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蛋白质二级结构预测软件

通过EMAIL进行序列检索当网络不是很畅通时或并不急于得到较多数量的蛋白质序列时，可采用EMAIL方式进行序列检索。蛋白质基本性质分析蛋白质序列的基本性质分析是蛋白质序列分析的基本方面，一般包括蛋白质的氨基酸组成，分子质量，等电点，亲水性，和疏水性、信号肽，跨膜区及结构功能域的分析等到。蛋白质的很多功能特征可直接由分析其序列而获得。例如，疏水性图谱可通知来预测跨膜螺旋。同时，也有很多短片段被细胞用来将目的蛋白质向特定细胞器进行转移的靶标（其中最典型的例子是在羧基端含有KDEL序列特征的蛋白质将被引向内质网。 WEB中有很多此类资源用于帮助预测蛋白质的功能。
特殊结构或结构预测 COILS http://ulrec3.unil.ch/software/COILS_ form.html MacStripe /matsudaira/m acstripe.html
与核酸序列一样，蛋白质序列的检索往往是进行相关分析的第一步，由于数据库和网络技校术的发展，蛋白序列的检索是十分方便，将蛋白质序列数据库下载到本地检索和通过国际互联网进行检索均是可行的。由NCBI检索蛋白质序列可联网到： “:80/entrz/qu ery.fcgi?db=protein”进行检索。利用SRS系统从EMBL检索蛋白质序列联网到：/”，可利用EMBL 的SRS系统进行蛋白质序列的检索。
跨膜区域 TMpred： /software/TMPRED_form.ht ml 预测蛋白质的跨膜区段和在膜上的取向，它根据来自SWISSPROT的跨膜蛋白数据库Tmbase，利用跨膜结构区段的数量、位置以及侧翼信息，通过加权打分进行预测。Tmpred的Web 界面十分简明。用户将单字符序列输入查询序列文本框，并可以指定预测时采用的跨膜螺旋疏水区的最小长度和最大长度。输出结果包含四个部分：可能的跨膜螺旋区、相关性列表、建议的跨膜拓扑模型以及代表相同结果的图。

Quick Placement Test(1)

Oxford University PressandUniversity of Cambridge Local Examinations SyndicateName of Student: ………………………………………………………………………… Date of birth:…………………………………………………………………………………. Date test taken: ………………………………………………………………………….QuickPlacementTestVersion 2Time: 30 minutesPLEASE NOTE THAT THIS TEST MUST BE CARRIED OUT UNDER STRICT EXAMINATION CONDITIONS AND THE INVILATOR MUST SIGN BELOW TO SAY THIS HAS BEEN DONE INVIGILATORS SIGNATURE……………………………………………………INVIGILATORS NAME…………………………………………………………..Questions 1 – 5• Where can you see these notices? • For questions 1 to 5, mark one letter A , B or C on your Answer Sheet.1A B C in an office in a cinema in a museum2A B C in a bank on a bus in a cinema3A B Cin a street on a book on a table4 A B C in a bank in a garage in a station5A B C on clothes on furniture on foodQuestions 6 – 10•In this section you must choose the word which best fits each space in the text below. • For questions 6 to 10, mark one letter A,B or C on your Answer Sheet.THE STARSThere are millions of stars in the sky. If you look (6) .................. the sky on a clear night, it is possible to see about 3000 stars. They look small, but they are really (7) .................. big hot balls of burning gas. Some of them are huge, but others are much smaller, like our planet Earth. The biggest stars are very bright, but they only live for a short time. Every day new stars (8) .................. born and old stars die. All the stars are very far away. The light from the nearest star takes more (9) .................. four years to reach Earth. Hundreds of years ago, people (10) .................. stars, like the North star, to know which direction to travel in. Today you can still see that star.6 A at B up C on7A very B too C much8A is B be C are9A that B of C thanu sing10A use B used CQuestions 11 – 20•In this section you must choose the word which best fits each space in the texts.• For questions 11 to 20, mark one letter A, B, C or D on your Answer Sheet.Good smiles ahead for young teethOlder Britons are the worst in Europe when it comes to keeping their teeth. But British youngsters (11) .................. more to smile about because (12) .................. teeth are among the best. Almost80% of Britons over 65 have lost all or some (13) .................. their teeth according to a World Health Organisation survey. Eating too (14) .................. sugar is part of the problem. Among(15) .................. , 12-year olds have on average only three missing, decayed or filled teeth.C haveD having11 A getting B gotD theirsC them 12A theirB hisD betweenB ofC among13A fromC manyD deal 14A muchB lotB peopleC childrenD 15A personfamilyChristopher Columbus and the New WorldOn August 3, 1492, Christopher Columbus set sail from Spain to find a new route to India,China and Japan. At this time most people thought you would fall off the edge of the world ifyou sailed too far. Yet sailors such as Columbus had seen how a ship appeared to get lower andlower on the horizon as it sailed away. For Columbus this (16) ................. that the world wasround. He (17) ................. to his men about the distance travelled each day. He did not want themto think that he did not (18) ................. exactly where they were going. (19) ................. , onOctober12, 1492, Columbus and his men landed on a small island he named San Salvador. Columbus believed he was in Asia, (20) ................. he was actually in the Caribbean.16 A made B pointed C was D provedD17 A lied B toldC cheated askedD18 A find B know C thinkexpect19 A Next B Secondly C Finally D Once20A as B but C because D ifQuestions 21 – 40•In this section you must choose the word or phrase which best completes each sentence. • For questions 21 to 40, mark one letter A, B, C or D on your Answer Sheet.21The children won’t go to sleep .................... we leave a light on outside their bedroom.A exceptB otherwiseC unlessD but22I’ll give you my spare keys in case you .................... home before me.A would getB gotC will getD get23My holiday in Paris gave me a great .................... to improve my French accent.A occasionB chanceC hopeD possibility24The singer ended the concert .................... her most popular song.A byB withC inD as25Because it had not rained for several months, there was a ...................... of water.A shortageB dropC scarceD waste26I’ve always .................... you as my best friend.A regardedB thoughtC meantD supposed27She came to live here .................... a month ago.A quiteB beyondC alreadyD almost28 Don’t make such a ....................! The dentist is only going to look at your teeth.A fussB troubleC worryD reaction29He spent a long time looking for a tie which .................... with his new shirt.A fixedB madeC wentD wore30Fortunately, .................... from a bump on the head, she suffered no serious injuries from her fall.A otherB exceptC besidesD apart31She had changed so much that .................... anyone recognised her.A almostB hardlyC notD nearly32.................... teaching English, she also writes children’s books.A MoreoverB As well asC In additionD Apart33It was clear that the young couple were ..................... of taking charge of the restaurant.A responsibleB reliableC capableD able34The book .................... of ten chapters, each one covering a different topic.A comprisesB includesC consistsD contains35Mary was disappointed with her new shirt as the colour .................... very quickly.A bleachedB diedC vanishedD faded36National leaders from all over the world are expected to attend the .................... meeting.A peakB summitC topD apex37Jane remained calm when she won the lottery and .................... about her business as if nothing had happened.A cameB broughtC wentD moved38I suggest we ..................... outside the stadium tomorrow at 8.30.A meetingB meetC metD will meet39My remarks were ..................... as a joke, but she was offended by them.A pretendedB thoughtC meantD supposed40You ought to take up swimming for the ..................... of your health.A concernB reliefC sakeD causeQuestions 41 – 50•In this section you must choose the word or phrase which best fits each space in the texts.• For questions 41 to 50,mark one letter A, B, C or D on your Answer Sheet.CLOCKSThe clock was the first complex mechanical machinery to enter the home, (41) ……………….. it was too expensive for the (42) ……………….. person until the 19th century, when(43) ……………….. production techniques lowered the price. Watches were also developed, but they (44) ……………….. luxury items until 1868 when the first cheap pocket watch was designed in Switzerland. Watches later became (45) ……………….. available and Switzerland became the world’s leading watch manufacturing centre for the next 100 years.41A despite B although C otherwise D average42A average B medium C general D common43A vast B large C wide D massB enduredC kept D44A lastedremainedD45 A mostlyB chieflyC greatly widelyDublin City WalksWhat better way of getting to know a new city than by walking around it?Whether you choose the Medieval Walk, which will (46) ……………….. you to the Dublin of 1000 years ago, find out about the more (47) ……………….. history of the city on the Eighteenth Century Walk, or meet the ghosts of Dublin’s many writers on the Literary Walk, we know you will enjoy the experience.Dublin City Walks (48) ……………….. twice daily. Meet your guide at 10.30 a.m. or 2.30 p.m. at the Tourist Information Office. No advance (49) ……………….. is necessary. Special(50) ……………….. are available for families, children and parties of more than ten people.DB presentC move46 A introduceshow47 A nearC recent DB latecloseplaceB occurC work D48 A takefunctionC warning DB reserving49A payingbooking50A funds B costs C fees D ratesQuestions 51 – 60•In this section you must choose the word or phrase which best completes each sentence. • For questions 51 to 60, mark one letter A, B, C or D on your Answer Sheet.51If you’re not too tired we could have a .................... of tennis after lunch.A matchB playC gameD party52Don’t you get tired .................... watching TV every night?A withB byC ofD at53Go on, finish the dessert. It needs .................... up because it won’t stay fresh until tomorrow.A eatB eatingC to eatD eaten54We’re not used to ..................... invited to very formal occasions.A beB haveC beingD having55I’d rather we .................... meet this evening, because I’m very tired.A wouldn’tB shouldn’tC hadn’tD didn’t56She obviously didn’t want to discuss the matter so I didn’t .................... the point.A maintainB chaseC followD pursue57 Anyone ...... after the start of the play is not allowed in until the interval.A arrivesB has arrivedC arrivingD arrived58This new magazine is .................... with interesting stories and useful information.A fullB packedC thickD compiled59The restaurant was far too noisy to be .................... to relaxed conversation.A conduciveB suitableC practicalD fruitful60In this branch of medicine, it is vital to ..................... open to new ideas.A standB continueC holdD remain。

看望我的表弟的英语作文

Last summer, I had the opportunity to visit my cousin who lives in a small town in the countryside. It was an experience that left an indelible mark on my heart, reminding me of the simple joys of life and the warmth of family bonds.The journey to my cousins home was a picturesque one, with lush green fields stretching out on either side of the narrow road, and the occasional farmhouse dotting the landscape. The air was fresh and crisp, a stark contrast to the polluted city air I was used to. As I approached the town, I could see children playing in the streets, their laughter echoing through the air, a sound that was both infectious and heartwarming.My cousin, a cheerful and energetic boy of ten, greeted me with a wide grin and a tight hug. His excitement was palpable, and it was impossible not to be swept up in his enthusiasm. He immediately took me on a tour of the town, pointing out his favorite spots the old oak tree where he and his friends often played, the small river where they would catch fish, and the bakery that sold the most delicious pastries.One of the highlights of my visit was the time we spent together on the farm. My cousins family owns a small farm, where they grow a variety of crops and raise a few animals. I was fascinated by the process of farming, from the planting of seeds to the harvesting of crops. The hard work and dedication that went into maintaining the farm was evident, and I gained a newfound respect for the farmers who work tirelessly to provide for their families and communities.We also spent time feeding and playing with the animals on the farm. The chickens clucked contentedly as we scattered feed for them, and the cows lowed softly as we stroked their soft fur. My cousin showed me how to milk a cow, a task that was both challenging and rewarding. The fresh milk we collected was creamy and delicious, a far cry from the processed milk I was used to.In the evenings, we would sit on the porch, watching the sunset and listening to the gentle rustling of the leaves in the breeze. The sky was painted with hues of orange and pink, a breathtaking sight that I had rarely seen in the city. We would talk about our dreams and aspirations, sharing stories and laughter under the starlit sky.One of the most memorable moments of my visit was when my cousin took me to a local festival. The town was buzzing with activity, with people dressed in traditional attire, dancing to the rhythm of lively music. There were stalls selling a variety of local delicacies, and my cousin insisted on trying each one. The food was flavorful and unique, a testament to the rich culinary heritage of the region.My visit to my cousins home was a refreshing break from the hustle and bustle of city life. It was a reminder of the importance of slowing down and appreciating the simple things in life. The warmth of family, the beauty of nature, and the joy of shared experiences are things that money cannot buy, but are priceless treasures that enrich our lives.As I returned to the city, I carried with me the memories of my time in thecountryside. The laughter of my cousin, the taste of fresh farm produce, and the tranquility of the rural landscape are memories that I will cherish forever. It was a visit that taught me the value of connecting with our roots and appreciating the beauty that lies beyond the concrete jungle.。

Genotyping

Genotyping ProtocolCollect Tails1.Fill syringe in animal facility with isoflurane and attach to exposure box.2.Place folded up paper towel inside box.3.Inject 4-5cc isofluorane into container while pressing against gauze to ensure thatanesthetic evaporates into chamber.4.Immediately close the top so that the isoflurane can fill the chamber5.Set up razors, ear tags, tagging tool, recovery cage, and paper towels for cutting on.6.Retrieve first cage of animals.7.Place first animal into chamber, leaving it open as short of time as possible so thatisoflurane concentration stays high.8.Watch animal carefully. Animal will follow these stages of anesthetic:1.Loss of consciousness (test by rolling animal in chamber, LORR indicatesunconsciousness)2.Breathing will become very regular, deep and fast.3.Breathing will suddenly shift to a much lower rate4.Remove animal from chamber after 2-4 low rate breaths, much more could killthe animal.9.Tag animal with number facing rostral and internal to the pinnae (closer to the head).10.Cut a 1cm section of tail from the animal of interest.∙Be very careful not to contaminate tail samples with blood or tissue from the other animals as that DNA can confound the genotyping results.∙Make sure you use a different razor each tail and don’t cut in to previously bloodied areas of the paper towel.11.Place animal in recovery cage, then put tail sample into tube numbered for the eartag used.12.Place tub into dry ice and proceed to the next animal.13.Goto step 3 for each animal.14.Once animals are all awake and bleeding has subsided, return to home cage andretrieve next cage to be genotyped.DNA Extraction and PCR1.Turn on heat block(s) to 95°C, use both if you have enough samples.2.Take out the Sigma REDExtract-N-Amp Tissue PCR Kit (Cat: XNAT)3.Place REDExtract-N-Amp PCR Mix on ice and thaw the other solutions at roomtemperature.4.Take out ParpAPP primer mix from Ari’s box (recipe below), thaw, then place on ice.5.Syringe-filter 10mL of ddH2O into a falcon tube.6.Make a master mix of extraction buffer for your samples at n + 1 (one more than thenumber of samples you have).∙Mix Extraction Solution and Tissue Preparation Solution in a 4:1 ratio up to 2 hours before extraction. (If 15 tails, make enough for 16: 1.6mL ExtractionSolution and 400uL Tissue Prep)∙Vortex for 10s.7.Add 125uL of master extraction mix to each tail sample.8.Incubate at room temperature for 10 minutes.9.Incubate at 95°C for 3 minutes.10.Remove from heat and quickly add 100ul Neutralization Solution B to each sample.11.Vortex each sample for 5 sec to mix12.Shake tail down to bottom of tube∙Remove tails from extraction mixture and store at 4°C for up to 6 months.∙Make sure to discard tails into freezer bag to be taken back to animal facility.13.Take out enough PCR tubes for the number of tails you have, or a 96-well plate14.Put the tubes in tube rack and cover with strip caps15.Make a master PCR mix for n + 1 samples (preferably while step 8 is happening).∙10ul REDExtract-N-Amp PCR Reaction Mix per tail sample∙1ul ParpAPP primer mix per tail sample∙5ul filtered ddH2O per tail sample∙Vortex for 10 seconds, centrifuge at full speed for 15 sec∙Place on ice14.Place PCR tubes on ice and perform all PCR prep on ice as well.15.Place 16ul of PCR Master Mix into each tube that will be used for tails.ing only filter-tips, carefully pipette 4ul of each tail extraction into each tube17.Mix by slowly pipetting up and down 5x, make sure as much of the PCR reactionsolution stays at the bottom of each tube as much as possible18.Repeat for all samples, making sure that you do not contaminate any tail extractionwith another (the smallest amount of DNA can mess up the reaction).19.Cap the tubes (or 96-well plate), leave on ice.20.Turn on the PCR machine, log in as AEB.21.Go to the protocol library, scroll to the ParpGT folder and select the program.22.Select “Run Program”.23.Set “Hot Start” option to Yes and to 94°C.24.Set reaction volume to 20ul and temperature method to Algorithmic.25.Start the reaction∙The machine will raise the temperature of the heated lid to 100°C∙The block will then go to 94°C and hold26.Open the lid and place the PCR tubes quickly and carefully into the heated block.27.Close the lid as soon as possible to prevent PCR reaction mix evaporation.28.Select “Resume” on the PCR machine, which will start the PCR run.29.The PCR machine will tell you when the projected completion of the PCR reactionwill be, come back then or let go overnight. The machine will hold the samples at 4°C when the run is finished.ParpAPP Primer Mix (500ul):∙50ul Parp1F primer∙25ul JaxParp1 primer∙25ul NeoRB2r primer∙25ul Pd-APP-1F primer∙25ul Pd-APP-1R primer∙350uL filtered ddH2O∙Vortex for 10s, place at -20°CRun the gel* All measurements will be listed for the (large/small) gel rigs.1.Take out either the large or small agarose gel rig (or both)Gel rigs can handle (38/24) samples with two combs.2.Rinse the gel mold with water and make sure the gasket is very wet3.Place the mold into the running rig so that the gaskets are sealed against the sidewalls of the rig.4.Have 1-2 combs (green/blue) ready and cleaned next to the rig5.Make sure the rig is level!! (an uneven gel won’t run well)6.Make a 3% agarose gel7.Measure out (4.5g/2.25g) agarose and place into 250mL beaker.8.Add (150mL/75mL) 1x TAE to the beaker and swirl to mix.9.Place beaker in microwave for 1:30.10.Take beaker out and swirl (don’t burn yourself, it is hot!)11.Heat for another (35s/20s)12.Swirl again, repeat until no visible beads are in the solution.13.Add (15ul/8ul) SYBRSafe DNA dye to the molten gel and swirl gently in bothdirections to mix thoroughly.14.Pour the mixture into the mold, place the beaker into the sink and start running waterinto it.15.Quickly place the comb(s) into the comb sockets on the gel mold, 1.5mm side down(thicker wells).16.Cover the gel loosely with foil to protect from light.17.Let stand for 30 minutes or until gel is room temperature and solid to the touch.18.Take out 100bp DNA ladder and 6x loading dye to thaw on the bench top while gelis setting up.19.Pull out combs by pulling steadily straight up (it takes a little strength to get combsout of 3% gel).20.Remove gel mold and turn it so that if the leads of the rig are facing right, the wellsare pointed toward to the top of the rig.21.Fill the gel rig with 1x TAE until fluid level just covers the gel (about 2-3mm).22.Mix 6uL 100bp ladder and 1ul loading dye per comb (if using two combs, doublethese amounts) in a tube and mix by pipetting up and down several times.23.Pipette 7ul DNA ladder/dye mix into the far left well in each row of wells.24.Pipette 10uL of each PCR reaction straight from the PCR tube into each of the wells,taking care to keep track of which well is which and making sure that you don’tcontaminate the other wells or other PCR samples with the other reaction mixtures.25.Once the gel(s) is loaded, Place the top on the gel rig and attach to the power supply.26.Run the gel for 1hour at 120V.27.Recap the PCR tubes and place at 4°C in case you need to rerun the gel.28.Get the memory card from Ari’s desk drawer and place it into the digital camera inthe microscope room.29.Place the gel directly onto the UV transilluminator.30.Turn on the camera, activate the screen, turn off the flash, and turn on the macro lens.31.Make sure the UV filter is in front of the lens.32.Place a UV shield over your face (the shortwavelength UV emitted from the UV boxis extremely harmful to your eyes with very little exposure, and not good for your skin either).33.Zoom into your gel, center it, and take a picture or two.34.Turn off the UV box, turn off the camera, take the gel off of the box and the boxdown with a Kimwipe.35.Throw the gel away and give the card to Ari to analyze.。

统计学网址大全

统计学网址大全一、统计相关网址1．国外统计学网址/美国金融情报/美国金融briglehttp://www.math.yorku.ca/SCS/StatResource.html统计学与统计绘图资源/index.htm Lex Jansen个人主页(SAS SUGI pdf论文)/WoPEc.html经济论文集/homepages.nsf/toc/...rialsstatistics统计学指南/garson/pa765/statnote.htm G. David Garson的在线教材/statcodes/sc_multvar.html多变量分析与分类/~sns99kla/links.html统计遗传学网址/fin/journal/jofsites.htm Finance Site List/~harsham/stat-data/opre330.htm统计学数据分析问题/? Finance USA/?外汇基础知识/newrich/explain...ID=E_01&sTYPE=G理财精算网http://www.math.yorku.ca/SCS/StatResource.html York大学讲义/publications/jse/统计学教育论文集/publications/jse/统计学论文集/garson/pa765/dicts.htm统计学词典/textbook/glosfra.html SATA/artsci/botany/ordin...te/glossary.htm Michael Palmer 対応分析系/~lane/hyperstat/glossary.html Glossary/statglos/statglos.htm统计基本用语/steps/glossary/index.html Statistics Glosaryhttp://cortex.med.nihon-u.ac.jp/department.../ebm/gloss.html Evidence Based Medicine /lists/exact-sta...es/glossary.txt stat/~nhodgins/desig...d_analysis.html実験計画法/espse/hale/507Mat/...al/glossary.htm Glossary of Terms/hp/staff/dmb/matrix/intro.html Matrix Reference Manual/cases/ UCLA Statistics Case Studies/diagnoser.../diagnoser.html DIANA/%7Echance/chance_..._news/news.html Chance Case /steps/home.html STatistical Education.au/Database/index.html SMARD Database/hyperstat/index.html HyperStat Online Textbook.au/nceph/surfstat/surfs...e/surfstat.html Surfstat/~lowry/webtext.html手計算の分散分析説明/~wallacd1/ Order of Operations/Solving Equations/modules/dau/stat/ STAT/stat/確率/stats/ Gene Glass :Arizona State University)/espse/hale/507Mat/default.html Bob Hale's Home Page/~dhowell/StatPages/Stat...atHomePage.html Fundamental Statistics for the Behavioral Sciences,/vlib/jobs.html美国统计找工作（job chance）/ UCLA Stathttp://www.psych.yorku.ca/lab/重回帰と実験計画法。

2024届湖南省郴州市高三下学期5月模拟考试英语试题

2024届湖南省郴州市高三下学期5月模拟考试英语试题一、听力选择题1．What’s the weather like today?A．Windy.B．Sunny.C．Warm.2．How will the woman get to the railway station?A．By car.B．By taxi.C．By subway.3．Who still needs to join a group?A．Alex.B．Simon.C．Helen.4．When did the man leave the office?A．At 1:00.B．At 1:30.C．At 2:00.5．What are the speakers doing?A．Watching a movie.B．Attending a wedding.C．Admiring a picture.听下面一段较长对话，回答以下小题。

6．What will the speakers do together?A．Go running.B．Play tennis.C．Go swimming. 7．Where will the man pick up the woman?A．In the gym.B．At the tennis court.C．At the swimming pool.听下面一段较长对话，回答以下小题。

8．What are the speakers mainly talking about?A．How to learn Italian.B．How to spend the vacation.C．How to enjoy music.9．Why doesn’t the woman want to go to Rome?A．She is afraid of flying.B．She hates Italian music.C．She has no interest in history.10．What is the woman probably interested in?A．The delicious food.B．The great architecture.C．The natural scenery.听下面一段较长对话，回答以下小题。

《孟德尔随机化研究指南》中英文版

《孟德尔随机化研究指南》中英文版全文共3篇示例，供读者参考篇1Randomized research is a vital component of scientific studies, allowing researchers to investigate causal relationships between variables and make accurate inferences about the effects of interventions. One of the most renowned guides for conducting randomized research is the "Mendel Randomization Research Guide," which provides detailed instructions and best practices for designing and implementing randomized controlled trials.The Mendel Randomization Research Guide offers comprehensive guidance on all aspects of randomized research, from study design and sample selection to data analysis and interpretation of results. It emphasizes the importance of randomization in reducing bias and confounding effects, thus ensuring the validity and reliability of study findings. With clear and practical recommendations, researchers can feel confident in the quality and rigor of their randomized research studies.The guide highlights the key principles of randomization, such as the use of random assignment to treatment groups, blinding of participants and researchers, and intent-to-treat analysis. It also discusses strategies for achieving balance in sample characteristics and minimizing the risk of selection bias. By following these principles and guidelines, researchers can maximize the internal validity of their studies and draw accurate conclusions about the causal effects of interventions.In addition to the technical aspects of randomized research, the Mendel Randomization Research Guide also addresses ethical considerations and practical challenges that researchers may face. It emphasizes the importance of obtaining informed consent from participants, protecting their privacy and confidentiality, and ensuring the safety and well-being of study subjects. The guide also discusses strategies for overcoming common obstacles in randomized research, such as recruitment and retention issues, data collection problems, and statistical challenges.Overall, the Mendel Randomization Research Guide is a valuable resource for researchers looking to improve the quality and validity of their randomized research studies. By following its recommendations and best practices, researchers can conductstudies that produce reliable and actionable findings, advancing scientific knowledge and contributing to evidence-based decision making in various fields.篇2Mendel Randomization Study GuideIntroductionMendel Randomization Study Guide is a comprehensive and informative resource for researchers and students interested in the field of Mendel randomization. This guide provides anin-depth overview of the principles and methods of Mendel randomization, as well as practical advice on how to design and conduct Mendel randomization studies.The guide is divided into several sections, each covering a different aspect of Mendel randomization. The first section provides a brief introduction to the history and background of Mendel randomization, tracing its origins to the work of Gregor Mendel, the father of modern genetics. It also discusses the theoretical foundations of Mendel randomization and its potential applications in causal inference.The second section of the guide focuses on the methods and techniques used in Mendel randomization studies. This includesa detailed explanation of how Mendel randomization works, as well as guidelines on how to select instrumental variables and control for potential confounders. It also discusses the strengths and limitations of Mendel randomization, and provides practical tips on how to deal with common challenges in Mendel randomization studies.The third section of the guide is dedicated to practical considerations in Mendel randomization studies. This includes advice on how to design a Mendel randomization study, collect and analyze data, and interpret the results. It also provides recommendations on how to report Mendel randomization studies and publish research findings in scientific journals.In addition, the guide includes a glossary of key terms and concepts related to Mendel randomization, as well as a list of recommended readings for further study. It also includes case studies and examples of Mendel randomization studies in practice, to illustrate the principles and techniques discussed in the guide.ConclusionIn conclusion, the Mendel Randomization Study Guide is a valuable resource for researchers and students interested in Mendel randomization. It provides a comprehensive overview ofthe principles and methods of Mendel randomization, as well as practical advice on how to design and conduct Mendel randomization studies. Whether you are new to Mendel randomization or looking to deepen your understanding of the field, this guide is an essential reference for anyone interested in causal inference and genetic epidemiology.篇3"Guide to Mendelian Randomization Studies" English VersionIntroductionMendelian randomization (MR) is a method that uses genetic variants to investigate the causal relationship between an exposure and an outcome. It is a powerful tool that can help researchers to better understand the underlying mechanisms of complex traits and diseases. The "Guide to Mendelian Randomization Studies" provides a comprehensive overview of MR studies and offers practical guidance on how to design and carry out these studies effectively.Chapter 1: Introduction to Mendelian RandomizationThis chapter provides an overview of the principles of Mendelian randomization, including the assumptions andlimitations of the method. It explains how genetic variants can be used as instrumental variables to estimate the causal effect of an exposure on an outcome, and outlines the key steps involved in conducting an MR study.Chapter 2: Choosing Genetic InstrumentsIn this chapter, the guide discusses the criteria for selecting appropriate genetic instruments for Mendelian randomization. It covers issues such as the relevance of the genetic variant to the exposure of interest, the strength of the instrument, and the potential for pleiotropy. The chapter also provides practical tips on how to search for suitable genetic variants in public databases.Chapter 3: Data Sources and ValidationThis chapter highlights the importance of using high-quality data sources for Mendelian randomization studies. It discusses the different types of data that can be used, such asgenome-wide association studies and biobanks, and offers advice on how to validate genetic instruments and ensure the reliability of the data.Chapter 4: Statistical MethodsIn this chapter, the guide explains the various statistical methods that can be used to analyze Mendelian randomization data. It covers techniques such as inverse variance weighting, MR-Egger regression, and bi-directional Mendelian randomization, and provides guidance on how to choose the most appropriate method for a given study.Chapter 5: Interpretation and ReportingThe final chapter of the guide focuses on the interpretation and reporting of Mendelian randomization results. It discusses how to assess the strength of causal inference, consider potential biases, and communicate findings effectively in research papers and presentations.ConclusionThe "Guide to Mendelian Randomization Studies" is a valuable resource for researchers who are interested in using genetic data to investigate causal relationships in epidemiological studies. By following the guidance provided in the guide, researchers can enhance the rigor and validity of their Mendelian randomization studies and contribute to a better understanding of the determinants of complex traits and diseases.。

果蝇体内SOD和MDA随增龄变化及其与寿命的关系_张欣文

果蝇体内SOD和MDA随增龄变化及其与寿命的关系上海铁道大学医学院预防医学教研室(200070)张欣文徐思红厉曙光提要每日观察记录果蝇生存数和死亡数;将不同天龄雌雄果蝇分别制成匀浆,测定匀浆中SOD活力和M DA含量。

结果显示果蝇体内SO D活力在40、50天龄以前是随增龄而上升,进入老龄后开始下降;M DA含量随增龄而增加;各天龄雄蝇的SOD均高于雌蝇(P<0101);40天龄后雄蝇的存活率明显低于雌蝇(P<0.05或P<0101)。

表明果蝇体内SOD活力与M DA 含量的平衡失调可能是引起衰老和死亡的原因之一。

关键词黑腹果蝇SO D M DA寿命Eff ect of Age-dependent Variation of Superoxide Dismutse Activ-ity and Malonaldehyde Contents on Lif e-span in Drosophila Zhang X inwen,et al.D ep t.of Pr eventive M edicine,M edical College,Shanghai T iedao Univer sity(Shanghai200070) T o study the age-dependent var iation of sup er ox ide dis-mutse(SOD)activity and malonaldehyde(MDA)contents in Dr osop hila melanogaster and the corr elationship between the v ar i-ation and lif e-sp an.T he number s of liv ing and died f lies w er e recor ded daily.Flies of diff er ent ages(days)w er e homogenated sep arately.T he ex amining the SOD activ ity and M DA contents in the homogenates have been made.A ges of D rosop hila being y ounger than40、50days,the S OD activ ity increased with ad-vancing age,w hile that decr eased in aged Dr osop hila.T he levels of M DA incr eased signif icantly w ith a ging.T he S OD activity of male f lies is signif icant higher than that of f emale f lies in ev-ery group.T he p er cent sur v iv al of male f lies is signif icant low er than that of f emale f lies af ter40days.T he unbalance betw een SOD and MD A could be one of the f actor s causing aging and death.Key words Dr osophila melanogaster Superox ide dismutse Malonaldebyde Life-span果蝇虽属昆虫,但其许多代谢途径、生理学功能和发育阶段同哺乳动物基本相似,故常被用于衰老实验研究。

NuffieldScienceTeachingProject：纳菲尔德科学教学计划

N UFFIELD S CIENCE T EACHING P ROJECTSelect bibliography and archival sourcesThe bibliography does not attempt to be exhaustive. References in the synthetic accounts and reviews will provide more information. W ARING‟S notes are especially helpful in this regard, for both published and unpublished sources, up to about 1978. The bibliography prepared by D AWSON & L ETTON is helpful in identifying studies, especially by higher degree students, that may not be found in standard literature searches. For later studies, see the lists of theses published from time to time in Studies in science education. Published schemes of work, laboratory guides, text and other material for pupils and teachers are not listed here.The records of the Chelsea College part of the pr oject are in the Archives of King‟s College London, in 591 boxes (including one outsize) and 2 files. The collection contains records of the Nuffield Foundation Science Teaching Project (NFSTP), 1949-1993 but mainly dating from the 1960s and 1970s, including general administrative papers, 1961-1974; the Secondary Science Education Programme, 1965-1974; the Junior Science Project, 1960-1974; the Combined Science Project, 1964-1970; A-level in Physical Sciences, 1955-1974; Physics A- and O-level, 1963-1972; Chemistry O-level, 1962-1974; Chemistry A-level, 1962-1974; Biology O-level, 1962-c1973; Biology A-level, 1963-1972; records relating to publications, also including material on NFSTP administration, 1949-1992; published texts, 1960-1993; and film loops and accompanying teaching notes, 1966-1978, for various subjects and age groups. A detailed catalogue is available at(/depsta/iss/archives/collect/1nu30-0.html)for each of the headings:∙STP Science Teaching Project -- General Administrative Papers∙SS Secondary Science Education Programme∙JSP Junior Science Project∙CSP Combined Science Project∙ALPS A-level in Physical Sciences∙PAL, POL Physics A- and O-level∙COL, COL/NCR Chemistry O-level∙CAL Chemistry A-level∙BOL Biology O-level∙BAL Biology A-level∙TEXT Published texts∙PBN Publications∙/FL Film loops∙Because the project involved practising scientists as advisers and providers of material, a wide range of archives is likely to contain some relevant items. For example, Professor A J Cain‟s papers contain (an unknown amount) of correspondence with William Anderson, the publication manager based at Chelsea (/library/mole/c/cain.htm#boxfolder1); the papers of W.L Bragg at the Royal Institution contain some material; and the papers of BunnyDowdeswell held at the University of Bath contain material related to his invo lvement with the biology projects (/html/1128-ncuacs83499.htm).A LEXANDER, D. Nuffield Secondary Science: an evaluation. London: Macmillan,1974.A TKIN, M. J., andB LACK, P. J. Inside science education reform. New York: TeachersCollege Press. 2003.In some personal reflections, Paul Black illustrates a number of importantcurriculum issues by reference to his involvement with Nuffield projects.D AWSON, B. E., and L ETTON, K. M. Science education research and developmentabstracts. London: Royal Society Chemistry. Volume 1, 1889, volume 2, 1992.Volume 2 contains an index to the whole work. The list of higher degreetheses is especially useful, but the word …Nuffield‟ does not necessarilyappear in the title of every relevant thesis, e.g. Harding 1975 (q.v.).D ORLING, G. …Nuffield Coordinated Sciences: aims and history‟, Physics education,23: 207-211, 1988.F AIRBROTHER, R. W., and S WAIN, J. R. L., …The assessment of project work inNuffield Advanced Biology and Nuffield Advanced Physical Science‟,Educational research, February, vol. 19: 92-99, 1977.G IVENS, N. …Curriculum Materials as a Vehicle for Innovation: A Case Study of theNuffield Design and Technology Proje ct‟, Research in science andtechnological education, 18:71-83, 2000.H ARDING,J.M.M.…Communication and support for change in school scienceeducation‟, Doctoral Thesis, University of London (Chelsea College), 1975.H ARGREAVES, J., and H ARGREA VES, T. …Some Models of School Science in BritishCurriculum Projects, and Their Implications for STS Teaching at the Secondary Level‟, Social studies of science, 13: 569-604, 1983.H OLFORD, D.…Nuffield Combined Science: Teams for the Seventies, Themes forEigh ties?‟, Education 3-13, 9(1):38-42, 1981.I NGLE, R. B. …Nuffield Chemistry in Britain 1961-1982. Part I. Development andReception of the O-Level Publications by the Teaching Profession‟, Scienceeducation, 68:523-39, 1984.–––, …–––, Part II. Evaluation and Revision of O-Level Publications‟, Science education, 68:541-61, 1984.K ELLY, P. J. …Evaluation studies of the Nuffield A-level Biology trials. 1. Overall achievements of students‟, Journal of biological education,5:315–27, 1971.–––, …––– 2. Evaluat ion of specific objectives‟, –––, 6:29–40, 1972.–––, …–––3. Student characteristics and achievement‟, –––, 6:99-107, 1972.–––, …–––4. School characteristics and achievement‟, –––, 6:197–205, 1972.–––, …–––5. Students after the trials‟, –––, 6:259–66, 1972.L EWIS, J. L. …A Nuffield view of physics‟, Physics education, 12:70-73, 1977.–––, …16+ Examination for Nuffield Physics‟, Physics education, 16:157-60, 1981.L UCAS, A. M. and C HISMAN, D. G. A review of British science curriculum projects: implications for curriculum developers. Columbus: Ohio State University ERC Information Analysis Center for Science Mathematics and EnvironmentalEducation. 1973.The report, primarily descriptive accounts aimed at the science educationcommunity of the United States, concentrates on projects that producedmaterials for secondary science courses that “integrate the specialsciences”. There are chapters on Nuffield Combined Science and NuffieldSecondary Science. The accounts of other projects and brief accounts ofthe educational systems in Britain at the time allow the projects to beplaced in context.M EYER, G. R. …Reactions of pupils to Nuffield Science Teaching Projects trail materials in England at the Ordinary level of the General Certificate ofEducatio n‟, Journal of research in science teaching, 7:283–302, 1970.S HAYER, M. …Nuffield combined science: do the pupils understand it?‟, School science review, December, vol. 60:, 210-223, 1978.S TEVENS, P. …On the Nuffield Philosophy of Science‟, Journal of philosophy of education,12:99-111, 1978.T AWNEY, D. A. …Evaluation and science curriculum projects in the U.K.‟, Studies in science education, 3:31–54, 1976.Summarises, contrasts and compares published evaluations of five sciencecurriculum projects in a useful discussion of general issues of evaluation,and helps situate the approaches to the two Nuffield projects: NuffieldSecondary Science (Alexander, 1974) and Nuffield A-level Biology(Kelly (1971 –72) q.v..T EBBUTT, M. J. Teachers' Views about the Nuffield Advanced Physics Course‟, Physics education, 16: 228-33, 1981.W ARING, Mary. Social pressures and curriculum innovation: a study of the Nuffield Foundation Science Teaching Project. London: Methuen. 1979Deals with the various political, social and education factors influencingthe foundation of the Project, details of its execution, and its outcomes. O-level Chemistry is the major exemplar in this analysis.W ASTNEDGE, R. …Nuffield Junior Science: fifteen years on‟, Primary education review, Number 19, 10-12, Spring 1984.Arthur Lucas, November 2006。

kruskal-wallis h检验描述

Kruskal-Wallis H检验是一种用于比较三个或更多不同组之间的连续数据的非参数统计检验方法。

它是一种扩展的Wilcoxon秩和检验，适用于多个独立的样本组，而不需要假设数据满足正态分布。

这个检验通常用于确定在不同组之间是否存在显著差异，尤其是在研究中不能满足方差齐性（各组方差相等）和正态性假设的情况下。

以下是Kruskal-Wallis H检验的主要步骤和描述：1. **提出假设**：首先，提出一个原假设（H0）和备择假设（H1）。

原假设通常是：不同组的总体中位数没有显著差异。

备择假设则是：至少有一组的总体中位数不同。

2. **数据收集**：收集来自不同组的样本数据。

每个组可以包含不同数量的观察值。

3. **秩分配**：将所有数据（来自不同组的数据汇总在一起）按照大小排列，并为每个数据点分配秩（从最小到最大）。

相同数值的数据被赋予相同的秩，秩的计算方式与Wilcoxon秩和检验类似。

4. **计算秩和**：对于每个组，计算该组的所有秩的和。

5. **计算Kruskal-Wallis H统计量**：根据秩和计算Kruskal-Wallis H统计量。

这个统计量度量了不同组之间的差异程度。

计算方法如下：- H = [(12 / (N(N + 1))) * Σ(R^2 / n)] - 3(N + 1)其中，H是Kruskal-Wallis H统计量，N是总样本大小，Σ表示对所有组的秩和进行求和，R是每个组的秩和，n是每个组的样本大小。

6. **计算自由度**：计算自由度，通常记为df，以便进行后续的假设检验。

7. **查找临界值**：根据所选的显著性水平（通常是0.05），查找Kruskal-Wallis分布表中的临界值。

8. **假设检验**：比较计算得到的Kruskal-Wallis H统计量与临界值。

如果计算值大于临界值，则拒绝原假设，认为组之间存在显著差异。

否则，接受原假设，认为没有足够的证据表明组之间存在显著差异。

海尔 Illuminated Switch 产品说明书

This document is only valid on the date of printing: 11/03/2020Document ControlPage Change Description Issued by Date: Revisionno1 All Created Jasmin Hsu 29.10.20122 All Page 1 & 2 :File link updateJasmin 27.11.2012 Page 3 & 4: Document content revise3 All Document format update Jasmin Hsu 11.04.20134 All Optimize the format according to newest templateJasmin Hsu 02.12.2013 same as the dec.flyer.20135 3 Add solder thickness and solder paste information Jasmin Hsu 28.10.20146 5 Extend the information to MSL 3 on chapter 4 Jasmin Hsu 22.02.20187 5 Corrections of the chapter MSL 3 on wriiten mistakes Jasmin Hsu 03.05.2018Jasmin Hsu 11.03.2020 8 7 Operation/Assembling ,extend handling information fordesign Tip for WS-TASLThis document is only valid on the date of printing: 11/03/2020 Precautions for the use of illuminated switch1. General information:Wuerth Elektronik starts to offer wide range of illuminated switch in Surface Mount and Through Hole types with different kind of outlooks, heights and dimension fit into different customer and application segments.Wuerth Elektronik would like to give you few information of handling of our products.If you choose products which can replace your existing source, please take care about the LED specification is also close or equally to your existing source, so that at the end you would not having to big color appearance difference on your products. All related information about the LED is to find in our catalogue and specification.2. Recommend soldering profilesThe switch is design and approved for a 1.6mm single-side PCB.Using the PCB with a different thickness or using double-sided, through hole PCBs may result in loose mounting, improper insertion, or poor heat resistance in soldering, The effects will occur, depending on the type of the holes and patterns of the PCB. Therefore it is recommended that a verification test on customer is conducted before use.2.1 Recommend soldering profile for SMT partsPlease download our Reflow standard from our website under following link:http://www.we-/web/en/passive_bauelemente_standard/download_center_pb s/Download_Center_PBS.php?p=2#dbfilterFile name: “Standard Reflow Soldering Profile”This document is only valid on the date of printing: 11/03/2020For our SMD illuminated switches 2 times reflow soldering max.The component could become a color change or deformed, in case to get in touch with exceeding temperature or overstress the component as we define.For internal test, WE use solder thickness of 150µm and solder past SAC3052.2 Recommend soldering for THT partsPlease download our Reflow standard from the Internet under following link:http://www.we-/web/en/passive_bauelemente_standard/download_center_pb s/Download_Center_PBS.php?p=2#dbfilterFile name: “Standard Reflow Soldering Profile”The component could become a color change or deformed, in case to get in touch with exceeding temperature or overstress the component as we define.2.3 Recommendation for hand soldering:350°C for 3 sec. maxNote : Please make sure, that the solder heat is not come in contact with the product body as it may can cause the damage to the partand result in malfunction.2.4 Recommendation of vapor phase solderingOur Products are not proven for the VPH. Verification on thisprocess is required on customer side.This document is only valid on the date of printing: 11/03/20202.5 Cleaning, washing and coating after reflow?For our illuminated products, we normally do not suggest to put into the cleaning process, because the cleaning agent mind be damage the LED. For individual case, please help to provide details information of cleaning process, name of the cleaning agent and if possible the specification of the cleaning agent for our evaluation.Do not pot the parts into the potting material, by doing so it may cause malfunction of the switch.If our product is potted in customer applications, the potting material might shrink during and after hardening. Accordingly to this the product is exposed to the pressure of the potting material with the effect that the product is possibly damaged by this pressure and so the electrical as well as the mechanical characteristics are in danger of being affected. After the potting material is cured, the products needs to be checked if any malfunction or destructions on the product have occurred.If coating the PCB, please take care that some aggressive chemicals can cause capillary ingress into the switch and cause malfunction. Verification process is required on customer side.3. Handling of the componentThe schematic of the LED and the Switch itself is separate as it shows in our specification, please read carefully our specification.The LED characteristics is showing in the specification, please be carefully not to overload the LED.ESD prevention methods need to be applied for manual handling and processing by machinery.Do not use excessive force to operate the switch, or it may damage or deform the switch.For Anode/Cathode direction of the LED’s, please refer to our specification.This document is only valid on the date of printing: 11/03/20204. Storage & operation conditionOperation temperature: -40°C ~ 85°COur SMD-parts (Match code WS-TASL) has MSL 3, others are specify as MSL1Storage temperature for MSL 3 :Condition and TimeSealed <40℃/90%RH, Max. storage time 12 months at this conditionUnsealed <30℃/60%RH, Max. allowable exposure time less than 168 hours When open the sealing, a check on humidity indicator card is require to check if a pre-baking before reflow process is necessary.We do recommend customer immediately to re-seal the packaging to the original seal status. With a new sealing, it is mandatory to use a new humidity indicator card.In the event, that the exposure time is ≤12 hours, a minimum desiccating period of 5 times to the exposure time is required to dry. This can be accomplished by dry pack according to clause 3.3 or a dry cabinet that capable of maintaining not greater than 5%RH.In the event, that the exposure time is >12 hours, a baking process according to IPC/JEDEC-J-STD-033 is required.The Floor life can time be re-start after the baking process.After bag is opened, devices that will be subjected to reflow solder or other higher temperature process must be mount within 168 hours of factory conditions ≤30°C / 60% RH or store per IPC/JEDEC J-STD-033 2. Baking time for components exposure ≤ 72 hours:Temperature DurationSingle component 125 ℃17hours90 ℃≤5%RH2dayComponent on Tray 40 ℃≤5%RH23daysComponent on Tape on40℃≤5% RH23daysReel or TubeOther terms than above mentioned is on customer own risks.This document is only valid on the date of printing: 11/03/2020All products are supposed to be use the end of the period of 12 months base on the product date code, if not a 100% solder ability cannot be warranted.5. Operation /AssemblingDo not repeatedly operate the switch with excessive force, or it may damage or deform the switch.To assemble the caps :Our caps are designed with notches to avoid the fall out afterwards.By insertion of the cap, please put the cap on the strait vertical down to the actuator. By hearing a crispy sound, the cap is latched.If you need to remove the cap, please use with your finger(nail) to pull up one side of the cap. Please do not use any sharp tools because it can damage the switch or the cap.This document is only valid on the date of printing: 11/03/2020To design our SMD illuminated switch WS-TASL :WS-TASL is the only series from our illuminated switches, which is not use for front panel. To design the cap or knob for it, please design so, that the operating part will operate in a straight vertical line to the center of the actuator or plunger of the switch. A decrease in the life of the switch may result if the operating part is pressed off-center or from an angle. Also it may cause function errors or broken actuators or plunger of the switch.6. PackagingOur SMD parts are generally pack on Tape on reel with ESD vacuum bag.This document is only valid on the date of printing: 11/03/2020Our THT parts are generally pack in ESD Tray with Dry back and sealed in plastic bag.7. ComplianceWuerth Elektronik products are RoHS compliance. For a 3rd parties test report, please contact us.For any further information, please feel free to contact our sales representatives.。

偏好逆转实验报告

一、实验背景偏好逆转（Preference Reversal）是指个体在面临选择时，其偏好与定价不一致的现象。

这一现象最早由心理学家利希滕斯坦（Lichtenstein）和斯洛维克（Slovic）于1971年提出。

通过一系列实验，他们发现个体在评估经济利益时，愿意支付的最大值与愿意接受的补偿额之间存在显著差异。

这一发现对于理解人类决策行为、市场定价策略以及消费者心理等方面具有重要意义。

二、实验目的本次实验旨在验证偏好逆转现象的存在，并探讨影响偏好逆转的因素。

通过实验，我们希望了解以下问题：1. 偏好逆转现象是否真实存在？2. 哪些因素会影响偏好逆转现象的发生？3. 偏好逆转现象在实际生活中的应用有哪些？三、实验方法1. 实验对象：选取30名大学生作为实验对象，男女比例均衡。

2. 实验材料：设计两组实验材料，每组包含三个选择项。

选择项的形式为：A. 获得X美元的概率为p，获得x美元的概率为1-p；B. 获得Y美元的概率为q，获得y美元的概率为1-q；其中X、x、Y、y、p、q均取正值。

3. 实验步骤：a. 向实验对象展示第一组选择项，要求他们从中选择一个他们认为最优的选择项。

b. 在实验对象做出选择后，询问他们如果以X、x、Y、y、p、q为条件，他们愿意为该选择项支付的最高金额。

c. 重复步骤a和b，对第二组选择项进行实验。

d. 在实验结束后，向实验对象发放调查问卷，了解他们的性别、年龄、专业等信息。

四、实验结果与分析1. 实验结果：通过对实验数据的整理和分析，我们发现：a. 在第一组选择项中，有25名实验对象选择了A，5名选择了B；b. 在第二组选择项中，有20名实验对象选择了B，10名选择了A；c. 在第一组选择项中，实验对象愿意支付的最高金额平均为78.6美元；d. 在第二组选择项中，实验对象愿意支付的最高金额平均为55.2美元。

2. 实验结果分析：a. 偏好逆转现象确实存在。

在第一组选择项中，实验对象倾向于选择A，但在支付意愿方面，他们更愿意为B支付更高的金额。

Testing the performance of spatial interpolation techniques

Computers and Electronics in Agriculture 50(2006)97–108Testing the performance of spatial interpolation techniquesfor mapping soil propertiesT.P.Robinson ∗,G.MetternichtDepartment of Spatial Sciences,Curtin University of Technology,GPO Box U 1987,Perth WA 6845,AustraliaReceived 9August 2004;received in revised form 30June 2005;accepted 27July 2005AbstractIn this paper,we implement and compare the accuracy of ordinary kriging,lognormal ordinary kriging,inverse distance weighting (IDW)and splines for interpolating seasonally stable soil properties (pH,electric conductivity and organic matter)that have been demonstrated to affect yield production.The choice of the exponent value for IDW and splines as well as the number of the closest neighbours to include was decided from the root mean squared error (RMSE)statistic,obtained from a cross-validation procedure.Experimental variograms were ﬁtted with the exponential,spherical,Gaussian and linear models using weighted least squares.The model with the smallest residual sum of squares (RSS)was further interrogated to ﬁnd the number of neighbours that returned the best cross-validation result.Overall,all of the methods gave similar RMSE values.On this experimental ﬁeld,ordinary kriging performed best for pH in the topsoil and lognormal ordinary kriging gave the best results when applied to electrical conductivity in the topsoil.IDW interpolated subsoil pH with the greatest accuracy and splines surpassed kriging and IDW for interpolating organic matter.In all uses of IDW,the power of one was the best choice,which may due to the low skewness of the soil properties interpolated.In all cases,a value of three was found to be the best power for splines.Lognormal kriging performed well when the dataset had a coefﬁcient of skewness larger than one.No other summary statistics offered insight into the choice of the interpolation procedure or its parameters.We conclude that many parameters would be better identiﬁed from the RMSE statistic obtained from cross-validation after an exhaustive testing.©2005Elsevier B.V .All rights reserved.Keywords:Interpolation;Spatial prediction;Geostatistics;Soil properties;Precision agriculture;Cross-validation1.IntroductionImplementation of variable-rate technology can provide considerable ﬁnancial gains to the farming industry.How-ever,its effectiveness relies on the accuracy of the spatial interpolation used to deﬁne the spatial variability of soil properties.The accuracy of interpolation methods for spatially predicting soil properties has been analysed in several studies.Kravchenko and Bullock (1999)compared inverse distance weighting (IDW),ordinary kriging and lognormal ordinary kriging for soil properties (phosphorous (P)and potassium (K))from 30experimental ﬁelds.They found that if the underlying dataset is lognormally distributed and contains less than 200points,lognormal ordinary kriging generally∗Corresponding author.Tel.:+61892663935;fax:+61892662707.E-mail addresses:T.Robinson@.au,pfrass@.au (T.P.Robinson),G.Metternicht@.au (G.Metternicht).0168-1699/$–see front matter ©2005Elsevier B.V .All rights reserved.doi:10.1016/pag.2005.07.00398T.P.Robinson,G.Metternicht/Computers and Electronics in Agriculture50(2006)97–108outperforms both ordinary kriging and IDW;otherwise,ordinary kriging is more successful.Further,Laslett et al. (1987)also found ordinary(isotropic)kriging to be a better method than IDW for interpolating pH.In fact,Laslett et al.(1987)judged splines to be a better than both IDW and kriging.In contrast,Gotway et al.(1996)observed better results than kriging for soil organic matter and nitrogen when using IDW.Weber and Englund(1992)also found that IDW produced better results than kriging(with lognormal kriging outperforming ordinary kriging).There have been many conﬂicting reports concerning the use of basic statistics to predetermine both interpolation methods and their parameters.For example,Kravchenko and Bullock(1999)report a signiﬁcant improvement in accuracy of soil properties interpolated using IDW by manipulating the exponent value.They found that data with high skewness(>2.5)were often best estimated with a power of four(ﬁve out of eight datasets)and for most of the soil properties with low skewness(<1),a power of one yielded the most accurate estimates(9out of15datasets). Alternatively,Weber and Englund(1994)report that IDW with a power of one resulted in a better estimation for data with skewness coefﬁcients in the range of four to six when interpolating blocks of contaminant waste sites.Likewise, a larger exponent produced better estimations when the data had low skewness.For organic matter,in particular,Gotway et al.(1996)found that the accuracy of the inverse distance method increased as the exponent value increased.Theirﬁndings show that properties with a low coefﬁcient of variation (<25%)were better explained by a higher power,in most cases a power of four.In addition,datasets with a high coefﬁcient of variation gave best results when a power of one was used.On the contrary,Kravchenko and Bullock (1999)found no signiﬁcant correlation between the exponent value used for IDW and the coefﬁcient of variation.Given the variability of results obtained by these previous studies the research reported hereafter aims to:-Assess the accuracy of various well-known interpolation techniques for mapping soil pH,electrical conductivity and organic matter through manipulation of the various parameters attributable to each technique;-Determine if non-spatial statistics could assist in determining the best interpolation method to implement without using exhaustive test parameters;-Identify the spatial prediction method that best illustrates the spatial variability of the soil properties studied.This would enable the identiﬁcation of areas where remediation is required to improve crop growth.2.Spatial prediction methods2.1.KrigingThe presence of a spatial structure where observations close to each other are more alike than those that are far apart(spatial autocorrelation)is a prerequisite to the application of geostatistics(Goovaerts,1999).The experimental variogram measures the average degree of dissimilarity between unsampled values and a nearby data value(Deutsch and Journel,1998),and thus can depict autocorrelation at various distances.The value of the experimental variogram for a separation distance of h(referred to as the lag)is half the average squared difference between the value at z(x i) and the value at z(x i+h)(Lark,2000b):ˆγ(h)=12N(h)N(h)i=1[z(x i)−z(x i+h)]2(1)where N(h)is the number of data pairs within a given class of distance and direction.If the values at z(x i)and z(x i+h) are autocorrelated the result of Eq.(1)will be small,relative to an uncorrelated pair of points.From analysis of the experimental variogram,a suitable model(e.g.spherical,exponential)is thenﬁtted,usually by weighted least squares, and the parameters(e.g.range,nugget and sill)are then used in the kriging procedure.2.2.Inverse distance weightingSimilar to kriging,inverse distance weighting directly implements the assumption that a value of an attribute at an unsampled location is a weighted average of known data points within a local neighborhood surrounding the unsampledT.P .Robinson,G.Metternicht /Computers and Electronics in Agriculture 50(2006)97–10899Fig.1.Study area location and map of the distribution of soil samples.location.The formula of this exact interpolator is (Burrough and McDonnell,1998):ˆz (x 0)= n i =1z (x i )d −r ijn i =1d −rij(2)where x 0is the estimation point and x i are the data points within a chosen neighborhood.The weights (r )are related to distance by d ij ,which is the distance between the estimation point and the data points.The IDW formula has the effect of giving data points close to the interpolation point relatively large weights whilst those far away exert little inﬂuence.The higher the weight used the more inﬂuence points close to x 0are given.2.3.SplinesSplines consist of polynomials,which describe pieces of a line or surface,and they are ﬁtted together so that they join smoothly (Webster and Oliver,2001).Splines produce good results with gently varying surfaces,and thus are often not appropriate when there are large changes in the surface values within a short horizontal distance.3.Materials3.1.Study area and sampling designThe study area is a 60ha paddock,called ‘Ardgowan ’on a dry land sheep and cropping farm,located in the Shire of Wickepin,in the South West of Western Australia.As a result of ongoing research activities in the application of remote sensing to agriculture,100soil samples were collected at 10and 30cm depth (Fig.1),geo-referenced using a GPS receiver (accuracy of ±5m)and analysed for organic matter,electrical conductivity and soil anic matter was assayed using the ‘loss on ignition’method.A pH electrode was used to measure pH in a 1:1mixture of soil to calcium chloride solution.Electrical conductivity was measured in a 1:5extract.The sampling design was based on slope (derived from a digital elevation model (DEM))and the change in the normalised difference vegetation index (NDVI).The NDVI was derived from a high-resolution digital multispectral image,acquired at 2m spatial resolution.The intent of this strategy is that areas with the greatest change in NDVI coupled with relatively steep slope characterise areas of high variability,which equates to heterogeneous soil properties.Therefore,more sample points were taken over areas with higher variability (Drysdale,2001;Drysdale et al.,2002).3.2.Description of soil propertiesAcidity is a soil property that has a devastating effect on crop growth,because acidiﬁcation causes a reduction in the availability of some essential nutrients (e.g.calcium and molybdenum)and also an increase of other nutrients to100T.P.Robinson,G.Metternicht/Computers and Electronics in Agriculture50(2006)97–108toxic levels(e.g.manganese and aluminium)(Charman,2000).Soils with a pH less than4.5in CaCl2in the topsoil (0–10cm)are considered toxic to most crops(Fenton and Helyar,2000).These soils,especially where the rainfall is over500mm,often present acidity problems further down the soil proﬁle,and so the subsoil(10–30cm)also requires assessment.If only the topsoil is affected then lime can be incorporated with good results.However,if the entire proﬁle is affected then even an application of lime will still not allow crops to develop deep-root systems.In this case,the pH in the lower levels will improve over several years(depending on the porosity of the soil)as the lime moves down the proﬁle.In general,soils with a pH of between5and7.5present no problems.A pH above9 indicates that salinity and sodicity are likely,although not all sodic and saline soils are alkaline(Fenton and Helyar, 2000).The cause of rising acidity is generally related to nitrate leaching and a build-up of organic anic matter build-up is often the result of pasture improvement procedures such as the application of fertilisers,and the break down of dead soil organisms and plant residues.Nitrate leaching is heavily induced when produce is removed from the paddock,because the surface is exposed and leftover nitrogen is not absorbed by plants(Charman,2000).Lit-erature reviewed states that soils with organic matter contents greater than2.6%have good nutrient storage(Purdie, 1998).Electrical conductivity(EC)of a soil solution can be used to estimate the salinity of an area.Charman(2000) recommend that saline soils are those with an EC greater than1.5dS/m for a1:5extract.More precisely,the yield of most plants is not restricted until the EC is greater than2dS/m(Charman,2000).4.Research approach4.1.Visualization and exploratory data analysisFig.2summarises the methods and techniques applied in this research for spatial prediction and comparative evaluation of the soil properties.This begins with a visual analysis by screening the data values to identify incorrect coordinate information and illogical data points.Visualization is also used to quickly identify the presence or absence of spatial autocorrelation.Description of the data values is achieved via basic summary statistics,including means, medians,variances and skewness.Further exploration is available through histograms,box-plots and normal plots. These tools are useful for examining the values for outliers,which are detrimental to spatial prediction.The variogram, in particular,is very sensitive to outliers because it is based on the squared differences among data(Lark,2000a).The worst effect is when the outlier is near the centre of the study area,as it contributes to the average many times for each lag.If the data are irregularly sampled,as in this study,the relative contributions of the extreme values are even less predictable.The result is that the experimental variogram is not inﬂated equally over its range,and thus can appear erratic(Webster and Oliver,2001).4.2.Data transformation and interpolationGeostatistical analysis is best performed on Gaussian distributions.When non-normality is apparent,transformations of the data can assist to make it approximately normal.Skewness is the most common form of departure from normality. If a variable has positive skewness,the conﬁdence limits on the variogram are wider than they would otherwise be and as a result,the variances are less reliable.A logarithmic transformation is considered where the coefﬁcient of skewness is greater than1and a square-root transformation if it is between0.5and1(Webster and Oliver,2001).Applying ordinary kriging to logarithmic transformed data is the essence of lognormal kriging.It is important to note that for logarithmic transformations,the back transformation through exponentiation tends to exaggerate any error associated with interpolation,with extreme values the worst affected.To mitigate this effect,we use an unbiased back-transform as shown in Eq.(3)(Deutsch and Journel,1998).ˆz(x i)=expˆγ(x i)+σ2(x i)2(3)whereσ2(x i)is the corresponding lognormal kriging variance,ˆγ(x i)the lognormal kriging estimate andˆz(x i)is the corresponding back-transformed result in the original data domain.T.P.Robinson,G.Metternicht/Computers and Electronics in Agriculture50(2006)97–108101Fig.2.Conceptual model for spatial prediction of soil properties.WLS,weighted least squares;RSS,residual sum of squares;RMSE,root mean squared error found from cross-validation;IDW,inverse distance weighting.4.3.Sample size requirements for variogram computationLiterature suggests some100–150data is the minimum requirement to achieve a stable variogram(e.g.V oltz and Webster,1990).This quota is satisﬁed in this research,with100data available for each soil property.Due to the need of over300samples to properly detect anisotropy,it is not feasible to explore directional effects for the dataset used in this research.Accordingly,the spatial variation is assumed isotropic and all variograms are omnidirectional.4.4.Criteria for comparisonIt is common practice to use cross-validation to validate the accuracy of an interpolation(V oltz and Webster,1990). Cross-validation is achieved by eliminating information,generally one observation at a time,estimating the value at that location with the remaining data and then computing the difference between the actual and estimated value for each data location(Davis,1987).Cross-validation is an excellent scheme for solving the inconvenience of redundant data collection(Olea,1999;Webster and Oliver,2001),and hence all of the collected data can be used for estimation. The cross-validation technique is used to choose the best variogram model among candidate models and to select the search radius and lag distance that minimises the kriging variance(Davis,1987;Olea,1999).It is also used to assist ﬁnding the best parameters from those tested for IDW(Tomczak,1998)and splines.To compare different interpolation techniques,we examined the difference between the known data and the predicted data using the mean error(Eq.(4)),the root mean squared error(Eq.(5)),the average kriging standard error(Eq.(6)), the root mean square standardized prediction error(Eq.(7))and the mean standardized prediction error(Eq.(8)).Eqs.102T.P.Robinson,G.Metternicht/Computers and Electronics in Agriculture50(2006)97–108(6)–(8)are only applicable to kriging as they require the kriging variance.Eqs.(4)and(5)are applicable to all of the interpolation techniques applied in this research.ME=1NNi=N{z(x i)−ˆz(x i)}(4)RMSE=1NNi=1{z(x i)−ˆz(x i)}2(5)AKSE=1NNi=1σ2(x i)(6)RMSP=1NNi=1MEσ(x i)2(7)MSPE=1NNi=1MEσ2(x i)(8)whereˆz(x i)is the predicted value,z(x i)the observed(known)value,N the number of values in the dataset andσ2is the kriging variance for location x i(Johnston et al.,2001;Webster and Oliver,2001;Kravchenko and Bullock,1999; V oltz and Webster,1990).The mean error should ideally be zero,if the interpolation method is unbiased.The calculated ME,however,is a weak diagnostic for kriging because it is insensitive to inaccuracies in the variogram.The value of ME also depends on the scale of the data,and is standardized by dividing by the kriging variance to form the MSPE.An accurate model would have a MSPE close to zero.If the model for the variogram is accurate,then the RMSE should equal the kriging variance,so the RMSP should equal1.If the RMSP is greater than1,then the variability in the predictions is being underestimated,and vice versa.Likewise if the average kriging standard errors(AKSE)are greater than the root mean square prediction errors(RMSP),then the variability is overestimated,and vice versa(Johnston et al.,2001;Webster and Oliver,2001).5.Implementation and discussion of results5.1.Data visualizationFig.3a shows the spatial distribution of the topsoil pH,classiﬁed into quartiles,depicting that the bulk of the data have a critical pH range of4.40–4.75.The classiﬁed map of subsoil pH(Fig.3b)exhibits a good degree of autocorrelation with similarly classiﬁed values clustering together in space.Fig.3c shows the spatial distribution of topsoil electrical conductivity,which illustrates that generally,the paddock does not seem to have a salinity problem in the topsoil(all values less than2dS/m).Fig.3d shows the spatial distribution of the topsoil organic matter with several clusters in the study area.It also appears that much of the paddock has satisfactory levels of organic matter.5.2.Summary statistics,outlier detection and transformationA statistical summary of the pH,EC and organic matter soil properties is presented in Table1.A histogram,box-plot and normal plot were constructed for all soil properties,revealing two outliers for pH.Their removal reduced the coefﬁcient of skewness from0.859to0.266avoiding the need for data transformation.Exploratory analysis suggested one outlier for subsoil pH(4.45),which was removed.Two potential outliers with an EC of0.35and0.4were found from exploratory analysis for electrical conductivity.The bulk of the data has an EC of0.1,which dramatically affects the normality of the distribution.However,it is those values that‘appear’as outliers in the data that are of most interest to the analysis of salinity and hence,they are kept in the dataset.Furthermore,since the coefﬁcient of skewness isT.P.Robinson,G.Metternicht/Computers and Electronics in Agriculture50(2006)97–108103Fig.3.Samples classiﬁed by quartiles for(a)topsoil pH,(b)subsoil pH,(c)topsoil electrical conductivity and(d)topsoil organic matter.greater than1(1.761),the natural logarithm is applied for a kriging analysis(thus,lognormal kriging)to stabilise the variance(Goovaerts,1999).This was later back-transformed using Eq.(3).Exploration of organic matter revealed one potential outlier(9%),however,visualization showed that this value is located on the periphery of the paddock and therefore it will not be included in many lags.It also has relatively large values contiguous to it.Consequently,the decision was to include the data in the analysis.Although the coefﬁcient of skewness for organic matter is located inTable1Summary statistics for pH,electrical conductivity(EC)and organic matter(OM)Soil property N Min Max Range Mean Median Var CV(%)Skewness Kurtosis pH(10cm)100 3.95 5.7 1.75 4.596 4.550.0860.859 2.044 pH(30cm)100 4.45 6.6 2.15 5.811 5.850.1757−0.6240.272 EC(dS/m)(10cm)10000.40.40.1340.100.00555 1.761 3.341 OM(%)(10cm)98a 1.9997.01 4.376 4.24 1.983320.610.238a Two samples cracked under laboratory conditions and were not tested.104T.P.Robinson,G.Metternicht/Computers and Electronics in Agriculture50(2006)97–108Table2Summary of the residual sum of squares(RSS)statistic produced for each different modelSoil property RSSTopsoil(10cm)pHExponential0.000215Spherical0.000284Linear0.000847Gaussian0.000228Subsoil(30cm)pHExponential0.000956Spherical0.001260Linear0.025700Gaussian0.001220Topsoil(10cm)electrical conductivity(dS/m)Exponential0.000003Spherical0.000003Linear0.000011Gaussian0.000003Topsoil(10cm)organic matter(%)Exponential0.000157Spherical0.000202Linear0.004400Gaussian0.000336Bolded RSS values were chosen as the best model.Fig.4.Fitted variograms for soil properties.(a)pH in the topsoil(10cm depth)is best represented by the exponential model,which shows a nugget (C0)of0.0539;a sill(C0+C)equal to0.1079;range(A0)equal to2110;coefﬁcient of determination(R2)of0.419;a residual sum of squares(RSS) equal to0.00021.(b)Fitted variogram of pH in the subsoil(30cm depth).(c)Fitted variogram of the electrical conductivity soil property in the topsoil.(d)Fitted variogram of the organic matter soil property in the topsoil.T.P.Robinson,G.Metternicht/Computers and Electronics in Agriculture50(2006)97–108105 Table3Parameters found when the kriging model returned the lowest cross-validation RMSE for all soil propertiesSoil property Neighbours ME RMSE AKSE RMSP MSPETopsoil(10cm)pH25−0.001070.24750.25310.9799−0.00218 Subsoil(30cm)pH300.0013250.3870.3487 1.0920.00247 Topsoil(10cm)EC(dS/m)15−0.00018790.071880.06902 1.0410.004407 Topsoil(10cm)OM(%)50.0004648 1.438 1.363 1.0450.003325ME,mean error;RMSE,root mean squared error;AKSE,average kriging standard error;RMSP,root mean square standardized prediction error; MSPE,mean standardized prediction error.the range where a square-root transformation is appropriate,it is that outlying value on the periphery that is skewing the data,so we chose to leave the data in its original form.5.3.Interpolation and interpretationOmnidirectional experimental variograms for all properties were calculated using Eq.(1).The exponential,spherical, Gaussian and linear models wereﬁtted to the experimental variogram and the model with the lowest residual sum of squares(RSS)was chosen as optimal.Table2summarises the RSS for eachﬁtted model for all soil properties.The bestﬁtting models for all of the soil properties are presented in Fig.4.The variogram of topsoil pH(Fig.4a)appears to exhibit a pure nugget effect,which may be because of too sparse a sampling to adequately capture autocorrelation. There is no clear range and sill,nor is the nugget variation small compared to the spatially dependent random variation. It is perhaps inappropriate toﬁt any model to this experimental variogram.Nonetheless,the exponential model was implemented as it returned the bestﬁt.Fig.4b shows theﬁtted variogram for subsoil pH,depicting the range to be around138m(95%of the sill).The exponential variogram model provided the bestﬁt to the experimental variogram. The experimental variogram for electrical conductivity(Fig.4c),appears erratic and without a distinct structure.The spherical model provided the bestﬁt to this sequence of data.The experimental variogram for organic matter appears to have quite good structure and a gradual approach to the range,with the exponential model providing the bestﬁt.The number of closest samples chosen varied from5to30,with aﬁve-sample interval.The best-found kriging parameters were selected from the cross-validation results(Table3).For topsoil pH the lowest root mean square error (RMSE)was found with a neighborhood of25points.The mean error(ME)and mean standardized prediction error (MSPE)suggests that the predictions are relatively unbiased.Since the average kriging standard error(AKSE)is greater than the RMSE,the kriging variance is larger than the true estimation variance and indicates that the variogram model is overestimating the variability of the predictions.The root mean square standardized error(RMSP)also suggests the same since it is less than1.With reference to Fig.4a,it is likely that the RMSP is less than1because theﬁtted Table4Parameters returning the lowest RMSE from cross-validation for IDW and splines for all soil propertiesSoil property Power Neighbours ME RMSETopsoil(10cm)pHIDW125−0.00770.2485 Splines325−0.00330.252 Subsoil(30cm)pHIDW115−0.0032580.3808 Splines330−0.00280.3839 Topsoil(10cm)EC(dS/m)IDW130−0.0015690.07391 Splines330−0.00010.0735 Topsoil(10cm)OM(%)IDW115−0.03093 1.438 Splines315−0.0134 1.43 ME,mean error;RMSE,root mean squared error;EC,electrical conductivity;OM,organic matter.106T.P.Robinson,G.Metternicht/Computers and Electronics in Agriculture50(2006)97–108exponential model exceeds the observed variances(shown by the squares)at short lags,particularly theﬁrst lag(and also the third,ﬁfth and seventh),and it is these lags that dominate the kriging systems(Webster and Oliver,2001).The lowest RMSE was found using30nearest neighbours for subsoil pH.The ME and MSPE suggests that the predictions are relatively unbiased.Given that the AKSE is smaller than the RMSE,the variability is being underpredicted.Since the RMSP is greater than1,the kriging variance is smaller than the true estimation variance, possibly a result of the fourth lag in Fig.4b being underestimated by the exponential model.For topsoil electrical conductivity,the most favourable number of neighbours was found to be15.The low values ME and MSPE suggest that the predictions are relatively unbiased.Given that the average standard errors are smaller than the RMSE,the variability is being underpredicted,though not signiﬁcantly(difference of0.003).Five neighbours were found to be optimal for organic matter.The RMSP is greater than one,and hence the variability is being under-predicted to a small extent.IDW was estimated with powers of one,two,three and four.The precision of IDW is also affected by the choice of the number of the closest samples used for estimation;hence,this was varied from5to30for the various powers used.Fig.5.Interpolated soil maps(a)topsoil pH using kriging,(b)subsoil pH using IDW,(c)topsoil EC using lognormal kriging and(d)topsoil OM using splines.T.P.Robinson,G.Metternicht/Computers and Electronics in Agriculture50(2006)97–108107 Cross-validation was used toﬁnd the best agreement between the measured data and the IDW estimates.In all cases, the best weighting parameter was found to be one.This suggests that the weights diminish slowly from the sample point over the chosen radius.Linear,quadratic and cubic splines were implemented using the same neighborhood variation as used for kriging and IDW.In all cases,the best exponent value was found to be three(cubic splines)suggesting that lower order polynomials were insufﬁcient at representing the variation on the paddock.The best cross-validation parameters for IDW and splines are shown in Table4.The interpolated maps of all soil properties using the method with the lowest RMSE from the cross-validation process can be seen in Fig.5.Fig.5a shows an interpolation of topsoil pH using ordinary kriging.The lowest pH values(and therefore highest acidity)occur on the middle to upper Western side of the paddock with pH values below4.5(critical).The highest pH is located in a large circular‘hole’to the Southeast of the paddock.This map would be useful at directing a differential liming application to lift pH.According to the kriged estimates,the entire paddock has a pH lower than5,which means that crops that are sensitive to acidity will have trouble establish-ing in these soils,resulting in a poor production.Furthermore,since the pH is below5.2(and rainfall is greater than500mm per annum)for the entire paddock there is likely to be a net movement of acidity down to the next layer of the soil(Fenton and Helyar,2000,p.234)and hence it was necessary to examine the subsoil pH.IDW proved to be the best method for interpolating subsoil pH,and the soil map is shown in Fig.5b.Subsoil pH does not show signs of acidic conditions at present with all pH values above5.In this case,a farmer would likely apply sufﬁcient lime to the topsoil to lift the pH of the soil,without the need to wait for the lime toﬁlter through to the subsoil over time.This would enable crops to establish and develop root systems that are adequate for long-term survival.Fig.5c shows the interpolation of electrical conductivity using lognormal kriging.It reveals that there are no topsoil salinity problems on the paddock,as all values are lower than1.5dS/m.Fig.5d shows the interpolation of organic matter over the paddock using the splines technique.Since a value greater than2.6%suggests good nutrient storage capacity,it can be seen that much of the paddock soil has sufﬁcient organic matter.6.ConclusionsThis study has shown that,out of the four spatial prediction methods used,there is not one single interpolator that can produce chief results for the generation of continuous soil property maps all of the time,particularly with a dataset that has not been designed with one particular interpolator in mind.Overall,all of the methods gave similar RMSE values,using the cross-validation technique for evaluation.Ordinary kriging performed best for pH in the topsoil and lognormal kriging outperformed both IDW and splines for interpolating electrical conductivity in the topsoil.The IDW technique interpolated subsoil pH with the greatest accuracy,and splines surpassed kriging and IDW for interpolating organic matter.In all implementations of IDW the power of one was the best choice(over powers of two,three and four),which is possibly due to the relatively low skewness inherent in all soil properties modelled(as also found by Kravchenko and Bullock,1999).For our dataset,the coefﬁcient of variation could not be used to identify the best a priori weight to use for IDW.The best exponent value for splines was found to be three for all implementations of the splines technique, suggesting lower order polynomials could not capture the variation of the soil properties across the paddock.Lognormal kriging,by stabilising the variance outperformed IDW and splines for the EC dataset,and thus in this research it was found to be a suitable choice when the coefﬁcient of skewness was larger than1.No other summary statistics were found to correlate to any of the parameters chosen after extensive trials.Especially in cases where sampling is not tailored to a particular interpolation technique,summary statistics should not be solely relied upon to infer an interpolation method or interpolation parameters.Instead,whilst the cross-validation technique is not a conﬁrmatory tool,as an exploratory tool it greatly assists in choosing appropriate interpolation procedures and their associated parameters.AcknowledgementsThis research has been supported by the Australian Research Council(ARC),under the Strategic Partnership with the Industry Scheme(SPIRT).The authors also thank Georgina Warren and Jacob Delfos for the collection of the soil samples.Additionally,we acknowledge industry partners SpecTerra Systems Pty Ltd.and the Department of。

高中高考英语一轮复习模拟试题精选高三全册英语试题_

时遁市安宁阳光实验学校2018高考一轮复习英语模拟试题精选03共150分，考试时间120分钟。

第I卷（选择题共115分）第一部分听力（共两节，满分30分）第一节（共5小题；每小题1．5分，满分7．5分）听下面5段对话。

每段对话后有一个小题，从题中所给的A、B、C三个选项中选出最佳选项，并标在试卷的相应位置。

听完每段对话后，你都有10秒钟的时间来回答有关小题和阅读下一小题。

每段对话仅读一遍。

1．What are the two speakers talking about?A．Their hobbies．B．Their favorite music．C．Their study．2．What are the speakers talking about?A．Time for the exam．B．Exam results．C．Change of class hours3．What will the woman tell the man?A．Her company’s name．B．Her new address．C．Herphone number．4．What can you learn about the man?A．He is quite confident．B．He is very slow．C．He is rather upset．5．Where does the woman usually have her breakfast?A．In the kitchen．B．In the school cafeteria．C．In a hotel．第二节（共15小题；每小题1．5分，满分22．5分）听下面5段对话或独白。

每段对话或独白后有几个小题，从题中所给的A、B、C三个选项中选出最佳选项，并标在试卷的相应位置。

听每段对话或独白前，你将有时间阅读各个小题，每小题5秒钟；听完后，各小题将给出5秒钟的作答时间。

Individual 24-Hour Dietary Recall Protocols

Individual 24-Hour Dietary Recall ProtocolsA. PurposeThe purpose of the individual administered 24-hour recall is to gain information regarding the participant’s diet. This information will be used to determine the nutritional and educational needs of the participant. Food recalls are also used to evaluate the effectiveness of the nutrition program.B. Materials Needed1. 24-hour recall form and a pencil2. Food Recall Kit containing each of the following:✓Measuring cups and spoons (Liquid and Dry)✓ 4 oz. cup = ½ cup of fresh fruit✓8 oz. cup = 1 cup of fresh fruit✓16 oz. cup = 2 cups of lettuce which is 1 portion of vegetables✓CD –1 slice of bread✓Deck of cards or the palm of your hand = 3 ounces of meat✓Food Models✓Red Dinner Plate to use as a visual to measure out portions or determine how large a pizza slice or a portion of dessert might be. Ask questions such as, “Did it take up the whole plate? Was it half a plate a fourth of the plate?”✓Plasti c container of 2 to 3 cups of riceRice will be used as an example of measuring more dense foods such as mashed potatoes and oatmeal.✓Plasti c container of 2 to 3 cups dried beans or dry cerealBeans or cereal may be used as an example of measuring foods that are more loosely packed, such as dry cereal or vegetablesC. Procedure1.Explain to the participant that you need to know only what she (he)actually ate. She (he) should not feel embarrassed about any food, as there are no “good” or “bad” foods. No one eats just the right foods all the time.2.Do not express in words or facial expressions either approval ordisapproval of foods mentioned by the participant.3.Do not ask questions that would lead the participant to feel she (he)“should” have had a certain item and, thus say that they di d.4. Use your Food Recall Kit to determine the amounts of foods consumed.5. Start with the most recent meal or snack that the participant consumed.Work backwards to cover all foods and beverage consumed in the last 24 hours or in a “typical day”. W eekends and holidays are not typical days and recalls from these days may provide an inaccurate view of the participant’s diet.6. Quick List:Record the list of foods as the homemaker remembers them; portion sizes and preparation methods will be recorded in the next step. This list of foods is termed the quick list. To obtain this list of foods from the participant use the following types of probes to find wh at foods were eaten:A. The first type of probing is related to time.Examples:“At what time was this? Did you eat or drink anything before or after that?”“What did you have at that time?”“At what time did you g o to bed?”B. The second type of probe is related to the participant’s activities.Examples:“What did you do this morning?”“While you were working around the house, did you take a break to havesomething to eat or drink?”“Did you watch TV last night? When you watched TV, did you eatanything?”“Did you have anything to drink with this?”C. The third type of probe tries to get more complete information abou tfoods already reported.Examples:“Do you remember anything else that you ate or drank with this food?”“What else did you have at this meal?”“Was the (bread, vegetable) eaten plain or did you put something on it?“Did you have anything in your coffee?”“Did you have a second helping?”7. Detailed Description:After you have recorded the participant’s quick list, you can then complete the detailed description of foods consumed. This will include recording preparation method, brand name, portion size, and the time the food or beverage was consumed. To get more information on the amounts and the type of foods eaten use the following techniques:A. Determine if all of the food was eaten or if some food was left on theplate.B. Encourage the participant to describe foods as clearly as possible. Theinterviewer may have to restate questions to get more information.C. Describe combination dishes carefully. Mixtures such as sandwiches,soups, stew, pizza, casseroles, etc. can be prepared in many ways.D. Ask to see packages, if available, on prepackaged foods, and recordbrand name and other pertinent information.8. Review:Once the 24 hour food recall is complete read the list back to the participant. Ask the participant if the recall is correct or if they forgot to mention anyfood that was consumed.9. Thank the participant for their cooperation. Do not comment on the recall at this time, unless the participant asks a specific question.10. Tell the participant that they will be getting a printout of their food recalland a summary of how their food intake meets USDA’s MyPyramidrecommendations.11. Wait and address deficiencies, excesses, etc. when the diet summary isreviewed and when lessons are taught that deal with that area of the diet.12. Give each participant a copy of “What Should I Eat.”。

toch五项实验流程

toch五项实验流程下载温馨提示:该文档是我店铺精心编制而成，希望大家下载以后，能够帮助大家解决实际的问题。

文档下载后可定制随意修改，请根据实际需要进行相应的调整和使用，谢谢!并且，本店铺为大家提供各种各样类型的实用资料，如教育随笔、日记赏析、句子摘抄、古诗大全、经典美文、话题作文、工作总结、词语解析、文案摘录、其他资料等等，如想了解不同资料格式和写法，敬请关注!Download tips: This document is carefully compiled by theeditor. I hope that after you download them,they can help yousolve practical problems. The document can be customized andmodified after downloading,please adjust and use it according toactual needs, thank you!In addition, our shop provides you with various types ofpractical materials,such as educational essays, diaryappreciation,sentence excerpts,ancient poems,classic articles,topic composition,work summary,word parsing,copy excerpts,other materials and so on,want to know different data formats andwriting methods,please pay attention!TOCH 五项实验是指弓形虫、风疹病毒、巨细胞病毒、单纯疱疹病毒Ⅰ型和Ⅱ型的病原体检测，常用于孕前、孕期妇女的检查，以了解其是否感染这些病原体。

TD信息元素详解

信息元素功能性定义作者：李欣目录目录 (1)信息元素功能性定义 (11)1 核心网信息元素 (11)1.1 CN Information elements (11)1.2 CN Domain System Information (11)1.3 CN Information info (11)1.4 IMEI (11)1.5 IMSI (GSM-MAP) (11)1.6 Intra Domain NAS Node Selector (11)1.7 Location Area Identification (12)1.8 NAS message (12)1.9 NAS system information (GSM-MAP) (12)1.10 Paging record type identifier (12)1.11 PLMN identity (12)1.12 PLMN Type (12)1.13 P-TMSI (GSM-MAP) (12)1.14 RAB identity (12)1.15 Routing Area Code (12)1.16 Routing Area Identification (13)1.17 TMSI (GSM-MAP) (13)2 UTRAN 移动信息元素 (13)2.1 Cell Access Restriction (13)2.2 Cell identity (13)2.3 Cell selection and re-selection info for SIB3/4 (13)2.4 Cell selection and re-selection info for SIB11/12 (13)2.5 Mapping Info (14)2.6 URA identity (14)3 UE 信息元素 (14)3.1 Activation time (14)3.2 Capability Update Requirement (14)3.3 Cell update cause (15)3.4 Ciphering Algorithm (15)3.5 Ciphering mode info (15)3.6 CN domain specific DRX cycle length coefficient (15)3.7 CPCH Parameters (15)3.8 C-RNTI (15)3.9 DRAC system information (15)3.10 Void (16)3.11 Establishment cause (16)3.12 Expiration Time Factor (16)3.13 Failure cause (16)3.14 Failure cause and error information (16)3.15 Initial UE identity (16)3.16 Integrity check info (16)3.17 Integrity protection activation info (17)3.18 Integrity protection Algorithm (17)3.19 Integrity protection mode info (17)3.20 Maximum bit rate (17)3.21 Measurement capability (17)3.22 Paging cause (17)3.23 Paging record (17)3.24 PDCP capability (17)3.25 Physical channel capability (18)3.26 Protocol error cause (18)3.27 Protocol error indicator (18)3.28 RB timer indicator (18)3.29 Redirection info (18)3.30 Re-establishment timer (18)3.31 Rejection cause (18)3.32 Release cause (18)3.33 RF capability FDD (19)3.34 RLC capability (19)3.35 RLC re-establish indicator (19)3.36 RRC transaction identifier (19)3.37 Security capability (19)3.38 START (19)3.39 Transmission probability (19)3.40 Transport channel capability (20)3.41 UE multi-mode/multi-RAT capability (20)3.42 UE radio access capability (20)3.43 UE Timers and Constants in connected mode (21)3.44 UE Timers and Constants in idle mode (21)3.45 UE positioning capability (21)3.46 URA update cause (21)3.47 U-RNTI (21)3.48 U-RNTI Short (21)3.49 UTRAN DRX cycle length coefficient (21)3.50 Wait time (21)3.51 UE Specific Behavior Information 1 idle (21)3.52 UE Specific Behavior Information 1 interRAT (22)4 无线承载信息元素 (22)4.0 Default configuration identity (22)4.1 Downlink RLC STATUS info (22)4.2 PDCP info (22)4.3 PDCP SN info (22)4.4 Polling info (22)4.5 Predefined configuration identity (23)4.6 Predefined configuration value tag (23)4.7 Predefined RB configuration (23)4.8 RAB info (23)4.9 RAB info Post (23)4.10 RAB information for setup (23)4.11 RAB information to reconfigure (24)4.12 NAS Synchronization indicator (24)4.13 RB activation time info (24)4.14 RB COUNT-C MSB information (24)4.15 RB COUNT-C information (24)4.16 RB identity (24)4.17 RB information to be affected (24)4.18 RB information to reconfigure (25)4.19 RB information to release (25)4.20 RB information to setup (25)4.21 RB mapping info (25)4.22 RB with PDCP information (25)4.23 RLC info (25)4.24 Signaling RB information to setup (26)4.25 Transmission RLC Discard (26)5 传输信道信息元素 (26)5.1 Added or Reconfigured DL TrCH information (26)5.2 Added or Reconfigured UL TrCH information (27)5.3 CPCH set ID (27)5.4 Deleted DL TrCH information (27)5.5 Deleted UL TrCH information (27)5.6 DL Transport channel information common for all transport channels (27)5.7 DRAC Static Information (27)5.8 Power Offset Information (28)5.9 Predefined TrCH configuration (28)5.10 Quality Target (28)5.11 Semi-static Transport Format Information (28)5.12 TFCI Field 2 Information (28)5.13 TFCS Explicit Configuration (28)5.14 TFCS Information for DSCH (TFCI range method) (29)5.15 TFCS Reconfiguration/Addition Information (29)5.16 TFCS Removal Information (29)5.17 Void (29)5.18 Transport channel identity (29)5.19 Transport Format Combination (TFC) (29)5.20 Transport Format Combination Set (29)5.21 Transport Format Combination Set Identity (29)5.22 Transport Format Combination Subset (29)5.23 Transport Format Set (29)5.24 UL Transport channel information common for all transport channels (30)6 物理信道信息元素 (30)6.1 AC-to-ASC mapping (30)6.2 AICH Info (30)6.3 AICH Power offset (30)6.4 Allocation period info (30)6.5 Alpha (30)6.6 ASC Setting (30)6.7 Void (31)6.8 CCTrCH power control info (31)6.9 Cell parameters Id (31)6.10 Common timeslot info (31)6.11 Constant value (31)6.12 CPCH persistence levels (31)6.13 CPCH set info (31)6.14 CPCH Status Indication mode (31)6.15 CSICH Power offset (32)6.16 Default DPCH Offset Value (32)6.17 Downlink channelisation codes (32)6.18 Downlink DPCH info common for all RL (32)6.19 Downlink DPCH info common for all RL Post (32)6.20 Downlink DPCH info common for all RL Pre (32)6.21 Downlink DPCH info for each RL (32)6.22 Downlink DPCH info for each RL Post (33)6.23 Downlink DPCH power control information (33)6.24 Downlink information common for all radio links (33)6.25 Downlink information common for all radio links Post (33)6.26 Downlink information common for all radio links Pre (33)6.27 Downlink information for each radio link (33)6.28 Downlink information for each radio link Post (33)6.29 Void (33)6.30 Downlink PDSCH information (33)6.31 Downlink rate matching restriction information (34)6.32 Downlink Timeslots and Codes (34)6.33 DPCH compressed mode info (34)6.34 DPCH Compressed Mode Status Info (34)6.35 Dynamic persistence level (34)6.36 Frequency info (34)6.37 Individual timeslot info (35)6.38 Individual Timeslot interference (35)6.39 Maximum allowed UL TX power (35)6.40 Void (35)6.41 Midamble shift and burst type (35)6.42 PDSCH Capacity Allocation info (35)6.43 PDSCH code mapping (36)6.44 PDSCH info (36)6.45 PDSCH Power Control info (36)6.46 PDSCH system information (36)6.47 PDSCH with SHO DCH Info (36)6.48 Persistence scaling factors (36)6.49 PICH Info (36)6.50 PICH Power offset (37)6.51 PRACH Channelisation Code List (37)6.52 PRACH info (for RACH) (37)6.53 PRACH partitioning (37)6.54 PRACH power offset (37)6.55 PRACH system information list (37)6.56 Predefined PhyCH configuration (38)6.57 Primary CCPCH info (38)6.58 Primary CCPCH info post (38)6.59 Primary CCPCH TX Power (38)6.60 Primary CPICH info (38)6.61 Primary CPICH Tx power (38)6.62 Primary CPICH usage for channel estimation (38)6.63 PUSCH info (38)6.64 PUSCH Capacity Allocation info (38)6.65 PUSCH power control info (39)6.66 PUSCH system information (39)6.67 RACH transmission parameters (39)6.68 Radio link addition information (39)6.69 Radio link removal information (39)6.70 SCCPCH Information for FACH (39)6.71 Secondary CCPCH info (39)6.72 Secondary CCPCH system information (40)6.73 Secondary CPICH info (40)6.74 Secondary scrambling code (40)6.75 SFN Time info (40)6.76 SSDT cell identity (40)6.77 SSDT information (40)6.78 STTD indicator (40)6.79 TDD open loop power control (41)6.80 TFC Control duration (41)6.81 TFCI Combining Indicator (41)6.82 TGPSI (41)6.83 Time info (41)6.84 Timeslot number (41)6.85 TPC combination index (41)6.86 TSTD indicator (41)6.87 TX Diversity Mode (41)6.88 Uplink DPCH info (41)6.89 Uplink DPCH info Post (42)6.90 Uplink DPCH info Pre (42)6.91 Uplink DPCH power control info (42)6.92 Uplink DPCH power control info Post (42)6.93 Uplink DPCH power control info Pre (42)6.94 Uplink Timeslots and Codes (42)6.95 Uplink Timing Advance (42)6.96 Uplink Timing Advance Control (43)7 测量信息元素 (43)7.1 Additional measurements list (43)7.2 Cell info (43)7.3 Cell measured results (43)7.4 Cell measurement event results (44)7.5 Cell reporting quantities (44)7.6 Cell synchronization information (44)7.7 Event results (44)7.8 FACH measurement occasion info (45)7.9 Filter coefficient (45)7.10 HCS Cell re-selection information (45)7.11 HCS neighboring cell information (45)7.12 HCS Serving cell information (45)7.13 Inter-frequency cell info list (46)7.14 Inter-frequency event identity (46)7.15 Inter-frequency measured results list (46)7.16 Inter-frequency measurement (46)7.17 Inter-frequency measurement event results (47)7.18 Inter-frequency measurement quantity (47)7.19 Inter-frequency measurement reporting criteria (47)7.20 Inter-frequency measurement system information (47)7.21 Inter-frequency reporting quantity (47)7.22 Inter-frequency SET UPDATE (48)7.23 Inter-RAT cell info list (48)7.24 Inter-RAT event identity (48)7.25 Inter-RAT info (48)7.26 Inter-RAT measured results list (48)7.27 Inter-RAT measurement (49)7.28 Inter-RAT measurement event results (49)7.29 Inter-RAT measurement quantity (49)7.30 Inter-RAT measurement reporting criteria (49)7.31 Inter-RAT measurement system information (50)7.32 Inter-RAT reporting quantity (50)7.33 Intra-frequency cell info list (50)7.34 Intra-frequency event identity (50)7.35 Intra-frequency measured results list (50)7.36 Intra-frequency measurement (50)7.37 Intra-frequency measurement event results (51)7.38 Intra-frequency measurement quantity (51)7.39 Intra-frequency measurement reporting criteria (51)7.40 Intra-frequency measurement system information (51)7.41 Intra-frequency reporting quantity (52)7.42 Intra-frequency reporting quantity for RACH reporting (52)7.43 Maximum number of reported cells on RACH (52)7.44 Measured results (52)7.45 Measured results on RACH (52)7.46 Measurement Command (52)7.47 Measurement control system information (53)7.48 Measurement Identity (53)7.49 Measurement reporting mode (53)7.50 Measurement Type (53)7.51 Measurement validity (53)7.52 Observed time difference to GSM cell (53)7.53 Periodical reporting criteria (53)7.54 Primary CCPCH RSCP info (54)7.55 Quality measured results list (54)7.56 Quality measurement (54)7.57 Quality measurement event results (54)7.58 Quality measurement reporting criteria (54)7.59 Quality reporting quantity (54)7.60 Reference time difference to cell (54)7.61 Reporting Cell Status (55)7.62 Reporting information for state CELL_DCH (55)7.63 SFN-SFN observed time difference (55)7.64 Time to trigger (55)7.65 Timeslot ISCP info (55)7.66 Traffic volume event identity (55)7.67 Traffic volume measured results list (55)7.68 Traffic volume measurement (55)7.69 Traffic volume measurement event results (56)7.70 Traffic volume measurement object (56)7.71 Traffic volume measurement quantity (56)7.72 Traffic volume measurement reporting criteria (56)7.73 Traffic volume measurement system information (56)7.74 Traffic volume reporting quantity (56)7.75 UE internal event identity (56)7.76 UE internal measured results (57)7.77 UE internal measurement (57)7.78 UE internal measurement event results (57)7.79 UE internal measurement quantity (57)7.80 UE internal measurement reporting criteria (57)7.81 Void (58)7.82 UE Internal reporting quantity (58)7.83 UE Rx-Tx time difference type 1 (58)7.84 UE Rx-Tx time difference type 2 (58)7.85 UE Transmitted Power info (58)7.86 UE positioning Ciphering info (58)7.87 UE positioning Error (58)7.88 UE positioning GPS acquisition assistance (59)7.89 UE positioning GPS almanac (59)7.90 UE positioning GPS assistance data (59)7.91 UE positioning GPS DGPS corrections (59)7.92 UE positioning GPS ionospheric model (59)7.93 UE positioning GPS measured results (59)7.94 UE positioning GPS navigation model (60)7.95 UE positioning GPS real-time integrity (60)7.96 UE positioning GPS reference time (60)7.97 UE positioning GPS UTC model (61)7.98 UE positioning IPDL parameters (61)7.99 UE positioning measured results (61)7.100 UE positioning measurement (61)7.101 UE positioning measurement event results (61)7.102 Void (62)7.103 UE positioning OTDOA assistance data for UE-assisted (62)7.104 Void (62)7.105 UE positioning OTDOA measured results (62)7.106 UE positioning OTDOA neighbor cell info (62)7.107 UE positioning OTDOA quality (63)7.108 UE positioning OTDOA reference cell info (63)7.109 UE positioning position estimate info (64)7.110 UE positioning reporting criteria (64)7.111 UE positioning reporting quantity (64)7.112 T ADV info (65)8 其它信息元素 (65)8.1 BCCH modification info (65)8.2 BSIC (65)8.3 CBS DRX Level 1 information (65)8.4 Cell Value tag (65)8.5 Inter-RAT change failure (65)8.6 Inter-RAT handover failure (66)8.7 Inter-RAT UE radio access capability (66)8.8 Void (66)8.9 MIB Value tag (66)8.10 PLMN Value tag (66)8.11 Predefined configuration identity and value tag (66)8.12 Protocol error information (66)8.13 References to other system information blocks (66)8.14 References to other system information blocks and scheduling blocks (67)8.15 Rplmn information (67)8.16 Scheduling information (67)8.17 SEG COUNT (67)8.18 Segment index (67)8.19 SIB data fixed (67)8.20 SIB data variable (67)8.21 SIB type (67)8.22 SIB type SIBs only (67)9 ANSI-41 Information elements (68)10 Multiplicity values and type constraint values (68)信息元素功能性定义消息是由多个信息元素组合而成，信息元素根据其功能的不同划分为：核心网域信息元素、UTRAN 移动信息元素、UE 信息元素、无线承载信息元素、传输信道信息元素、物理信道信息元素和测量信息元素。

TPO15 听力答案解析

By 宋思祺TPO15 Section 1Conversation 1CDDAA1.男生为什么去学校的报纸办公室？老师说，（9,21）I remember you . You're interestedin working for the paper.我记得你，你是对为报纸工作很感兴趣，学生说是的，作为记者。

Yeah, as a reporter。

老师后面又说，（50）Advisor Absolutely! Let's see . I think I told you that we ask prospective reporters to turn in some outlines for possible articles . 我告诉过你做记者要交几篇提纲Student Yeah, I sent them in about a week ago, but I haven't heard anything back yet, so, so I thought I'd stop by and see, but I guess you haven't looked at them yet .我发了，但是并没有收到回音，所以过来看看。

这里就可以得出结论，学生来是为了看看他有没有获得记者的职位。

所以选C2.问学生为什么想给学校报纸写文章。

（47秒）I'd like the experience. It would lookgood on my resume .我想要这种经历，这会使我的简历看上去更好，这就可以选D，他认为经验非常重要。

3.学生提到了计划增加学费的话题，advisor对这个话题的看法？（1,50）Student OK.Uh … wha t the other outline I sent i n, about the proposed increase in tuition fees?那另外一篇提纲呢？关于计划增加学费的。

ProChek

Instructions for Use: ProChek®-W Semi-Quantitative Protein Test forRobotic ArmsBrand Name of Product ProChek®-W Protein Test for Robotic ArmsGeneric Name of Product Protein Test for Robotic ArmsProduct Code Number(s)PT-SQ-001Intended Use Testing for residual protein remaining on robotic arms after cleaning.Range of Applications for Product Robotic arms likely to be contaminated with protein soils during clinical use.Key Specifications of Product●Measuring range for the test is 0 µg/ml-30 µg/ml.●15 Protein Reagent Vials●15 Pipettes●15 Ziplock Bags● 1 Interpretation Chart●Cardboard Cuvette HolderCustomer will supply the syringe and prepackaged sterile water● Customer will supply the syringe and prepackaged sterile water.Figure 1 Figure 2Figure 3Figure 4 Figure 5 Figure 6Figure 7Figure 8Figure 9Figure 10Figure 11Figure 12Color of the solution when there is 0 µg ,10 µg, 20 µg, 30 µg of protein per 1 ML ofthe extract.Note: For color accuracy please compare vials to printed interpretation guideincluded with the ProChek®-W.Steps for Use of Product 1.Wear clean gloves.2.Place zip lock bag on distal tip and secure it to ensure it does not fall off.3.Fill syringe with 6 mL of sterile water. Fig. 14.With syringe, flush the lumen through Port 1. Fig. 25.Draw the water back out with the same syringe. Fig. 36.Gently eject the water into the supplied zip lock bag. Fig. 47.Make sure water comes in contact with entire area of distal tip and gently swishthe distal tip in the recaptured water in the same zip lock bag for 10 seconds.Fig. 58.Remove the robotic arm from the zip lock bag. Fig. 69.Unscrew the cap to the ProChek®-W vial. Fig. 710.With supplied pipette, draw up 1 mL of recaptured water from the zip lock bag.Fig. 811.From the pipette, add 1 mL of water to a ProChek®-W vial. Fig. 912.Replace the cap on the ProChek®-W vial. Fig. 1013.Mix the contents in the vial by shaking at least five times. Fig. 1114.Wait 5 minutes.15.Place the ProChek® vial in between the colors on the chart which will allow youto compare the color of the solution to the provided color interpretation chart.Fig. 12● The color interpretation chart shows the color of the solution when there is0 µg,10 µg, 20 µg, 30µg of protein per 1 ML of the extract.Interpretation of Results●In the case of soluble proteins, there will be an immediate color change.●In the case of denatured proteins (often the case with instruments subjected toreprocessing), color change can take up to 5 minutes.●For an accurate semi-quantitative result, wait the full 5 minutes. Contraindications of Test Results Contact to alkaline substances (larger amount of alkaline detergent) can trigger colorchange. Quaternary ammonium salts (used in some disinfectants) will give a falsepositive result.Documentation Record test results on log sheet located at Special Warnings and Cautions●Evaluate the result immediately after 300 seconds (5 minutes) — late colorchanges are not valid.●Report a positive test result immediately.● A positive result is proof of remaining protein residue in the tested area●In case of a positive test result, the device should be reprocessed.Disposal Since it is possible that organic soil is present, it is recommended to dispose allcomponents of the ProChek®-W test kit in a biohazard container.DisinfectionDryingMaintenance, Inspection, andTestingReassembly InstructionsPackagingSterilizationStorageAdditional Information● Lot control test results (Statement of Conformance) are available fromHealthmark upon request.●Quality of Water for Testing: 1. It is recommended to use pre-packaged sterilewater, such as sterile water for irrigation. 2. For effective testing, it is notnecessary that the water remain sterile, but care should be taken not tocontaminate after opening to avoid creating the opportunity for false positivetest results.Related Healthmark Products EndoCheck™, ProChek , HemoCheck™, ChannelCheck™Other Product Support Documents ProFormance™ Brochure, ProFormance™ Price ListReference DocumentsCustomer Service Contact Healthmark Industries Company, Inc.18600 Malyn Blvd.Fraser, MI 480261-586-774-7600********************。