Morphology and Evolution in Galaxy Clusters I Simulated Clusters in the Adiabatic limit and

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人工智能英文参考文献(最新120个)

人工智能是一门新兴的具有挑战力的学科。

自人工智能诞生以来,发展迅速,产生了许多分支。

诸如强化学习、模拟环境、智能硬件、机器学习等。

但是,在当前人工智能技术迅猛发展,为人们的生活带来许多便利。

下面是搜索整理的人工智能英文参考文献的分享，供大家借鉴参考。

人工智能英文参考文献一：[1]Lars Egevad,Peter Str?m,Kimmo Kartasalo,Henrik Olsson,Hemamali Samaratunga,Brett Delahunt,Martin Eklund. The utility of artificial intelligence in the assessment of prostate pathology[J]. Histopathology,2020,76(6).[2]Rudy van Belkom. The Impact of Artificial Intelligence on the Activities ofa Futurist[J]. World Futures Review,2020,12(2).[3]Reza Hafezi. How Artificial Intelligence Can Improve Understanding in Challenging Chaotic Environments[J]. World Futures Review,2020,12(2).[4]Alejandro Díaz-Domínguez. How Futures Studies and Foresight Could Address Ethical Dilemmas of Machine Learning and Artificial Intelligence[J]. World Futures Review,2020,12(2).[5]Russell T. Warne,Jared Z. Burton. Beliefs About Human Intelligence in a Sample of Teachers and Nonteachers[J]. Journal for the Education of the Gifted,2020,43(2).[6]Russell Belk,Mariam Humayun,Ahir Gopaldas. Artificial Life[J]. Journal of Macromarketing,2020,40(2).[7]Walter Kehl,Mike Jackson,Alessandro Fergnani. Natural Language Processing and Futures Studies[J]. World Futures Review,2020,12(2).[8]Anne Boysen. Mine the Gap: Augmenting Foresight Methodologies with Data Analytics[J]. World Futures Review,2020,12(2).[9]Marco Bevolo,Filiberto Amati. The Potential Role of AI in Anticipating Futures from a Design Process Perspective: From the Reflexive Description of “Design” to a Discussion of Influences by the Inclusion of AI in the Futures Research Process[J]. World Futures Review,2020,12(2).[10]Lan Xu,Paul Tu,Qian Tang,Dan Seli?teanu. Contract Design for Cloud Logistics (CL) Based on Blockchain Technology (BT)[J]. Complexity,2020,2020.[11]L. Grant,X. Xue,Z. Vajihi,A. Azuelos,S. Rosenthal,D. Hopkins,R. Aroutiunian,B. Unger,A. Guttman,M. Afilalo. LO32: Artificial intelligence to predict disposition to improve flow in the emergency department[J]. CJEM,2020,22(S1).[12]A. Kirubarajan,A. Taher,S. Khan,S. Masood. P071: Artificial intelligence in emergency medicine: A scoping review[J]. CJEM,2020,22(S1).[13]L. Grant,P. Joo,B. Eng,A. Carrington,M. Nemnom,V. Thiruganasambandamoorthy. LO22: Risk-stratification of emergency department syncope by artificial intelligence using machine learning: human, statistics or machine[J]. CJEM,2020,22(S1).[14]Riva Giuseppe,Riva Eleonora. OS for Ind Robots: Manufacturing Robots Get Smarter Thanks to Artificial Intelligence.[J]. Cyberpsychology, behavior and social networking,2020,23(5).[15]Markus M. Obmann,Aurelio Cosentino,Joshy Cyriac,Verena Hofmann,Bram Stieltjes,Daniel T. Boll,Benjamin M. Yeh,Matthias R. Benz. Quantitative enhancement thresholds and machine learning algorithms for the evaluation of renal lesions using single-phase split-filter dual-energy CT[J]. Abdominal Radiology,2020,45(1).[16]Haytham H. Elmousalami,Mahmoud Elaskary. Drilling stuck pipe classification and mitigation in the Gulf of Suez oil fields using artificial intelligence[J]. Journal of Petroleum Exploration and Production Technology,2020,10(10).[17]Rüdiger Schulz-Wendtland,Karin Bock. Bildgebung in der Mammadiagnostik –Ein Ausblick <trans-title xml:lang="en">Imaging in breast diagnostics—an outlook [J]. Der Gyn?kologe,2020,53(6).</trans-title>[18]Nowakowski Piotr,Szwarc Krzysztof,Boryczka Urszula. Combining an artificial intelligence algorithm and a novel vehicle for sustainable e-waste collection[J]. Science of the Total Environment,2020,730.[19]Wang Huaizhi,Liu Yangyang,Zhou Bin,Li Canbing,Cao Guangzhong,Voropai Nikolai,Barakhtenko Evgeny. Taxonomy research of artificial intelligence for deterministic solar power forecasting[J]. Energy Conversion and Management,2020,214.[20]Kagemoto Hiroshi. Forecasting a water-surface wave train with artificial intelligence- A case study[J]. Ocean Engineering,2020,207.[21]Tomonori Aoki,Atsuo Yamada,Kazuharu Aoyama,Hiroaki Saito,Gota Fujisawa,Nariaki Odawara,Ryo Kondo,Akiyoshi Tsuboi,Rei Ishibashi,Ayako Nakada,Ryota Niikura,Mitsuhiro Fujishiro,Shiro Oka,Soichiro Ishihara,Tomoki Matsuda,Masato Nakahori,Shinji Tanaka,Kazuhiko Koike,Tomohiro Tada. Clinical usefulness of a deep learning‐based system as the first screening on small‐bowel capsule endoscopy reading[J]. Digestive Endoscopy,2020,32(4).[22]Masashi Fujii,Hajime Isomoto. Next generation of endoscopy: Harmony with artificial intelligence and robotic‐assisted devices[J]. Digestive Endoscopy,2020,32(4).[23]Roberto Verganti,Luca Vendraminelli,Marco Iansiti. Innovation and Design in the Age of Artificial Intelligence[J]. Journal of Product Innovation Management,2020,37(3).[24]Yuval Elbaz,David Furman,Maytal Caspary Toroker. Modeling Diffusion in Functional Materials: From Density Functional Theory to Artificial Intelligence[J]. Advanced Functional Materials,2020,30(18).[25]Dinesh Visva Gunasekeran,Tien Yin Wong. Artificial Intelligence in Ophthalmology in 2020: A Technology on the Cusp for Translation and Implementation[J]. Asia-Pacific Journal of Ophthalmology,2020,9(2).[26]Fu-Neng Jiang,Li-Jun Dai,Yong-Ding Wu,Sheng-Bang Yang,Yu-Xiang Liang,Xin Zhang,Cui-Yun Zou,Ren-Qiang He,Xiao-Ming Xu,Wei-De Zhong. The study of multiple diagnosis models of human prostate cancer based on Taylor database by artificial neural networks[J]. Journal of the Chinese Medical Association,2020,83(5).[27]Matheus Calil Faleiros,Marcello Henrique Nogueira-Barbosa,Vitor Faeda Dalto,JoséRaniery Ferreira Júnior,Ariane Priscilla Magalh?es Tenório,Rodrigo Luppino-Assad,Paulo Louzada-Junior,Rangaraj Mandayam Rangayyan,Paulo Mazzoncini de Azevedo-Marques. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging[J]. Advances in Rheumatology,2020,60(1078).[28]Balamurugan Balakreshnan,Grant Richards,Gaurav Nanda,Huachao Mao,Ragu Athinarayanan,Joseph Zaccaria. PPE Compliance Detection using Artificial Intelligence in Learning Factories[J]. Procedia Manufacturing,2020,45.[29]M. Stévenin,V. Avisse,N. Ducarme,A. de Broca. Qui est responsable si un robot autonome vient à entra?ner un dommage ?[J]. Ethique et Santé,2020.[30]Fatemeh Barzegari Banadkooki,Mohammad Ehteram,Fatemeh Panahi,Saad Sh. Sammen,Faridah Binti Othman,Ahmed EL-Shafie. Estimation of Total Dissolved Solids (TDS) using New Hybrid Machine Learning Models[J]. Journal of Hydrology,2020.[31]Adam J. Schwartz,Henry D. Clarke,Mark J. Spangehl,Joshua S. Bingham,DavidA. Etzioni,Matthew R. Neville. Can a Convolutional Neural Network Classify Knee Osteoarthritis on Plain Radiographs as Accurately as Fellowship-Trained Knee Arthroplasty Surgeons?[J]. The Journal of Arthroplasty,2020.[32]Ivana Nizetic Kosovic,Toni Mastelic,Damir Ivankovic. Using Artificial Intelligence on environmental data from Internet of Things for estimating solar radiation: Comprehensive analysis[J]. Journal of Cleaner Production,2020.[33]Lauren Fried,Andrea Tan,Shirin Bajaj,Tracey N. Liebman,David Polsky,Jennifer A. Stein. Technological advances for the detection of melanoma: Part I. Advances in diagnostic techniques[J]. Journal of the American Academy of Dermatology,2020.[34]Mohammed Amoon,Torki Altameem,Ayman Altameem. Internet of things Sensor Assisted Security and Quality Analysis for Health Care Data Sets Using Artificial Intelligent Based Heuristic Health Management System[J]. Measurement,2020.[35]E. Lotan,C. Tschider,D.K. Sodickson,A. Caplan,M. Bruno,B. Zhang,Yvonne W. Lui. Medical Imaging and Privacy in the Era of Artificial Intelligence: Myth, Fallacy, and the Future[J]. Journal of the American College of Radiology,2020.[36]Fabien Lareyre,Cédric Adam,Marion Carrier,Juliette Raffort. Artificial Intelligence in Vascular Surgery: moving from Big Data to Smart Data[J]. Annals of Vascular Surgery,2020.[37]Ilesanmi Daniyan,Khumbulani Mpofu,Moses Oyesola,Boitumelo Ramatsetse,Adefemi Adeodu. Artificial intelligence for predictive maintenance in the railcar learning factories[J]. Procedia Manufacturing,2020,45.[38]Janet L. McCauley,Anthony E. Swartz. Reframing Telehealth[J]. Obstetrics and Gynecology Clinics of North America,2020.[39]Jean-Emmanuel Bibault,Lei Xing. Screening for chronic obstructive pulmonary disease with artificial intelligence[J]. The Lancet Digital Health,2020,2(5).[40]Andrea Laghi. Cautions about radiologic diagnosis of COVID-19 infection driven by artificial intelligence[J]. The Lancet Digital Health,2020,2(5).人工智能英文参考文献二：[41]K. Orhan,I. S. Bayrakdar,M. Ezhov,A. Kravtsov,T. ?zyürek. Evaluation of artificial intelligence for detecting periapical pathosis on cone‐beam computed tomography scans[J]. International Endodontic Journal,2020,53(5).[42]Avila A M,Mezi? I. Data-driven analysis and forecasting of highway traffic dynamics.[J]. Nature communications,2020,11(1).[43]Neri Emanuele,Miele Vittorio,Coppola Francesca,Grassi Roberto. Use of CT andartificial intelligence in suspected or COVID-19 positive patients: statement of the Italian Society of Medical and Interventional Radiology.[J]. La Radiologia medica,2020.[44]Tau Noam,Stundzia Audrius,Yasufuku Kazuhiro,Hussey Douglas,Metser Ur. Convolutional Neural Networks in Predicting Nodal and Distant Metastatic Potential of Newly Diagnosed Non-Small Cell Lung Cancer on FDG PET Images.[J]. AJR. American journal of roentgenology,2020.[45]Coppola Francesca,Faggioni Lorenzo,Regge Daniele,Giovagnoni Andrea,Golfieri Rita,Bibbolino Corrado,Miele Vittorio,Neri Emanuele,Grassi Roberto. Artificial intelligence: radiologists' expectations and opinions gleaned from a nationwide online survey.[J]. La Radiologia medica,2020.[46]?. ? ? ? ? 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Clinical Implementation of Deep Learning in Thoracic Radiology: Potential Applications and Challenges.[J]. Korean journal of radiology,2020,21(5).[55]Mateen Bilal A,David Anna L,Denaxas Spiros. Electronic Health Records to Predict Gestational Diabetes Risk.[J]. Trends in pharmacological sciences,2020,41(5).[56]Yao Xiang,Mao Ling,Lv Shunli,Ren Zhenghong,Li Wentao,Ren Ke. CT radiomics features as a diagnostic tool for classifying basal ganglia infarction onset time.[J]. Journal of the neurological sciences,2020,412.[57]van Assen Marly,Banerjee Imon,De Cecco Carlo N. Beyond the Artificial Intelligence Hype: What Lies Behind the Algorithms and What We Can Achieve.[J]. Journal of thoracic imaging,2020,35 Suppl 1.[58]Guzik Tomasz J,Fuster Valentin. Leaders in Cardiovascular Research: Valentin Fuster.[J]. Cardiovascular research,2020,116(6).[59]Fischer Andreas M,Eid Marwen,De Cecco Carlo N,Gulsun Mehmet A,van Assen Marly,Nance John W,Sahbaee Pooyan,De Santis Domenico,Bauer Maximilian J,Jacobs Brian E,Varga-Szemes Akos,Kabakus Ismail M,Sharma Puneet,Jackson Logan J,Schoepf U Joseph. Accuracy of an Artificial Intelligence Deep Learning Algorithm Implementing a Recurrent Neural Network With Long Short-term Memory for the Automated Detection of Calcified Plaques From Coronary Computed Tomography Angiography.[J]. Journal of thoracic imaging,2020,35 Suppl 1.[60]Ghosh Adarsh,Kandasamy Devasenathipathy. Interpretable Artificial Intelligence: Why and When.[J]. AJR. American journal of roentgenology,2020,214(5).[61]M.Rosario González-Rodríguez,M.Carmen Díaz-Fernández,Carmen Pacheco Gómez. Facial-expression recognition: An emergent approach to the measurement of tourist satisfaction through emotions[J]. Telematics and Informatics,2020,51.[62]Ru-Xi Ding,Iván Palomares,Xueqing Wang,Guo-Rui Yang,Bingsheng Liu,Yucheng Dong,Enrique Herrera-Viedma,Francisco Herrera. Large-Scale decision-making: Characterization, taxonomy, challenges and future directions from an Artificial Intelligence and applications perspective[J]. Information Fusion,2020,59.[63]Abdulrhman H. Al-Jebrni,Brendan Chwyl,Xiao Yu Wang,Alexander Wong,Bechara J. Saab. AI-enabled remote and objective quantification of stress at scale[J]. Biomedical Signal Processing and Control,2020,59.[64]Gillian Thomas,Elizabeth Eisenhauer,Robert G. Bristow,Cai Grau,Coen Hurkmans,Piet Ost,Matthias Guckenberger,Eric Deutsch,Denis Lacombe,Damien C. Weber. The European Organisation for Research and Treatment of Cancer, State of Science in radiation oncology and priorities for clinical trials meeting report[J]. European Journal of Cancer,2020,131.[65]Muhammad Asif. Are QM models aligned with Industry 4.0? A perspective on current practices[J]. Journal of Cleaner Production,2020,258.[66]Siva Teja Kakileti,Himanshu J. Madhu,Geetha Manjunath,Leonard Wee,Andre Dekker,Sudhakar Sampangi. Personalized risk prediction for breast cancer pre-screening using artificial intelligence and thermal radiomics[J]. Artificial Intelligence In Medicine,2020,105.[67]. Evaluation of Payer Budget Impact Associated with the Use of Artificial Intelligence in Vitro Diagnostic, Kidneyintelx, to Modify DKD Progression:[J]. American Journal of Kidney Diseases,2020,75(5).[68]Rohit Nishant,Mike Kennedy,Jacqueline Corbett. Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda[J]. International Journal of Information Management,2020,53.[69]Hoang Nguyen,Xuan-Nam Bui. Soft computing models for predicting blast-induced air over-pressure: A novel artificial intelligence approach[J]. Applied Soft Computing Journal,2020,92.[70]Benjamin S. Hopkins,Aditya Mazmudar,Conor Driscoll,Mark Svet,Jack Goergen,Max Kelsten,Nathan A. 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Cold Regions Science and Technology,2020,174.[73]Steve Chukwuebuka Arum,David Grace,Paul Daniel Mitchell. A review of wireless communication using high-altitude platforms for extended coverage and capacity[J]. Computer Communications,2020,157.[74]Yong-Hong Kuo,Nicholas B. Chan,Janny M.Y. Leung,Helen Meng,Anthony Man-Cho So,Kelvin K.F. Tsoi,Colin A. Graham. An Integrated Approach of Machine Learning and Systems Thinking for Waiting Time Prediction in an Emergency Department[J]. International Journal of Medical Informatics,2020,139.[75]Matteo Terzi,Gian Antonio Susto,Pratik Chaudhari. Directional adversarial training for cost sensitive deep learning classification applications[J]. Engineering Applications of Artificial Intelligence,2020,91.[76]Arman Kilic. Artificial Intelligence and Machine Learning in Cardiovascular Health Care[J]. The Annals of Thoracic Surgery,2020,109(5).[77]Hossein Azarmdel,Ahmad Jahanbakhshi,Seyed Saeid Mohtasebi,Alfredo Rosado Mu?oz. Evaluation of image processing technique as an expert system in mulberry fruit grading based on ripeness level using artificial neural networks (ANNs) and support vector machine (SVM)[J]. Postharvest Biology and Technology,2020,166.[78]Wafaa Wardah,Abdollah Dehzangi,Ghazaleh Taherzadeh,Mahmood A. Rashid,M.G.M. Khan,Tatsuhiko Tsunoda,Alok Sharma. Predicting protein-peptide binding sites with a deep convolutional neural network[J]. Journal of Theoretical Biology,2020,496.[79]Francisco F.X. Vasconcelos,Róger M. Sarmento,Pedro P. Rebou?as Filho,Victor Hugo C. de Albuquerque. Artificial intelligence techniques empowered edge-cloud architecture for brain CT image analysis[J]. Engineering Applications of Artificial Intelligence,2020,91.[80]Masaaki Konishi. Bioethanol production estimated from volatile compositions in hydrolysates of lignocellulosic biomass by deep learning[J]. Journal of Bioscience and Bioengineering,2020,129(6).人工智能英文参考文献三：[81]J. Kwon,K. Kim. Artificial Intelligence for Early Prediction of Pulmonary Hypertension Using Electrocardiography[J]. Journal of Heart and Lung Transplantation,2020,39(4).[82]C. Maathuis,W. Pieters,J. van den Berg. Decision support model for effects estimation and proportionality assessment for targeting in cyber operations[J]. Defence Technology,2020.[83]Samer Ellahham. Artificial Intelligence in Diabetes Care[J]. The American Journal of Medicine,2020.[84]Yi-Ting Hsieh,Lee-Ming Chuang,Yi-Der Jiang,Tien-Jyun Chang,Chung-May Yang,Chang-Hao Yang,Li-Wei Chan,Tzu-Yun Kao,Ta-Ching Chen,Hsuan-Chieh Lin,Chin-Han Tsai,Mingke Chen. Application of deep learning image assessment software VeriSee? for diabetic retinopathy screening[J]. Journal of the Formosan Medical Association,2020.[85]Emre ARTUN,Burak KULGA. Selection of candidate wells for re-fracturing in tight gas sand reservoirs using fuzzy inference[J]. 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ANSYS错误提示及其含义

1 在Ansys中出现“Shape testing revealed that 450 of the 1500 new or modified elements violate shape warning limits.”，是什么原因造成的呢？单元网格质量不够好，尽量用规则化网格，或者再较为细密一点。

2 在Ansys中，用Area Fillet对两空间曲面进行倒角时出现以下错误：Area 6 offset could not fully converge to offset distance 10. Maximum error between the two surfaces is 1% of offset distance.请问这是什么错误？怎么解决？其中一个是圆柱接管表面，一个是碟形封头表面。

ansys的布尔操作能力比较弱。

如果一定要在ansys里面做的话，那么你试试看先对线进行倒角，然后由倒角后的线形成倒角的面。

建议最好用UG、PRO/E这类软件生成实体模型然后导入到ansys。

3 在Ansys中，出现错误“There are 21 small equation solver pivot terms。

”，是否是在建立接触contact时出现的错误？不是建立接触对的错误，一般是单元形状质量太差（例如有接近零度的锐角或者接近180度的钝角）造成small equation solver pivot terms4 在Ansys中，出现警告“SOLID45 wedges are recommended only in regions of relatively low stress gradients.”，是什么意思？"这只是一个警告，它告诉你：推荐SOLID45单元只用在应力梯度较低的区域。

它只是告诉你注意这个问题，如果应力梯度较高，则可能计算结果不可信。

"5 ansys向adams导的过程中，出现如下问题“There is not enough memory for the Sparse Matrix Solver to proceed.Please shut down other applications that may be running or increase the virtual memory on your system and return ANSYS.Memory currently allocated for the Sparse Matrix Solver=50MB.Memory currently required for the Sparse Matrix Solver to continue=25MB”，是什么原因造成的？不清楚你ansys导入adams过程中怎么还需要使用Sparse Matrix Solver（稀疏矩阵求解器）。

C.parvum全基因组序列

DOI: 10.1126/science.1094786, 441 (2004);304Science et al.Mitchell S. Abrahamsen,Cryptosporidium parvum Complete Genome Sequence of the Apicomplexan, (this information is current as of October 7, 2009 ):The following resources related to this article are available online at/cgi/content/full/304/5669/441version of this article at:including high-resolution figures, can be found in the online Updated information and services,/cgi/content/full/1094786/DC1 can be found at:Supporting Online Material/cgi/content/full/304/5669/441#otherarticles , 9 of which can be accessed for free: cites 25 articles This article 239 article(s) on the ISI Web of Science. cited by This article has been /cgi/content/full/304/5669/441#otherarticles 53 articles hosted by HighWire Press; see: cited by This article has been/cgi/collection/genetics Genetics: subject collections This article appears in the following/about/permissions.dtl in whole or in part can be found at: this article permission to reproduce of this article or about obtaining reprints Information about obtaining registered trademark of AAAS.is a Science 2004 by the American Association for the Advancement of Science; all rights reserved. The title Copyright American Association for the Advancement of Science, 1200 New York Avenue NW, Washington, DC 20005. (print ISSN 0036-8075; online ISSN 1095-9203) is published weekly, except the last week in December, by the Science o n O c t o b e r 7, 2009w w w .s c i e n c e m a g .o r g D o w n l o a d e d f r o m3.R.Jackendoff,Foundations of Language:Brain,Gram-mar,Evolution(Oxford Univ.Press,Oxford,2003).4.Although for Frege(1),reference was established rela-tive to objects in the world,here we follow Jackendoff’s suggestion(3)that this is done relative to objects and the state of affairs as mentally represented.5.S.Zola-Morgan,L.R.Squire,in The Development andNeural Bases of Higher Cognitive Functions(New York Academy of Sciences,New York,1990),pp.434–456.6.N.Chomsky,Reﬂections on Language(Pantheon,New York,1975).7.J.Katz,Semantic Theory(Harper&Row,New York,1972).8.D.Sperber,D.Wilson,Relevance(Harvard Univ.Press,Cambridge,MA,1986).9.K.I.Forster,in Sentence Processing,W.E.Cooper,C.T.Walker,Eds.(Erlbaum,Hillsdale,NJ,1989),pp.27–85.10.H.H.Clark,Using Language(Cambridge Univ.Press,Cambridge,1996).11.Often word meanings can only be fully determined byinvokingworld knowledg e.For instance,the meaningof “ﬂat”in a“ﬂat road”implies the absence of holes.However,in the expression“aﬂat tire,”it indicates the presence of a hole.The meaningof“ﬁnish”in the phrase “Billﬁnished the book”implies that Bill completed readingthe book.However,the phrase“the g oatﬁn-ished the book”can only be interpreted as the goat eatingor destroyingthe book.The examples illustrate that word meaningis often underdetermined and nec-essarily intertwined with general world knowledge.In such cases,it is hard to see how the integration of lexical meaning and general world knowledge could be strictly separated(3,31).12.W.Marslen-Wilson,C.M.Brown,L.K.Tyler,Lang.Cognit.Process.3,1(1988).13.ERPs for30subjects were averaged time-locked to theonset of the critical words,with40items per condition.Sentences were presented word by word on the centerof a computer screen,with a stimulus onset asynchronyof600ms.While subjects were readingthe sentences,their EEG was recorded and ampliﬁed with a high-cut-off frequency of70Hz,a time constant of8s,and asamplingfrequency of200Hz.14.Materials and methods are available as supportingmaterial on Science Online.15.M.Kutas,S.A.Hillyard,Science207,203(1980).16.C.Brown,P.Hagoort,J.Cognit.Neurosci.5,34(1993).17.C.M.Brown,P.Hagoort,in Architectures and Mech-anisms for Language Processing,M.W.Crocker,M.Pickering,C.Clifton Jr.,Eds.(Cambridge Univ.Press,Cambridge,1999),pp.213–237.18.F.Varela et al.,Nature Rev.Neurosci.2,229(2001).19.We obtained TFRs of the single-trial EEG data by con-volvingcomplex Morlet wavelets with the EEG data andcomputingthe squared norm for the result of theconvolution.We used wavelets with a7-cycle width,with frequencies ranging from1to70Hz,in1-Hz steps.Power values thus obtained were expressed as a per-centage change relative to the power in a baselineinterval,which was taken from150to0ms before theonset of the critical word.This was done in order tonormalize for individual differences in EEG power anddifferences in baseline power between different fre-quency bands.Two relevant time-frequency compo-nents were identiﬁed:(i)a theta component,rangingfrom4to7Hz and from300to800ms after wordonset,and(ii)a gamma component,ranging from35to45Hz and from400to600ms after word onset.20.C.Tallon-Baudry,O.Bertrand,Trends Cognit.Sci.3,151(1999).tner et al.,Nature397,434(1999).22.M.Bastiaansen,P.Hagoort,Cortex39(2003).23.O.Jensen,C.D.Tesche,Eur.J.Neurosci.15,1395(2002).24.Whole brain T2*-weighted echo planar imaging bloodoxygen level–dependent(EPI-BOLD)fMRI data wereacquired with a Siemens Sonata1.5-T magnetic reso-nance scanner with interleaved slice ordering,a volumerepetition time of2.48s,an echo time of40ms,a90°ﬂip angle,31horizontal slices,a64ϫ64slice matrix,and isotropic voxel size of3.5ϫ3.5ϫ3.5mm.For thestructural magnetic resonance image,we used a high-resolution(isotropic voxels of1mm3)T1-weightedmagnetization-prepared rapid gradient-echo pulse se-quence.The fMRI data were preprocessed and analyzedby statistical parametric mappingwith SPM99software(http://www.ﬁ/spm99).25.S.E.Petersen et al.,Nature331,585(1988).26.B.T.Gold,R.L.Buckner,Neuron35,803(2002).27.E.Halgren et al.,J.Psychophysiol.88,1(1994).28.E.Halgren et al.,Neuroimage17,1101(2002).29.M.K.Tanenhaus et al.,Science268,1632(1995).30.J.J.A.van Berkum et al.,J.Cognit.Neurosci.11,657(1999).31.P.A.M.Seuren,Discourse Semantics(Basil Blackwell,Oxford,1985).32.We thank P.Indefrey,P.Fries,P.A.M.Seuren,and M.van Turennout for helpful discussions.Supported bythe Netherlands Organization for Scientiﬁc Research,grant no.400-56-384(P.H.).Supporting Online Material/cgi/content/full/1095455/DC1Materials and MethodsFig.S1References and Notes8January2004;accepted9March2004Published online18March2004;10.1126/science.1095455Include this information when citingthis paper.Complete Genome Sequence ofthe Apicomplexan,Cryptosporidium parvumMitchell S.Abrahamsen,1,2*†Thomas J.Templeton,3†Shinichiro Enomoto,1Juan E.Abrahante,1Guan Zhu,4 Cheryl ncto,1Mingqi Deng,1Chang Liu,1‡Giovanni Widmer,5Saul Tzipori,5GregoryA.Buck,6Ping Xu,6 Alan T.Bankier,7Paul H.Dear,7Bernard A.Konfortov,7 Helen F.Spriggs,7Lakshminarayan Iyer,8Vivek Anantharaman,8L.Aravind,8Vivek Kapur2,9The apicomplexan Cryptosporidium parvum is an intestinal parasite that affects healthy humans and animals,and causes an unrelenting infection in immuno-compromised individuals such as AIDS patients.We report the complete ge-nome sequence of C.parvum,type II isolate.Genome analysis identiﬁes ex-tremely streamlined metabolic pathways and a reliance on the host for nu-trients.In contrast to Plasmodium and Toxoplasma,the parasite lacks an api-coplast and its genome,and possesses a degenerate mitochondrion that has lost its genome.Several novel classes of cell-surface and secreted proteins with a potential role in host interactions and pathogenesis were also detected.Elu-cidation of the core metabolism,including enzymes with high similarities to bacterial and plant counterparts,opens new avenues for drug development.Cryptosporidium parvum is a globally impor-tant intracellular pathogen of humans and animals.The duration of infection and patho-genesis of cryptosporidiosis depends on host immune status,ranging from a severe but self-limiting diarrhea in immunocompetent individuals to a life-threatening,prolonged infection in immunocompromised patients.Asubstantial degree of morbidity and mortalityis associated with infections in AIDS pa-tients.Despite intensive efforts over the past20years,there is currently no effective ther-apy for treating or preventing C.parvuminfection in humans.Cryptosporidium belongs to the phylumApicomplexa,whose members share a com-mon apical secretory apparatus mediating lo-comotion and tissue or cellular invasion.Many apicomplexans are of medical or vet-erinary importance,including Plasmodium,Babesia,Toxoplasma,Neosprora,Sarcocys-tis,Cyclospora,and Eimeria.The life cycle ofC.parvum is similar to that of other cyst-forming apicomplexans(e.g.,Eimeria and Tox-oplasma),resulting in the formation of oocysts1Department of Veterinary and Biomedical Science,College of Veterinary Medicine,2Biomedical Genom-ics Center,University of Minnesota,St.Paul,MN55108,USA.3Department of Microbiology and Immu-nology,Weill Medical College and Program in Immu-nology,Weill Graduate School of Medical Sciences ofCornell University,New York,NY10021,USA.4De-partment of Veterinary Pathobiology,College of Vet-erinary Medicine,Texas A&M University,College Sta-tion,TX77843,USA.5Division of Infectious Diseases,Tufts University School of Veterinary Medicine,NorthGrafton,MA01536,USA.6Center for the Study ofBiological Complexity and Department of Microbiol-ogy and Immunology,Virginia Commonwealth Uni-versity,Richmond,VA23198,USA.7MRC Laboratoryof Molecular Biology,Hills Road,Cambridge CB22QH,UK.8National Center for Biotechnology Infor-mation,National Library of Medicine,National Insti-tutes of Health,Bethesda,MD20894,USA.9Depart-ment of Microbiology,University of Minnesota,Min-neapolis,MN55455,USA.*To whom correspondence should be addressed.E-mail:abe@†These authors contributed equally to this work.‡Present address:Bioinformatics Division,Genetic Re-search,GlaxoSmithKline Pharmaceuticals,5MooreDrive,Research Triangle Park,NC27009,USA.R E P O R T S SCIENCE VOL30416APRIL2004441o n O c t o b e r 7 , 2 0 0 9 w w w . s c i e n c e m a g . o r g D o w n l o a d e d f r o mthat are shed in the feces of infected hosts.C.parvum oocysts are highly resistant to environ-mental stresses,including chlorine treatment of community water supplies;hence,the parasite is an important water-and food-borne pathogen (1).The obligate intracellular nature of the par-asite ’s life cycle and the inability to culture the parasite continuously in vitro greatly impair researchers ’ability to obtain purified samples of the different developmental stages.The par-asite cannot be genetically manipulated,and transformation methodologies are currently un-available.To begin to address these limitations,we have obtained the complete C.parvum ge-nome sequence and its predicted protein com-plement.(This whole-genome shotgun project has been deposited at DDBJ/EMBL/GenBank under the project accession AAEE00000000.The version described in this paper is the first version,AAEE01000000.)The random shotgun approach was used to obtain the complete DNA sequence (2)of the Iowa “type II ”isolate of C.parvum .This isolate readily transmits disease among numerous mammals,including humans.The resulting ge-nome sequence has roughly 13ϫgenome cov-erage containing five gaps and 9.1Mb of totalDNA sequence within eight chromosomes.The C.parvum genome is thus quite compact rela-tive to the 23-Mb,14-chromosome genome of Plasmodium falciparum (3);this size difference is predominantly the result of shorter intergenic regions,fewer introns,and a smaller number of genes (Table 1).Comparison of the assembled sequence of chromosome VI to that of the recently published sequence of chromosome VI (4)revealed that our assembly contains an ad-ditional 160kb of sequence and a single gap versus two,with the common sequences dis-playing a 99.993%sequence identity (2).The relative paucity of introns greatly simplified gene predictions and facilitated an-notation (2)of predicted open reading frames (ORFs).These analyses provided an estimate of 3807protein-encoding genes for the C.parvum genome,far fewer than the estimated 5300genes predicted for the Plasmodium genome (3).This difference is primarily due to the absence of an apicoplast and mitochondrial genome,as well as the pres-ence of fewer genes encoding metabolic functions and variant surface proteins,such as the P.falciparum var and rifin molecules (Table 2).An analysis of the encoded pro-tein sequences with the program SEG (5)shows that these protein-encoding genes are not enriched in low-complexity se-quences (34%)to the extent observed in the proteins from Plasmodium (70%).Our sequence analysis indicates that Cryptosporidium ,unlike Plasmodium and Toxoplasma ,lacks both mitochondrion and apicoplast genomes.The overall complete-ness of the genome sequence,together with the fact that similar DNA extraction proce-dures used to isolate total genomic DNA from C.parvum efficiently yielded mito-chondrion and apicoplast genomes from Ei-meria sp.and Toxoplasma (6,7),indicates that the absence of organellar genomes was unlikely to have been the result of method-ological error.These conclusions are con-sistent with the absence of nuclear genes for the DNA replication and translation machinery characteristic of mitochondria and apicoplasts,and with the lack of mito-chondrial or apicoplast targeting signals for tRNA synthetases.A number of putative mitochondrial pro-teins were identified,including components of a mitochondrial protein import apparatus,chaperones,uncoupling proteins,and solute translocators (table S1).However,the ge-nome does not encode any Krebs cycle en-zymes,nor the components constituting the mitochondrial complexes I to IV;this finding indicates that the parasite does not rely on complete oxidation and respiratory chains for synthesizing adenosine triphosphate (ATP).Similar to Plasmodium ,no orthologs for the ␥,␦,or εsubunits or the c subunit of the F 0proton channel were detected (whereas all subunits were found for a V-type ATPase).Cryptosporidium ,like Eimeria (8)and Plas-modium ,possesses a pyridine nucleotide tran-shydrogenase integral membrane protein that may couple reduced nicotinamide adenine dinucleotide (NADH)and reduced nico-tinamide adenine dinucleotide phosphate (NADPH)redox to proton translocation across the inner mitochondrial membrane.Unlike Plasmodium ,the parasite has two copies of the pyridine nucleotide transhydrogenase gene.Also present is a likely mitochondrial membrane –associated,cyanide-resistant alter-native oxidase (AOX )that catalyzes the reduction of molecular oxygen by ubiquinol to produce H 2O,but not superoxide or H 2O 2.Several genes were identified as involved in biogenesis of iron-sulfur [Fe-S]complexes with potential mitochondrial targeting signals (e.g.,nifS,nifU,frataxin,and ferredoxin),supporting the presence of a limited electron flux in the mitochondrial remnant (table S2).Our sequence analysis confirms the absence of a plastid genome (7)and,additionally,the loss of plastid-associated metabolic pathways including the type II fatty acid synthases (FASs)and isoprenoid synthetic enzymes thatTable 1.General features of the C.parvum genome and comparison with other single-celled eukaryotes.Values are derived from respective genome project summaries (3,26–28).ND,not determined.FeatureC.parvum P.falciparum S.pombe S.cerevisiae E.cuniculiSize (Mbp)9.122.912.512.5 2.5(G ϩC)content (%)3019.43638.347No.of genes 38075268492957701997Mean gene length (bp)excluding introns 1795228314261424ND Gene density (bp per gene)23824338252820881256Percent coding75.352.657.570.590Genes with introns (%)553.9435ND Intergenic regions (G ϩC)content %23.913.632.435.145Mean length (bp)5661694952515129RNAsNo.of tRNA genes 454317429944No.of 5S rRNA genes 6330100–2003No.of 5.8S ,18S ,and 28S rRNA units 57200–400100–20022Table parison between predicted C.parvum and P.falciparum proteins.FeatureC.parvum P.falciparum *Common †Total predicted proteins380752681883Mitochondrial targeted/encoded 17(0.45%)246(4.7%)15Apicoplast targeted/encoded 0581(11.0%)0var/rif/stevor ‡0236(4.5%)0Annotated as protease §50(1.3%)31(0.59%)27Annotated as transporter ࿣69(1.8%)34(0.65%)34Assigned EC function ¶167(4.4%)389(7.4%)113Hypothetical proteins925(24.3%)3208(60.9%)126*Values indicated for P.falciparum are as reported (3)with the exception of those for proteins annotated as protease or transporter.†TBLASTN hits (e Ͻ–5)between C.parvum and P.falciparum .‡As reported in (3).§Pre-dicted proteins annotated as “protease or peptidase”for C.parvum (CryptoGenome database,)and P.falciparum (PlasmoDB database,).࿣Predicted proteins annotated as “trans-porter,permease of P-type ATPase”for C.parvum (CryptoGenome)and P.falciparum (PlasmoDB).¶Bidirectional BLAST hit (e Ͻ–15)to orthologs with assigned Enzyme Commission (EC)numbers.Does not include EC assignment numbers for protein kinases or protein phosphatases (due to inconsistent annotation across genomes),or DNA polymerases or RNA polymerases,as a result of issues related to subunit inclusion.(For consistency,46proteins were excluded from the reported P.falciparum values.)R E P O R T S16APRIL 2004VOL 304SCIENCE 442 o n O c t o b e r 7, 2009w w w .s c i e n c e m a g .o r g D o w n l o a d e d f r o mare otherwise localized to the plastid in other apicomplexans.C.parvum fatty acid biosynthe-sis appears to be cytoplasmic,conducted by a large(8252amino acids)modular type I FAS (9)and possibly by another large enzyme that is related to the multidomain bacterial polyketide synthase(10).Comprehensive screening of the C.parvum genome sequence also did not detect orthologs of Plasmodium nuclear-encoded genes that contain apicoplast-targeting and transit sequences(11).C.parvum metabolism is greatly stream-lined relative to that of Plasmodium,and in certain ways it is reminiscent of that of another obligate eukaryotic parasite,the microsporidian Encephalitozoon.The degeneration of the mi-tochondrion and associated metabolic capabili-ties suggests that the parasite largely relies on glycolysis for energy production.The parasite is capable of uptake and catabolism of mono-sugars(e.g.,glucose and fructose)as well as synthesis,storage,and catabolism of polysac-charides such as trehalose and amylopectin. Like many anaerobic organisms,it economizes ATP through the use of pyrophosphate-dependent phosphofructokinases.The conver-sion of pyruvate to acetyl–coenzyme A(CoA) is catalyzed by an atypical pyruvate-NADPH oxidoreductase(Cp PNO)that contains an N-terminal pyruvate–ferredoxin oxidoreductase (PFO)domain fused with a C-terminal NADPH–cytochrome P450reductase domain (CPR).Such a PFO-CPR fusion has previously been observed only in the euglenozoan protist Euglena gracilis(12).Acetyl-CoA can be con-verted to malonyl-CoA,an important precursor for fatty acid and polyketide biosynthesis.Gly-colysis leads to several possible organic end products,including lactate,acetate,and ethanol. The production of acetate from acetyl-CoA may be economically beneficial to the parasite via coupling with ATP production.Ethanol is potentially produced via two in-dependent pathways:(i)from the combination of pyruvate decarboxylase and alcohol dehy-drogenase,or(ii)from acetyl-CoA by means of a bifunctional dehydrogenase(adhE)with ac-etaldehyde and alcohol dehydrogenase activi-ties;adhE first converts acetyl-CoA to acetal-dehyde and then reduces the latter to ethanol. AdhE predominantly occurs in bacteria but has recently been identified in several protozoans, including vertebrate gut parasites such as Enta-moeba and Giardia(13,14).Adjacent to the adhE gene resides a second gene encoding only the AdhE C-terminal Fe-dependent alcohol de-hydrogenase domain.This gene product may form a multisubunit complex with AdhE,or it may function as an alternative alcohol dehydro-genase that is specific to certain growth condi-tions.C.parvum has a glycerol3-phosphate dehydrogenase similar to those of plants,fungi, and the kinetoplastid Trypanosoma,but(unlike trypanosomes)the parasite lacks an ortholog of glycerol kinase and thus this pathway does not yield glycerol production.In addition to themodular fatty acid synthase(Cp FAS1)andpolyketide synthase homolog(Cp PKS1), C.parvum possesses several fatty acyl–CoA syn-thases and a fatty acyl elongase that may partici-pate in fatty acid metabolism.Further,enzymesfor the metabolism of complex lipids(e.g.,glyc-erolipid and inositol phosphate)were identified inthe genome.Fatty acids are apparently not anenergy source,because enzymes of the fatty acidoxidative pathway are absent,with the exceptionof a3-hydroxyacyl-CoA dehydrogenase.C.parvum purine metabolism is greatlysimplified,retaining only an adenosine ki-nase and enzymes catalyzing conversionsof adenosine5Ј-monophosphate(AMP)toinosine,xanthosine,and guanosine5Ј-monophosphates(IMP,XMP,and GMP).Among these enzymes,IMP dehydrogenase(IMPDH)is phylogenetically related toε-proteobacterial IMPDH and is strikinglydifferent from its counterparts in both thehost and other apicomplexans(15).In con-trast to other apicomplexans such as Toxo-plasma gondii and P.falciparum,no geneencoding hypoxanthine-xanthineguaninephosphoribosyltransferase(HXGPRT)is de-tected,in contrast to a previous report on theactivity of this enzyme in C.parvum sporo-zoites(16).The absence of HXGPRT sug-gests that the parasite may rely solely on asingle enzyme system including IMPDH toproduce GMP from AMP.In contrast to otherapicomplexans,the parasite appears to relyon adenosine for purine salvage,a modelsupported by the identification of an adeno-sine transporter.Unlike other apicomplexansand many parasitic protists that can synthe-size pyrimidines de novo,C.parvum relies onpyrimidine salvage and retains the ability forinterconversions among uridine and cytidine5Ј-monophosphates(UMP and CMP),theirdeoxy forms(dUMP and dCMP),and dAMP,as well as their corresponding di-and triphos-phonucleotides.The parasite has also largelyshed the ability to synthesize amino acids denovo,although it retains the ability to convertselect amino acids,and instead appears torely on amino acid uptake from the host bymeans of a set of at least11amino acidtransporters(table S2).Most of the Cryptosporidium core pro-cesses involved in DNA replication,repair,transcription,and translation conform to thebasic eukaryotic blueprint(2).The transcrip-tional apparatus resembles Plasmodium interms of basal transcription machinery.How-ever,a striking numerical difference is seenin the complements of two RNA bindingdomains,Sm and RRM,between P.falcipa-rum(17and71domains,respectively)and C.parvum(9and51domains).This reductionresults in part from the loss of conservedproteins belonging to the spliceosomal ma-chinery,including all genes encoding Smdomain proteins belonging to the U6spliceo-somal particle,which suggests that this par-ticle activity is degenerate or entirely lost.This reduction in spliceosomal machinery isconsistent with the reduced number of pre-dicted introns in Cryptosporidium(5%)rela-tive to Plasmodium(Ͼ50%).In addition,keycomponents of the small RNA–mediatedposttranscriptional gene silencing system aremissing,such as the RNA-dependent RNApolymerase,Argonaute,and Dicer orthologs;hence,RNA interference–related technolo-gies are unlikely to be of much value intargeted disruption of genes in C.parvum.Cryptosporidium invasion of columnarbrush border epithelial cells has been de-scribed as“intracellular,but extracytoplas-mic,”as the parasite resides on the surface ofthe intestinal epithelium but lies underneaththe host cell membrane.This niche may al-low the parasite to evade immune surveil-lance but take advantage of solute transportacross the host microvillus membrane or theextensively convoluted parasitophorous vac-uole.Indeed,Cryptosporidium has numerousgenes(table S2)encoding families of putativesugar transporters(up to9genes)and aminoacid transporters(11genes).This is in starkcontrast to Plasmodium,which has fewersugar transporters and only one putative ami-no acid transporter(GenBank identificationnumber23612372).As a first step toward identification ofmulti–drug-resistant pumps,the genome se-quence was analyzed for all occurrences ofgenes encoding multitransmembrane proteins.Notable are a set of four paralogous proteinsthat belong to the sbmA family(table S2)thatare involved in the transport of peptide antibi-otics in bacteria.A putative ortholog of thePlasmodium chloroquine resistance–linkedgene Pf CRT(17)was also identified,althoughthe parasite does not possess a food vacuole likethe one seen in Plasmodium.Unlike Plasmodium,C.parvum does notpossess extensive subtelomeric clusters of anti-genically variant proteins(exemplified by thelarge families of var and rif/stevor genes)thatare involved in immune evasion.In contrast,more than20genes were identified that encodemucin-like proteins(18,19)having hallmarksof extensive Thr or Ser stretches suggestive ofglycosylation and signal peptide sequences sug-gesting secretion(table S2).One notable exam-ple is an11,700–amino acid protein with anuninterrupted stretch of308Thr residues(cgd3_720).Although large families of secretedproteins analogous to the Plasmodium multi-gene families were not found,several smallermultigene clusters were observed that encodepredicted secreted proteins,with no detectablesimilarity to proteins from other organisms(Fig.1,A and B).Within this group,at leastfour distinct families appear to have emergedthrough gene expansions specific to the Cryp-R E P O R T S SCIENCE VOL30416APRIL2004443o n O c t o b e r 7 , 2 0 0 9 w w w . s c i e n c e m a g . o r g D o w n l o a d e d f r o mtosporidium clade.These families —SKSR,MEDLE,WYLE,FGLN,and GGC —were named after well-conserved sequence motifs (table S2).Reverse transcription polymerase chain reaction (RT-PCR)expression analysis (20)of one cluster,a locus of seven adjacent CpLSP genes (Fig.1B),shows coexpression during the course of in vitro development (Fig.1C).An additional eight genes were identified that encode proteins having a periodic cysteine structure similar to the Cryptosporidium oocyst wall protein;these eight genes are similarly expressed during the onset of oocyst formation and likely participate in the formation of the coccidian rigid oocyst wall in both Cryptospo-ridium and Toxoplasma (21).Whereas the extracellular proteins described above are of apparent apicomplexan or lineage-specific in-vention,Cryptosporidium possesses many genesencodingsecretedproteinshavinglineage-specific multidomain architectures composed of animal-and bacterial-like extracellular adhe-sive domains (fig.S1).Lineage-specific expansions were ob-served for several proteases (table S2),in-cluding an aspartyl protease (six genes),a subtilisin-like protease,a cryptopain-like cys-teine protease (five genes),and a Plas-modium falcilysin-like (insulin degrading enzyme –like)protease (19genes).Nine of the Cryptosporidium falcilysin genes lack the Zn-chelating “HXXEH ”active site motif and are likely to be catalytically inactive copies that may have been reused for specific protein-protein interactions on the cell sur-face.In contrast to the Plasmodium falcilysin,the Cryptosporidium genes possess signal peptide sequences and are likely trafficked to a secretory pathway.The expansion of this family suggests either that the proteins have distinct cleavage specificities or that their diversity may be related to evasion of a host immune response.Completion of the C.parvum genome se-quence has highlighted the lack of conven-tional drug targets currently pursued for the control and treatment of other parasitic protists.On the basis of molecular and bio-chemical studies and drug screening of other apicomplexans,several putative Cryptospo-ridium metabolic pathways or enzymes have been erroneously proposed to be potential drug targets (22),including the apicoplast and its associated metabolic pathways,the shikimate pathway,the mannitol cycle,the electron transport chain,and HXGPRT.Nonetheless,complete genome sequence analysis identifies a number of classic and novel molecular candidates for drug explora-tion,including numerous plant-like and bacterial-like enzymes (tables S3and S4).Although the C.parvum genome lacks HXGPRT,a potent drug target in other api-complexans,it has only the single pathway dependent on IMPDH to convert AMP to GMP.The bacterial-type IMPDH may be a promising target because it differs substan-tially from that of eukaryotic enzymes (15).Because of the lack of de novo biosynthetic capacity for purines,pyrimidines,and amino acids,C.parvum relies solely on scavenge from the host via a series of transporters,which may be exploited for chemotherapy.C.parvum possesses a bacterial-type thymidine kinase,and the role of this enzyme in pyrim-idine metabolism and its drug target candida-cy should be pursued.The presence of an alternative oxidase,likely targeted to the remnant mitochondrion,gives promise to the study of salicylhydroxamic acid (SHAM),as-cofuranone,and their analogs as inhibitors of energy metabolism in the parasite (23).Cryptosporidium possesses at least 15“plant-like ”enzymes that are either absent in or highly divergent from those typically found in mammals (table S3).Within the glycolytic pathway,the plant-like PPi-PFK has been shown to be a potential target in other parasites including T.gondii ,and PEPCL and PGI ap-pear to be plant-type enzymes in C.parvum .Another example is a trehalose-6-phosphate synthase/phosphatase catalyzing trehalose bio-synthesis from glucose-6-phosphate and uridine diphosphate –glucose.Trehalose may serve as a sugar storage source or may function as an antidesiccant,antioxidant,or protein stability agent in oocysts,playing a role similar to that of mannitol in Eimeria oocysts (24).Orthologs of putative Eimeria mannitol synthesis enzymes were not found.However,two oxidoreductases (table S2)were identified in C.parvum ,one of which belongs to the same families as the plant mannose dehydrogenases (25)and the other to the plant cinnamyl alcohol dehydrogenases.In principle,these enzymes could synthesize protective polyol compounds,and the former enzyme could use host-derived mannose to syn-thesize mannitol.References and Notes1.D.G.Korich et al .,Appl.Environ.Microbiol.56,1423(1990).2.See supportingdata on Science Online.3.M.J.Gardner et al .,Nature 419,498(2002).4.A.T.Bankier et al .,Genome Res.13,1787(2003).5.J.C.Wootton,Comput.Chem.18,269(1994).Fig.1.(A )Schematic showing the chromosomal locations of clusters of potentially secreted proteins.Numbers of adjacent genes are indicated in paren-theses.Arrows indicate direc-tion of clusters containinguni-directional genes (encoded on the same strand);squares indi-cate clusters containingg enes encoded on both strands.Non-paralogous genes are indicated by solid gray squares or direc-tional triangles;SKSR (green triangles),FGLN (red trian-gles),and MEDLE (blue trian-gles)indicate three C.parvum –speciﬁc families of paralogous genes predominantly located at telomeres.Insl (yellow tri-angles)indicates an insulinase/falcilysin-like paralogous gene family.Cp LSP (white square)indicates the location of a clus-ter of adjacent large secreted proteins (table S2)that are cotranscriptionally regulated.Identiﬁed anchored telomeric repeat sequences are indicated by circles.(B )Schematic show-inga select locus containinga cluster of coexpressed large secreted proteins (Cp LSP).Genes and intergenic regions (regions between identiﬁed genes)are drawn to scale at the nucleotide level.The length of the intergenic re-gions is indicated above or be-low the locus.(C )Relative ex-pression levels of CpLSP (red lines)and,as a control,C.parvum Hedgehog-type HINT domain gene (blue line)duringin vitro development,as determined by semiquantitative RT-PCR usingg ene-speciﬁc primers correspondingto the seven adjacent g enes within the CpLSP locus as shown in (B).Expression levels from three independent time-course experiments are represented as the ratio of the expression of each gene to that of C.parvum 18S rRNA present in each of the infected samples (20).R E P O R T S16APRIL 2004VOL 304SCIENCE 444 o n O c t o b e r 7, 2009w w w .s c i e n c e m a g .o r g D o w n l o a d e d f r o m。

mm5说明书(中文)

中尺度模式（Mesoscale Model 5 v3）用户手册一、概述1.mm5模式系统的结构第五代中尺度模式mm5是近年来由美国大气研究中心（NCAR）和美国滨州大学（PSU）在mm4基础上联合研制发展起来的中尺度数值预报模式，已被广泛应用于各种中尺度现象的研究。

Mm5在以往的模式基础上作了许多变化，主要有以下几点：1）复合区域嵌套功能，2）菲静力部分扩展3）四位数据同化功能以及较多的物理过程参数化，能够方便、广泛地应用于各种计算平台。

这些变化使得许多工作在这一模式系统下建立起来。

图1.1是整个mm5模式系统的结构框图，它表现了模式的模块次序、数据流程以及各模块主要功能的简短说明。

TERRAIN和REGRID模块用来处理在麦卡托或兰博托或极射赤面投影下，地形数据和等压面气象数据从规则经纬网格点到高分辨可变中尺度区域的水平插值。

由于插值不能提供全面的中尺度信息，因此插值数据必须加大，RAWINS/little_r就是用连续扫描Cressman客观分析方法和复合二次曲面技术来处理水平网格观测资料和无线电探空资料。

INTERP模块处理MM5系统中气压坐标到sigma坐标的垂直插值，接近地面的sigma平面与地形相似，高水平sigma面与等压面近似。

MM5模块是系统的核心部分，包含气象过程的主控程序，主要求解大气运动基本方程组。

INTERB模块与INTERP 模块作用相反，主要是把MM5模块计算结果从sigma坐标插值到气压坐标中。

2．Mm5模式的水平和垂直格点介绍模式的格点构造是非常有用的，模式系统通常是从等压面上获得、分析数据的，但是这些资料在进入模式之前不得不被插值到模式的垂直坐标中。

垂直坐标是地形伴随的，也就是在底层水平网格伴随地形，而上层表面是平坦的。

中间层是随着气压的减小趋向顶层气压逐渐变得平坦（如图1.2）。

σ用来定义模式水平层：p是气压，p t是顶层气压，p s是表面气压。

从上图可以看出：在顶层σ等于0，在底层σ等于1，模式的每一水平层由σ值来定义，模式的垂直分辨率由0到1之间的数目决定，通常边界层的分辨率高于顶层分辨率，水平层数尽管原则上没有限制，但通常在10到40层之间变化。

Newtonian motion as origin of anisotropy of the local velocity field of galaxies

a r X i v :a s t r o -p h /0206114v 6 6 N o v 2003Newtonian motion as origin of anisotropy of the local velocity ﬁeld ofgalaxiesMonika Biernacka,1Piotr Flin,1,2,∗Victor Pervushin,2,†and Andrey Zorin 31Pedagogical University,Institute of Physics,25-406Kielce,Poland2Bogoliubov Laboratory of Theoretical Physics,Joint Institute for Nuclear Research,141980,Dubna,Russia3Faculty of Physics,MSU,Vorobjovy Gory,Moscow,119899,RussiaAbstractThe origins of recently reported anisotropy of the local velocity ﬁeld of nearby galaxies (velocities <500km/s corresponding to the distance less than 8Mpc)are studied.The exact solution of the Newtonian equation for the expanding Universe is obtained.This solution allows us to separate the Newtonian motion of nearby galaxies from the Hubble ﬂow by the transition to the conformal coordinates.The relation between the Hubble ﬂow and the Newtonian motion is established.We show that the anisotropic local velocity ﬁeld of nearby galaxies can be formed by such a Newtonian motion in the expanding Universe,if at the moment of the capture of galaxies by the central gravitational ﬁeld.PACS numbers:98.80.-k,98.62.Py,98.56.-pKeywords:Cosmology,Hubble constant,Local groupI.INTRODUCTIONRecent observation of the local velocityﬁeld of galaxies gives a three-dimensional ellipsoid with diﬀerent values of the Hubble parameter,clearly showing its anisotropic character[3,4].In this paper,we present a possible point of view that this local velocityﬁeld of galaxies can be explained by their Newtonian motions.The analysis of the observational data will be based on the radial velocities of nearby galaxies, belonging to the Local Group.Our paper is organized in the following manner.In Section II,the cosmic evolution is described.In Section III,we introduce the Newtonian motion and separate this motion from the cosmic one.In Section IV,the initial data of the galaxies capture by a central gravitationalﬁeld is considered.In Sections V,the simplest example is given to elucidate our results. The paper ends with the conclusions.II.COSMIC EVOLUTION OF A FREE PARTICLEEﬀects of cosmic evolutions are considered in the Friedmann–Lemˆa itre–Robertson–Walker (FLRW)metrics(ds2)=(dt)2−a(t)2(dx i)2.(1) The formulation of the Newtonian problem in this metrics proposes a choice of physical variables and coordinates.The modern cosmology uses two choices of such variables:the conformal time(η) and coordinate distance(x i)with the interval(ds2)=a(η)2 (dη)2−(dx i)2 ,(2) and the Friedmann time(t)and distance X i=ax i in terms of which the interval(1)takes the form(ds2)=(dt)2− dX i−H(t)X i dt 2,(3) where H(t)=˙a(t)/a(t)is the Hubble parameter,we have used here the formula of diﬀerential calculus adx=d(ax)−xda.Both the sets are mathematically equivalent1.In terms of the Friedmann variables X i=ax i the Newton action in the space with the interval (3)takes the formS A=t0t Idt P i(˙X i−HX i)−P2i1Note that a(t)=a(η(t))is connected with a(η)by equation dt=a(η)dη.The equations of motion˙X i−HX i=P idη−p2iR dRX21+X22+X23 (7)from possible Newtonian motion.Substituting R=ar,where r=a dardrrdr2m0+α2The action(4)and(6)diﬀer from the one(7.4)in monograph[1],that is not compatible with quantumﬁeld theory on the conformalﬂat metric(2)[2].takes the formS A=t0t Idt P R(˙R−HR)+Pθ˙θ−P2R2m0R2+α2m0a(η)−P2θr .(13)IV.THE CAPTURE OF GALAXIES BY THE CENTRAL GRA VITATIONAL FIELD The energy of a particle with the running mass m(η)=a(η)m0described by the action(13)E(η)=p2r2m0a(η)r2−αm0a(ηI)≡(r′I)2+v2Im I r I,w I= m I r I(16) are the orbital velocity and Newtonian one,respectively.It is known that the change of a sign of the energy means the change of an unrestricted motion of a particle by aﬁnite motion in the central ﬁeld.Therefore,the timeηI can be treated as the time of the capture of a particle(cosmic object) by the central gravitationalﬁeld.If the initial radial velocity is too equal to zero r′I=0,the zero–energy constraint(15)v2I=2w2I(17) becomes the equation for the initial data m0a(ηI)r(ηI)≡m I r I.The solution of this equation m I r I=P2θ/(2α)can give a orbital velocity for all trajectories of the captured cosmic objectsv I=2αThe fact of the universality of the orbital velocity (18)for all ellipsoidal trajectories (due to thezeroenergyinitialdataof theformationof alocaluniverse)gives us a possibility of expanding both the numerous observational data on the law of the constant orbital velocity [4,5,6,7]and the anizotropy of the local velocity ﬁeld [3,4].The anisotropy of the local velocity ﬁeld ∆H =0[1,2]is not compatible with the class of the isotropic circular trajectories r (η0)≡r 0,r ′=r ′′=0with the equation of motionv 20=w 20v 0=P θαda+v 0dθc 0p 2y +v 20/y2y,(21)where w 0=r 0m 0=12−aw 203Remind that the hypothesis of the Cold Dark Matter was proposed in [7,8]to explain the law of the constant orbital velocity in the class of the circular trajectories in the nonexpanding Universe where (19)is valid.It is easy to see that v0is a constant of the motion dv0/da=0.The equations of the radial motionp y=c0dyda=v20y2(23)can be written in the Lagrangian formd2yc0 2v0y3−ada2a=1=w0w0 2−1 (25)in terms of three velocities w0,v0,c0,and it allows us to choose any relations between w0and v0,in particular v20=2w20,in contrast to the circular trajectory where v20=w20.The general solution of this equation(24)can be obtained in the parametrical form:a(τ)=c1N2(τ)dτ+ 2w0 3c02ω∆1/2,(30)c2= v03c0 1/311+z I ,y|τ=0=r Ida τ=0=0;(32)here for the upper sign(restricted solution at inﬁnity,τ=+∞)in(28)U(τ)=J1/3(τ),V(τ)=Y1/3(τ),andω=2where I1/3(τ)and K1/3(τ)are the modiﬁed Bessel functions of theﬁrst and second(or MacDonald function)kind(see,e.g.[14]).A solution of the equation of motion following from the action(13)is given in Fig.1and Fig.2. We use this solution for construction of two plots.Figure3gives the values of the correction(9)to the Friedmann Hubbleﬂow resulting from taking into account eq.(9).It is clearly seen that the corrections are dumped with time and have a quasi–periodical character.In Fig.4the angular distribution of the Hubbleﬂow correction,as given by(9),is presented. The correction is anisotropic.We consider the2-dimensional case while Karachentsev’s anisotropy is observed in3-dimensions.Nevertheless,our2-dimensional analysis allows one to see the anisotropy of the Hubbleﬂow and to estimate the order of the magnitude of the anisotropy.We have considered the case when the formation of a galaxy began from the zero–energy state (the initial data E0=0,and velocity y′0=0).These data correspond to the relation v20=2w20.VI.CONCLUSIONOur paper was motivated by theﬁnding that in the local Universe the velocityﬁeld is anisotropic[3, 4].This eﬀect is diﬃcult for explanation.The only possible suggestion,but rejected by Karachentsev, was rotation[4].We are trying toﬁnd the origin of this anisotropy.In ordered to do this,we consider the general uniform expansion of the Universe.Since this is the nearby(less than8Mpc)part of the Universe around us,we use the Newtonian approach.We studied the motion of the test massive particle in the central gravitationalﬁeld on the background of cosmic evolution of the type of FLRW space–time with uniform expansion.We assume the rigid state of the matter when densities of energy and pressure are equal and which corresponds to conformal cosmology[10]compatibles with Supernova data[11].We obtained the exact solution of the above–mentioned Kepler problem,toﬁnd the diﬀerence between the uniform Hubbleﬂow and our case.We have shown that this diﬀerence was anisotropic.In such a way we explained the anisotropy of the local velocityﬁeld by the Newtonian motion of galaxies in the centralﬁeld.Of course,our2–D consideration shows a possible mechanism of the observed3–D anisotropy.Having the solution of the Kepler problem we admit the rotation of galaxies around the center of the local Universe.This local Universe must be regarded as the Local Group of galaxies.In such a way,we support the picture in which galaxies rotate around the center of the Local Group in theclass of ellipsoidal trajectories.[1]P.J.E.Peebles,The Large-Scale Structure of the Universe.Princenton University Press,Princenton,New Jersey,1980[2]V.N.Pervushin,V.I.Smirichinski,J.Phys.A:Math.Gen.32(1999)6191[3]I.D.Karachentsev,Usp.Fiz.Nauk,171(2001)860[4]I.D.Karachentsev,D.I.Makarov,Astroﬁzika44(2001)1[5]ndau,E.M.Lifshits,Mekhanika,(Moscow:GIFML,1963)(Translated into English:Oxford:Pergamon Press,1965)[6]L.E.Gurevich and A.D.Chernin,Vvedenie v Kosmologiuy(Introduction to cosmogony),Moscow,Nauka,1978(In Russian)[7]J.Einasto,E.Saar,and A.Kaasik,Nature250(1974)309[8]J.Einasto,E.Saar,A.Kaasik,and A.Chernin,Nature252(1974)111[9]J.R.Primack,Proceedings of5th International UCLA Symposium on Sources and Detection of DarkMatter,Marina del Rey,February2002,ed.D.Cline,astro-ph/0205391[10] D.Behnke,D.Blaschke,V.Pervushin,and D.Proskurin,Phys.Lett.B530(2002)20,gr-qc/0102039[11]S.Perlmutter et al.,Astrophys.J.517(1991)565[12] A.G.Riess et al.,Astron.J.116(1998)1009[13] A.G.Riess et al.,Astrophys.J.560(2001)49,astro-ph/0104455[14] A.D.Poljanin,V.F.Zaitsev,Handbook for Non-Liner Ordinary Diﬀerential Equations.Factorial,Moscow,1997Figure 1:Graph of function y (τ)=a (τ)r (τ)/r 0(26)at v 20/c 20=0.2and w 20/c 20=0.1.Figure 2:Graph of functions product a (τ)y (τ)(26)at v 20/c 20=0.2and w 20/c 20=0.1for −3<a (τ)<14.Figure 3:Graph of function ∆H (9)in units H 0atv 20/c 20=0.2and w 20/c 20=0.1.Figure 4:Graph of function ∆H (9)in units H 0atv 20/c 20=0.2and w 20/c 20=0.1for 0.8<a (τ)<14.。

庞加莱猜想前言

庞加莱猜想-前言Wir m\"ussen wissen! Wir werden wissen!(我们必须知道！我们必将知道！)—— David Hilbert两年前科学版举行过一次版聚，我报告了低维拓扑里面的一些问题和进展，其中有一半篇幅是关于Poincar\'e 猜想。

版聚后，flyleaf 要求大家回去后把自己所讲的内容发在版上。

当时我甚至已经开始写了一两段，但后来又搁置了。

主要是因为自己对于低维拓扑还是一个门外汉，写出来的东西难免有疏漏之处，不敢妄下笔。

两年过去，我对低维拓扑这门学科的了解比原先多了，说话的底气也就比原先足了。

另外，由于Clay 研究所的百万巨赏，近年来Poincar\'e 猜想频频在媒体上曝光；而且Perelman 最近的工作使数学家们有理由相信我们已经充分接近于这一猜想的最后解决。

所以大概会有很多人对Poincar\'e 猜想的来龙去脉感兴趣，我也好借机一偿两年来的宿愿。

现代科学的高速发展使各学科之间的鸿沟加大，不同学科之间难以互相理解，所以非数学专业的读者在阅读本文时可能会遇到一些困难。

但限于篇幅和文章的形式，我也不可能对很多东西详细解释。

一些最基本的拓扑概念如“流形”，我将在本文的附录中解释。

还有一些“同调群”、“基本群”之类的名词，读者见到时大可不去理会它们的确切含义。

我将尽量避免使用这一类的专业术语。

作者并非拓扑方面的专家，对下面要说的很多内容都是道听途说，只知其然而不知其所以然；作者更不善于写作，写出来的东东总会枯燥无味，难登大雅之堂。

凡此种种，还请读者诸君海涵。

问题的由来Consid\'erons maintenant une vari\'et\'e [ferm\'ee] $V$ \`a trois dimensions ... Est-il possible que le groupe fondamental de $V$ ser\'eduise \`a la substitution identique, et que pourtant $V$ ne soit pas simplement connexe?—— Henri Poincar\'e在拓扑学家的眼里，篮球、排球和乒乓球并没有什么不同，它们都同胚于三维空间中的球面S^2. (我们把n+1维欧氏空间中到原点距离为1的点的集合记作S^n，称为n维球面(sphere)。

一类动力学方程及流体力学方程解的Gevrey类正则性

Boltzmann 方程 . . . . . . . . . . . . . . . . . . . . . . . . 碰撞算子 Q(f, f ) 的基本性质 . . . . . . . . . . . . . . . . . Fokker-Planck 方程、Landau 方程以及 Boltzmann 方程线性化模型 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Navier-Stokes 方程 . . . . . . . . . . . . . . . . . . . . . . . Gevrey 函数空间 . . . . . . . . . . . . . . . . . . . . . . . .
研究现状及本文主要结果 . . . . . . . . . . . . . . . . . . . . . . . 1.2.1 1.2.2 1.2.3 1.2.4 存在性及唯一性 . . . . . . . . . . . . . . . . . . . . . . . . . 动力学方程的正则性理论: 空间齐次情形 . . . . . . . . . . . 动力学方程的正则性理论: 空间非齐次情形 . . . . . . . . . . Navier-Stokes 方程的正则性理论 . . . . . . . . . . . . . . .
第二章预备知识 2.1 2.2 2.3 基本记号
Fourier 变换 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 基本函数空间及常用不等式 . . . . . . . . . . . . . . . . . . . . . . 2.3.1 2.3.2 Lp 空间及其性质 . . . . . . . . . . . . . . . . . . . . . . . . Sobolev 空间及其性质 . . . . . . . . . . . . . . . . . . . . .

aspen 色谱操作

Che558 实验一.阿斯色谱的入门2005年一月20日注意实验结束的指示你可以和其他同学在实验室进行分工合作本实验的目标是使你掌握阿斯色谱的入门。

包括了一份关于运行阿四色谱仪器的说明书和一些有用的提示。

我们也将模拟一个真正的分离过程。

保证实验任务的分配。

直到运行阿瑟色谱仪变得自动化为止，你将要参考这个说明。

标记实验分配结束。

Nadia abunasser的协助对于发展这个实验是非常有帮助。

1.登录到计算机。

依次打开Programs, ChE Software, AspenTech, Aspen Engineering Suite, Aspen Chromatography 12.1, Aspen Chromatography. 如果你在一个可以允许你访问硬盘驱动器的位置，这将会打开一个窗口。

否则，本质上说，你将会得到一个消息显示工作文件夹不可用。

在这种情况下，改变工作文件到你的N驱动。

点击OK，窗口将打开如果没有，就去请求帮助吧。

2. 我们将首先开发一个简单的色谱系统(或吸附)列。

要做到这一点,去菜单栏、左侧文件。

点击文件,去模板,并在窗口中点击“空白微量液体批处理流程,并单击复制。

它将要求一个文件名。

column1使用类似。

”“这将被保存在你的工作文件。

注意:在所有文件名称和名称的组件,列,等等必须没有空格。

3. “探索模拟(Exploring simulation)”框(LHS),点击“组件列表。

”然后下面框中双击默认(内容)。

这个列表A和B。

这些名称更改为组件的名称(果糖和右旋糖酐T6(fructose and dextran T6))分离。

首先,点击“删除”按钮。

然后在窗口下面键入第一个组件名称(如。

果糖fructose),单击“添加”按钮。

做同样的所有其他组件。

然后单击OK。

4. 现在绘制列。

单击+到左侧的“色谱”探索模拟盒子。

这将打开其他的可用功能。

点击单词“chromatography ”这应该给“色谱法的内容Contents of Chromatography ”在盒子下面。

数学-科学的王后与仆人

数学: 科学的王后和仆人Mathematics: Queen and Servant of Science北京理工大学叶其孝本文的题目是已故的美国科学院院士、著名数学家、数学史学家和科普作家Eric Temple Bell(贝尔, 1883, 02, 07 ~ 1960, 12, 21)于1951年写的一本书的书名Mathematics: Queen and Servant of Science (数学: 科学的王后和仆人). 该书主要是为大学生和非数学领域的人士写的, 介绍纯粹和应用数学的各个方面, 更着重在说明数学科学的极端重要性.The Mathematical Association of America, 1996, 463 pages实际上这是他1931年写的The Queen of the Sciences (科学的王后)和1937年写的The Handmaiden of the Sciences (科学的女仆)这两本通俗数学论著的合一修订扩大版.Eric Temple Bell Alexander Graham Bell (1847 ~ 1922) 按常识的理解, 女王是优美、高雅、无懈可击、至尊至贵的, 在科学中只有纯粹数学才具有这样的特点, 简洁明了的数学定理一经证明就是永恒的真理, 极其优美而且无懈可击;另一方面, 科学和工程的各个分支都在不同程度上大量应用数学, 这时数学科学就是仆人, 这些仆人是否强有力, 用起来是否得心应手是雇佣这些仆人的主人最为关心的事. 事实上, servant这个字本身就有“供人们利用之物, 有用的服务工具”的意思. 毫无疑问, 我们的目的不是为数学争一个好的名分, 而是想说明数学是怎样通过数学建模来解决各种实际问题的; 数学(数学建模)的极端重要性, 以及探讨正确认识和理解数学科学的作用对于发展我国科学技术、经济以及教育, 从而争取在21世纪把我国真正建设成为屹立于世界民族之林的强国，乃至个人事业发展的至关重要性. 当然, 我们也希望说明王后和仆人集于一身并不矛盾. 历史上, 很多特别受人尊敬的科学家, 不仅仅是由于他们的科学成就, 更因为他们的科学成就能够服务于人类.数学是科学的王后, 算术是数学的王后. 她常常放下架子为天文学和其他科学效劳, 但是在所有情况下, 第一位的是她(数学)应尽的责任. (高斯)Mathematics is the Queen of the Sciences, and Arithmetic the Queen of Mathematics. She often condescends to render service to astronomy and other natural sciences, but under all circumstance the first place is her due.— Carl Friedrich Gauss (卡尔·弗里德里希·高斯, 1777, 4, 30 ~ 1855, 2, 23)From: Bell, Eric T., Mathematics: Queen and Servant of Science, MAA, 1951, p.1;Men of Mathematics, Simon and Schuster, New York, 1937, p. xv.***************************************************自古以来，数学的发展始终与科学技术的发展紧密相连，反之亦然. 首先, 我们来看一下导致我们现在这个飞速发展的信息社会的19、20世纪几乎所有重大科学理论的发展和完善过程中数学(数学建模)所起到的不可勿缺的作用.数学研究的成果往往是重大科学发明的催生素(仅就19、20世纪而言, 流体力学、电磁理论、相对论、量子力学、计算机、信息论、控制论、现代经济学、万维网和互联网搜索引擎、生物学、CT、甚至社会政治学领域等). 但是20世纪上半世纪, 数学虽然也直接为工程技术提供一些工具, 但基本方式是间接的: 先促进其他科学的发展, 再由这些科学提供工程原理和设计的基础. 数学是幕后的无名英雄.现在, 数学无处不在, 数学和工程技术之间,在更广阔的范围内和更深刻的程度上, 直接地相互作用着, 极大地推动了科学和工程科学的发展, 也极大地推动了技术的发展. 数学不仅是幕后的无名英雄, 很多方面开始走向“前台”. 但是对数学的极端重要性迄今尚未有共识, 取得共识对加强一个国家的竞争力来说是至关重要的.硬能力―一位美国朋友谈及对未来中国人的看法: 20年后, 中国年轻人会丢了中国人现在的硬能力, 他们崇拜各种明星, 不愿献身科学, 不再以学术研究为荣, 聪明拔尖的学生都去学金融、法律等赚钱的专业; 而美国人因为认识到其硬能力(例如数学)不行, 进行教育改革, 20年后, 不但保持了其软实力即非专业能力的优势, 而且在硬能力上赶上中国人.‖“正在丢失的硬实力”, 鲁鸣, 《青年文摘》2011年第5期动向：美国很多州新办STEM高中, 一些大学开始开设STEM课程等.STEM = Science + Technology + Engineering + Mathematics2012年2月7日公布的美国总统科技顾问委员会给总统的报告，参与超越：培养额外的100万具有科学、技术、工程和数学学位的大学生(Engage to Excel: Producing One Million Additional College Graduates with Degrees in Science, Technology, Engineering, and Mathematics)The Mathematical Sciences in 2025, the National Academies Press, 2013人们使用的数学科学思想、概念和方法的范围在不断扩大的同时，数学科学的用途也在不断扩展. 21世纪的大部分科学与工程将建立在数学科学的基础上.This major expansion in the uses of the mathematical sciences has been paralleled by a broadening in the range of mathematical science ideas and techniques being used. Much of twenty-first century science and engineering is going to be built on a mathematical science foundation, and that foundation must continue to evolve and expand.数学科学是日常生活的几乎每个方面的组成部分.互联网搜索、医疗成像、电脑动画、数值天气预报和其他计算机模拟、所有类型的数字通信、商业和军事中的优化问题以及金融风险的分析——普通公民都从支撑这些应用功能的数学科学的各种进展中获益，这样的例子不胜枚举.The mathematical sciences are part of almost every aspect of everyday life. Internet search, medical imaging, computer animation, numerical weather predictions and othercomputer simulations, digital communications of all types, optimization in business and the military, analyses of financial risks —average citizens all benefit from the mathematical science advances that underpin these capabilities, and the list goes on and on.调查发现:数学科学研究工作正日益成为生物学、医学、社会科学、商业、先进设计、气候、金融、先进材料等许多研究领域不可或缺的重要组成部分. 这种研究工作涉及最广泛意义下数学、统计学和计算综合，以及这些领域与潜在应用领域的相互作用. 所有这些活动对于经济增长、国家竞争力和国家安全都是至关重要的，而且这种事实应该对作为整体的数学科学的资助性质和资助规模产生影响. 数学科学的教育也应该反映数学科学领域的新的状况.Finding: Mathematical sciences work is becoming an increasingly integral and essential component of a growing array of areas of investigation in biology, medicine, social sciences, business, advanced design, climate, finance, advanced materials, and many more. This work involves the integration of mathematics, statistics, and computation in the broadest sense and the interplay of these areas withareas of potential application. All of these activities are crucial to economic growth, national competitiveness, and national security, and this fact should inform both the nature and scale of funding for the mathematical sciences as a whole. Education in the mathematical sciences should also reflect this new stature of the field.****************************************************************为了以下讲述的方便, 我们先来了解一下什么是数学建模.数学模型(Mathematical Model)是用数学符号对一类实际问题或实际发生的现象的(近似的)描述.数学建模(Mathematical Modeling)则是获得该模型并对之求解、验证并得到结论的全过程.数学建模不仅是了解基本规律, 而且从应用的观点来看更重要的是预测和控制所建模的系统的行为的强有力的工具.数学建模是数学用来解决各种实际问题的桥梁.↑→→→→→→→→↓↑↓↑↓↓↑↓←←←←←通不过↓↓通过)定义：数学建模就是上述框图多次执行的过程数学建模的难点观察、分析实际问题, 作出合理的假设, 明确变量和参数, 形成明确的数学问题. 不仅仅是翻译的问题; 涉及的数学问题可能是复杂、困难的, 求解也许涉及深刻的数学方法. 如何作出正确的判断, 寻找合适、简洁的(解析或近似) 解法; 如何验证模型.简言之:合理假设、模型建立、模型求解、解释验证.记住这16个字, 将会终生受用.数学建模的重要作用：源头创新当然数学建模也有局限性, 不能单独包打天下, 因为实际问题是非常复杂的, 需要多学科协同解决.在图灵(A. M. Turing)的文章: The Chemical Basis of Morphogenesis (形态生成的化学基础), Philosophical Transactions of the Royal Society of London (伦敦皇家学会哲学公报), Series B (Biological Sciences),v.237(1952), 37-72.1. 一个胚胎的模型. 成形素本节将描述一个正在生长的胚胎的数学模型. 该模型是一种简化和理想化, 因此是对原问题的篡改. 希望本文论述中保留的一些特征, 就现今的知识状况而言, 是那些最重要的特征.1. A model of the embryo. MorphogensIn this section a mathematical model of the growing embryo will be described. This model will be asimplification and an idealization, and consequently a falsification. It is to be hoped that the features retained for discussion are those of greatest importance in the present state of knowledge.想单靠数学建模本身来解决重大的生物学问题是不可能的，另一方面，想仅仅依靠实验来获得对生物学的合理、完整的理解也是极不可能的. There is no way mathematical modeling can solve major biological problems on its own. On the other hand, it ishighly unlikely that even a reasonably complete understanding could come solely from experiment.—— J. D. Murray, Why Are There No 3-Headed Monsters? Mathematical Modeling in Biology, Notices of the AMS,v. 59 (2012), no. 6, p.793.自古以来公平、公正的竞赛都是培养、选拔人才的重要手段, 科学和数学也不例外.中学生IMO (国际数学奥林匹克(International Mathematical Olympiad), 1959 ～)北美的大学生Putnbam数学竞赛(1938 ～)全国大学生数学竞赛(2010 ～)Mathematical Contest in Modeling (MCM, 1985 ～)美国大学生数学建模竞赛Interdisciplinary Contest in Modeling (ICM, 1999～)美国大学生跨学科建模竞赛China Undergraduate Mathematical Contest in Modeling (CUMCM, 1992～) 中国大学生数学建模竞赛中国大学生参加美国大学生数学建模竞赛情况中国大学生数学建模竞赛情况在以下讲述中涉及物理方面的具体的数学模型 (问题)的叙述和初步讨论可参考《物理学与偏微分方程》, 李大潜、秦铁虎编著, (上册, 1997; 下册, 2000), 高等教育出版社.Seven equations that rule your world (主宰你生活的七个方程式), by Ian Stewart, NewScientist, 13 February 2012.Fourier transformation 2ˆ()()ix f f x e dx πξξ∞--∞=⎰Wave equation 22222u u c t x ∂∂=∂∂ Ma xwell‘s equation110, , 0, H E E E H H c t c t∂∂∇⋅=∇⨯=-∇⋅=∇⨯=∂∂Schrödinger‘s equation ˆψH ψi t∂=∂Ian Stewart, In Pursuit of the Unknown:17 Equations That Changed the World (追求对未知的认识：改变世界的17个方程), Basic Books, March 13, 2012.目录(Contents)Why Equations? /viii1. The squaw on the hippopotamus ——Pythagoras‘sTheorem/12. Shortening the proceedings —— Logarithms/213. Ghosts of departed quantities —— Calculus/354. The system of the world ——Newton‘s Law ofGravity/535. Portent of the ideal world —— The Square Root ofMinus One/736. Much ado about knotting ——Euler‘s Formula forPolyhedra/837. Patterns of chance —— Normal Distribution/1078. Good vibrations —— Wave Equation/1319. Ripples and blips —— Fourier Transform/14910. The ascent of humanity —— Navier-StokesEquation/16511. Wave in the ether ——Maxwell‘s Equations/17912. Law and disorder —— Second Law ofThermodynamics /19513. One thing is absolute —— Relativity/21714. Quantum weirdness —— Schrödinger Equation/24515. Codes, communications, and computers ——Information Theory/26516. The imbalance of nature —— Chaos Theory/28317. The Midas formula —— Black-Scholes Equation/195Where Next?/317Notes/321Illustration Credits/330Index/331相对论Albert Einstein(1879, 3, 14 ～1955, 4, 18)20世纪最伟大的科学成就莫过于Einstein(爱因斯坦)的狭义和广义相对论了, 但是如果没有Minkowski (闵可夫斯基)几何、Riemann(黎曼)于1854年发明的Riemann几何, 以及Cayley(凯莱), Sylvester(西勒维斯特)和Noether(诺特)等数学家发展的不变量理论, Einstein的广义相对论和引力理论就不可能有如此完善的数学表述. Einstein自己也不止一次地说过.早在1905年, 年仅26岁的爱因斯坦就已提出了狭义相对论. 狭义相对论推倒了牛顿力学的质量守恒、能量守恒、质量能量互不相关、时空永恒不变的基本命题. 这是一场真正的科学革命.为了导出狭义相对论，爱因斯坦作出了两个假设：运动的相对性(所有匀速运动都是相对的)和光速为常数(光的运动例外, 它是绝对的). (1)狭义相对性原理,即在所有惯性系中, 物理学定律具有相同的数学表达形式;(2)光速不变原理,真空中光沿各个方向传播的速率都相等，与光源和观察者的运动状态无关.时空不是绝对独立的.由此可以导出一些推论: 相对论坐标变换式和速度变换式, 同时的相对性, 钟慢尺缩效应和质能关系式等.他的好友物理学家P.Ehrenfest指出实际上还蕴涵着第三个假设, 即这两个假设是不矛盾的. 物体运动的相对性和光速的绝对性, 两者之间的相互制约和作用乃是相对论里一切我们不熟悉的时空特征的根源.(部分参阅李新洲:《寻找自然之律--- 20世纪物理学革命》, 上海科技教育出版社, 2001.)1907 年德国数学家H. Minkowski (1864 ～1909) 提出了―Minkowski 空间‖,即把时间和空间融合在一起的四维空间1,3R. Minkowski 几何为Einstein 狭义相对论提供了合适的数学模型.“没有任何客观合理的方法能够把四维连续统分离成三维空间连续统和一维时间连续统. 因此从逻辑上讲, 在四维时空连续统(space- time continuum)中表述自然定律会更令人满意. 相对论在方法上的巨大进步正是建立在这个基础之上的, 这种进步归功于闵可夫斯基(Minkowski).”—Albert Einstein, The Meaning of Relativity, 1922, Princeton University Press. 中译本, 阿尔伯特·爱因斯坦著, 相对论的意义, (普林斯顿科学文库(Princeton Science Library) 1), 郝建纲、刘道军译, 上海科技教育出版社, 2001, p. 27.有了Minkowski 时空模型后, Einstein 又进一步研究引力场理论以建立广义相对论. 1912 年夏他已经概括出新的引力理论的基本物理原理, 但是为了实现广义相对论的目标, 还必须寻求理论的数学结构, Einstein 为此花了 3 年的时间, 最后, 在数学家M. Grossmann 的介绍下学习掌握了发展相对论引力学说所必需的数学工具—以Riemann几何和Ricci, Levi - Civita的绝对微分学, 也就是Einstein 后来所称的张量分析.“根据前面的讨论, 很显然, 如果要表达广义相对论, 就需要对不变量理论以及张量理论加以推广. 这就产生了一个问题, 即要求方程的形式必须对于任意的点变换都是协变的. 在相对论产生以前很久, 数学家们就已经建立了推广的张量演算理论. 黎曼(Riemann)首先把高斯(Gauss)的思路推广到了任意维连续统, 他很有预见性地看到了……进行这种推广的物理意义. 随后, 这个理论以张量微积分的形式得到了发展, 对此里奇(Ricci)和莱维·齐维塔(Tulio Levi-Civita, 1873～1941)做出了重要贡献. ”—阿尔伯特·爱因斯坦著, 相对论的意义, 郝建纲、刘道军译, 上海科技教育出版社, 2001, p. 57.从数学建模的角度看, 广义相对论讨论的中心问题是引力理论, 其基础是以下两个假设: 1. (等效原理)惯性力场与引力场的动力学效应是局部不可分辨的，(或说引力和非惯性系中的惯性力等效)；2. (广义相对性原理) 一切参考系都是平权的，换言之，客观的真实的物理规律应该在任意坐标变换下形式不变——广义协变性(即一切物理定律在所有参考系[无论是惯性的或非惯性的]中都具有相同的形式)。

星系团Abell 2199的恒星形成性质

第49卷第3期2008年7月天文学报

ACTAASTRoNoMICASINICAV01．49N0．3

Jul．，2008

星系团Abell21

99的恒星形成性质*

袁启荣1+何莹莹1李峰2张立1赵丽芳3(1南京师范大学物理科学与技术学院南京z10097)(2江苏工业学院信息科学系常州213164)

(3南京信息职业技术学院微电子系南京210046)

摘要通过对近邻星系团Abell2199中290颗成员星系进行形态分类，研究这些星系

的恒星形成率及其与形态和相关物理特性之间的关系．该星系团中星系的特征恒星形成率与Ha等值宽度、星系光谱在4000A处的跃变程度以及星系所包含的恒星质量之间有较强的相关性．这些星系的恒星形成活动没有表现出明显的环境效应，表明该星系团仍处在剧烈的动力学演化阶段，远没有达到动力学平衡．

关键词星系：星系团：个别，星系：基本参数，星系：运动学与动力学中图分类号：P157．8；文献标识码：A

1引言研究星系的恒星形成性质已成为近十年来河外天体物理学最热门的研究领域之一．探索星系团中成员星系的恒星形成性质及其与星系形态、环境以及其他一些星系物理特性之间的关系，有助于我们了解星系的形成和演化，从而了解整个宇宙的形成和演化的历史[1-3]．恒星形成率(StarFomationRate：SFR)是表征星系中恒星形成活动的重要物理参量，可以通过测量星系在光学波段的发射线(Hn和[OII])或者紫外、远红外、射电等波段的光度来获得[3．4|．影响星系的恒星形成率的因素很多，包括星系的形态、光度、质量、环境以及星系间的相互作用和合并等等[3]．以往的研究表明，晚型星系的恒星形成要比早型星系活跃，场星系比团星系的恒星形成率高，小质量星系比大质量星系的恒星形成率高[3]．根据宇宙大尺度结构的等级成团理论，星系团是随着时间不断吸积周围场星系而形成的，当场星系进入一个致密环境(如星系团)中，它们的恒星形成活动就会受到多种物理机制的制约而慢慢衰竭，如星系之间的引力相互作用[4]、星系的气体／尘埃盘被剥离等[5]．有迹象表明，在一些高红移富星系团中，星系的恒星形成活动也受到抑制[6]．要清楚地了解抑制星系中恒星形成活动的各种机制，需要对不同环境中不同形态的星系样本进行多方面的研究．近年来，SloanDigitalSkySurvey(SDss)的数据释放为研究星系的恒星形成活动

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arXiv:astro-ph/0405097v1 5 May 2004Mon.Not.R.Astron.Soc.000,000–000(0000)Printed2February2008(MNLATEXstyleﬁlev1.4)MorphologyandEvolutioninGalaxyClustersI:SimulatedClustersintheAdiabaticlimitandwithRadiativeCooling

NururRahman1,SergeiF.Shandarin1,PatrickM.Motl2,andAdrianL.Melott11DepartmentofPhysicsandAstronomy,UniversityofKansas,Lawrence,KS66045,USA;

2CenterforAstrophysicsandSpaceAstronomy,UniversityofColorado,Boulder,CO80309,USA;

nurur@kusmos.phsx.ukans.edu,sergei@ku.edu,motl@casa.colorado.edu,melott@kusmos.phsx.ukans.edu

ABSTRACTWehavestudiedmorphologicalevolutioninclusterssimulatedintheadiabaticlimitandwithradiativecooling.Clustermorphologyintheredshiftrange,0isquantiﬁedbymultiplicityandellipticity.Intermsofellipticity,ourresultindicatesslowevolutioninclustershapescomparedtothoseobservedintheX-rayandopticalwavelengths.TheresultisconsistentwithFloor,Melott&Motl(2003).Intermsofmultiplicity,however,theresultindicaterelativelystrongerevolution(comparedtoellipticitybutstillweakerthanobservation)inthestructureofsimulatedclusterssuggestingthatforcomparativestudiesofsimulationandobservation,sub-structuremeasuresaremoresensitivethantheshapemeasures.Wehighlightafewpossibilitiesresponsibleforthediscrepancyintheshapeevolutionofsimulatedandrealclusters.

Keywords:clusters:morphology-clusters:structure-clusters:evolution-clusters:statistics

1INTRODUCTIONThehierarchicalclusteringisthemostpopularmodelfortheLargeScaleStructure(LSS)formation.Themodelrelysontheassumptionthatthelargerclumpsofmatterdistri-butionsresultduetothemergingofsmallersub-clumpsincosmologicaltime.Structuralevolutionincosmologicalsys-temssuchasgalaxiesandclustersofgalaxiesisthereforetheunderlyingprincipleinthisscenario.

Melott,Chambers&Miller(2001;hereafterMCM)hasreportedevolutioninthegrossmorphologyofgalaxy-clusters(quantiﬁedbyellipticity)foravarietyofopticalandX-raysamplesovertheredshift,z<0.1.Theyinferthattheevidenceisconsistentwithlowmatterdensityuniverse.Us-ingellipticityaswellasintraclustermediumtemperatureandX-rayluminosity,Plionis(2002)haspresentedevidencefortherecentevolutioninopticalandX-rayclusterofgalax-iesforredshift,z≤0.18.Inbothstudiesevolutionisquan-tiﬁedbythechangeofclusterellipticitywithredshift.Inarecentstudy,Jeltemaetal.(2003)havereportedstructuralevolutionofclusterswithredshiftwhereclustermorphologyisquantiﬁedbypowerratiomethod(Buote&Tsai1995).Theauthorsusedasampleof40X-rayclustersovertheredshiftrange0.1−0.8obtainedfromChandraObserva-tory.Theresultsofthesepreviousstudies,althougheachoneemployeddiﬀerenttechniquesintheiranalyses,indicateevolutioninthemorphologyofthelargestgravitationallyboundsystemsoverawiderangeoflook-backtime.

Theobservationalevidencespromptedconcernsonthe

formationandevolutionofstructuresinnumericalsimu-lations.Iftheresultsofsimulationsgiveusfaithfulrepre-sentationsoftheevolutionaryhistoryofcosmologicalob-jectsthanonewouldexpectasimilartrendinthestruc-tureofsimulatedobjects.Sofaralmostallstudiesofsim-ulatedclustersarefocusedonunderstandingthenatureofthebackgroundcosmologywithinwhichthepresentuniverseisevolving(Jingetal.1995;Crone,Evrard&Richstone1996;Buote&Xu1997;Valdarnini,Ghizzardi&Bonometto1999).Untilrecentlyacomparativestudyofmorphologi-calevolutioninthesimulatedandrealclusterswasabsent.Flooretal.(2003)andFloor,Melott&Motl(2003;here-afterFMM)haveinvestigatedevolutioninclustersmorphol-ogysimulatedwithdiﬀerentinitialconditions,backgroundcosmology,anddiﬀerentphysics(e.g.,simulationwithandwithoutradiativecooling).Theyhaveusedeccentricityasaprobetoquantifyevolution.Theirstudies,emphasizingonmeasuringshapesintheouterregionsofclusters,suggestslowevolutioninsimulatedclustershapescomparedtotheobservedclusters.Inthispaperwestudyevolutioninsimulatedclustersinﬂatcolddarkmatteruniverse(ΛCDM;Ωm=0.3,Ωλ=0.7)byusinghighresolutionsimulations(Motletal.2003).Weusetwodatasets:theﬁrstsethaveclusterssimulatedintheadiabaticlimitandtheothersetcontainsclusterssimulatedwithradiativecooling.EachsamplecontainX-rayanddarkmatterdistributionsandhasbeenanalyzedatfourdiﬀerentredshifts,z=0.0,0.10,0.25,and0.50.Thisistheﬁrstinaseriesofpapersaimedtostudythe

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