中英文文献数据库集锦
9个常用的国外英文论文文献数据库.doc
9个常用的国外英文论文文献数据库9个常用的国外英文论文文献数据库9个论文文献数据库，科研搬砖，阅读涨姿势，论文写作小帮手！先说说什么是数据库：学术科研中说的「数据库」和「文献数据库」，往往是一种网站的形式，这个网站的贮存了大量文献数据（比如论文）可以简单的理解为一个网络图书馆。
数据库中的论文往往都是耗费了大量的时间和精力整理出来的，还有很多是需要购买版权才可以放在互联网上的，再加上维护这个网站本身就耗费颇多，因此这些数据库通常不是完全免费的，你可以在上面免费查找文献，浏览摘要等简介内容，但是如果你要下载文献，就要付钱。
大学因为科研和教学需要，常年要下载大量的论文材料，所以就会和数据库的经营者签订很多协议，例如包年，就是给一定量的钱，然后就可以无限制下载论文。
也有按照下载的数量进行计费。
那英语作为世界第一学术语言，有哪些数据库是值得大家分享的呢？1、Wiley InterScience(英文文献期刊)Wiley InterScience是John Wiely & Sons公司创建的动态在线内容服务，1997年开始在网上开通。
通过InterScience，Wiley公司以许可协议形式向用户提供在线访问全文内容的服务。
Wiley InterScience收录了360多种科学、工程技术、医疗领域及相关专业期刊、30多种大型专业随着人们的信息越来越多地来自Internet，IEEE需要为会员提供更加完善和全面的电子信息产品和服务。
网址：/Xplore/home.jspIEEE应成为IEEE 会员获得信息的首选之地。
IEEE必须识别正确的信息，并提供对它们的访问方法。
实现这个目标的重要一步是通过IEEE Xplore与IEEE/IEE Electronic Library (IEL)连接。
IEL包括了1988年以来IEEE和IEE的所有期刊杂志和会议录，以及IEEE的标准，可以通过题目、关键词和摘要进行查阅。
重要的检索生态学文献的中英文数据库
重要的检索生态学文献的中英文数据库一、应用二次文献库检索文献1、ISI Web of ScienceISI Web of Science 是全球最大、覆盖学科最多的综合性学术信息资源，收录了自然科学、工程技术、生物医学等各个研究领域最具影响力的超过8700多种核心学术期刊。
利用Web of Science 丰富而强大的检索功能--普通检索、被引文献检索、化学结构检索，您可以方便快速地找到有价值的科研信息，即可以越查越旧，也可以越查越新，全面了解有关某一学科、某一课题的研究信息。
2、EI, 即《工程索引》，系美国工程信息公司出版的一个著名工程技术类综合检索工具，其不收录基础理论研究文章。
浏览器内输入ei engineering village- Login得到EI 检索界面，在 Quick search 里面输入例如作者，关键字等就可以得到想要的内容。
3、其他数据库：1）PubMed, PubMed是一个提供生物医学方面的论文搜寻以及摘要，并且免费搜寻的数据库。
它的数据库来源为MEDLINE。
其核心主题为医学，但亦包括其他与医学相关的领域，像是护理学或者其他健康学科。
2）Medline, MEDLINE是美国国立医学图书馆(The National Library of Medicine, 简称NLM)生产的国际性综合生物医学信息书目数据库，是当前国际上最权威的生物医学文献数据库。
内容包括美国《医学索引》（Index Medicus, IM）的全部内容和《牙科文献索引》（Index to Dental Literature）、《国际护理索引》（International Nursing Index）的部分内容3）CSA, CSA是加拿大标准协会（Canadian Standards Association）的简称。
它成立于1919年，是加拿大首家专为制定工业标准的非盈利性机构。
在北美市场上销售的电子，电器，卫浴，燃气等产品都需要取得安全方面的认证。
数据库中英文对照外文翻译文献
中英文对照外文翻译Database Management SystemsA database (sometimes spelled data base) is also called an electronic database , referring to any collection of data, or information, that is specially organized for rapid search and retrieval by a computer. Databases are structured to facilitate the storage, retrieval , modification, and deletion of data in conjunction with various data-processing operations .Databases can be stored on magnetic disk or tape, optical disk, or some other secondary storage device.A database consists of a file or a set of files. The information in these files may be broken down into records, each of which consists of one or more fields. Fields are the basic units of data storage , and each field typically contains information pertaining to one aspect or attribute of the entity described by the database . Using keywords and various sorting commands, users can rapidly search , rearrange, group, and select the fields in many records to retrieve or create reports on particular aggregate of data.Complex data relationships and linkages may be found in all but the simplest databases .The system software package that handles the difficult tasks associated with creating ,accessing, and maintaining database records is called a database management system(DBMS).The programs in a DBMS package establish an interface between the database itself and the users of the database.. (These users may be applications programmers, managers and others with information needs, and various OS programs.)A DBMS can organize, process, and present selected data elements form the database. This capability enables decision makers to search, probe, and query database contents in order to extract answers to nonrecurring and unplanned questions that aren’t available in regular reports. These questions might initially be vague and/or poorly defined ,but people can “browse” through the database until they have the needed information. In short, the DBMS will “manage” the stored data items and assemble the needed items from the common database in response to the queries of those who aren’t programmers.A database management system (DBMS) is composed of three major parts:(1)a storage subsystemthat stores and retrieves data in files;(2) a modeling and manipulation subsystem that provides the means with which to organize the data and to add , delete, maintain, and update the data;(3)and an interface between the DBMS and its users. Several major trends are emerging that enhance the value and usefulness of database management systems;Managers: who require more up-to-data information to make effective decisionCustomers: who demand increasingly sophisticated information services and more current information about the status of their orders, invoices, and accounts.Users: who find that they can develop custom applications with database systems in a fraction of the time it takes to use traditional programming languages.Organizations : that discover information has a strategic value; they utilize their database systems to gain an edge over their competitors.The Database ModelA data model describes a way to structure and manipulate the data in a database. The structural part of the model specifies how data should be represented(such as tree, tables, and so on ).The manipulative part of the model specifies the operation with which to add, delete, display, maintain, print, search, select, sort and update the data.Hierarchical ModelThe first database management systems used a hierarchical model-that is-they arranged records into a tree structure. Some records are root records and all others have unique parent records. The structure of the tree is designed to reflect the order in which the data will be used that is ,the record at the root of a tree will be accessed first, then records one level below the root ,and so on.The hierarchical model was developed because hierarchical relationships are commonly found in business applications. As you have known, an organization char often describes a hierarchical relationship: top management is at the highest level, middle management at lower levels, and operational employees at the lowest levels. Note that within a strict hierarchy, each level of management may have many employees or levels of employees beneath it, but each employee has only one manager. Hierarchical data are characterized by this one-to-many relationship among data.In the hierarchical approach, each relationship must be explicitly defined when the database is created. Each record in a hierarchical database can contain only one key field and only one relationship is allowed between any two fields. This can create a problem because data do not always conform to such a strict hierarchy.Relational ModelA major breakthrough in database research occurred in 1970 when E. F. Codd proposed a fundamentally different approach to database management called relational model ,which uses a table asits data structure.The relational database is the most widely used database structure. Data is organized into related tables. Each table is made up of rows called and columns called fields. Each record contains fields of data about some specific item. For example, in a table containing information on employees, a record would contain fields of data such as a person’s last name ,first name ,and street address.Structured query language(SQL)is a query language for manipulating data in a relational database .It is nonprocedural or declarative, in which the user need only specify an English-like description that specifies the operation and the described record or combination of records. A query optimizer translates the description into a procedure to perform the database manipulation.Network ModelThe network model creates relationships among data through a linked-list structure in which subordinate records can be linked to more than one parent record. This approach combines records with links, which are called pointers. The pointers are addresses that indicate the location of a record. With the network approach, a subordinate record can be linked to a key record and at the same time itself be a key record linked to other sets of subordinate records. The network mode historically has had a performance advantage over other database models. Today , such performance characteristics are only important in high-volume ,high-speed transaction processing such as automatic teller machine networks or airline reservation system.Both hierarchical and network databases are application specific. If a new application is developed ,maintaining the consistency of databases in different applications can be very difficult. For example, suppose a new pension application is developed .The data are the same, but a new database must be created.Object ModelThe newest approach to database management uses an object model , in which records are represented by entities called objects that can both store data and provide methods or procedures to perform specific tasks.The query language used for the object model is the same object-oriented programming language used to develop the database application .This can create problems because there is no simple , uniform query language such as SQL . The object model is relatively new, and only a few examples of object-oriented database exist. It has attracted attention because developers who choose an object-oriented programming language want a database based on an object-oriented model. Distributed DatabaseSimilarly , a distributed database is one in which different parts of the database reside on physically separated computers . One goal of distributed databases is the access of informationwithout regard to where the data might be stored. Keeping in mind that once the users and their data are separated , the communication and networking concepts come into play .Distributed databases require software that resides partially in the larger computer. This software bridges the gap between personal and large computers and resolves the problems of incompatible data formats. Ideally, it would make the mainframe databases appear to be large libraries of information, with most of the processing accomplished on the personal computer.A drawback to some distributed systems is that they are often based on what is called a mainframe-entire model , in which the larger host computer is seen as the master and the terminal or personal computer is seen as a slave. There are some advantages to this approach . With databases under centralized control , many of the problems of data integrity that we mentioned earlier are solved . But today’s personal computers, departmental computers, and distributed processing require computers and their applications to communicate with each other on a more equal or peer-to-peer basis. In a database, the client/server model provides the framework for distributing databases.One way to take advantage of many connected computers running database applications is to distribute the application into cooperating parts that are independent of one anther. A client is an end user or computer program that requests resources across a network. A server is a computer running software that fulfills those requests across a network . When the resources are data in a database ,the client/server model provides the framework for distributing database.A file serve is software that provides access to files across a network. A dedicated file server is a single computer dedicated to being a file server. This is useful ,for example ,if the files are large and require fast access .In such cases, a minicomputer or mainframe would be used as a file server. A distributed file server spreads the files around on individual computers instead of placing them on one dedicated computer.Advantages of the latter server include the ability to store and retrieve files on other computers and the elimination of duplicate files on each computer. A major disadvantage , however, is that individual read/write requests are being moved across the network and problems can arise when updating files. Suppose a user requests a record from a file and changes it while another user requests the same record and changes it too. The solution to this problems called record locking, which means that the first request makes others requests wait until the first request is satisfied . Other users may be able to read the record, but they will not be able to change it .A database server is software that services requests to a database across a network. For example, suppose a user types in a query for data on his or her personal computer . If the application is designed with the client/server model in mind ,the query language part on the personal computer simple sends the query across the network to the database server and requests to be notified when the data are found.Examples of distributed database systems can be found in the engineering world. Sun’s Network Filing System(NFS),for example, is used in computer-aided engineering applications to distribute data among the hard disks in a network of Sun workstation.Distributing databases is an evolutionary step because it is logical that data should exist at the location where they are being used . Departmental computers within a large corporation ,for example, should have data reside locally , yet those data should be accessible by authorized corporate management when they want to consolidate departmental data . DBMS software will protect the security and integrity of the database , and the distributed database will appear to its users as no different from the non-distributed database .In this information age, the data server has become the heart of a company. This one piece of software controls the rhythm of most organizations and is used to pump information lifeblood through the arteries of the network. Because of the critical nature of this application, the data server is also the one of the most popular targets for hackers. If a hacker owns this application, he can cause the company's "heart" to suffer a fatal arrest.Ironically, although most users are now aware of hackers, they still do not realize how susceptible their database servers are to hack attacks. Thus, this article presents a description of the primary methods of attacking database servers (also known as SQL servers) and shows you how to protect yourself from these attacks.You should note this information is not new. Many technical white papers go into great detail about how to perform SQL attacks, and numerous vulnerabilities have been posted to security lists that describe exactly how certain database applications can be exploited. This article was written for the curious non-SQL experts who do not care to know the details, and as a review to those who do use SQL regularly.What Is a SQL Server?A database application is a program that provides clients with access to data. There are many variations of this type of application, ranging from the expensive enterprise-level Microsoft SQL Server to the free and open source mySQL. Regardless of the flavor, most database server applications have several things in common.First, database applications use the same general programming language known as SQL, or Structured Query Language. This language, also known as a fourth-level language due to its simplistic syntax, is at the core of how a client communicates its requests to the server. Using SQL in its simplest form, a programmer can select, add, update, and delete information in a database. However, SQL can also be used to create and design entire databases, perform various functions on the returned information, and even execute other programs.To illustrate how SQL can be used, the following is an example of a simple standard SQL query and a more powerful SQL query:Simple: "Select * from dbFurniture.tblChair"This returns all information in the table tblChair from the database dbFurniture.Complex: "EXEC master..xp_cmdshell 'dir c:\'"This short SQL command returns to the client the list of files and folders under the c:\ directory of the SQL server. Note that this example uses an extended stored procedure that is exclusive to MS SQL Server.The second function that database server applications share is that they all require some form of authenticated connection between client and host. Although the SQL language is fairly easy to use, at least in its basic form, any client that wants to perform queries must first provide some form of credentials that will authorize the client; the client also must define the format of the request and response.This connection is defined by several attributes, depending on the relative location of the client and what operating systems are in use. We could spend a whole article discussing various technologies such as DSN connections, DSN-less connections, RDO, ADO, and more, but these subjects are outside the scope of this article. If you want to learn more about them, a little Google'ing will provide you with more than enough information. However, the following is a list of the more common items included in a connection request.Database sourceRequest typeDatabaseUser IDPasswordBefore any connection can be made, the client must define what type of database server it is connecting to. This is handled by a software component that provides the client with the instructions needed to create the request in the correct format. In addition to the type of database, the request type can be used to further define how the client's request will be handled by the server. Next comes the database name and finally the authentication information.All the connection information is important, but by far the weakest link is the authentication information—or lack thereof. In a properly managed server, each database has its own users with specifically designated permissions that control what type of activity they can perform. For example, a user account would be set up as read only for applications that need to only access information. Another account should be used for inserts or updates, and maybe even a third account would be used for deletes.This type of account control ensures that any compromised account is limited in functionality. Unfortunately, many database programs are set up with null or easy passwords, which leads to successful hack attacks.译文数据库管理系统介绍数据库（database,有时拼作data base）又称为电子数据库，是专门组织起来的一组数据或信息，其目的是为了便于计算机快速查询及检索。
常用文献检索数据库
一、常用文献检索数据库1、Springerlink数据库</>Springer是德国施普林格（Springer）出版公司出版的全文数据库数据库。
所提供的全文电子期刊共包含439种学术期刊(其中近400种为英文期刊)，按学科分为以下11个“在线图书馆”：生命科学、医学、数学、化学、计算机科学、经济、法律、工程学、环境科学、地球科学、物理学与天文学，是科研人员的重要信息源。
2、HighWire Press数据库</>HighWire Press是提供免费全文的、全球最大的学术文献出版商之一，于1995年由美国斯坦福大学图书馆创立。
最初，仅出版著名的周刊“Journal of Biological Chemistry”，目前已收录电子期刊340多种，文章总数已达130多万篇，其中超过47万篇文章可免费获得全文；这些数据仍在不断增加。
通过该界面还可以检索Me564034381 19:25:58dline收录的4500余种期刊中的1200多万篇文章，可看到文摘题录。
HighWire Press收录的期刊覆盖以下学科：生命科学、医学、物理学、社会科学。
3、NCBI PUBMED数据库/pubmedPubMed系统是由NLM的国家生物技术信息中心（National Center for Biotechnology Information，NCBI）开发的用于检索MEDLINE、PreMEDLINE数据库的网上检索系统。
从1997年6月起，PubMed在网上免费向用户开放。
它具有收录范围广泛、更新速度快、检索系统完备、链接广泛的特点。
PubMed系统包含三个数据库：MEDLINE、PreMEDLINE和Record supplied by Publisher。
4、sciencedirect数据库</>SD是荷兰Elsevier公司的核心产品，是全学科的全文数据库，它拥有1263种科技和医学电子全文期刊数据库5、Blackwell数据库<http://564034381 19:25:59/>英国Blackwell出版公司是世界上最大的期刊出版商之一，出版期刊总数已超过700种，其中理科类期刊占54%左右，其余为人文社会科学类。
常用中外文数据库
高级检索 （推荐）
专家检索
提供多个检索框，以及多 种约束条件，基本能够表 达用户的检索意愿；不需 要构造复杂的检索式，一 般只提供检索词即可，简 单灵活
只有一个检索框，可随意 书写合法的检索表达式， 比较灵活
有的数据库不允许在 检索框中使用运算符
需要掌握一定的检索 指令，指令的书写容 易出错
内容丰富
时效性强
ARL—Academic Research Library （比较研究）
ProQuest Science JournalPorQuest EBSCO
Nature Science
权威性强 科学前沿
基础性强 图片公司名录库
万方数据科技视 主要内容为北大光华管理学
频数据库
院系列和赢家大讲堂系列 。
外文数据库
全文数据库 IEEE/IEE Elsevier ProQuest
文摘数据库 CSA(CUP) OCLC EI
学协会数据库
AIAA ASCE
全文数据库
综合性强 全文率高
Elsevier
ห้องสมุดไป่ตู้
IEEE/IEE
专业性强 质量很高
第三章 常用中外文数据库
中文数据库 中国知识资源总库
中国期刊（世纪期刊）
维普+万方 超星数字图书馆
博士论文
硕士论文
视频数据库
知识世界
收录了材料化学、医学保健、建筑装 饰、历史文化、工业设计、生命科学、 军事侦探等十八大类2000多个视频 教育节目，其特色是中英文双语字幕 外挂的科教视频节目 。
爱迪科森<网 上报告厅>
全文数据库
权重性强 质量很高
Springer
World Scientific
一些免费的外文文献数据库
一些免费的外文文献数据库文献数据库, 外文方便大家查找外文文献1. The NASA Astrophysics Data System -- 世界最大免费全文网站，超过300,000篇全文主要学科：天体物理学2. HighWire Press -- 世界第二大免费全文网站，超过235，812篇全文主要学科：生物学、医学3. 主要学科：物理、数学、非线性科学、计算机科学等。
文件格式以PostScript为主，如没有相应的阅读软件，可以选择生成PDF文件格式。
4. Behavioral and Brain Sciences主要学科：行为科学、脑科学5. Centers for Disease Control and Prevention (CDC)主要学科：医学6. CogPrints主要学科：心理学、神经科学、行为科学、语言学、人工智能、哲学7. GPO Access美国政府文献8. Inter-university Consortium for Political and Social Research (ICPSR)世界最大的社会科学文献网站9. National Academy Press美国国家科学院、国家工程院、医学协会等机构报告10. National Center for Health Statistics (NCHS)美国国家卫生统计中心的统计报告11. NCSTRL计算机科学研究报告和论文12. Project Gutenberg Electronic Public Library电子图书，2002前提供10000种全文电子图书13. Thomas Legislative Information on the Internet美国国会图书馆提供的美国国会报告和历史文献14. UNESCO联合国教科文组织提供的文档15. United States Geological Survey美国地质考察报告16. World Development Sources (World Bank)世界银行报告17. Delphion世界各国专利，可看到前十三页全文18 美国数学学会(AMS)的三种免费期刊BulletinElectronic Research AnnouncementsNotices of the American Mathematical Society19 Physics Today美国物理学会(American Institute of Physics)提供的免费杂志。
常用免费外文全文数据库
常用免费外文全文数据库1.SpringerLINK数据库德国施普林格(Springer-Verlag)是世界上著名的科技出版集团, 通过SpringerLink系统提供其学术期刊及电子图书的在线服务。
2002年7月开始，Springer公司和EBSCO/Metapress 公司在国内开通了SpringerLink服务。
访问方式：镜像服务器(本校读者无需登录)、国外站点（用户需登录出国并自付国际网络通信费）。
访问权限：校园网IP地址范围。
访问全文：(PDF格式)需要使用Acrobat Reader软件，如需安装，可由此下载Acrobat Reader。
2.EBSCOhost数据库EBSCO公司通过国际专线提供检索服务，校园网的用户检索、下载无需支付国际网络通信费。
采用IP控制访问权限，不需要帐号和口令。
3.WorldSciNet数据库WorldSciNet为新加坡世界科学出版社(World Scientific Publishing Co.)电子期刊发行网站，该出版社委托EBSCO / MetaPress 公司在清华大学图书馆建立了世界科学出版社全文电子期刊镜像站.4.Ptics ExpressOptics Express由美国光学学会创办，刊登光学技术领域方面的报告和新进展。
提供1997年创刊以来的全部文献，以平均49天一期的速度出版，并支持彩色图像和多媒体文件。
网站地址：/创建者：Optical Society 0f America5.New Journal 0f PhysicsNew Journal 0fPhysics由英国皇家物理学会和德国物理学会出版，提供1998年创刊以来的全部文献。
所有用户可免费获取电子版文章。
网站地址：创建者：Institute of Physics & German Physical Society6.The Journal of Machine Learning ResearchThe Journal of Machine Learning Research由麻省理工学院出版，是机械研究领域的优质学术性论文的平台，用户可下载2000年创刊以来的全部文章。
常用外文数据库
常用外文数据库（ZT）常用英文数据库简介AACM Digital Library收录了美国计算机协会（Association for Computing Machinery）的各种电子期刊、会议录、快报等文献AGRICOLA 农业参考文献数据库，涉及美国农业和生命科学等领域，提供了1970年至今的重要农业信息。
American Chemical Socitey 美国化学学会全文期刊数据库American Mathematics Society 美国数学学会数据库，世界上最权威的数学学术团体，数据库内容涉及数学及数学在统计学、工程学、物理学、经济学、生物学、运筹学、计算机科学中的应用等American Physical Society (APS) 美国物理学会数据库，为用户提供期刊的在线阅读。
Annual Reviews 为全世界的科学团体服务，提供由著名科学家撰写的评论。
Annual Reviews分生物医学、物理学和社会科学三个主题，共出版29种期刊。
ASCE The American Society of Civil Engineers美国土木工程师协会数据库ASME Technical Journal 美国机械工程师学会数据库。
美国机械工程师学会,主持着世界上最大的技术出版之一，制定各种工业和制造业行业标准。
由于工程领域各学科间交叉性不断增长，ASME出版物也相应提供了跨学科前沿科技的资讯。
BBeilstein/Gmelin crossfire 以电子方式提供包含可供检索的化学结构和化学反应、相关的化学和物理性质，以及详细的药理学和生态学数据在内的最全面的信息资源。
BIOSIS Previews 世界上最大的关于生命科学的文摘索引数据库。
Blackwell 英国Blackwell(英文文献期刊)()Blackwell出版公司是世界上最大的期刊出版商之一(总部设在英国伦敦的牛津)，以出版国际性期刊为主，包含很多非英美地区出版的英文期刊。
中外文常用数据库及网络资源介绍
Apabi电子教学参考书
CALIS中国高校教学参考书
由CALIS成员馆51家高校图书馆参建，提供电子书6万多册
CADAL
数字资源1225645册，其中学位论文192425册，民国图书/期 刊269094册，古籍187993册，现代图书444951册，英文图书 126729册，其它4426册
Apabi电子教学参考书 Apabi是五个英文单词Author（作者）Publisher （出版社）、Artery（渠道）、Buyer（购买者）、 Internet(互联网)的首字母缩写。 Apabi系统最大的特色在于收录的电子图书均可 以是经采访人员针对各校学科建设以及读者需求， 从与北大方正公司合作的400多家出版社出版的图 书中精心挑选而来，因此它的学科专业性、系统 性更为突出；同时，也是对 各馆纸本书的有效补 充。
中文数据库—文摘索引
全国报刊索引 社科版 自科版 中文社会科学引文索引CSSCI
1857年～ 期刊8500多种，报纸200余种 2000年～
中文人文科学、社会科学学术期刊400余种，海外 出版的期刊近20种。1998年～
中国科学引文数据库（CSCD）
四部丛刊
文渊阁四库全书
中国基本古籍库中文电子期刊—全数据库中国知网—中国期刊全文数据库
重庆维普—中文科技期刊数据库
万方—中国数字化期刊群
． ． 人大复印资料 ． ． ． ． ． ． ． ． ．
中国知网 中国知网为同方知网（北京）技术有限公司所 有，中国学术期刊（光盘版）电子杂志社出版， 是世界上最大的连续动态更新的中国学术文献数 据库。该库深度集成整合了学术期刊、博硕士学 位论文、会议论文、报纸、年鉴、专利、国内外 标准、科技成果等中文资源以及 Springer 等外文 资源。数据每日更新。
英文常用全文数据库检索
SpringerLink-4
主页
期刊浏览
快速检索
高级检索
SpringerLink-5
高级检索界面
检索结果排序方式 年代限制
常用英文全文数据库
ScienceDirect Online （ SDOL ）
概况-1
荷兰爱思唯尔出版集团（Elsevier）公司是全球最
大的科技与医学出版发行商之一。
ScienceDirect Online系统是Elsevier公司的核心产
品，是全学科的全文数据库。
提供包括Elsevier 出版集团所属的各出版社出版的
nanocomposites
构造检索式：Abstract=polymer and Title=
nanocomposites
检索实例-2
使用高级检索方式，检索过程如下:
检索实例-3
检索结果
检索结果排序 检索结果现实条目 精炼检索结果
获取全文
其他全文数据库
SpringerLink-1
德国施普林格出版集团（Springer）是世界上著名
ACS）创立于1876年，是世界上最大的科技协会之 一，其会员数超过16.3万，是世界上最权威的科技 信息来源之一。
ACS的期刊被ISI的期刊引证报告（JCR）评为“化
学领域中被引用次数最多的期刊”。
ACS出版的文献类型有图书、期刊、会议文献、新
闻等，其中期刊50种，最早回溯到1879年。
概况-2
ACS的网址为。 任何用户均可访问并免费检索获取该数据库的文摘
题录信息，正式用户可以下载全文，对于机构用户 采用IP地址控制使用权限。
概况-3
进入方式
直接点击进入
检索方式
中英文文献翻译
Database introduction and ACCESS2000The database is the latest technology of data management, and the important branch of computer science. The database , as its name suggests, is the warehouse to preserve the data. The warehouse to store apparatus in computer only, and data to deposit according to sure forms。
The so-called database is refers to the long-term storage the data acquisition which in the computer, organized, may share。
In the database data according to the certain data model organization, the description, and the storage, has a smaller redundance, the higher data independence and the easy extension, and may altogether shine for each kind of user。
The effective management database, frequently has needed some database management systems (DBMS) is the user provides to database operation each kind of order, the tool and the method, including database establishment and recording input, revision, retrieval, demonstration, deletion and statistics。
世界各大英文数据库汇总
世界各大英文数据库汇总1. PubMed: This database, maintained by the U.S. National Library of Medicine, provides access to a vast collection of biomedical literature, including articles, journals, and research papers.2. Scopus: Scopus, owned and operated by Elsevier, is a multidisciplinary abstract and citation database that covers literature across various disciplines. It includes journals, conference proceedings, patents, and more.3. Web of Science: Hosted by Clarivate Analytics, the Web of Science is a widely used database for academic research. It covers scientific, social sciences, arts, and humanities literature. It also provides citation indexing for tracking research impact.5. JSTOR: JSTOR is a digital library that provides access to scholarly literature, including journals, books, and primary sources, in various disciplines such as arts, humanities, social sciences, and more.6. ScienceDirect: Operated by Elsevier, ScienceDirect offers access to a wide range of scientific, technical, and medical literature, including journals, books, and reference works.7. ProQuest: ProQuest is a general research database that covers a broad range of subjects. It offers access to scholarlyjournals, newspapers, dissertations, and more, making it useful for multidisciplinary research.8. DOAJ (Directory of Open Access Journals): DOAJ is anonline directory of open-access, peer-reviewed journals invarious fields, providing free access to research articles.9. ERIC (Education Resources Information Center): ERIC is sponsored by the U.S. Department of Education and offers accessto literature in the field of education, including journals, reports, conference papers, and more.12. MEDLINE: MEDLINE, accessed through platforms like PubMed, is a premier bibliographic database for biomedical literature.It covers a range of topics like medicine, nursing, dentistry, and veterinary medicine.13. British Library EThOS: EThOS is a centralized repository for electronic theses and dissertations from UK Higher Education institutions.14. Taylor & Francis Online: Taylor & Francis Online offers access to a vast collection of scholarly literature across multiple disciplines, including journals, books, and reference works.15. PLOS ONE: PLOS ONE is an open-access journal that publishes research in various fields, making it a valuableresource for researchers who prioritize accessibility and openness.These are just a few examples, and there are many more English databases available worldwide. Researchers should select the appropriate database based on their specific research needs and subject area.。
中英文常见数据库吉检索方法
中英文常见数据库吉检索方法在当今信息爆炸的时代，数据库为我们提供了丰富的信息资源。
掌握常见的数据库检索方法，能够帮助我们更高效地获取所需信息。
本文将为您详细介绍中英文常见数据库的检索方法。
一、中文常见数据库检索方法1.中国知网（CNKI）中国知网是我国最大的学术文献数据库，主要收录了中文期刊、学位论文、会议论文等。
检索方法如下：（1）快速检索：在首页输入关键词，点击“检索”按钮。
（2）高级检索：进入高级检索页面，可设置检索范围、检索条件等。
2.万方数据万方数据包括学术期刊、学位论文、会议论文等资源。
检索方法如下：（1）简单检索：在首页输入关键词，点击“搜索”按钮。
（2）高级检索：进入高级检索页面，可设置检索条件、排序方式等。
3.维普资讯维普资讯主要收录了中文期刊、学位论文等。
检索方法如下：（1）基本检索：在首页输入关键词，点击“搜索”按钮。
（2）高级检索：进入高级检索页面，可设置检索条件、检索范围等。
二、英文常见数据库检索方法1.PubMedPubMed是生物医学领域的重要数据库，检索方法如下：（1）基本检索：在首页输入关键词，点击“Search”按钮。
（2）高级检索：点击“Advanced”进入高级检索页面，可设置检索条件、检索范围等。
2.Web of ScienceWeb of Science是涵盖多个学科领域的综合性数据库，检索方法如下：（1）基本检索：在首页输入关键词，点击“Search”按钮。
（2）高级检索：点击“Advanced Search”进入高级检索页面，可设置检索条件、检索范围等。
3.ScopusScopus是涵盖多个学科领域的综合性数据库，检索方法如下：（1）基本检索：在首页输入关键词，点击“Search”按钮。
（2）高级检索：点击“Advanced Search”进入高级检索页面，可设置检索条件、检索范围等。
总结：掌握常见数据库的检索方法，能够帮助我们快速、准确地获取所需信息。
中英文文献翻译-信息系统开发和数据库开发
英文原文：Information System Development and Database DevelopmentIn many organizations, database development from the beginning of enterprise data modeling, data modeling enterprises determine the scope of the database and the general content. This step usually occurs in an organization's information system planning process, it aims to help organizations create an overall data description or explanation, and not the design of a specific database. A specific database for one or more information systems provide data and the corporate data model (which may involve a number of databases) described by the organization maintaining the scope of the data. Data modeling in the enterprise, you review of the current system, the need to support analysis of the nature of the business areas, the need for further description of the abstract data, and planning one or more database development project. Figure 1 shows Pine Valley furniture company's enterprise data model of a part.1.1 Information System ArchitectureAs shown in figure 1, senior data model is only general information system architecture (ISA) or a part of an organization's information system blueprint. In the information system planning, you can build an enterprise data model as a whole information system architecture part. According to Zachman (1987), Sowa and Zachman (1992) views of an information system architecture consists of the following six key components:Data (Figure 1 shows, but there are other methods that).Manipulation of data processing (of a data flow diagram can be used, with the object model methods, or other symbols that).Networks, which organizations and in organizations with its main transmission of data between business partners (it can connect through the network topology map and to demonstrate).People who deal with the implementation of data and information and is the source and receiver (in the process model for the data shows that the sender and the receiver). Implementation of the events and time points (they can use state transition diagram and other means.)The reasons for the incident and data processing rules (often in the form of text display, but there are also a number of charts for the planning tools such as decision tables).1.2 Information EngineeringInformation systems planners in accordance with the specific information system planning methods developed information system architecture. Information engineering is a popular and formal methods. Information engineering is a data-oriented creation and maintenance of the information system. Information engineering is because the data-oriented, so when you begin to understand how the database is defined by the logo and when information engineering a concise explanation is very helpful. Information Engineering follow top-down planning approach, in which specific information systems from a wide range of informationneeds in the understanding derived from (for example, we need about customers, products, suppliers, sales and processing of the data center), rather than merging many detailed information requested ( orders such as a screen or in accordance with the importation of geographical sales summary report). Top-down planning will enable developers to plan more comprehensive information system, consider system components provide an integrated approach to enhance the information system and the relationship between the business objectives of the understanding, deepen their understanding of information systems throughout the organization in understanding the impact.Information Engineering includes four steps: planning, analysis, design and implementation. The planning stage of project information generated information system architecture, including enterprise data model.1.3 Information System Planning Information systems planning objective is to enable IT organizations and the business strategy closely integrated, such integration for the information systems and technology to make the most of the investment interest is very important. As the table as a description, information engineering approach the planning stage include three steps, we in the follow-up of three sections they discussed.1. Critical factors determining the planning Planning is the key factor that organizational objectives, critical success factors and problem areas. These factors determine the purpose of the establishment of planning and environment planning and information systems linked to strategic business planning. Table 2 shows the Pine Valley furniture company's key planning a number of possible factors, these factors contribute to the information systems manager for the new information systems and databases clubs top priority to deal with the demand. For example, given the imprecise sales forecasts this problem areas, information systems managers in the organization may be stored in the database additional historical sales data, new market research data and new product test data.2. The planning organizations set targetsOrganizations planning targets defined scope of business, and business scope will limit the subsequent analysis and information systems may change places. Five key planning targets as follows:●organizational units in the various sectors.●organizations location of the place of business operations.●functions of the business support organizations handling mission of the relevant group. Unlike business organizations function modules, in fact a function can be assigned to various organizations modules (for example, product development function is the production and sale of the common responsibility of the Ministry).●types of entities managed by the organization on the people, places and things of the major types of data.●Information System data set processing software applications and support procedures.3. To set up a business modelA comprehensive business model including the functions of each enterprisefunctional decomposition model, the enterprise data model and the various planning matrix. Functional decomposition is the function of the organization for a more detailed decomposition process, the functional decomposition is to simplify the analysis of the issue, distracted and identify components and the use of the classical approach. Pine Valley furniture company in order to function in the functional decomposition example in figure 2 below. In dealing with business functions and support functions of the full set, multiple databases, is essential to a specific database therefore likely only to support functions (as shown in Figure 2) provide a subset of support. In order to reduce data redundancy and to make data more meaningful, has a complete, high-level business view is very helpful.The use of specific enterprise data model to describe the symbol. Apart from the graphical description of this type of entity, a complete enterprise data model should also include a description of each entity type description of business operations and a summary of that business rules. Business rules determine the validity of the data.An enterprise data model includes not only the types of entities, including the link between the data entities, as well as various other objects planning links. Showed that the linkage between planning targets a common form of matrix. Because of planning matrix need not be explicit modeling database can be clearly described business needs, planning matrix is an important function. Regular planning matrix derived from the operational rules, it will help social development activities that top priority will be sorting and development activities under the top-down view through an enterprise-wide approach for the development of these activities. There are many types of planning matrix is available, their commonalities are:●locations - features show business function in which the implementation of operational locations.●unit - functions which showed that business function or business unit responsible for implementation.●Information System - data entities to explain how each information system interact with each data entity (for example, whether or not each system in each entity have the data to create, retrieve, update and delete).●support functions - data in each functional entities in the data set for the acquisition, use, update and delete.●Information System - target indication for each information system to support business objectives.Figure 3 illustrate a possible functions - data entities matrix. Such a matrix can be used for a variety of purposes, including the following three objectives:1) identify gaps in the data entities to indicate the types of entities not use any function or functions which do not use any entity.2) found that the loss of each functional entities involved in the inspection staff through the matrix to identify any possible loss of the entity.3) The distinction between development activities if the priority to the top of a system development function for a high-priority (probably because it important organizational objectives related), then this area used by entities in the development of the database has a high priority. Hoffer, George and Valacich (2002) are theworks of the matrix on how to use the planning and completion of the Information EngineeringThe planning system more complete description.2 database development processBased on information engineering information systems planning database is a source of development projects. These new database development projects is usually in order to meet the strategic needs of organizations, such as improving customer support, improve product and inventory management, or a more accurate sales forecast. However, many more database development project is the bottom-up approach emerging, such as information system user needs specific information to complete their work, thus beginning a project request, and as other information systems experts found that organizations need to improve data management and begin new projects. Bottom-up even in the circumstances, to set up an enterprise data model is also necessary to understand the existing database can provide the necessary data, otherwise, the new database, data entities and attributes can be added to the current data resources to the organization. Both the strategic needs or operational information needs of each database development projects normally concentrated in a database. Some projects only concentrated in the database definition, design and implementation of a database, as a follow-up to the basis of the development of information systems. However, in most cases, the database and associated information processing function as a complete information systems development project was part of the development. 2.1 System Development Life CycleGuide management information system development projects is the traditional process of system development life cycle (SDLC). System development life cycle is an organization of the database designers and programmers information system composed of the Panel of Experts detailed description, development, maintenance and replacement of the entire information system steps. This process is because Waterfall than for every step into the adjacent the next step, that is, the information system is a specification developed by a piece of land, every piece of the output is under an input. However shown in the figure, these steps are not purely linear, each of the steps overlap in time (and thus can manage parallel steps), but when the need to reconsider previous decisions, but also to roll back some steps ahead. (And therefore water can be put back in the waterfall!)Figure 4 on the system development life cycle and the purpose of each stage of the product can be delivered concise notes. The system development life cycle including each stage and database development-related activities, therefore, the question of database management systems throughout the entire development process. In Figure 5 we repeat of the system development life cycle stage of the seven, and outlines the common database at each stage of development activities. Please note that the systems development life cycle stages and database development steps一一对应exists between the relationship between the concept of modeling data in both systems development life cycle stages between.Enterprise ModelingDatabase development process from the enterprise modeling (system developmentlife cycle stage of the project feasibility studies, and to choose a part), Organizations set the scope and general database content. Enterprise modeling in information systems planning and other activities, these activities determine which part of information systems need to change and strengthen the entire organization and outlines the scope of data. In this step, check the current database and information systems, development of the project as the main areas of the nature of the business, with a very general description of each term in the development of information systems when needed data. Each item only when it achieved the expected goals of organizations can be when the next step.Conceptual Data ModelingOne has already begun on the Information System project, the concept of data modeling phase of the information systems needs of all the data. It is divided into two stages. First, it began the project in the planning stage and the establishment of a plan similar to Figure 1. At the same time outlining the establishment of other documents to the existing database without considering the circumstances specific development projects in the scope of the required data. This category only includes high-level data (entities), and main contact. Then in the system development life-cycle analysis stage must have a management information system set the entire organization Details of the data model definition of all data attributes, listing all data types that all data inter-entity business linkages, defining description of the full data integrity rules. In the analysis phase, but also the concept of inspection data model (also called the concept behind the model) and the goal of information systems used to explain other aspects of the model of consistency categories, such as processing steps, rules and data processing time of timing. However, even if the concept is such detailed data model is only preliminary, because follow-up information system life cycle activities in the design of services, statements, display and inquiries may find that missing element or mistakes. Therefore, the concept of data often said that modeling is a top-down manner, its areas of operation from the general understanding of the driver, rather than the specific information processing activities by the driver.3. Logical Database Design Logical database design from two perspectives database development. First, the concept of data model transform into relational database theory based on the criteria that means - between. Then, as the design of information systems, every computer procedures (including procedures for the input and output format), database support services, statements, and inquiries revealed that a detailed examination. In this so-called Bottom-up analysis, accurate verification of the need to maintain the database and the data in each affairs, statements and so on the needs of those in the nature of the data.For each separate statements, services, and so on the analysis must take into account a specific, limited but complete database view. When statements, services, and other analysis might be necessary to change the concept of data model. Especially in large-scale projects, the different analytical systems development staff and the team can work independently in different procedures or in a centralized, the details of their work until all the logic design stage may be displayed. In these circumstances, logic database design stage must be the original concept of data model and user view theseindependent or merged into a comprehensive design. In logic design information systems also identify additional information processing needs of these new demands at this time must be integrated into the logic of earlier identified in the database design.Logical database design is based on the final step for the formation of good data specifications and determine the rules, the combination, the data after consultation specifications or converted into basic atomic element. Most of today's database, these rules from the relational database theory and the process known as standardization. This step is the result of management of these data have not cited any database management system for a complete description of the database map. Logical database design completed, we began to identify in detail the logic of the computer program and maintenance, the report contents of the database for inquiries.4. Physical database design and definitionPhysical database design and definition phase decisions computer memory (usually disk) database in the organization, definition of According to the library management system for physical structure, the procedures outlined processing services, produce the desired management information and decision support statements. The objective of this stage is to design an effective and safe management of all data-processing database, the physical database design to closely integrate the information systems of other physical aspects of the design, including procedures, computer hardware, operating systems and data communications networks.5. Database ImplementationThe database prepared by the realization stage, testing and installation procedures for handling databases. Designers can use the standard programming language (such as COBOL, C or Visual Basic), the dedicated database processing languages (such as SQL), or the process of the non-exclusive language programming in order to produce a statement of the fixed format, the result will be displayed, and may also include charts. In achieving stage, but also the completion of all the database files, training users for information systems (database) user setup program. The final step is to use existing sources of information (documents legacy applications and databases and now needs new data) loading data. Loading data is often the first step in data from existing files and databases to an intermediate format (such as binary or text files) and then to turn intermediate loading data to a new database. Finally, running databases and related applications for the actual user maintenance and retrieval of data. In operation, the regular backup database and the database when damaged or affected resume database.6. Database maintenance During the database in the progressive development of database maintenance. In this step, in order to meet changing business conditions, in order to correct the erroneous database design, database applications or processing speed increase, delete or change the structure of the database. When a procedure or failure of the computer database affect or damage the database may also be reconstruction. This step usually is the longest in the database development process step, as it continued to databases and related applications throughout the life cycle, the development of each database can be seen as a brief database development processand data modeling concepts arise, logical and physical database design and database to achieve dealing with the changes.信息系统开发和数据库开发在许多组织中，从企业数据建模开始的数据库开发，企业数据建模确定数据库的范围和一般内容。
列举国内外常用的文献检索数据库
列举国内外常用的文献检索数据库常用的国内外文献检索数据库一、国内常用的文献检索数据库1. 中国知网中国知网是中国最大的综合性学术数据库，提供了包括学术期刊、学位论文、会议论文、报纸、年鉴、标准、专利等多种资源的检索和下载服务。
2. 万方数据库万方数据库是国内领先的综合性学术资源平台，拥有丰富的学术期刊、学位论文、会议论文、报纸、年鉴、图书等资源，涵盖了各个学科领域。
3. 维普中文科技期刊数据库维普中文科技期刊数据库收录了广泛的学术期刊，涵盖了自然科学、工程技术、农业科学、医药卫生、经济管理、人文社科等多个学科领域。
4. 中国期刊全文数据库中国期刊全文数据库是中国国家图书馆主办的学术期刊数据库，收录了大量的中文学术期刊，提供了全文检索和下载服务。
5. 北大法宝北大法宝是中国最大的法律法规数据库，收录了中国的法律法规、法律案例、法学期刊等资源，为法律研究提供了重要的参考资料。
二、国外常用的文献检索数据库1. PubMedPubMed是美国国家医学图书馆提供的生物医学文献数据库，收录了包括医学、生物学、生物化学、生物工程等领域的学术期刊文章。
2. IEEE XploreIEEE Xplore是电气和电子工程师学会（IEEE）提供的学术数据库，收录了电子工程、计算机科学、通信技术等领域的期刊、会议论文、标准等资源。
3. ScienceDirectScienceDirect是爱思唯尔旗下的学术数据库，涵盖了自然科学、工程技术、医学、社会科学等学科领域的期刊、书籍、参考工具等资源。
4. Web of ScienceWeb of Science是由汤森路透公司推出的学术文献数据库，包括了科学引文索引（SCI）、社会科学引文索引（SSCI）和艺术与人文科学引文索引（AHCI）等子数据库。
5. Google 学术Google 学术是Google推出的学术搜索引擎，通过搜索学术文献、论文、学位论文等资源，提供了全文检索和引用检索的功能。
图书馆馆藏资源宣传篇(4)——外文论文全文数据库
综合性外文全文数据库（10个）1 Web of Science数据库Web of Science收录了12,000多种世界权威的、高影响力的学术期刊，内容涵盖自然科学、社会科学、艺术与人文等领域，我馆购买了其中的SCI、SSCI和JCR数据库。
SCI 为自然科学引文索引（Science Citation Index)，SSCI为社会科学引文索引（Social Sciences Citation Index），JCR为期刊引用报告（Journal Citation Reports）描述了各种期刊的影响因子、立即影响指数、被引半衰期等。
WOS可以看做是一个收录了全球核心期刊的统一检索平台,可以查找到世界领域各个学科发表的核心文献的线索。
2 EBSCOhost期刊全文数据库我馆购买了ASP（Academic Search Premier）学术期刊全文库、BSP （Business Source Premier）商业资源精粹全文库、EconLit with Full Text 美国经济学会经济学全文数据库三个子库。
ASP是当今规模最大的多学科全文数据库, 提供学术性全文期刊；BSP涉及的主题范围有商业、管理、经济学、金融、会计等。
3 ABI/INFORM Complete 商业经济管理全文期刊数据库该数据库收录全球1300多家出版商的7700多种商业经济管理领域的优秀刊物，其中6300多种为全文刊，是商业学术理论与实践领域的顶级资源。
ProQuest所收录的期刊包含了许多独家收藏的全球著名商业期刊出版社的内容：•英国剑桥大学出版社（Cambridge University Press）•美国道琼斯公司（Dow Jones & Company Inc.）•英国爱墨瑞得出版集团（Emerald Group Publishing）•英国金融时报有限公司（Financial Times Limited）•英国Palgrave Macmillan出版社（Palgrave Macmillan）•美国华尔街日报（The Wall Street Journal）•美国麻省理工斯隆管理评论协会（Sloan Management Review Association）•英国经济学家杂志（The Economist）•美国巴伦周刊（Barron’s）还有英国经济学家智囊团报告（EIU ViewsWire）、SSRN (Social Science Research Network)163000+工作底稿、ProQuest商学论文（ProQuest Business Dissertations）、商业案例（Business Cases）等。
数据库英文参考文献(最新推荐120个)
由于我国经济的高速发展,计算机科学技术在当前各个科技领域中迅速发展,成为了应用最广泛的技术之一.其中数据库又是计算机科学技术中发展最快,应用最广泛的重要分支之一.它已成为计算机信息系统和计算机应用系统的重要技术基础和支柱。
下面是数据库英文参考文献的分享，希望对你有所帮助。
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Future Generation Computer Systems,2020.[6]Jo?o Peixoto Martins,António Andrade-Campos,Sandrine Thuillier. Calibration of Johnson-Cook Model Using Heterogeneous Thermo-Mechanical Tests[J]. Procedia Manufacturing,2020,47.[7]Anna Soriani,Roberto Gemignani,Matteo Strano. A Metamodel for the Management of Large Databases: Toward Industry 4.0 in Metal Forming[J]. Procedia Manufacturing,2020,47.[8]Ayman Elbadawi,Karim Mahmoud,Islam Y. Elgendy,Mohammed Elzeneini,Michael Megaly,Gbolahan Ogunbayo,Mohamed A. Omer,Michelle Albert,Samir Kapadia,Hani Jneid. Racial disparities in the utilization and outcomes of transcatheter mitral valve repair: Insights from a national database[J]. Cardiovascular Revascularization Medicine,2020.[9]Maurizio Boccia,Antonio Sforza,Claudio Sterle. Simple Pattern Minimality Problems: Integer Linear Programming Formulations and Covering-Based Heuristic Solving Approaches[J]. INFORMS Journal on Computing,2020.[10]. 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Learning supervised embeddings for large scale sequence comparisons.[J]. PloS one,2020,15(3).[15]. Information Technology; Studies from University of California San Diego (UCSD) Reveal New Findings on Information Technology (A Physics-constrained Data-driven Approach Based On Locally Convex Reconstruction for Noisy Database)[J]. Information Technology Newsweekly,2020.[16]. Information Technology; Researchers from National Institute of Information and Communications Technology Describe Findings in Information Technology (Efficient Discovery of Weighted Frequent Neighborhood Itemsets in Very Large Spatiotemporal Databases)[J]. Information Technology Newsweekly,2020.[17]. Information Technology; Investigators at Gdansk University of Technology Report Findings in Information Technology (A Framework for Accelerated Optimization of Antennas Using Design Database and Initial Parameter Set Estimation)[J]. Information Technology Newsweekly,2020.[18]. Information Technology; Study Results from Palacky University Update Understanding of Information Technology (Evaluation of Replication Mechanisms on Selected Database Systems)[J]. Information Technology Newsweekly,2020.[19]Runfola Daniel,Anderson Austin,Baier Heather,Crittenden Matt,Dowker Elizabeth,Fuhrig Sydney,Goodman Seth,Grimsley Grace,Layko Rachel,MelvilleGraham,Mulder Maddy,Oberman Rachel,Panganiban Joshua,Peck Andrew,Seitz Leigh,Shea Sylvia,Slevin Hannah,Youngerman Rebecca,Hobbs Lauren. geoBoundaries: A global database of political administrative boundaries.[J]. PloS one,2020,15(4).[20]Dupré Damien,Krumhuber Eva G,Küster Dennis,McKeown Gary J. A performance comparison of eight commercially available automatic classifiers for facial affect recognition.[J]. PloS one,2020,15(4).[21]Partha Pratim Banik,Rappy Saha,Ki-Doo Kim. An Automatic Nucleus Segmentation and CNN Model based Classification Method of White Blood Cell[J]. Expert Systems With Applications,2020,149.[22]Hang Dong,Wei Wang,Frans Coenen,Kaizhu Huang. Knowledge base enrichment by relation learning from social tagging data[J]. Information Sciences,2020,526.[23]Xiaodong Zhao,Dechang Pi,Junfu Chen. Novel trajectory privacy-preserving method based on clustering using differential privacy[J]. Expert Systems With Applications,2020,149.[24]. Information Technology; Researchers at Beijing University of Posts and Telecommunications Have Reported New Data on Information Technology (Mining top-k sequential patterns in transaction database graphs)[J]. Internet Weekly News,2020.[25]Sunil Kumar Sharma. An empirical model (EM: CCO) for clustering, convergence and center optimization in distributive databases[J]. Journal of Ambient Intelligence and Humanized Computing,2020(prepublish).[26]Naryzhny Stanislav,Klopov Nikolay,Ronzhina Natalia,Zorina Elena,Zgoda Victor,Kleyst Olga,Belyakova Natalia,Legina Olga. A database for inventory of proteoform profiles: "2DE-pattern".[J]. Electrophoresis,2020.[27]Noel Varela,Jesus Silva,Fredy Marin Gonzalez,Pablo Palencia,Hugo Hernandez Palma,Omar Bonerge Pineda. Method for the Recovery of Images in Databases of Rice Grains from Visual Content[J]. Procedia Computer Science,2020,170.[28]Ahmad Rabanimotlagh,Prabhu Janakaraj,Pu Wang. Optimal Crowd-Augmented Spectrum Mapping via an Iterative Bayesian Decision Framework[J]. Ad Hoc Networks,2020.[29]Ismail Boucherit,Mohamed Ould Zmirli,Hamza Hentabli,Bakhtiar Affendi Rosdi. Finger vein identification using deeply-fused Convolutional Neural Network[J]. Journal of King Saud University - Computer and Information Sciences,2020.[30]Sachin P. Patel,S.H. Upadhyay. Euclidean Distance based Feature Ranking andSubset Selection for Bearing Fault Diagnosis[J]. Expert Systems With Applications,2020.[31]Julia Fomina,Denis Safikanov,Alexey Artamonov,Evgeniy Tretyakov. Parametric and semantic analytical search indexes in hieroglyphic languages[J]. Procedia Computer Science,2020,169.[32]Selvine G. Mathias,Sebastian Schmied,Daniel Grossmann. An Investigation on Database Connections in OPC UA Applications[J]. Procedia Computer Science,2020,170.[33]Abdourrahmane Mahamane Atto,Alexandre Benoit,Patrick Lambert. Timed-image based deep learning for action recognition in video sequences[J]. Pattern Recognition,2020.[34]Yonis Gulzar,Ali A. Alwan,Abedallah Zaid Abualkishik,Abid Mehmood. A Model for Computing Skyline Data Items in Cloud Incomplete Databases[J]. Procedia Computer Science,2020,170.[35]Xiaohan Yang,Fan Li,Hantao Liu. Deep feature importance awareness based no-reference image quality prediction[J]. Neurocomputing,2020.[36]Dilana Hazer-Rau,Sascha Meudt,Andreas Daucher,Jennifer Spohrs,Holger Hoffmann,Friedhelm Schwenker,Harald C. Traue. The uulmMAC Database—A Multimodal Affective Corpus for Affective Computing in Human-Computer Interaction[J]. 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Optimizing the Analytical Value of Oncology-Related Data Based on an In-Memory Analysis Layer: Development and Assessment of the Munich OnlineComprehensive Cancer Analysis Platform.[J]. Journal of medical Internet research,2020,22(4).数据库英文参考文献二：[41]Meiling Chai,Changgeng Li,Hui Huang. A New Indoor Positioning Algorithm of Cellular and Wi-Fi Networks[J]. Journal of Navigation,2020,73(3).[42]Mandy Watson. How to undertake a literature search: a step-by-step guide[J]. British Journal of Nursing,2020,29(7).[43]. Patent Application; "Memorial Facility With Memorabilia, Meeting Room, Secure Memorial Database, And Data Needed For An Interactive Computer Conversation With The Deceased" in Patent Application Approval Process (USPTO 20200089455)[J]. Computer Technology Journal,2020.[44]. Information Technology; Data on Information Technology Detailed by Researchers at Complutense University Madrid (Hr-sql: Extending Sql With Hypothetical Reasoning and Improved Recursion for Current Database Systems)[J]. Computer Technology Journal,2020.[45]. Science - Metabolomics; Study Data from Wake Forest University School of Medicine Update Knowledge of Metabolomics (Software tools, databases and resources in metabolomics: updates from 2018 to 2019)[J]. Computer Technology Journal,2020.[46]. Sigma Computing Inc.; Researchers Submit Patent Application, "GeneratingA Database Query To Dynamically Aggregate Rows Of A Data Set", for Approval (USPTO 20200089796)[J]. Computer Technology Journal,2020.[47]. Machine Learning; Findings on Machine Learning Reported by Investigators at Tongji University (Comparing Machine Learning Algorithms In Predicting Thermal Sensation Using Ashrae Comfort Database Ii)[J]. Computer Technology Journal,2020.[48]. Sigma Computing Inc.; "Generating A Database Query Using A Dimensional Hierarchy Within A Graphical User Interface" in Patent Application Approval Process (USPTO 20200089794)[J]. Computer Technology Journal,2020.[49]Qizhi He,Jiun-Shyan Chen. A physics-constrained data-driven approach based on locally convex reconstruction for noisy database[J]. Computer Methods in Applied Mechanics and Engineering,2020,363.[50]José A. Delgado-Osuna,Carlos García-Martínez,JoséGómez-Barbadillo,Sebastián Ventura. Heuristics for interesting class association rule mining a colorectal cancer database[J]. Information Processing andManagement,2020,57(3).[51]Edival Lima,Thales Vieira,Evandro de Barros Costa. Evaluating deep models for absenteeism prediction of public security agents[J]. Applied Soft Computing Journal,2020,91.[52]S. Fareri,G. Fantoni,F. Chiarello,E. Coli,A. Binda. Estimating Industry 4.0 impact on job profiles and skills using text mining[J]. 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Information Technology - Database Management; New Findings from Guangzhou Medical University Update Understanding of Database Management (GREG-studying transcriptional regulation using integrative graph databases)[J]. Information Technology Newsweekly,2020.[58]. Technology - Laser Research; Reports from Nicolaus Copernicus University in Torun Add New Data to Findings in Laser Research (Nonlinear optical study of Schiff bases using Z-scan technique)[J]. Journal of Technology,2020.[59]Loeffler Caitlin,Karlsberg Aaron,Martin Lana S,Eskin Eleazar,Koslicki David,Mangul Serghei. Improving the usability and comprehensiveness of microbial databases.[J]. BMC biology,2020,18(1).[60]Caitlin Loeffler,Aaron Karlsberg,Lana S. Martin,Eleazar Eskin,David Koslicki,Serghei Mangul. Improving the usability and comprehensiveness of microbial databases[J]. BMC Biology,2020,18(1).[61]Dean H. Barrett,Aderemi Haruna. Artificial intelligence and machine learningfor targeted energy storage solutions[J]. Current Opinion in Electrochemistry,2020,21.[62]Chenghao Sun. Research on investment decision-making model from the perspective of “Internet of Things + Big data”[J]. Future Generation Computer Systems,2020,107.[63]Sa?a Adamovi?,Vladislav Mi?kovic,Nemanja Ma?ek,Milan Milosavljevi?,Marko ?arac,Muzafer Sara?evi?,Milan Gnjatovi?. An efficient novel approach for iris recognition based on stylometric features and machine learning techniques[J]. Future Generation Computer Systems,2020,107.[64]Olivier Pivert,Etienne Scholly,Grégory Smits,Virginie Thion. Fuzzy quality-Aware queries to graph databases[J]. Information Sciences,2020,521.[65]Javier Fernando Botía Valderrama,Diego José Luis Botía Valderrama. Two cluster validity indices for the LAMDA clustering method[J]. Applied Soft Computing Journal,2020,89.[66]Amer N. Kadri,Marie Bernardo,Steven W. Werns,Amr E. Abbas. TAVR VS. SAVR IN PATIENTS WITH CANCER AND AORTIC STENOSIS: A NATIONWIDE READMISSION DATABASE REGISTRY STUDY[J]. Journal of the American College of Cardiology,2020,75(11).[67]. Information Technology; Findings from P. Sjolund and Co-Authors Update Knowledge of Information Technology (Whole-genome sequencing of human remains to enable genealogy DNA database searches - A case report)[J]. Information Technology Newsweekly,2020.[68]. Information Technology; New Findings from P. Yan and Co-Researchers in the Area of Information Technology Described (BrainEXP: a database featuring with spatiotemporal expression variations and co-expression organizations in human brains)[J]. Information Technology Newsweekly,2020.[69]. IDERA; IDERA Database Tools Expand Support for Cloud-Hosted Databases[J]. Information Technology Newsweekly,2020.[70]Adrienne Warner,David A. Hurley,Jonathan Wheeler,Todd Quinn. Proactive chat in research databases: Inviting new and different questions[J]. The Journal of Academic Librarianship,2020,46(2).[71]Chidentree Treesatayapun. Discrete-time adaptive controller based on IF-THEN rules database for novel architecture of ABB IRB-1400[J]. Journal of the Franklin Institute,2020.[72]Tian Fang,Tan Han,Cheng Zhang,Ya Juan Yao. Research and Construction of the Online Pesticide Information Center and Discovery Platform Based on Web Crawler[J]. Procedia Computer Science,2020,166.[73]Dinusha Vatsalan,Peter Christen,Erhard Rahm. Incremental clustering techniques for multi-party Privacy-Preserving Record Linkage[J]. Data & Knowledge Engineering,2020.[74]Ying Xin Liu,Xi Yuan Li. Design and Implementation of a Business Platform System Based on Java[J]. Procedia Computer Science,2020,166.[75]Akhilesh Kumar Bajpai,Sravanthi Davuluri,Kriti Tiwary,Sithalechumi Narayanan,Sailaja Oguru,Kavyashree Basavaraju,Deena Dayalan,Kavitha Thirumurugan,Kshitish K. Acharya. Systematic comparison of the protein-protein interaction databases from a user's perspective[J]. Journal of Biomedical Informatics,2020,103.[76]P. Raveendra,V. Siva Reddy,G.V. Subbaiah. Vision based weed recognition using LabVIEW environment for agricultural applications[J]. Materials Today: Proceedings,2020,23(Pt 3).[77]Christine Rosati,Emily Bakinowski. Preparing for the Implementation of an Agnis Enabled Data Reporting System and Comprehensive Research Level Data Repository for All Cellular Therapy Patients[J]. Biology of Blood and Marrow Transplantation,2020,26(3).[78]Zeiser Felipe André,da Costa Cristiano André,Zonta Tiago,Marques Nuno M C,Roehe Adriana Vial,Moreno Marcelo,da Rosa Righi Rodrigo. Segmentation of Masses on Mammograms Using Data Augmentation and Deep Learning.[J]. Journal of digital imaging,2020.[79]Dhaked Devendra K,Guasch Laura,Nicklaus Marc C. Tautomer Database: A Comprehensive Resource for Tautomerism Analyses.[J]. Journal of chemical information and modeling,2020,60(3).[80]Pian Cong,Zhang Guangle,Gao Libin,Fan Xiaodan,Li Fei. miR+Pathway: the integration and visualization of miRNA and KEGG pathways.[J]. 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Medical fusion framework using discrete fractional wavelets and non-subsampled directional filter banks[J]. IET Image Processing,2020,14(4).[90]Qian Liu,Bo Jiang,Jia-lei Zhang,Peng Gao,Zhi-jian Xia. Semi-supervised uncorrelated dictionary learning for colour face recognition[J]. IET Computer Vision,2020,14(3).[91]Yipo Huang,Leida Li,Yu Zhou,Bo Hu. No-reference quality assessment for live broadcasting videos in temporal and spatial domains[J]. IET Image Processing,2020,14(4).[92]Panetta Karen,Wan Qianwen,Agaian Sos,Rajeev Srijith,Kamath Shreyas,Rajendran Rahul,Rao Shishir Paramathma,Kaszowska Aleksandra,Taylor Holly A,Samani Arash,Yuan Xin. A Comprehensive Database for Benchmarking Imaging Systems.[J]. IEEE transactions on pattern analysis and machine intelligence,2020,42(3).[93]Rahnev Dobromir,Desender Kobe,Lee Alan L F,Adler William T,Aguilar-Lleyda David,Akdo?an Ba?ak,Arbuzova Polina,Atlas Lauren Y,Balc? 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Christina,Kvam Peter D,Kwok Sze Chai,Lebreton Ma?l,Lempert Karolina M,Ming Lo Chien,Luo Liang,Maniscalco Brian,Martin Antonio,Massoni Sébastien,Matthews Julian,Mazancieux Audrey,Merfeld Daniel M,O'Hora Denis,Palser Eleanor R,Paulewicz Borys?aw,Pereira Michael,Peters Caroline,Philiastides Marios G,Pfuhl Gerit,Prieto Fernanda,Rausch Manuel,Recht Samuel,Reyes Gabriel,Rouault Marion,Sackur Jér?me,Sadeghi Saeedeh,Samaha Jason,Seow Tricia X F,Shekhar Medha,Sherman Maxine T,Siedlecka Marta,Skóra Zuzanna,Song Chen,Soto David,Sun Sai,van Boxtel Jeroen J A,Wang Shuo,Weidemann Christoph T,Weindel Gabriel,WierzchońMicha?,Xu Xinming,Ye Qun,Yeon Jiwon,Zou Futing,Zylberberg Ariel. The Confidence Database.[J]. Nature human behaviour,2020,4(3).[94]Taipalus Toni. The Effects of Database Complexity on SQL Query Formulation[J]. Journal of Systems and Software,2020(prepublish).[95]. Information Technology; Investigators from Deakin University Target Information Technology (Conjunctive query pattern structures: A relational database model for Formal Concept Analysis)[J]. Computer Technology Journal,2020.[96]. Machine Learning; Findings from Rensselaer Polytechnic Institute Broaden Understanding of Machine Learning (Self Healing Databases for Predictive Risk Analytics In Safety-critical Systems)[J]. Computer Technology Journal,2020.[97]. Science - Library Science; Investigators from Cumhuriyet University Release New Data on Library Science (Scholarly databases under scrutiny)[J]. Computer Technology Journal,2020.[98]. Information Technology; Investigators from Faculty of Computer Science and Engineering Release New Data on Information Technology (FGSA for optimal quality of service based transaction in real-time database systems under different workload condition)[J]. Computer Technology Journal,2020.[99]Muhammad Aqib Javed,M.A. Naveed,Azam Hussain,S. Hussain. Integrated data acquisition, storage and retrieval for glass spherical tokamak (GLAST)[J]. Fusion Engineering and Design,2020,152.[100]Vinay M.S.,Jayant R. Haritsa. Operator implementation of Result Set Dependent KWS scoring functions[J]. Information Systems,2020,89.[101]. Capital One Services LLC; Patent Issued for Computer-Based Systems Configured For Managing Authentication Challenge Questions In A Database And Methods Of Use (USPTO 10,572,653)[J]. Journal of Robotics & Machine Learning,2020.[102]Ikawa Fusao,Michihata Nobuaki. In Reply to Letter to the Editor Regarding "Treatment Risk for Elderly Patients with Unruptured Cerebral Aneurysm from a Nationwide Database in Japan".[J]. World neurosurgery,2020,135.[103]Chen Wei,You Chao. Letter to the Editor Regarding "Treatment Risk for Elderly Patients with Unruptured Cerebral Aneurysm from a Nationwide Database in Japan".[J]. World neurosurgery,2020,135.[104]Zhitao Xiao,Lei Pei,Lei Geng,Ying Sun,Fang Zhang,Jun Wu. Surface Parameter Measurement of Braided Composite Preform Based on Faster R-CNN[J]. Fibers and Polymers,2020,21(3).[105]Xiaoyu Cui,Ruifan Cai,Xiangjun Tang,Zhigang Deng,Xiaogang Jin. Sketch‐based shape‐constrained fireworks simulation in head‐mounted virtual reality[J]. Computer Animation and Virtual Worlds,2020,31(2).[106]Klaus B?hm,Tibor Kubjatko,Daniel Paula,Hans-Georg Schweiger. New developments on EDR (Event Data Recorder) for automated vehicles[J]. Open Engineering,2020,10(1).[107]Ming Li,Ruizhi Chen,Xuan Liao,Bingxuan Guo,Weilong Zhang,Ge Guo. A Precise Indoor Visual Positioning Approach Using a Built Image Feature Database and Single User Image from Smartphone Cameras[J]. Remote Sensing,2020,12(5).[108]Matthew Grewe,Phillip Sexton,David Dellenbach. Use Risk‐Based Asset Prioritization to Develop Accurate Capital Budgets[J]. Opflow,2020,46(3).[109]Jose R. Salvador,D. Mu?oz de la Pe?a,D.R. Ramirez,T. Alamo. Predictive control of a water distribution system based on process historian data[J]. Optimal Control Applications and Methods,2020,41(2).[110]Esmaeil Nourani,Vahideh Reshadat. Association extraction from biomedicalliterature based on representation and transfer learning[J]. Journal of Theoretical Biology,2020,488.[111]Ikram Saima,Ahmad Jamshaid,Durdagi Serdar. Screening of FDA approved drugs for finding potential inhibitors against Granzyme B as a potent drug-repurposing target.[J]. Journal of molecular graphics & modelling,2020,95.[112]Keiron O’Shea,Biswapriya B. Misra. Software tools, databases and resources in metabolomics: updates from 2018 to 2019[J]. Metabolomics,2020,16(D1).[113]. Information Technology; Researchers from Virginia Polytechnic Institute and State University (Virginia Tech) Describe Findings in Information Technology (A database for global soil health assessment)[J]. Energy & Ecology,2020.[114]Moosa Johra Muhammad,Guan Shenheng,Moran Michael F,Ma Bin. Repeat-Preserving Decoy Database for False Discovery Rate Estimation in Peptide Identification.[J]. Journal of proteome research,2020,19(3).[115]Huttunen Janne M J,K?rkk?inen Leo,Honkala Mikko,Lindholm Harri. Deep learning for prediction of cardiac indices from photoplethysmographic waveform: A virtual database approach.[J]. International journal for numerical methods in biomedical engineering,2020,36(3).[116]Kunxia Wang,Guoxin Su,Li Liu,Shu Wang. Wavelet packet analysis for speaker-independent emotion recognition[J]. Neurocomputing,2020.[117]Fusao Ikawa,Nobuaki Michihata. In Reply to Letter to the Editor Regarding “Treatment Risk for Elderly Patients with Unruptured Cerebral Aneurysm from a Nationwide Database in Japan”[J]. World Neurosurgery,2020,135.[118]Wei Chen,Chao You. Letter to the Editor Regarding “Treatment Risk for Elderly Patients with Unruptured Cerebral Aneurysm from a Nationwide Database in Japan”[J]. World Neurosurgery,2020,135.[119]Lindsey A. Parsons,Jonathan A. Jenks,Andrew J. Gregory. Accuracy Assessment of National Land Cover Database Shrubland Products on the Sagebrush Steppe Fringe[J]. Rangeland Ecology & Management,2020,73(2).[120]Jing Hua,Yilu Xu,Jianjun Tang,Jizhong Liu,Jihao Zhang. ECG heartbeat classification in compressive domain for wearable devices[J]. Journal of Systems Architecture,2020,104.以上就是关于数据库英文参考文献的全部内容，希望看完后对你有所启发。
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12、 Nucleic Acids Research /
13、 Plant Cell http://www.plantcell
14、 Plant Physiology
University of Pretoria : Electronic Theses and Dissertations
http://upetd.up.ac.za/
10、 Kluwer
荷兰Kluwer Academic Publisher是具有国际性声誉的学术出版商，它出版的图书、期刊一向品质较高，备受专家和学者的信赖和赞誉。Kluwer Online是Kluwer出版的750余种期刊的网络版，专门基于互联网提供Kluwer电子期刊的查询、阅览服务。
德国著名出版社Springer提供的数据库，包括该出版社出版的430余种期刊的全文。
18、UMI /pqdweb
商业数据库
三、关于生命科学的出版物
1、 美国科学杂志中文版：
2、 遗传：
8、 Idealibrary
世界著名全文数据库，与Elsvier 等出版社有合作,今年年底将于SCIENCEDIRECT合并
9、 Ingenta/Uncover
是Ingenta公司的一个主要产品，是一个全球性学术研究的大型网关。它致力于学术研究性文章的网上检索和传递，目前收集有25，000种出版物的摘要和4，500种出版物全文。140个出版商在上提供了他们的文章全文。
Williams Obstetrics - 22nd Ed. (2005)
还有一些免费外文文献网站。
/cgi/collection/MDG?page=77
/cgi/search/
6、 ECO /oclcpsp/oclclogin.jsp
即OCLC或First Search也是一个综合性较强的数据库，大部分文章都有全文。
7、 Highwire
世界上第二大免费数据库（最大的免费数据库没有生物学、农业方面的文献），该网站提供部分文献的免费检索，和所用文献的超级链接，免费文献在左边标有FREE.
15、 Science Magazine：/
===============================================
1.Nova Southeastern University（高权限）
入口：
Universitatsbibliothek Munchen ( Germany )
http://edoc.ub.uni-muenchen.de/perl/advsearch
University of Campinas Faculty of Education
/cr/uchsc/main
/Pubs/ETD/
University of Florida
/etd.html
University of Georgia Electronic Theses and Dissertations (Summer 1999 to present)
ID：hpdlibrary PW：library
资源列表：
ACP Medicine (2006)
AHFS Drug Information? (2006)
Basic and Clinical Pharmacology - 9th Ed. (2004)
Current Diagnosis & Treatment in Orthopedics - 4th Ed. (2006)
/current.shtml
/
/
:2048/menu
/data/databases_alpha.htm
Rudolph's Pediatrics - 21st Ed. (2003)
Schwartz's Principles of Surgery - 8th Ed. (2005)
Smith's General Urology - 16th Ed. (2004)
USP DI? Drug Info. for the Health Care Pro. - 26th Ed. (2006)
3、 万方数据库
收录了核心期刊的全文，文件为pdf格式，阅读全文需Acrobat Reader 浏览器。
二、 外文全文站点(所有外文数据库，阅读全文均需要Acrobat Reader)：
1、 Annual Reviews
该数据库收录各学科的综述性文章按SCI影响因子极高。
OVID Kluwer .br/kluwer
北京大学镜像站点：/
11、 Lexis-nexis /universe
12、Nature Press
一、 中文数据库
1、 清华同方学术期刊网
中国最大的数据库，内容较全。收录了5000多种中文期刊，1994年以 来的数百万篇文章，并且目前正以每天数千篇的速度进行更新。阅读全文需在网站主页下载CAJ全文浏览器（3.7M）。
2、维谱全文数据库
文献收录1989年以来的全文。只是扫描质量有点差劲，1994年以后的数据不如CNKI全。阅读全文需下载维谱全文浏览器，约7M。
2、 BiomedNet 即BMN
世界上著名医学、生命科学数据库。
3、 Blackwell-syn /
该数据库包括Plant J. Plant Molecular Biotechnology等影响因子较高的期刊
/
/
/yxbslw/pxjg/2004/2004ybxk.htm（SupFree52004年国家获奖论文集）
国外大学免费硕博全文数据库以及部分期刊全文
16、Sciencedirect ience建立的全文检索数据库，包括原来的Idealibrary在内的期刊总计1500多种。
17、Springer 德国站点http://link.springer.de/
/cgi-bin ... on=search&_cc=1
Australian Digital Theses Program
.au/
University of New Orleans
/
/
:2048/login
/
/
/
Current Medical Diagnosis & Treatment - 45th Ed. (2006)
Current Obstetric & Gynecologic Diagnosis & Treatment - 9th Ed. (2003)
Delmar's Fundamental & Advanced Nursing Skills - 2nd Ed. (2004)
13、OVID：
综合性数据库有medline等
14、Oxford Reference http://www.oxfordreference.
15、Oxford Press http://www.oup.co牛津大学出版社出版的150多种期刊
7、 Genes and Development
8、 JBC（著名生化）
10、 Journal of Molecular Biology /journals/list/latest?jcode=jmb
3、 Cell /
4、 Crop Science /
5、 Developmental Biology http://www.ijdb.ehu.es
6、 EMBO /
Geriatric Medicine: An Evidence Based Approach - 4th Ed. (2003)
Griffith's 5-Minute Clinical Consult - 14th Ed. (2006)
Merck Manual - 17th Ed. (1999) Centennial Edition
4、 Carctword /
一个综合性数据库
5、 EBSCO
EBSCO公司是专门经营纸本期刊、电子期刊发行和电子文献数据库出版发行业务的集团公司。其数据库是一个大型综合数据库，其中的学术研究精粹数据库（Academic Search Elit）包括生物科学、工商经济、咨询科技、通讯传播、工程、教育、艺术、医药学等领域的1,700余种全文期刊，该数据库每天更新。Academic Search Premier 包括3，400余种科技期刊。
/content/vol11/issue3/index.shtml
/retrieval/English.htm
/entrez/query.cgi
/content/vol32/suppl_1/