BIPS:BIANA Interolog Prediction Server.A tool for protein–protein interaction inference
Javier Garcia-Garcia 1,Sylvia Schleker 2,Judith Klein-Seetharaman 2,3and Baldo Oliva 1,*
1
Structural Bioinformatics Laboratory (GRIB-IMIM),Universitat Pompeu Fabra,Barcelona Research Park of
Biomedicine (PRBB),08003Barcelona,Catalonia,Spain,2Forschungszentrum Ju
¨lich,Institute of Complex Systems (ICS-5),52425Ju
¨lich,Germany and 3
Department of Structural Biology,University of Pittsburgh,Pittsburgh,PA 15260,USA
Received February 25,2012;Revised May 16,2012;Accepted May 17,2012
ABSTRACT
Protein–protein interactions (PPIs)play a crucial role in biology,and high-throughput experiments have greatly increased the coverage of known inter-actions.Still,identification of complete inter-and intraspecies interactomes is far from being complete.Experimental data can be complemented by the prediction of PPIs within an organism or between two organisms based on the known interactions of the orthologous genes of other organisms (interologs).Here,we present the BIANA (Biologic Interactions and Network Analysis)Interolog Prediction Server (BIPS),which offers a web-based interface to facilitate PPI predictions based on interolog information.BIPS benefits from the capabilities of the framework BIANA to integrate the several PPI-related databases.Additional metadata can be used to improve the reliability of the predicted interactions.Sensitivity and specificity of the server have been calculated using known PPIs from different interactomes using a leave-one-out approach.The specificity is between 72and 98%,whereas sensitivity varies between 1and 59%,depending on the sequence identity cut-off used to calculate similarities between sequences.BIPS is freely accessible at http://sbi.imim.es/BIPS.php.INTRODUCTION
The number of protein–protein interactions (PPIs)experi-mentally obtained for proteomes of entire species is smaller than the number of expected PPIs (1).Even the number of interactions between proteins in yeast,one of the most studied organisms,is still believed to be underestimated (2).To complement experimental data,several computational methods have been developed to predict PPIs (3,4).One example is the use of experimen-tally identi?ed interactions in one organism to predict the interactions in other organisms assuming that homolog proteins preserve their ability to interact (5,6).The basis of this hypothesis is to assume that homologs have similar functional behaviour;therefore,they preserve the same PPIs.The prediction of the interaction between the homologs of two interacting proteins is de?ned as interolog (conservation of PPIs).Several works have used interologs to extend our knowledge about interactomes (7,8)or to predict pathogen/host cross-species PPIs (9,10).Up to now,most predictions based on interologs are restricted to a few species or a limited set of template interactions.For example,Yu et al .(5)transferred the known interactions of yeast to four different species.Similarly,Wiles et al .(11)developed InterologFinder,a tool to map the interactions integrated in MiMi (12)to ?ve species.Interestingly,PPISearch (13)implements the interolog approach providing different scoring functions,but is restricted to the analysis of a single protein pair at any submission instance.Recently,Gallone et al .(14)developed a Perl module to automate predictions based on interologs,using optional metadata to rank the interactions.However,this still requires programming skills.The current limitations stem from the fact that information of known PPIs is spread among several repositories,and sets of PPIs from different databases show a low intersection (15,16).This challenge has led to the development of data integration strategies,such as Biologic Interactions and Network Analysis (BIANA)(17).BIANA is a program framework used in the integration of biological databases mostly focused on PPI databases.
Here,we present the BIANA Interolog Prediction Server (BIPS).BIPS offers a web interface to facilitate the prediction of PPIs based on interologs for a set of proteins provided by the user as input,including entire proteomes.The server bene?ts from the integration capabilities of BIANA to use a large data set of experi-mentally identi?ed PPIs.BIANA also offers additional
*To whom correspondence should be addressed.Tel:+34933160509;Fax:+34933160550;Email:baldo.oliva@https://www.doczj.com/doc/b05485406.html,
Published online 11June 2012
Nucleic Acids Research,2012,Vol.40,Web Server issue W147–W151
doi:10.1093/nar/gks553
?The Author(s)2012.Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://www.doczj.com/doc/b05485406.html,/licenses/by-nc/3.0),which permits unrestricted non-commercial use,distribution,and reproduction in any medium,provided the original work is properly cited.
information such as gene ontology(GO)terms,clusters of orthologous genes and many other attributes such as pre-dicted number of transmembrane helices,which gives the user the freedom to restrict the predictions according to selected features.
MATERIALS AND METHODS
The interolog hypothesis implies that two proteins(A and B)are predicted to interact if a known interaction between two proteins(A’and B’)exists,such that A is similar to A’and B similar to B’.The interaction between the proteins A and B is called target interaction(with A and B being de?ned as protein targets),whereas the interaction between proteins A’and B’is called template interaction (with A’and B’being de?ned as templates).In the BIPS server,protein A is the query protein submitted by the user,and protein B is the predicted partner.This broad de?nition of interologs implies that the hypothesis works not only for orthologs but also for paralogs of the same species.
Sequence similarity measure
Sequence similarity between proteins relies on basic local alignment search tool(BLAST)alignments(18).Query protein sequences are aligned against all sequences with known interactions stored in the BIANA MySQL database(17).The alignments provide a similarity measure based on the percentage of identical residues aligned and the percentage of the sequence length of the queries and templates covered by the alignment(query and template coverage,respectively).We use a threshold of 90%of template coverage to ensure that the prediction is not inferred from local regions of the template inter-action.The geometric mean of individual identities(joint identities)and the geometric mean of individual BLAST E-values(joint E-value)are also considered,as proposed by Yu et al.(5).The BIPS server uses a local database of stored similarity measures to avoid unnecessary repeated BLAST searches.This speeds up the server,allowing users to obtain predictions of interactions of full proteomes in manageable time.In this manner,only entirely new se-quences consume extra time in the?rst run.
Domain interactions
We hypothesize that protein A interacts with protein B if a domain A’can be assigned to A and a domain B’to B,such that A’and B’are interacting domains in the iPfam(19)or the3DID(20)database.We measure the similarity of the target sequences(A and B)with Pfam domains as a function of the E-value calculated with the package HMMER 3.0(21).We assign Pfam domains using an E-value cut-off of10à5in the Pfam A database. Source databases
Template interactions were extracted using the BIANA framework(17)integrating the following10databases: DIP(22),HPRD(23),IntAct(24),MINT(25),MPact (26),PHI_base(27),PIG(28),BioGRID(29),BIND (30)and VirusMINT(31).It has been noted that PPI databases share little overlap(16).Therefore,using the integration of multiple sources instead of a single source greatly enlarges the set of predictions.Furthermore,we have used BIANA to include information from other databases such as Uniprot(32)and GO(33).This add-itional information can be used to interpret the prediction results and select predicted interactions deemed interesting e.g.for experimental validation.Finally,sources of domain–domain interactions are also included,using iPfam(19)and3DID(20).
Functional annotation
Interacting proteins likely share biological processes or share similar locations compared with non-interacting proteins(4).Thus,we can use a number of similar func-tional annotations between each pair of proteins predicted to interact to rank the predictions.BIPS uses GO annotations to select the most probable prediction for a query protein by selecting those partners that share similar GO terms.The similarity between GO terms implies that either they are equal or there is a parenthood relationship between them.In addition,GO term semantic similarity and the functional similarity of genes are computed using the method proposed by Wang et al.(34) Clusters of orthologous genes
Two proteins are considered orthologous if they are included in the same cluster of orthologous genes. Ortholog de?nitions between proteins are extracted from eggNOG(35)and Ensembl Compara(36)databases.Our predictions can be?ltered assuming the traditional de?n-ition of interologs:two target proteins are supposed to interact if they are orthologous to two known interaction partners.
DESCRIPTION OF THE WEBSERVER
Input
Proteins for which the user wants to predict putative binding partners can be uploaded as a list of sequences in FASTA format or a list of protein identi?ers (i.e.UniProt Accession,Uniprot entry and gene symbol,etc.).
Output
The output is a list of predictions that can be viewed or downloaded.The user can browse the data associated with the predicted partners.Some details of the template inter-action,such as the source database of the interaction and the method of detection,are provided.The user can select several parameters helping estimate the reliability of the predictions:(i)sequence similarity measures,(ii)checking domain–domain interactions(either using domains from 3DID or iPfam),(iii)checking common GO terms between the predicted partners of an interaction and (iv)using clusters of orthologous genes for the prediction. Additionally,template interactions can be restricted to a subset of proteins to improve the reliability of the pre-dictions.For example,the user can select interactions
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based on the experimental methods by which the template interactions were observed,the number of experiments con?rming the template interaction or the number of species in which the interaction between homolog pairs of the template was observed.
Finally,the user can restrict the list of predictions, reducing the number of predictions to a manageable size.The user can select speci?c partners:(i)those with speci?c keywords in their descriptive attributes,(ii)those associated with a certain pathology,(iii)those belonging to a speci?c taxon,including the case in which query proteins are from a particular pathogen,and the predicted partners are from selected hosts,(iv)those belonging to a subset of proteins uploaded by the user and(v)those with transmembrane predicted regions[calculated with TMHMM(37)].
BENCHMARK
We have checked the validity of our predictions by two approaches.In the?rst approach,speci?c known interactomes reported in BIANA were predicted using the leave-one-out strategy.For each interaction being tested,all interactions reported in BIANA were used as templates including the interactions of the same organism, but excluding the interaction being tested.Several organ-isms covering different taxonomy groups were considered (see Table1).Sensitivity was calculated by testing the percentage of known interactions correctly predicted over the total of known interactions.Between1and 59%of known interactions were predicted by using a sequence identity cut-off ranging from30to90%.In a complementary approach,we used the negatome database(38)as a source for non-interactions to calculate speci?city.Speci?city was calculated as the percentage of correctly predicted negative interactions(true negatives) out of1291non-interacting pairs.The speci?city ranged between72and98%.However,the study of speci?city is not enough to quantify false positive predictions in the PPI context because the number of non-interacting protein pairs is larger than the number of interacting pairs.Indeed,a high speci?city does not necessarily mean that a large proportion of the predicted interactions is correct[i.e.positive predictive value(PPV)].We selected the Arabidopsis interactome(39)to estimate an example of the PPV of our predictions(see Table1).This is one of the newest data sets of PPIs available,and we have to note that its authors estimated that their experiment had already a precision of80%and a sensitivity of16%.A more detailed comparison with a previous interolog approach is shown in Supplementary Table S1. DISCUSSION
We have presented a PPI prediction server,BIPS,which is based on the similarity between protein sequences and PPIs reported in several biological databases integrated using the BIANA framework.BIPS bene?ts from the large amount of information deposited in these databases. By increasing the number of template interactions, coverage of the predictions is greatly improved. Traditionally,the interolog approach has been de?ned as the transference of interactions between orthologs from different species.However,the distinction between orthologs(gene pairs that trace back to speciation)and paralogs(gene pairs resulting from duplication events)is not always clear,as it depends on the last common ancestor applied.BIPS makes no distinction between orthologs and paralogs.In contrast,BIPS relies directly on pair-to-pair similarities to perform its inferences. Comparison of predictions based only on groups of orthologous genes show comparable results when applying a pair-to-pair sequence similarity cut-off between30and70%identity(see Table1).The main advantages of BIPS over other servers are the capability to predict interactions on a large scale such as for whole proteomes,in a reasonable time,the use of up-to-date database information and the option for the user to select several?lters to improve con?dence in the results. The latter is based on the notion that using additional information about the protein targets and template inter-actions increases the reliability of the predictions.The most trustable predictions are observed when the sequence similarity measure is restrictive and some?lters
Table1.Sensitivity(a),speci?city(b)and PPV(c)of the prediction of different data sets by varying the?ltering conditions
Data set90%identity70%identity30%identity eggNOG
All Dom GO COG All Dom GO COG All Dom GO COG All
Arabidopsis(a)17%3%8%7%31%5%16%13%53%8%25%21%32% Yeast(a)13%0%4%6%17%0%5%6%30%1%10%14%33% Human(a)11%1%5%4%23%2%10%8%42%4%17%15%28% Mouse(a)17%1%6%8%36%2%12%14%59%3%18%20%27% Drosophila(a)4%0%1%0%5%0%1%1%10%1%2%2%8% Worm(a)1%0%0%0%4%1%2%1%12%2%6%4%11% Negatome(b)92%98%95%97%88%97%91%96%72%92%78%97%77% Arabidopsis(c)(d) 1.27% 4.92% 2.33% 1.67%0.56%4% 1.23%0.63%0.07%0.56%0.17%0.06%0.03%
The percentage indicates sensitivity(a),speci?city(b)or PPV(c).(d)Main screen data set from the Arabidopsis interactome map for8596 Arabidopsis proteins,with a precision of80%and a sensitivity of16%(38).All,all predictions without applying any restriction;Dom,predictions ?ltered by known interacting domains reported in3DID or iPfam;GO,predictions?ltered by GO term similarity(biological process or cellular compartment);COG,predictions?ltered by known interacting proteins in the same clusters of orthologous groups.Clusters of orthologous genes were as de?ned in the eggNOG database excluding non-supervised clusters.
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are applied(see sensitivity and speci?city values in Table1).All these capabilities provide the user with a useful tool to select predictions and focus on a speci?c research area.
SUPPLEMENTARY DATA
Supplementary Data are available at NAR Online: Supplementary Table1.
FUNDING
Spanish Ministry of Science and Innovation(MICINN); German Federal Ministry of Education and Research (BMBF);partners of the ERASysBio+initiative sup-ported under the EU ERA-NET Plus scheme in FP7 (SHIPREC)Euroinvestigacio n[EUI2009-04018],as well as FEDER[BIO2011-22568,PSE-0100000-2009]. Funding for the open access charge:ERASysBio+initia-tive supported under the EU ERA-NET Plus schme in FP7(SHIPREC)Euroinvestigacio n[EUI2009-04018]. Con?ict of interest statement.None declared. REFERENCES
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Nucleic Acids Research,2012,Vol.40,Web Server issue W151
前言 一、车辆使用过程中的重要注意事项 承蒙您选购本公司的汽车，谨表谢意。 欢迎您加入驾驶本公司车辆的行列。 我们确信，您一定会对自己的选择感到满意。 本车辆是集中了东风汽车有限公司最先进的技术而制造的，我们为了使各位驾驶员更好地了解本公司车辆的正确使用方法及保养方法，同时为了既能安全、经济驾驶又能延长车辆的使用寿命，在各车辆上配各了汇集使用注意事项的车辆使用说明手册。 请您在驾驶之前。务必阅读本车辆的使用说明手册，熟悉车辆的正确使用方法。如果对本车辆的装置及其操作方法、车辆的维修保养等有不明之处时请您向东风NISSAN专营店询问，他们一定会高兴地为您服务。 1、关于起动发动机 1）确实拉紧驻车制动器。确认变速杆是 否在空档的位置（自动变速器的变速杆放到 P或N的位置）。为了减少发动机转动时的阻 力，把离合器踩到底后再起动发动机。 2）为延长起动机和蓄电池的寿命，起动 机的连续起动时间请不要超过10秒钟。需要 再次起动时把点火钥匙转回OFF的位置，等 待10秒钟以后再起动。 3）冬季使用车辆时必须预热发动机，当 水温表的指针开始移动时，方可驾驶。
2、关于经济驾驶方法 1）离合器的连接要缓慢，车辆起步要平 稳。在发动机高转速的状态下起步，会使燃 料的消耗量增加，离合器的寿命也会缩短。 2）绝对禁止二档起步。二档起步会给发 动机、离合器、变速器、齿轮等带来不必要 的负荷而加速损坏。 3）为了节省燃料和延长发动机的使用寿 命，一档起步以后，请务必按照说明手册所 推荐的车速来进行换挡。比如四档，车速必 须在50公里以上使用；低速（如30公里） 时，若过早换到高速档，发动机会发生爆震。 运行中发生爆震，除了使发动机的动力下降 以外，燃料消耗量也会极端恶化；另外，严 重爆震会成为发生汽缸密封垫冲坏、曲轴瓦 烧接等重大故障的原因；当然，在低速档运 转车辆在推荐速度以上行驶，这也会成为发 动机超速运转而造成轴 瓦、活塞环烧接等的原因， 且在这种情况下燃料消耗 量也必然会增加。 4）关于的内外清洗 车辆使用的燃料，请 参看推荐的燃料／润滑油 表。 汽油车不能使用低标 号汽油，若使用将会显著 缩短发动机寿命。 >$@对于因使用规定以外的燃料及操作不当而发生的故障，本公司将不进行任何保证。>$@
本科毕业设计 题目：DF12型手扶拖拉机变速驱动系统设计 学院： 姓名： 学号： 专业：机械设计制造及其自动化 年级： 指导教师：
摘要 随着变型运输拖拉机和农用运输车的发展，原来依靠农村运输业发展起来的小四轮拖拉机逐步转向田间地头。然而，目前小四轮拖拉机田间作业能力差，又没有很多配套的农业机械，农忙季节短，致使大量小四轮拖拉机一年中作业时间短，被迫长期闲置着。这影响了农村专业户的作业效益，也造成了不应该有的资源浪费。针对这些情况，我们在原有小四轮拖拉机的基础上稍微作些改动，使它的功能延伸。譬如可在原来小四轮拖拉机的基础上，改变座位、方向盘、离合、油门、刹车的方位，把拖拉机变成倒开式，在变速箱后安装挖掘装置、铲运装置或装载装置而成。 本次毕业设计是对机械专业学生在毕业前的一次全面训练，目的在于巩固和扩大学生在校期间所学的基础知识和专业知识，训练学生综合运用所学知识分析和解决问题的能力。是培养、锻炼学生独立工作能力和创新精神之最佳手段。毕业设计要求每个学生在工作过程中，要独立思考，刻苦钻研，有所创造的分析、解决技术问题。通过毕业设计，使学生掌握改造方案的拟定、比较、分析及进行必要的计算。 关键字：齿轮操纵机构轴轴承锁定机构
DESING of a CERTAIN TYPE of TRACTOR GEARBOX With variant transport tractors and agricultural the development of carriage car, depends on rural transportation industry to develop the small four-wheel tractor to field edge of a field. However, at present, small four-wheel the tractor field work ability is poor, and not many ancillary agricultural machinery, busy season is short, resulting in a large number of small four-wheel tractor year short operation time, forced long-term idle. The influence of rural specialist work benefit, also cause should not be some waste of resources. In light of these circumstances, we in the original small four-wheel tractor based on slightly to make some changes, make it functional extension. For example, in the original small four-wheel tractor based on, change seats, steering wheel, clutch, throttle, brake position, the tractor into inverted open, in a gearbox installed after digging device, lifting device or a loading device. The graduation design is about mechanical speciality students before graduation and a comprehensive training, purpose is to consolidate and expand the students learn the basic knowledge and professional knowledge, training students' comprehensive use of the knowledge the ability to analyze and solve problems. Is training, training students the ability to work independently and the spirit of innovation is the best means. Graduation design requirements of each student in the course of the work, we need to think independently, study assiduously, create somewhat analysis, solving technical problems. Through the graduation project, so that students master the transformation plan formulation, comparison, analysis and necessary calculation. Key words:Gear Manipulation of body Axis Bearing Locking mechanism
DAQ数据撷取卡快速使用指南 首先感谢您选购NI的DAQ产品，以下将简短地为您叙述快速安装与使用DAQ卡的步骤。 在安装DAQ的硬件之前，请您先确认是否安装了DAQ的驱动程序，基本上您的计算机必须有Measurement And Automation (MAX)来管理您所有的NI装置，另外您必须安装NI-DAQ软件，目前建议安装最新的版本(您可利用光盘安装或是上网下载最新版本驱动程序https://www.doczj.com/doc/b05485406.html,/support点选Drivers and Updates)，新版驱动程序可支持大多数NI的DAQ卡片，包含S、E、M系列以及USB接口产品。 在安装完成NI-DAQ之后，您可以在桌面上发现有MAX应用程序，此时您可以关闭计算机，进行硬件安装，将PCI或是PCMCIA接口的DAQ卡片插入并重新开机，开机之后操作系统会自行侦测到该装置，并且自动安装驱动程序，依照对话框的带领便能顺利完成安装程序。 安装程序完成后，建议您开启MAX在Device and interface选项中会有Traditional DAQ 以及DAQmx两个类别，那是依照您的卡片型号支持哪一种API而分类，一般而言，Ｅ系列卡片两种都支持，而Ｍ系列只支持DAQmx，Ｓ系列则不一定，在对应的Traditional DAQ 或DAQmx中找到您的DAQ卡片型号，然后建议您先进行校正以及测试。 您可参考https://www.doczj.com/doc/b05485406.html,/support/daq/versions确认您硬件适用的版本 如何做校正与硬件测试:
若需校正硬件，请于MAX中，您所安装的卡片型号上按鼠标右键选择self-calibration 即可，系统会对DAQ卡以现在温度做一次校正。 若需测试硬件，请于MAX中，您所安装的卡片型号上按鼠标右键选择Test Panels，然后选择所要测试的项目，并且依照接脚图将讯号连接妥当即可测试，建议您分别测试AI、AO、DI以及Counter。 接脚图： 您可以在MAX中的DAQmx找到您所安装的卡片型号，并按鼠标右键，选择Device Pinout便可以依照接脚图去连接相关接法，进行量测。 接线模式(Input Configuration)：接线模式一般有分为Differential、RSE、NRSE三种，其中以Differential最为准确，但此模式需要一次使用掉两个channel，一般而言，选择Differential
Package leaflet: Information for the user GeloMyrtol? forte 300 mg, gastro-resistant capsules, soft Active substance: Myrtol standardized to at least 75 mg limonene, 75 mg cineole and 20 mg alpha-pinene. Read all of this package leaflet carefully because it contains important information for you. This medicinal product is available without prescription. However, you still need to take GeloMyrtol? forte carefully to get the best results from it. - Keep this leaflet. You may need to read it again. - Ask your pharmacist if you need more information or advice. - You must contact a doctor if your symptoms worsen or do not improve after 10 days. - If any of the side effects affects gets serious or if you notice any side effects not listed in this leaflet, please tell your doctor or pharmacist. In this leaflet: 1. What GeloMyrtol? forte is and what it is used for 2. Before you take GeloMyrtol? forte 3. How to take GeloMyrtol? forte 4. Possible side effects 5. How to store GeloMyrtol? forte 6. Further information GeloMyrtol? forte is available in packs of 20, 50 and 100 gastro-resistant capsules, soft. 1. What GeloMyrtol? forte is and what it is used for Effect: GeloMyrtol? forte is a herbal medicine. It liquefies mucus and promotes its transport, makes mucus easier to cough up and reduces inflammation. Used to treat acute and chronic bronchitis and inflammation of paranasal sinuses (sinusitis) 2. Before you take GeloMyrtol? forte Do not take GeloMyrtol? forte: - if you have an inflammatory disorder of the stomach, gut or bile duct region, or if you have a severe liver disorder; - if you are known to be allergic (hypersensitive) to eucalyptus oil, sweet orange oil, myrtle oil, lemon oil or cineole (the main constituent of eucalyptus oil), or to any of the other ingredients. Take special care with GeloMyrtol? forte: - if your symptoms should persist or get worse, or if you develop shortness of breath or fever, or if you start coughing up mucus containing blood or pus-like matter, you should consult a doctor immediately. - if you suffer from bronchial asthma, whooping cough or other respiratory diseases accompanied by manifest hypersensitivity of the respiratory system, always consult your doctor before you take GeloMyrtol? forte. Taking other medicines Inform your doctor or pharmacist if you take/apply other medicines or did so recently even if it is/was a non-prescription product. Pregnancy and breast feeding Before you take any medicine ask your doctor or pharmacist. - Pregnancy: Animal studies do not indicate direct or indirect harmful effects on the foetus. Caution is basically advised when taking it during pregnancy. - Breast feeding: Due to the liposoluble properties of the active ingredient it can be assumed that its constituents are also present in the breast milk at minor concentrations. So far there has been no indication of any risk when using GeloMyrtol? forte during the time of breast feeding
新车主您看过车辆使用说明书吗 新老车主近八成以上的人都没有认真看过汽车使用说明书。有的车主甚至开了很长时间，也不知道备胎放在哪里，这实在是个尴尬的笑话；也有的车主一遇到问题就打电话找4S店求救，不但浪费时间还浪费金钱，其实翻开说明书，很多小故障都可以自己解决。而且不同的车型有很多不同之处，按以往的驾驶习惯来开，不见得正确。因此，找出你的说明书，花点时间仔细阅读，一定会有意外的收获。 1、发动机如何预热？ 错误观点：点火后等5分钟再起步，等水温升高了再走。 说明书观点：请勿在停车状态下预热发动机，在车外视野良好时要立即起步。这样发动机可更快达到其工作温度，开且有害物质排放更少。 根据一项统计数字显示：引擎机件部分的磨损，超过90％是在冷车发动后3分钟内造成的。正确的热车方法应该是在发动后3U秒兰1分钾后工贻。入木川午、期阴仪’后发动引擎，引擎
的上半部是处于没有机油、缺乏润滑的状况，大约要在发动后30s,才会因机油泵浦的运转而将机油运送到引擎最需要润滑的活塞、连杆及曲轴等部件。 2、点火后如何起步？ 错误观点：在怠速空转时大力轰几脚油门；只要热了车，上路可以随意开。 说明书观点：在发动机处于冷态时要避免高发动机转速、油门全开和加大发动机负荷。 尽管热了车，也要避免马上高转速行驶，正确的方法是保持低车速，引擎转速以不超过3000-3500转／分钟为限，一般保持在2000转1分钟。待引擎上升至正常工作温度后，再恢复“个人习惯”开车即可。 3、怎样刹车最科学最安全？ 错误观点：下坡全程踩住刹车控制车速。 说明书观点：在驶过较长的陡下坡之前要降低车速，挂入某个较低的挡位或选择某个较低的行驶挡。这样可以充分利用发动机制动并减轻制动器负荷。 下坡时，科学的方法是通过降挡来减速制动，而不是踩刹车。特别要提醒的是，有的有经验驾驶人为了省油，下坡或者下桥时用空挡滑行，而汽车放空挡（或熄火滑行）时，无法给油路或气路加压，汽车将无法正常使用制动。 4、车子积炭怎么处理？
在LabVIEW中驱动数据采集卡的三种方法 作者：EEFOCUS 文章来源：EDN China 一、引言 近年来，面向仪器的软件开发平台，如美国NI公司LabVIEW的成熟和商业化，使用者在配有专用或通用插卡式硬件和软件开发平台的个人计算机上，可按自己的需求，设计和组建各种测试分析仪器和测控系统。由于LabVIEW提供的是一种适应工程技术人员思维习惯的图形化编程语言，图形界面丰富，内含大量分析处理子程序，使用十分方便，个人仪器发展到了使用者也能设计，开发的新阶段。 鉴于是工程技术人员自己编制，调用软件来开发仪器功能，软件成了仪器的关键。故人们也称这类个人仪器为虚拟仪器，称这种主要由使用者自己设计，制造仪器的技术为虚拟仪器技术（Virtual Instrumentation Technology）。使用虚拟仪器技术，开发周期短、仪器成本低、界面友好、使用方便、可靠性高, 可赋于检测仪初步智能，能共享PC机丰富的软硬件资源，是当前仪器业发展的一个重要方面。 虚拟仪器的典型形式是在台式微机系统主板扩展槽中插入各类数据采集插卡，与微机外被测信号或仪器相连，组成测试与控制系统。但NI公司出售的，直接支持LabVIEW的插卡价格十分昂贵，严重限制着人们用LabVIEW来开发各种虚拟仪器系统。在LabVIEW中如何驱动其它低价位的数据采集插卡，成为了国内许多使用者面临的关键问题。 二、三种在LabVIEW中使用国产数据采集插卡的方法 笔者将近年来工程应用中总结出的三种在LabVIEW中驱动通用数据采集插卡的方法介绍如下。介绍中，以某市售8通道12位A/D插卡为例。设插卡基地址为base=0x100，在C语言中，选择信号通道ch的指令是_outp（base，ch），启动A/D的指令是_inp（base），采样量化后的12位二进制数的高4位存于base+2中，低8位存于base+3中。 1、直接用LabVIEW的In Port , Out Port图标编程 LabVIEW的Functions模板内Adevanced \ Memory中的In Port 、Out Port 图标，与_inp、_outp功能相同，因此可用它们画程序方框图, 设计该A/D插卡的驱动程序。N个通道扫描，各采集n点数据的LabVIEW程序方框图如图1所示。图中用LabVIEW的计时图标控制扫描速率。
产品说明书范文英文版 电子产品说明书——媒体音响英文说明书范例(中英) 便携式多媒体音响 Portable Multimedia Acoustics 使用说明书User’s Manual 专注于完美音质的追求?? Concentrate on perfect sound pursuit? 感谢您使用本公司出品的数码产品，为了让您轻松体验 产品，我们随机配备了内容详尽的使用说明，您从中可以获 取有关产品的介绍，使用方法等方面的知识。在您开始使用 本机之前请先仔细阅读说明书，以便您能正确的使用本机， 如有任何印刷错误或翻译失误望广大用户谅解，当涉及内容 有所更改时，恕不另行通知。 Thank you for using this digital product of our company. In order to let you experience the product swimmingly, detailed instruction is provided which you can find the product’s introduction, usage and other information. Before using this product, please read the manual carefully, so that you can correctly use it. In case of any printing or translation error, we apologize for the inconvenience. As for the content change, we are sorry for no further notice. 一、产品概述 General Information 本机是一款外观小巧，设计精美、携带方便多媒体小音响， 适用于家居、户外旅游、办公室等场所，随时随地享受音乐
车辆使用 1范围 适用于公司各部门办公用车的申请、调度及使用 2控制目标 2.1确保公司车辆使用均为办公所需，而且具有合理化与规范化 2.2确保为公司各部门的业务提供及时、完善的用车服务 3主要控制点 3.1部门用车应该根据车辆的标准经部门经理、主管副总或总经理的的审批 3.2办公室主任根据用车规定审批部门签批的车辆使用申请 3.3车辆使用人在用车之后需要在用车登记单上签署车辆服务反馈 4特定政策 4.1鼓励各部门业务用车提前48小时进行预定，但是不得晚于用车前24小时 4.2部门使用公司车辆，应该支付相应费用，小车费用计算方法：基本成本（公里数× 单价）＋紧急定车附加费，车辆单价由财务部负责计算 4.3车辆的折旧费、司机工资、修理费、保险费、养路费、汽油费等成本打入车辆租借 费用，折合成每公里单价，向各用车单位收取（具体单价示例见附表） 4.4用车部门自己承担使用车辆而产生的过路过桥费、出车津贴、停车费等费用 4.5对于紧急用车，可由公司领导、办公室主任电话通知车队队长派车，事后补办相关 手续，但是应该支付一定的紧急定车附加费 4.6对于紧急用车，若办公室主任无法及时审核车辆使用申请表，可授权他人
4.7紧急定车附加费用计算如下：r临时定车在原有单价的基础上加收一定比例的紧急 附加费，比例如下：提前12小时－－3％，提前8小时－－6％，提前4小时－－10％，提前2小时－－15％，提前1小时－－20％，提前30分钟－－25％，提前15分钟－－30％ 4.8一般用车由车队队长根据用车标准安排车型种类，有特殊要求的应经办公室主任审 批在车辆使用申请表上注明 4.9车辆使用人根据工作需要，确需改变目标和路线的要事先向办公室主任申请，同意 后方可实施 4.10夜间确保至少有一辆车，为两公司的生产服务，须做到随叫随到 4.11神马实业股份有限公司的办公用车交由集团公司一并管理 5车辆使用流程C-15-05-001
一种电动车辆技术领域的电动车辆无级变速驱动系统、变速控制系统及方法，包括：第一驱动电机、行星轮系、第二驱动电机和第三输出机构，其中，行星轮系设有齿圈、行星支架、太阳轮和若干行星齿轮，行星齿轮周向均布在行星支架上，行星支架和齿圈之一与第二驱动电机的输出轴啮合、另一与第三输出机构啮合，齿圈与行星齿轮啮合，太阳轮与第一驱动电机输出端连接并与行星齿轮啮合。本技术采用行星减速机构，通过第二驱动电机带动行星支架或者齿圈的转动达到所需要的减速比，完成电动车的无级变速，实现换挡自动化。 技术要求 1.一种电动车辆无级变速驱动系统，其特征在于，包括：第一驱动电机、行星轮系、第二驱动电机和第三输出机构，其中：行星轮系设有齿圈、行星支架、太阳轮和若干行星齿轮，行星齿轮周向均布在行星支架上，行星支架和齿圈之一与第二驱动电机的输出轴啮合、另一与第三输出机构啮合，齿圈与行星齿轮啮合，太阳轮与第一驱动电机输出端连 接并与行星齿轮啮合。 2.根据权利要求1所述的电动车辆无级变速驱动系统，其特征是，所述的齿圈、行星支架和太阳轮均套设在主轴上。 3.根据权利要求1所述的电动车辆无级变速驱动系统，其特征是，所述第三输出机构设有轮轴，所述的轮轴与电动车辆的驱动轴固定连接。 4.根据权利要求2所述的电动车辆无级变速驱动系统，其特征是，所述的第一驱动电机包括转子总成和绕线定子，其中，转子总成设有转子内衬套，转子内衬套一端固定有太阳轮。 5.根据权利要求2所述的电动车辆无级变速驱动系统，其特征是，所述第一驱动电机的输出端与太阳轮通过减速机构相连，所述的减速机构为皮带、链条、齿轮传动机构中任意 一种。
6.一种应用于上述任一权利要求所述电动车辆无级变速驱动系统的变速控制系统，其特征在于，包括：行车电脑、制动传感器、变速传感器、第一驱动电机控制单元、第二驱动电机控制单元、第一转速传感器和第二转速传感器，其中， 制动传感器与行车电脑相连并输出制动信号； 变速传感器与行车电脑相连并输出加速信号或减速信号； 行车电脑与第一驱动电机控制单元、第二驱动电机控制单元相连并传输两驱动电机的控制信息； 第一转速传感器与行车电脑相连并输出第一驱动电机转速信息； 第二转速传感器与行车电脑相连并输出第二驱动电机转速信息。 7.根据权利要求6所述电动车辆无级变速驱动系统的变速控制系统，其特征在于，所述的变速控制系统还包括：第一电流传感器、第二电流传感器、第一电压传感器、第二电压传感器、第一扭矩传感器和第二扭矩传感器，其中， 第一扭矩传感器与行车电脑相连并输出第一驱动电机扭矩信息； 第二扭矩传感器与行车电脑相连并输出第二驱动电机扭矩信息； 第一电流传感器、第一电压传感器与第一驱动电机控制单元相连并分别输出第一驱动电机的输入电流和输入电压信息； 第二电流传感器、第二电压传感器与第二驱动电机控制单元相连并分别输出第二驱动电机的输入电流和输入电压信息。 8.一种基于权利要求6或7所述变速控制系统的电动车辆变速控制方法，其特征在于，包括以下步骤： S1，首先判断输入信号是否为制动信号，若为制动信号，则第一驱动电机和第二驱动电机停转，电动车辆停车，否则判断为变速信号；
基于Labview的研华数据采集卡的安装和使用数据采集卡型号：USB 4704，要求用labview采集研华的采集卡上的数据第一节研华设备管理器DAQNavi SDK安装 安装前的准备: 要求先安装好labview, 然后再进行以下安装 第一步: 安装研华的DAQ设备管理程序DAQNavi SDK包 1. 双击""文件，弹出安装对话框， 选择第1项“Update and DAQNavi”并点击“Next”： 点击“Next”：
如左上所示勾选，并点击“Next”： 点击“Next”，得如下图所示对话框，表示正在安装，请耐心等待。
耐心等待安装结束。安装结束后，选择操作系统上的“程序”，在程序列表中应该有“Advantech Automation”选项，点击该选项展开应有“DAQNavi”，如下图所示： 单击上图中的“Advantech Nagigator”选项，即可打开研华的设备管理器对话框，如下图所示，在这里，左侧的“Device”栏中列出了本机上连接的所有采集卡，可以对这些卡进行管理和测试，具体如何测试，请参照帮助文档。
第三二步.usb4704采集卡驱动安装 1. 双击“进行安装； 2. 安装完毕后，将采集卡与PC机相连（将usb数据线一端连上采集卡，另外一端连到计算机的USB口上），系统将自动安装采集卡的驱动，并识别采集卡。 3. 检查采集卡安装成功否 首先查看插在PC机上的采集卡上的灯是否呈绿色； 其次，打开“DAQNavi”，如下图所示，观察设备列表中是否显示出了“USB-4704” 第三步：在研华的设备列表中添加模拟卡（Demo Device） 若没有实际的采集卡，可以添加模拟卡进行模拟测试和数据采集编程练习 那么如何添加模拟卡呢？ 如下图所示，点击“Advantech Automation”——〉DAQNavi ——〉Add Demo Device
高空作业车使用说明书 一、概述 湖北楚胜汽车高空作业车以东风小霸王、江铃五十铃、福田奥铃、东风140、东风145 系列等底盘（也可采用其他车辆改装），全回转三折臂式液压多功能工程作业车，它能将工作人员平稳，安全的送到14-20 米的高空作业，进行维修、安装、清洗、摄影、造船、化工、电力、剪枝、更换路灯及其他工程抢修作业。该车的主臂上还设有起重结构，故该车的使用领域较宽。 该车驾驶室外型美观，内部舒适，可载（座）3-6 人，整车外形尺寸小于国内同类产品，整车移动方便，能适合狭窄的地段，小街小巷作业。该车的上臂、下臂、回转和起重液压系统均为独特无级调速系统，具有节能和动作灵活，平稳安全可靠的特点。该车的支腿分单独、可调，能实现整车在平路上调平。该车液压和电器控制系统均设有各种限位装置及发动机紧急熄火装置。能在操作人操作失误，出现故障自动切断电源或紧急停止发动机，及时停止危险动作，确保安全可靠。该车电动操作系统均采用防水开关，避免了开关易进水，锈蚀漏电的问题，工作斗采用管状工作斗，外形美观，在工作斗和转台实行双位置操作，使用方便，维修简便，安全可靠。 二、结构简图（如图1）：
三、操作步骤 步骤1.根据如下指示牌先伸出后横,然后伸出后左右脚及前左右脚，如图2： 步骤2.按住上述操作指示牌的“升臂操作”换向阀向里推,然后准备操作各臂; 步骤3.操作各臂时分为站臂操作和吊栏操作
步骤4.操作各臂时最先升小臂举升一定角度,如图3： 步骤5.然后将二臂举升一定角度,如图4： 步骤6.再将大臂举升一定角度,如图5： 步骤7.将小臂油缸伸出到最大高度,如图6： 步骤8.接着再将二臂举升一定角度，如图7：
前言 Preface 感您使用燃烧控制研究院生产的就地点火控制柜装置。 本公司的就地点火控制柜装置是燃烧控制研究院自主开发生产的高品质就地控制装置，在使用系列本程控装置之前请您仔细阅读该手册以保证正确使用并充分发挥其优越性。 本说明书对就地控制柜（以下简称控制柜）的操作和安装方法等做了详细的介绍。使用控制柜以前，在阅读本说明书的基础上，进行安全正确使用。Thank you for choosing the Local Ignition Control Cabinet designed by our company. The local ignition control device is explored by our company for the ignition control of boiler. This manual describes installation and operation of the cabinet clearly, please read this manual before using. 容介绍Brief introduction 本手册介绍了点火控制柜的组成、安装、配线、功能参数、日常使用维护及对故障的处理 The manual includes the cabinet’s components, installation, wiring, data, maintenance, and troubleshooting. 读者对象Applicable readers 本书适合下列人员阅读This manual is applicable for 设备安装人员、维护人员、设计人员 Installer, maintenance man, and designer 本书约定Stipulation 符号约定Symbol stipulations 说明提醒操作者需重点关注的地方 Points operator should pay attention to 由于没有按要求操作可能造成死亡或重伤的场合危险! This symbol indicates death or GBH that may occur as a result
前言 前言 本车随车交接上图所示钥匙A2把和钥匙标牌B。 配备无线遥控装置*的捷达轿车随车交接两把无线遥控钥匙。关于无线遥控钥匙
的作用范围和功能请参阅13页的说明。 A—钥匙 该钥匙可用于开启或闭锁车上所有锁。 B—钥匙标牌 其上标有钥匙编码及电子防盗器密码。若钥匙丢失，可按上述两编码向本公司订制钥匙，订制时应出示上述两编码。 >$@钥匙标牌不应存放在车内，须单独存放，妥善保管，防止被盗复制。>$@ 基于安全理由，请务必向本公司订购钥匙若将轿车转售给他人，请将该标牌转交新车主。 前言 该系统可防止他人非法盗用您的轿车。 >$@钥匙手柄内装有一电子集成块，钥匙插入点火开关，系统自动解除防盗警戒状态；关闭点火开关，拔出点火钥匙，系统自动进入防盗警戒状态，防盗指示灯随即闪亮用正确编码的原装钥匙方能起动发动机。>$@ 制动器 操作须知 1 新的制动衬片必须经过磨合方能达到其最佳制动效果。最初200公里内，制动效果不能达到最佳状态，这种情况下，只要适当加大踏板压力即可补偿制动效果，本要点也适用于更换后的新衬片。 2 如果踏板行程突然增大，其原因可能是双回路制动系统中的一条回路出现故障，出现这种情况时，必须立即检修制动系统。此时车辆仍可制动，但必须加大踏板压力，制动距离也将加长。 3 按要求定期检查制动液液面高度，见本书第70页。 4 制动衬片的磨损状况很大程度取决于工况及驾驶方式，对于主要用于城市交通的车辆，因频繁起动和停车，制动衬片的工作条件较为苛刻，因此请务必按《保养手册》规定的保养里程到本公司特许经销商处检查制动衬片厚度或更换衬片。 5 下坡行驶时，应适时换入低档，充分利用发动机的制动作用，减轻制动系统的负担，此时，即使需要制动，也不应持续踏住制动踏板。 6 涉水、暴雨或洗车后，因制动衬片受潮或结冰，制动效果可能略有下降，这种情况下应轻踏制动踏板，使制动盘和制动衬片摩擦生热，将水蒸发，恢复制动效果。 7 在撒盐路面上行驶后，盐层将附着在制动盘及制动衬块表面，从而使制动力降低，因此再
Getting Started with ER win (Erwin 入门) by Dr. Peter Wolcott Department of Information Systems and Quantitative Analysis College of Information Science and Technology University of Nebraska at Omaha（由内布拉斯加州的奥马哈大学信息科学与技术学院门的信息系统和定量分析博士彼得著） Introduction （介绍） ER win is a popular data modeling tool used by a number of major companies in Omaha and throughout the world. （Erwin是受奥马哈和世界各地的一些主要的公司欢迎的数据模型工具） The product is currently owned, developed, and marketed by Computer Associates, a leading software developer.（该产品是由具有领导地位的CA软件开发公司拥有、开发和销售） The product supports a variety of aspects of database design, including data modeling, forward engineering (the creation of a database schema and physical database on the basis of a data model), and reverse engineering (the creation of a data model on the basis of an existing database) for a wide variety of relational DBMS, including Microsoft Access, Oracle, DB2, Sybase, and others.该软件为多种多样的关系型数据库管理系统,包括 Microsoft Access,甲骨文,Sybase,DB2,和其他人提供支持数据库设计的各个方面，包括数据建模、正向工程（在现有的数据模型的基础上创建数据模式和物理数据库）和逆向工程（在现在的数据库基础上创建数据模型） This brief tutorial steps you through the process of creating a data model using ER win.（你可以通过这个简单教程中的步骤运用Erwin来创建数据模 型） It will not explain all aspects of ERwin, but will show you the minimum necessary to create and use data models for this class. （这个课程不可能全面地讲解Erwin，但它向你展示了必要的最基本的创建和使用数据模型的知识） It consists of three major segments, which correspond to the project-related assignments in your class: （这个课程由三个主要部分组成，它与有关项目任务相符） 1.Creation of a basic data model (Conceptual data model) 创建一个 基本的数据模型(概念数据模型) 2.Creation of a database schema 建立数据库模式 3.Creation of the database创建数据库
PCI-8344A驱动1.2版说明 一、驱动适用范围 1. 适用于windows98,2K,XP系统 2. 编程适用于VC,VB,Delphi等决大多数编程语言 二、与上一个版本驱动的区别 1. 增加了一些错误号 2. 函数名普遍加了前缀“ZT8344A” 3. 废弃了用结构体传递参数的方式 三、驱动函数的参数说明 请以这个版本驱动中的《PCI8344A.h》文件中所述为准。 《PCI8344A.h》是一个纯文本文件，可用写字板或WORD打开。 推荐：如果用 VC 或 UltraEdit 打开，其中的注释及关键字会有不同的颜色， 从而有助于阅读。 四、连续AD采集的编程思路 1. 首先在程序初始化时调用 ZT8344A_OpenDevice 函数，用于打开设备，只调一次即可； 2. 调用 ZT8344A_DisableAD 函数，禁止AD 调用 ZT8344A_ClearHFifo 函数，清硬件缓冲区(HFIFO) 调用 ZT8344A_ClearSFifo 函数，清软件缓冲区(SFIFO) 调用 ZT8344A_OpenIRQ 函数，打开HFIFO半满中断 调用 ZT8344A_AIinit 函数，做一些AD初始化工作 3. 在一个循环中不断调用ZT8344A_GetSFifoDataCount 判断SFIFO中数据的个数， 申请一个数组，并把这个数组中传入 ZT8344A_AISFifo 用于接收数据, 把读出的数据保存到文件或直接显示， 注意：SFIFO的默认大小为 819200，用户要不断读数，使SFIFO有空间放入新的来自 HFIFO的数，如果SFIFO中的有效数据的个数接近 819200，会使整个AD过程停止。如果想重新采集，必须重复2—3步。 4. 调用 ZT8344A_CloseIRQ 函数，停止采集过程 5. 在程序退出前调用 ZT8344A_CloseDevice 函数 提示：1. 在这版驱动中，板卡的序号是从1开始的 2. 如果函数返回 -1，应该调用ZT8344A_ClearLastErr 函数得到错误号， 然后去《PCI8344A.h》文件中查找这个错误号对应的含义。 3. 一旦错误号不为0，如果想重新使函数正常工作，必须调用 ZT8344A_ClearLastErr 函数清除错误号。