric scissors, will also bring gains, but the incremental increase is not likely to be as great as that generated by the sewing machine. After all, if buying the scissors added more to output than the sewing machine, the wise tailor would have bought the scissors first. The size of the incremental gains matter since the marginal return to capital determines the borrowers’ ability to pay.5 As figure 1.1 shows, concav-ity implies that the poor entrepreneur has a higher marginal return to capital (and thus a higher ability to repay lenders) than a richerentrepreneur.O u t p u t CapitalFigure 1.1Marginal returns to capital with a concave production function. The poorer entrepreneur has a greater return on his next unit of capital and is willing to pay higher interest rates than the richer entrepreneur.Rethinking Banking 7On a larger scale, if this basic tool of introductory economics is correct, global investors have got it all wrong. Instead of investing more money in New York, London, and Tokyo, wise investors should direct their funds toward India, Kenya, Bolivia, and other low-income countries where capital is relatively scarce. Money should move from North to South, not out of altruism but in pursuit of profit. The Nobel-winning economist Robert Lucas Jr. has measured the extent of the expected difference in returns across countries (assuming that marginal returns to capital depend just on the amount of capital relative to other productive inputs). Based on his estimates of marginal returns to capital, Lucas (1990) finds that borrowers in India should be willing to pay fifty-eight times as much for capital as borrowers in the United States. Money should thus flow from New York to New Delhi.6The logic can be pushed even further. Not only should funds move from the United States to India, but also, by the same argument, capital should naturally flow from rich to poor borrowers within any given country. Money should flow from Wall Street to Harlem and to the poor mountain communities of Appalachia, from New Delhi to villages throughout India. The principle of diminishing marginal returns says that a simple cobbler working on the streets or a woman selling flowers in a market stall should be able to offer investors higher returns than General Motors or IBM or the Tata Group can—and banks and inves-tors should respond accordingly.Lucas’s ultimate aim is to point to a puzzle: given that investors are basically prudent and self-interested, how has introductory economics got it wrong? Why are investments in fact far more likely to flow from poor to rich countries, and not in the other direction? Why do large corporations have a far easier time obtaining financing from banks than self-employed cobblers and flower sellers?The first place to start in sorting out the puzzle is with risk. Investing in Kenya, India, or Bolivia is for many a far riskier prospect than invest-ing in U.S. or European equities, especially for global investors without the time and resources to keep up-to-date on shifting local conditions. The same is true of lending to cobblers and flower sellers versus lending to large, regulated corporations. But why can’t cobblers and flower sellers in the hinterlands offer such high returns to investors that their risk is well compensated for?One school argues that poor borrowers can pay high interest rates in principle but that government-imposed interest rate restrictions prevent banks from charging the interest rates required to draw capital8 Chapter1from North to South and from cities to villages.7 If this is so, the chal-lenge for microfinance is wholly political. Advocates should just con-vince governments to remove usury laws and other restrictions onbanks, then sit back and watch the banks flood into poor regions. Thatis easier said than done of course, especially since usury laws (i.e., lawsthat put upper limits on the interest rates that lenders can charge) havelong histories and strong constituencies.Reality is both more complicated and more interesting. Even if usurylaws could be removed, providing banks with added freedom to servethe poor and cover costs is not the only answer. Indeed, as we showin chapter 2, raising interest rates can undermine institutions by weak-ening incentives for borrowers. Once (lack of) information is broughtinto the picture (together with the lack of collateral), we can more fullyexplain why lenders have such a hard time serving the poor, evenhouseholds with seemingly high returns. The important factors are thebank’s incomplete information about poor borrowers and the poorborrowers’ lack of collateral to offer as security to banks.The first problem—adverse selection—occurs when banks cannoteasily determine which customers are likely to be more risky thanothers. Banks would like to charge riskier customers more than safercustomers in order to compensate for the added probability of default.But the bank does not know who is who, and raising average interestrates for everyone often drives safer customers out of the credit market.The second problem, moral hazard, arises because banks are unable toensure that customers are making the full effort required for theirinvestment projects to be successful. Moral hazard also arises whencustomers try to abscond with the bank’s money. Both problems aremade worse by the difficulty of enforcing contracts in regions withweak judicial systems.These problems could potentially be eliminated if banks had cheapways to gather and evaluate information on their clients and to enforcecontracts. But banks typically face relatively high transactions costswhen working in poor communities since handling many small trans-actions is far more expensive than servicing one large transaction fora richer borrower. Another potential solution would be available ifborrowers had marketable assets to offer as collateral. If that were so,banks could lend without risk, knowing that problem loans werecovered by assets. But the starting point for microfinance is that newways of delivering loans are needed precisely because borrowers aretoo poor to have much in the way of marketable assets. In this sense,1.3 Good Intentions Gone Awry: The Failures of State-Owned Development BanksThe lack of banks does not mean that poor individuals are unable to borrow. They do—but from informal sources such as moneylenders, neighbors, relatives, and local traders. Such lenders often have the rich information (and effective means of enforcing contracts) that banks lack. Their resources, however, are limited. Microfinance presents itself as the latest solution to the age-old challenge of finding a way to combine the banks’ resources with the local informational and cost advantages of neighbors and moneylenders. Like traditional banks, microfinance institutions can bring in resources from outside the com-munity. Microfinance is not the first attempt to do this, but it is by far the most successful.The success of microfinance depends in part on studiously avoiding the mistakes of the past. As low-income countries attempted to develop their agricultural sectors after World War II, rural finance emerged as a large concern then too. Large state agricultural banks were given the responsibility for allocating funds, with the hope that providing sub-sidized credit would induce farmers to irrigate, apply fertilizers, and adopt new crop varieties and technologies (e.g., Reserve Bank of India 1954). The hope was to increase land productivity, increase labor demand, and thereby to increase agricultural wages.Heavy subsidies were also deployed to compensate the banks for entering into markets where they feared taking huge losses due to high transactions costs and inherent risks. The subsidies were also used to keep interest rates low for poor borrowers. In the Philippines, for example, interest rates charged to borrowers were capped at 16 percent before a reform in 1981, while inflation rates were around 20 percent annually (David 1984). The negative real interest rates created excess demand for loans, adding pressure to allocate loans to politically favored residents, rather than to target groups. Meanwhile, the interest rates offered to rural depositors were only about 6 percent per year, so inflation eroded the purchasing power of savings at a rate of about 14 percent per year. Not surprisingly, such policies turnedout disastrously. David (1984, 222) concludes that in the PhilippinesIndia’s Integrated Rural Development Program (IRDP) is, to many, a too perfect example of inefficient subsidized credit. The program allocated credit according to “social targets” that in principle pushed 30 percent of loans toward socially excluded groups (as signified by being a member of a “scheduled” tribe or caste) and 30 percent toward women. Achieving social goals became as important as achieving efficiency. Under the system, capital was allocated according to a series of nested planning exercises, with village plans aggregating to block plans aggregating to district plans aggregating to state plans. Subsidies between 1979 and 1989, a period of rapid IRDP growth, amounted to $6 billion (roughly 25 percent to 50 percent of loan volume made to weak sectors). Those resources did not generate good institutional performance. According to Pulley (1989), IRDP repayment rates fell below 60 percent, and just 11 percent of borrowers took out a second loan after the first (which is particularly striking given the importance accorded to repeat lending by microfinance practitioners). In 2000, the IRDP loan recovery rate fell to just 31 percent (Meyer 2002).10 As insti-tutional performance dramatically weakened, the IRDP failed to be a reliable and meaningful source of services for the poor.In the late 1970s and early 1980s, the Rural Finance Program at Ohio State University launched a devastating critique of government-led development banks like the IRDP and the Philippine programs.11 Its starting point was that credit is not like fertilizer or seeds. Instead, Ohio School critics argued, credit should be thought of as a fungible tool of financial intermediation (with many uses) and not as a specific input into particular production processes. Thus one problem, according to such criticisms, came from mistakenly believing that credit could be “directed” to particular ends favored by policymakers (e.g., expanding the use of high-yielding crop varieties). And that, coupled with cheap credit policies, created havoc in rural financial markets and ultimately undermined attempts to reduce poverty (Adams, Graham, and von Pischke 1984). The story hinges on a failure to adequately account forthe incentive effects and politics associated with subsidies. SubsidizingThus, critics of the subsidized state banks argue that poor house-holds would often have been better off without the subsidies. This is in part because, first, subsidized banks pushed out informal credit sup-pliers on which the poor rely. Second, the market rate of interest is a rationing mechanism—those who are willing to pay for credit are only those with projects that are most worthy. But with subsidies driving interest rates well below market rates of interest, the rationing mecha-nism broke down. Credit was no longer allocated to the most produc-tive recipients, but instead was often allocated on the basis of politics or social concerns. Good projects thus went unfunded. Third, bankers’ incentives to collect savings deposits were diminished by the steady flow of capital from the government, so poor households were left with relatively unattractive and inefficient ways to save. Fourth, the fact that the banks were state banks led to pressure to forgive loans just before elections, to privilege the powerful with access to cheap funds meant for the poor, and to remove incentives for management to build tight, efficient institutions. Braverman and Guasch (1986) conclude that gov-ernment credit programs in Africa, the Middle East, Latin America, South Asia, and Southeast Asia have, with a few exceptions, ended up with default rates between 40 percent and 95 percent. And at such rates, borrowers can be excused for seeing the credit programs as pro-viding grants rather than loans. The misallocation of resources hap-pened so regularly that González-Vega (1984) dubs it the “iron law of interest rate restrictions.”Critics hold that these kinds of subsidies undermined the poor, although the evidence from India at least provides a more nuanced picture. Empirical work by Burgess and Pande (2005), for example, shows net positive average impacts on the poor in India.12 Similarly, Binswanger and Khandker (1995) find that between 1972–1973 and 1980–1981 the state banks in India increased nonfarm growth, employ-ment, and rural wages. Still, the Indian programs have been clearly inefficient, and a great deal of money that was originally targeted to the poor ended up being wasted or going into the “wrong” hands. As a result, Binswanger and Khandker find only modest impacts on agri-cultural output and none on agricultural employment, and they con-clude that the costs of the government programs were so high that they nearly swamped the economic benefits. More than any positive histori-cal precedent, it is the repudiation of these negative legacies that has1.4 Grameen Bank and the Beginnings of MicrofinanceThe roots of microfinance can be found in many places, but the best-known story is that of Muhammad Yunus and the founding of Bangladesh’s Grameen Bank. We briefly tell the story now and return to Grameen’s experience in later chapters.13In the middle of the 1970s, Bangladesh was starting down the long road to build a new nation. The challenges were great: independence from Pakistan had been won in December 1971 after a fierce war, and two years later widespread flooding brought on a famine that killed tens of thousands (Sen 1981). Government surveys found over 80 percent of the population living in poverty in 1973–1974 (Bangladesh Bureau of Statistics 1992).Muhammad Yunus, an economist trained at Vanderbilt University, was teaching at Chittagong University in southeast Bangladesh. The famine, though, brought him disillusionment with his career as an economics professor. In 1976, Yunus started a series of experiments lending to poor households in the nearby village of Jobra. Even the little money he could lend from his own pocket was enough for villag-ers to run simple business activities like rice husking and bamboo weaving. Yunus found that borrowers were not only profiting greatly by access to the loans but that they were also repaying reliably, even though the villagers could offer no collateral. Realizing that he could only go so far with his own resources, in 1976 Yunus convinced the Bangladesh Bank (the central bank of Bangladesh) to help him set up a special branch that catered to the poor of Jobra. That soon spawned another trial project, this time in Tangail in North-Central Bangladesh. Assured that the successes were not region-specific flukes, Grameen went nation-wide. One innovation that allowed Grameen to grow explosively was group lending, a mechanism that essentially allows the poor borrowers to act as guarantors for each other. With group lending in place, the bank could quickly grow village by village as funding permitted. And funding—supplied in the early years by the International Fund for Agriculture and Development, the Ford Foun-dation, and the governments of Bangladesh, Sweden, Norway, and the Netherlands—permitted rapid growth indeed. As figure 1.2 shows, thebank grew by 40 percent per year at its peak. By 1991 the Grameen。
CH19THE ECONOMICS OF INFORMATION(微观经济学( 南开大学 Lee Junqing))PPT课件
Lee, Junqing
3
Department of Economics , Nankai University
Properties of Information
4
Properties of Information
Information is not easy to define
it is difficult to measure the quantity of information obtainable from different actions
We need to set up the Lagrangian
L = gU(Wg) + bU(Wb) + (I-pgWg-pbWb-pmm)
Lee, Junqing
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Department of Economics , Nankai University
The Value of Information
The Value of Information
Assume that information can be measured by the number of “messages” (m) purchased
g and b will be functions of m
Lee, Junqing
Chapter 19
THE ECONOMICS OF INFORMATION
1
整体 概述
入您的主要叙述内容
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三 请在这里输入您的主要叙述内容
2
Department of Economics , Nankai University
CONTENTS
information science的latex模板 -回复
information science的latex模板-回复如何使用信息科学的LaTeX模板？LaTeX是一种非常强大的排版系统，用于创建精美的文档。
对于信息科学专业的学生和研究人员来说，使用LaTeX来撰写论文、报告和其他学术文档是非常常见的。
为了帮助您更好地使用LaTeX来创建信息科学相关的文档，本文将逐步介绍如何使用信息科学的LaTeX模板。
第一步：选择合适的模板在使用LaTeX之前，您需要选择一个适合您需求的模板。
有许多不同种类的LaTeX模板可供选择，其中包括特定领域的模板。
对于信息科学领域，您可以搜索并找到一些相关的LaTeX模板。
一种常见的方式是在学术网站和论坛上查找，或者在LaTeX模板的集合网站上浏览。
第二步：安装LaTeX发行版和编辑器要使用LaTeX，您需要安装一个LaTeX发行版和一个编辑器。
LaTeX发行版是LaTeX的核心程序，而编辑器则用于编写和编辑LaTeX代码。
一些常见的LaTeX发行版包括TeX Live和MiKTeX，而编辑器可以使用TeXstudio、TeXMaker等。
在安装好这些软件后，您就准备好使用LaTeX来创建您的信息科学文档了。
第三步：下载并导入模板在选择了合适的信息科学LaTeX模板后，您可以从模板的官方网站或其他资源中下载该模板的zip文件。
下载完成后，您需要解压缩该文件，并确保将模板的文件放在一个易于访问和组织的位置。
接下来，您需要在LaTeX编辑器中导入该模板。
具体导入方式可能因编辑器而异，但通常可以在编辑器的菜单中找到“导入模板”或“导入文件”的选项。
通过导入模板文件，您可以在编辑器中使用模板提供的样式和格式。
第四步：编辑和调整模板通过导入模板后，您可以开始编辑和调整模板，以满足您的具体需求。
为了创建一个信息科学的论文，您需要指定标题、作者、摘要、关键字等基本信息。
可以通过替换模板中的示例内容或使用LaTeX代码来实现。
在编辑过程中，您可能还需要根据您的具体要求进行一些调整。
德国信用数据集的描述
德国信用数据集的描述。
1.标题：德国信用数据2.源信息汉斯霍夫曼教授统计研究所和“经济汉堡系计量经济学大学”冯·梅勒园52000汉堡133.实例数：1000提供了两个数据集。
原始数据集，由霍夫曼教授以提供的形式，包含分类/符号属性和是在文件“german.data”。
对于需要数值属性的算法，斯特拉斯克莱德大学产生文件“german.data-numeric”。
此文件已编辑并添加了几个指示符变量以使其适合不能处理分类变量的算法。
一些排序分类（例如属性17）的属性被编码为整数。
这是StatLog使用的形式。
6.german文件包括20个变量: 20 (7 numerical, 13 categorical)german.numer文件包括24个变量: 24 (24 numerical)7.德国人的属性描述属性1：（定性）现有支票帐户的状态A11：... <0 DMA12：0 <= ... <200DMA13：...> = 200 DM/工资分配至少1年A14：不检查帐户属性2：（数值）月份持续时间A2属性3：（定性）信用记录A30：没有学分/所有积分支付回来A31：所有在这家银行的信用卡已收回A32：到现在支付的现有贷项A33：延迟过去的回报A34：关键帐户/存在的其他信用（不在此银行）属性4：（定性）目的A40：汽车（新）A41：汽车（使用）A42：家具/设备A43：广播/电视A44：家用电器A45：修理A46：教育A47：（vacation - 不存在？）A48：再培训A49：业务A410：其他属性5：（数值）信用额A5Attibute 6：（定性）储蓄账户/债券A61：... <100 DMA62：100 <= ... <500DMA63：500 <= ... <1000DMA64：..> = 1000 DMA65：未知/不存储储蓄帐户属性7：（定性）目前就业A71：失业A72： (1)A73：1 <= (4)A74：4 <= (7)A75：..> = = 7年属性8：（数值）分期付款率按可支配收入的百分比计算A8属性9：（定性）个人地位和性别A91：男：离婚/分居A92：女性：离婚/分居/已婚A93：男：单身A94：男性：已婚/丧偶A95：女：单身属性10：（定性）其他债务人/担保人A101：无A102：共同申请人A103：担保人属性11：（数值）现在居住地A11属性12：（定性）属性A121：房地产A122：如果不是A121：建筑社会储蓄协议/人寿保险A123：如果不是A121 / A122：汽车或其他，不属于属性6 A124：未知/无属性属性13：（数值）年龄A13属性14：（定性）其他分期付款计划A141：银行A142：商店A143：无属性15：（定性）住房A151：租金A152：自己A153：免费属性16：（数值）此银行现有的信用额A16属性17：（定性）工作A171：失业/非技术 - 非居民A172：不熟练A173：熟练的员工/官员A174：管理/个体经营/高度合格的员工/官员属性18：（数值）负责提供维修的人数A18属性19：（定性）电话A191：无A192：是，以客户名称注册属性20：（定性）外国工人A201：是的A202：不8.成本矩阵此数据集所需要使用成本矩阵（参见下文）1 2----------------------------1 0 1-----------------------2 5 0（1 =好，2 =差）其中，行表示实际分类和列表示预测分类。
经济数据建模与分析-大纲
福建省晋江市平山中学2017-2018 学年高二下学期期末考试文综试题一、选择题：本题共35小题，每小题4分，共140分。
在每小题给出第四个选项中，只有一项是符合题目要求的。
读图，回答1-2小题。
1．若甲、丙两点间的图上距离为2.2cm，则该图的比例尺约为（）A. 1∶1000B. 1∶10000万C. 1∶500万D. 1∶5000万2．图中四地（）A. 乙、丁两地地方时相同B. 甲、丙两地昼夜长短相同C. 乙、丁两地正午太阳高度相同D. 甲、丙两地日出、日落时间相同净光合作用量=光合作用量-呼吸作用量。
下图是某地绿色植物的光合作用量、呼吸作用量与气温关系统计曲线。
完成3-4 题。
3．绿色植物净光合作用量会受太阳辐射、气温、降水量、土壤养分等因素的影响，这反映出自然地理环境具有A．整体性B．差异性C．可塑性D．临界性4．气温25℃以上，该地绿色植物光合作用量不再随气温升高而增加，其主要制约因素最有可能是A．光照B．水分C．热量D．C02图为“南美洲自然带分布示意图”。
读图回答5-6题。
5.图中各数字对应的自然带名称，正确的是A．②热带草原带B．③温带落叶阔叶林带 C．④亚热带常绿硬叶林带D．⑥热带荒漠带6.影响⑥自然带出现南、北狭长分布的主要原因是 A．受南美洲西部山脉阻挡，呈南、北狭长分布 B．受海陆分布的影响，向南伸展到30°S附近C．受所跨纬度影响，向西直通海岸 D．受西风带的影响，向北延伸范围更广2016年9月2日0时37分，在新西兰北岛附近海域发生6.9级地震，震源深度30千米。
读图“震中位置示意图”。
据此完成7-8题。
7．新西兰多地震的原因主要是A. 印度洋板块与太平洋板块挤压碰撞B. 亚欧板块与印度洋板块挤压碰撞C. 印度洋板块与南极洲板块挤压碰撞D. 南极洲板块与太平洋板块挤压碰撞8．社会经济基础雄厚、政治稳定的地区，能够“缩小”灾情，主要是因为①有能力建设健全的防灾系统②灾害发生时能迅速救援③能够把自然灾害消灭在萌芽状态④能得到国际社会的援助A．①②B．③④C．①③D．②④水进型三角洲是三角洲体系中的一个重要类型,是指当水盆(湖和海)水面不断上升，河流所携沉积物在河湖(海)交汇地带沉积下来,并逐渐往陆地方向退积,在其有效沉积率小于水面上升速度的条件下,在原三角洲沿岸平原之上所形成的一套水下沉积的、粒度规律的沉积体。
一些重要经济学网站和数据库网站[1]
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lesson 13
Unit 3 Employment Correspondence
Lesson 13 Resumes
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• Section 1 Getting Started • Section 2 Sample Study • Section 3 Composing Your Message • Section 4 Writing Your Message • Section 5 Resume Practice • Section 6 Supplementary Materials
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Sample Study
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Liu Xiaoming Huang He Nan Da Jie #532 Shenyang, Liaoning Province 110023 China (86)(024) 8903-8956 xmliu@ Objective: To obtain a position in the human resources department of a major international firm. Experience: Internal Communications Associate, General Motors, Shenyang (July 2005-present) -Research and write articles relevant to employee issues for monthly newsletter -Develop and present cross-cultural workshops
电子书：基于Excel和VBA的高级金融建模
第 3 章 VBA介绍 ..................................................................... 38
3.1 掌握VBA的好处 ............................................................................................................. 38 3.2 VBA的面向对象观点 ...................................................................................................... 39 3.3 编写VBA宏 ..................................................................................................................... 40 3.3.1 简单VBA子程序 .................................................................................................. 40 3.3.2 交互函数MsgBox ................................................................................................. 41 3.3.3 编写环境............................................................................................................... 42 3.3.4 输入代码并运行宏 ............................................................................................... 43 3.3.5 录制按键和编辑代码 ........................................................................................... 43 3.4 编程要素.......................................................................................................................... 45 3.4.1 变量和数据类型 ................................................................................................... 45 3.4.2 VBA数组变量 ....................................................................................................... 46 3.4.3 控制结构............................................................................................................... 48 3.4.4 控制重复过程 ....................................................................................................... 48 3.4.5 在代码中使用Excel和VBA函数 ......................................................................... 50 3.4.6 编程的一般观点 ................................................................................................... 50 3.5 宏与电子表格之间的通信 .............................................................................................. 50 3.6 子程序实例...................................................................................................................... 53 3.6.1 图表....................................................................................................................... 54 3.6.2 正态概率散点图 ................................................................................................... 56 3.6.3 用规划求解产生有效边界 ................................................................................... 58 小结......................................................................................................................................... 61 附录 3A Visual Basic编辑器 .................................................................................................. 62 附录 3B 用‘相对引用’模式来录制按键 ......................................................................... 65
information sciences tex模板格式
information sciences tex模板格式Information Sciences:The Power of Data and KnowledgeAbstract:Information Sciences is an interdisciplinary field that combines computer science, statistics, and other related disciplines to analyze, manage, and utilize data and knowledge. This article discusses the importance of Information Sciences in various domains, including healthcare, finance, and social media, and provides a comprehensive overview of the key concepts, methodologies, and applications in this field. It also explores the challenges and future directions of Information Sciences, highlighting the growing need for skilled professionals in this area.Keywords: Information Sciences, data analysis, knowledge management, interdisciplinary, applications1. Introduction:Information Sciences is a rapidly growing discipline that focuses on the creation, analysis, and management of data and knowledge. In today's world, data is being generated at an unprecedented rate, and organizations are increasingly realizing the potential value of harnessing this data to gain insights, make informed decisions, and drive innovation.2. Key Concepts:2.1 Data Mining:Data mining is a key concept in Information Sciences, which involves the extraction of useful patterns, knowledge, and insightsfrom large datasets. This process often utilizes techniques from machine learning, statistics, and database systems to discover hidden relationships and trends within the data.2.2 Artificial Intelligence and Machine Learning:Artificial Intelligence (AI) and Machine Learning (ML) are closely related fields that play a significant role in Information Sciences. AI focuses on creating intelligent machines that can simulate human cognitive abilities, while ML algorithms allow computers to learn from data and improve their performance over time.2.3 Knowledge Management:Knowledge Management is the process of capturing, organizing, and utilizing the collective knowledge and expertise within an organization. Information Sciences provide techniques such as semantic web, natural language processing, and knowledge discovery to enable effective knowledge management.3. Methodologies in Information Sciences:3.1 Data Collection and Preprocessing:Data collection involves gathering relevant data from various sources, such as surveys, sensors, and social media platforms. Preprocessing techniques, such as data cleaning, normalization, and feature extraction, are then applied to ensure the data is suitable for analysis.3.2 Data Analysis and Modeling:Data analysis involves applying statistical and computational techniques to identify patterns, trends, and relationships within the data. Modeling techniques, such as regression, clustering, andclassification, are used to build predictive models and make informed decisions based on the analyzed data.3.3 Data Visualization:Data visualization techniques are employed to present complex data in a visual and understandable format. Various visualization tools and techniques, such as charts, graphs, and interactive dashboards, aid in the interpretation and communication of the analyzed data.4. Applications of Information Sciences:4.1 Healthcare:Information Sciences play a crucial role in healthcare, enabling the analysis of patient data to improve diagnosis, treatment, and overall patient care. Techniques like predictive modeling and data mining help identify risk factors, optimize treatment plans, and predict disease outbreaks.4.2 Finance:In the finance industry, Information Sciences are utilized for stock market prediction, fraud detection, and portfolio optimization. Advanced algorithms, coupled with vast amounts of financial data, enable accurate predictions and efficient decision-making.4.3 Social Media and Web Analytics:Social media platforms generate enormous amounts of data, which can be analyzed using Information Sciences techniques to understand user behavior, sentiment analysis, and optimize marketing strategies. Web analytics involve tracking website usage patterns, user engagement, and conversion rates to improvewebsite performance.5. Challenges and Future Directions:Despite its promising potential and applications, Information Sciences face several challenges, including data privacy and security concerns, ethical considerations, and the need for skilled professionals. Addressing these challenges will require interdisciplinary collaborations, development of advanced algorithms, and the establishment of ethical guidelines.6. Conclusion:Information Sciences have revolutionized the way we analyze, manage, and utilize data and knowledge. This interdisciplinary field has transformed various domains, including healthcare, finance, and social media, by providing valuable insights, predictions, and strategies. As we move towards a data-driven era, the importance of Information Sciences and the demand for skilled professionals in this field are only expected to grow. References:[Provide a list of relevant references/sources used in the article.] Note: This template provides a general structure for an Information Sciences article; however, specific sections, subsections, and the content may vary depending on the requirements of the target publication.。
经济学英语作文模板
核电厂应急柴油机启动失败故障分析与处理黄健彬摘要：应急柴油机是核电厂应急电源系统的动力，当全厂断电的超设计基准事故状态下，柴油机启动为设备供电，其可靠性直接影响核电机组安全稳定运行。
针对某核电厂试验过程出现的启动失败故障，结合柴油机启动回路组成及工作原理，对可能原因进行分析排查，确定了柴油机启动失败根本原因，完成缺陷处理，确保了柴油机安全稳定运行。
关键词：应急柴油机；启动失败1 概述应急柴油机[1]为核电厂独立电源系统的动力，一旦核电厂发生事故时，柴油机启动为安全设备供电。
四台核电机组有9台应急柴油机，均采用德国MTU公司生产的20V956TB33机型，为直喷式四冲程柴油机，共有20个气缸，呈60°V型分布，采用水冷方式冷却，两级涡轮增压，额定转速1500rpm，额定功率6000kW。
2 故障描述该应急柴油机执行低功率试验过程中，柴油机启动信号下达，但柴油机未启动，现场发出嗡嗡嗡声音，柴油机未转动，启动失败。
现场针对该缺陷对可能原因进行排查，最终查明原因为进气母管止回阀锈蚀卡涩，更换新止回阀后，柴油机启动成功。
3 柴油机进气系统介绍柴油机启动压缩空气进气分为三路，两路进气缸，一路进空气分配器。
空气分配器由凸轮轴驱动，它按发火顺序将压缩空气送至各启动阀，启动阀又控制气缸的进气燃烧，然后气缸活塞依次做功驱动柴油机转动。
压缩空气进气流程如图1所示，红色为两路压缩空气经主启动阀（250/251EL，启动信号触发电磁先导阀250/251VA使压缩空气释放打开主启动阀）汇集进入空气分配器及气缸，紫色回路为红色回路分支汇集进入气缸燃烧。
图1 柴油机启动进气简图4故障原因分析与排查针对现场现象，针对启动回路，从曲轴卡涩、废气涡轮增压器空气进气蝶阀未开启、空气限流阀卡涩未开启、启动空气分配器压缩空气分配顺序错乱、两列主启动阀（250/251EL）均未打开、进气母管止回阀卡涩等原因进行分析排查。
（1）柴油机曲轴卡涩，无法转动。
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The Economics of Information, 2012, 12, 29 Name:Code:21001-02Paper Title(Affiliation): department name of organization, name of organization, City, CountryE-mail address desiredABSTRACTThis electronic document is a “live” template. The various components of your paper [title, text, heads, etc.]are already defined on the style sheet, as illustrated by the portions given in this document. (Abstract)Keywords: Omponent, Formatting, Style, Styling, insert (keywords)1. Introduction (Heading 1)This template, created in MS Word 2000 and saved as “Word 97-2000 & 6.0/95 –RTF” for the PC, provides authors with most of the formatting specifications needed for preparing electronic versions of their papers. All standard paper components have been specified for three reasons: 1) ease of use when formatting individual papers, 2) automatic compliance to electronic requirements that facilitate the concurrent or later production of electronic products, and 3) conformity of style throughout a conference proceedings. Margins, column widths, line spacing, and type styles are built-in; examples of the type styles are provided throughout this document and are identified in italic type, within parentheses, following the example. Some components, such as multi-leveled equations, graphics, and tables are not prescribed, although the various table text styles are provided. The formatter will need to create these components, incorporating the applicable criteria that follow.2. Ease of Use (Heading 2)First, confirm that you have the correct template for your paper size. This template has been tailored for output on the custom paper size (21 cm * 28.5 cm). If you are using US letter-sized paper, please close this file and download the file for “MSW US ltr format”.2.2. Maintaining the Integrity of the Specifications The template is used to format your paper and style the text. All margins, column widths, line spaces, and text fonts are prescribed; please do not alter them. You may note peculiarities. For example, the head margin in this template measures proportionately more than is customary. This measurement and others are deliberate, using specifications that anticipate your paper as one part of the entire proceedings, and not as an independent document. Please do not revise any of the current designations.3. Prepare Your Paper before StylingBefore you begin to format your paper, first write and save the content as a separate text file. Keep your text and graphic files separate until after the text has been formatted and styled. Do not use hard tabs, and limit use of hard returns to only one return at the end of a paragraph. Do not add any kind of pagination anywhere in the paper. Do not number text heads-the template will do that for you.Finally, complete content and organizational editing before formatting. Please take note of the following items when proofreading spelling and grammar:3.1. Abbreviations and AcronymsDefine abbreviations and acronyms the first time they are used in the text, even after they have been defined in the abstract. Abbreviations such as IEEE, SI, MKS, CGS, sc, dc, and rms do not have to be defined. Do not use abbreviations in the title or heads unless they are unavoidable.3.2. Units●Use either SI (MKS) or CGS as primary units. (SIunits are encouraged.) English units may be used as secondary units (in parentheses). An exception would be the use of English units as identifiers in trade, such as “3.5-inch disk drive”.●Avoid combining SI and CGS units, such as currentin amperes and magnetic field in oersteds. This2.1. Selecting a TemplatePaper Titleoften leads to confusion because equations do not balance dimensionally. If you must use mixed units, clearly state the units for each quantity that you use in an equation.●Do not mix complete spellings and abbreviations ofunits: “Wb/m2” or “webers per square meter”, not “w ebers/m2”. Spell out units when they appear in text: “. . . a few henries”, not “. . . a few H”.●Use a zero before decimal points: “0.25”, not “.25”.Use “cm3”, not “cc”. (bullet list)3.3. EquationsThe equations are an exception to the prescribed specifications of this template. You will need to determine whether or not your equation should be typed using either the Times New Roman or the Symbol font (please no other font). To create multileveled equations, it may be necessary to treat the equation as a graphic and insert it into the text after your paper is styled.Number equations consecutively. Equation numbers, within parentheses, are to position flush right, as in (1), using a right tab stop. To make your equations more compact, you may use the solidus ( / ), the exp function, or appropriate exponents. Italicize Roman symbols for quantities and variables, but not Greek symbols. Use a long dash rather than a hyphen for a minus sign. Punctuate equations with commas or periods when they are part of a sentence, as inx=+βα(1) Note that the equation is centered using a center tab stop. Be sure that the symbols in your equation have been defined before or immediately following the equation. Use “(1)”, not “Eq. (1)” or “equation (1)”, except at the beginning of a sentence: “Equation (1) is . . .”3.4. Some Common Mistakes●The word “data” is plural, not singular.●The subscript for the permeability of vacuum 0, andother common scientific constants, is zero with subscript forma tting, not a lowercase letter “o”.●In American English, commas, semi-/colons,periods, question and exclamation marks are located within quotation marks only when a complete thought or name is cited, such as a title or full quotation. When quotation marks are used, instead of a bold or italic typeface, to highlight a word or phrase, punctuation should appear outside of the quotation marks. A parenthetical phrase or statement at the end of a sentence is punctuated outside of the closing parenthesis (like this). (A parenthetical sentence is punctuated within the parentheses.) ● A graph within a graph is an “inset”, not an “insert”.The word alternatively is preferred to the word “alternately” (unless you really mean something that alternates).●Do not use the wor d “essentially” to mean“approximately” or “effectively”.●In your paper title, if the words “that uses” canaccurately replace the word “using”, capitalize the “u”; if not, keep using lower-cased.●Be aware of the different meanings of thehomophones “affect” and “effect”, “complement”and “compliment”, “discreet” and “discrete”, “principal” and “principle”.●Do not confuse “imply” and “infer”.●The prefix “non” is not a word; it should be joinedto the word it modifies, usually without a hyphen. ●There is no p eriod after the “et” in the Latinabbreviation “et al.”.●The abbreviation “i.e.” means “that is”, and theabbreviation “e.g.” means “for example”.An excellent style manual for science writers is [7]. 4. Using the TemplateAfter the text edit has been comp leted, the paper is ready for the template. Duplicate the template file by using the Save As command, and use the naming convention prescribed by your conference for the name of your paper. In this newly created file, highlight all of the contents and import your prepared text file. You are now ready to style your paper; use the scroll down window on the left of the MS Word Formatting toolbar.4.1. Authors and AffiliationsThe template is designed so that author affiliations are not repeated each time for multiple authors of the same affiliation. Please keep your affiliations as succinct as possible (for example, do not differentiate among departments of the same organization). This template was designed for two affiliations.1) For author/s of only one affiliation (Heading 3): To change the default, adjust the template as follows.a) Selection (Heading 4): Highlight all author and affiliation lines.b) Change number of columns: Select the Columns icon from the MS Word Standard toolbar and then select “1 Column” from the selection palette.c) Deletion: Delete the author and affiliation lines for the second affiliation.2) For author/s of more than two affiliations: To change the default, adjust the template as follows.a) Selection: Highlight all author and affiliation lines.Paper Titleb) Change number of columns: Select the “Columns” icon from the MS Word Standard toolbar and then select “1 Column” from the selection palette.c) Highlight author and affiliation lines of affiliation 1 and copy this selection.d) Formatting: Insert one hard return immediately after the last character of the last affiliation line. Then paste down the copy of affiliation 1. Repeat as necessary for each additional affiliation.e) Reassign number of columns: Place your cursor to the right of the last character of the last affiliation line of an even numbered affiliation (e.g., if there are five affiliations, place your cursor at end of fourth affiliation). Drag the cursor up to highlight all of the above author and affiliation lines. Go to Colu mn icon and select “2 Columns”. If you have an odd number of affiliations, the final affiliation will be centered on the page; all previous will be in two columns.4.2. Identify the HeadingsHeadings, or heads, are organizational devices that guide the reader through your paper. There are two types: component heads and text heads.Component heads identify the different components of your paper and are not topically subordinate to each other. Examples include Acknowledgments and References and, for these, the correct style to use is “Heading 5”. Use “figure caption” for your Figure captions, and “table head” for your table title. Run-in heads, such as “Abstract”, will require you to apply a style (in this case, italic) in addition to the style provided by the drop down menu to differentiate the head from the text.Text heads organize the topics on a relational, hierarchical basis. For example, the paper title is the primary text head because all subsequent material relates and elaborates on this one topic. If there are two or more sub-topics, the next level head (uppercase Roman numerals) should be used and, conversely, if there are not at least two sub-topics, then no subheads should be introduced. Styles named “Heading 1”, “Heading 2”, “Heading 3”, and “Heading 4” are prescribed.4.3. Figures and TablesPositioning Figures and Tables: Place figures and tables at the top and bottom of columns. Avoid placing them in the middle of columns. Large figures and tables may span across both columns. Figure captions should be below the figures; table heads should appear above the tables. Insert figures and tables after they are cited in the text. Use “Figure 1” in bold fonts, even at the beginning of a sentence.Figure Labels: Use 8 point Times New Roman for Figure labels. Us e words rather than s ymbols or abbreviations when writing Figure axis labels to avoid confusing the reader. As an example, write the quantity “M a g n e t i z a-Table 1. Table type styles. (Table caption is indispensable)TableHeadTable C olumn HeadTable column subhead Subhead Subhead Copy More table copy aa. Sample of a Table f ootnote. (Table footnote is dispensable)Figure 1. Example of a figure caption (figure caption). tion”, or “Magnetization, M”, not just “M”. If i ncluding units in the label, present them within parentheses. Do not label axes only with units. In the example, write “Magnetization (A/m)” or “Magnetization {A[m(1)]}”, not just “A/m”. Do not label axes with a ratio of quantities and units. For example, write “Temperature (K)”, not “Temperature/K”.5. Acknowledgements (Heading 5)Avoid the stilted expression, “One of us (R. B. G.) thanks...” Instead, try “R. B. G. thanks”. Put sponsor acknowledgements in the unnumbered footnote on the first page.6. References(Note: The template will number citations consecutively within brackets [1]. The sentence punctuation follows the bracket [2]. Refer simply to the reference number, as in [3]-do not use “Ref. [3]” or “reference [3]” except at the beginning of a sentence: “Reference [3] was the first . . .”Number footnotes separately in superscripts. Place the actual footnote at the bottom of the column in which it was cited. Do not put footnotes in the reference list. Use letters for table footnotes.Unless there are six authors or more give all authors' names; do not use “et al.”. Papers that have not been published, even if they have been submitted for publication, should be cited as “unpublished” [4]. PapersPaper Titlethat have been accepted for publication should be cited as “in press” [5]. Capitalize only the first word in a paper title, except for proper nouns and element symbols.For papers published in translation journals, please give the English citation first, followed by the original foreign-language citation [6-8].[1] A. S. Malik, O. Boyko, N. Atkar and W. F. Young, “AComparative Study of MR Imaging Profile of Titanium Pedicle Screws,” Acta Radiologica, Vol. 42, No. 3, 2001, pp. 291-293.[2]T. Hu and J. P. Desai, “Soft-Tissue Material Propertiesunder Large Deformati on: Strain Rate Effect,”Proceedings of the 26th Annual International Conference of the IEEE EMBS, San Francisco, 1-5 September 2004, pp. 2758-2761.[3]R. Ortega, A. Loria and R. Kelly, “A Semiglobally StableOutput Feedback PI2D Regulator for Robot Manipulat ors,” IEEE Transactions on Automatic Control, Vol. 40, No. 8, 1995, pp. 1432-1436. [4] E. Wit and J. McClure, “Statistics for Microarrays:Design, Analysis, And Inference,” 5th Edition, John Wiley & Sons Ltd., Chichester, 2004.[5] A. S. Prasad, “Clinical and Bioc hemical Spectrum ofZinc Deficiency in Human Subjects,” In: A. S. Prasad, Ed., Clinical,Biochemical and Nutritional Aspects of Trace Elements, Alan R. Liss, Inc., New York, 1982, pp.5-15.[6] B. M. S. Giambastiani, “Evoluzione Idrologica edIdrogeologica Del la Pineta di San Vitale (Ravenna),”Ph.D. Thesis, Bologna University, Bologna, 2007.[7]J. K. Wu, “Two Problems of Computer MechanicsProgram System,” Proceedings of Finite Element Analysis and CAD, Peking University Press, Beijing, 1994, pp. 9-15.[8]L. Honeycu tt, “Communication and Design Course,”1998. /commdesign/class1.html。