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Institution

Tokyo Institute of Technology

EducationTokyo, Tôkyô, Japan
About: Tokyo Institute of Technology is a education organization based out in Tokyo, Tôkyô, Japan. It is known for research contribution in the topics: Catalysis & Thin film. The organization has 46775 authors who have published 101656 publications receiving 2357893 citations. The organization is also known as: Tokyo Tech & Tokodai.


Papers
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Journal ArticleDOI
TL;DR: In this article, a novel feed structure was proposed to excite a plane TEM wave in a parallel-plate waveguide, which is composed of densely arrayed posts on the same layer as the parallel plate.
Abstract: The authors propose a novel feed structure to excite a plane TEM wave in a parallel-plate waveguide. The feed waveguide is composed of densely arrayed posts on the same layer as the parallel plate. The posts can be easily fabricated at low cost by making metalized via holes in a grounded dielectric substrate. Such a procedure results in a quite simple fabrication of the antenna. The feed waveguide is designed to obtain a uniform division, which is confirmed by measurements on a 40-GHz band model.

568 citations

Journal ArticleDOI
01 Jun 1989
TL;DR: The authors develop a control method for space manipulators based on the resolved motion control concept that is widely applicable in solving not only free-flying manipulation problems but also attitude-control problems.
Abstract: The authors establish a control method for space manipulators taking dynamical interaction between the manipulator arm and the base satellite into account. The kinematics of free-flying multibody systems is investigated by introducing the momentum conservation law into the formulation and a novel Jacobian matrix in generalized form for space robotic arms is derived. The authors develop a control method for space manipulators based on the resolved motion control concept. The proposed method is widely applicable in solving not only free-flying manipulation problems but also attitude-control problems. The validity of the method is demonstrated by computer simulations with a realistic model of a robot satellite. >

568 citations

Journal ArticleDOI
S. Fukuda1, Y. Fukuda1, M. Ishitsuka1, Yoshitaka Itow1, Takaaki Kajita1, J. Kameda1, K. Kaneyuki1, K. Kobayashi1, Yusuke Koshio1, M. Miura1, S. Moriyama1, Masayuki Nakahata1, S. Nakayama1, Y. Obayashi1, A. Okada1, Ko Okumura1, N. Sakurai1, Masato Shiozawa1, Yoshihiro Suzuki1, H. Takeuchi1, Y. Takeuchi1, T. Toshito1, Y. Totsuka1, Shoichi Yamada1, M. Earl2, Alec Habig3, Alec Habig2, E. Kearns2, M. D. Messier2, Kate Scholberg2, J. L. Stone2, L. R. Sulak2, C. W. Walter2, M. Goldhaber4, T. Barszczak5, David William Casper5, W. Gajewski5, W. R. Kropp5, S. Mine5, L. R. Price5, M. B. Smy5, Henry W. Sobel5, M. R. Vagins5, K. S. Ganezer6, W. E. Keig6, R. W. Ellsworth7, S. Tasaka8, A. Kibayashi9, John G. Learned9, S. Matsuno9, D. Takemori9, Y. Hayato, T. Ishii, Takashi Kobayashi, Koji Nakamura, Y. Oyama, A. Sakai, Makoto Sakuda, Osamu Sasaki, M. Kohama10, Atsumu Suzuki10, T. Inagaki11, K. Nishikawa11, Todd Haines12, Todd Haines5, E. Blaufuss13, B. K. Kim13, R. Sanford13, R. Svoboda13, M. L. Chen14, J. A. Goodman14, G. Guillian14, G. W. Sullivan14, J. Hill15, C. K. Jung15, K. Martens15, Magdalena Malek15, C. Mauger15, C. McGrew15, E. Sharkey15, B. Viren15, C. Yanagisawa15, M. Kirisawa16, S. Inaba16, C. Mitsuda16, K. Miyano16, H. Okazawa16, C. Saji16, M. Takahashi16, M. Takahata16, Y. Nagashima17, K. Nitta17, M. Takita17, Minoru Yoshida17, Soo-Bong Kim18, T. Ishizuka19, M. Etoh20, Y. Gando20, Takehisa Hasegawa20, Kunio Inoue20, K. Ishihara20, T. Maruyama20, J. Shirai20, A. Suzuki20, Masatoshi Koshiba1, Y. Hatakeyama21, Y. Ichikawa21, M. Koike21, Kyoshi Nishijima21, H. Fujiyasu22, Hirokazu Ishino22, M. Morii22, Y. Watanabe22, U. Golebiewska23, D. Kielczewska23, D. Kielczewska5, S. C. Boyd24, A. L. Stachyra24, R. J. Wilkes24, K. K. Young24 
TL;DR: Using data recorded in 1100 live days of the Super-Kamiokande detector, three complementary data samples are used to study the difference in zenith angle distribution due to neutral currents and matter effects and find no evidence favoring sterile neutrinos, and reject the hypothesis at the 99% confidence level.
Abstract: The previously published atmospheric neutrino data did not distinguish whether muon neutrinos were oscillating into tau neutrinos or sterile neutrinos, as both hypotheses fit the data. Using data recorded in 1100 live days of the Super-Kamiokande detector, we use three complementary data samples to study the difference in zenith angle distribution due to neutral currents and matter effects. We find no evidence favoring sterile neutrinos, and reject the hypothesis at the $99%$ confidence level. On the other hand, we find that oscillation between muon and tau neutrinos suffices to explain all the results in hand.

568 citations

Journal ArticleDOI
TL;DR: The Database of Disordered Protein Prediction (D2P2) will increase the understanding of the interplay between disorder and structure, the genomic distribution of disorder, and its evolutionary history.
Abstract: We present the Database of Disordered Protein Prediction (D2P2), available at http://d2p2.pro (including website source code). A battery of disorder predictors and their variants, VL-XT, VSL2b, PrDOS, PV2, Espritz and IUPred, were run on all protein sequences from 1765 complete proteomes (to be updated as more genomes are completed). Integrated with these results are all of the predicted (mostly structured) SCOP domains using the SUPERFAMILY predictor. These disorder/structure annotations together enable comparison of the disorder predictors with each other and examination of the overlap between disordered predictions and SCOP domains on a large scale. D2P2 will increase our understanding of the interplay between disorder and structure, the genomic distribution of disorder, and its evolutionary history. The parsed data are made available in a unified format for download as flat files or SQL tables either by genome, by predictor, or for the complete set. An interactive website provides a graphical view of each protein annotated with the SCOP domains and disordered regions from all predictors overlaid (or shown as a consensus). There are statistics and tools for browsing and comparing genomes and their disorder within the context of their position on the tree of life. © The Author(s) 2012. Published by Oxford University Press.

567 citations

Journal ArticleDOI
Ayuko Hoshino1, Ayuko Hoshino2, Han Sang Kim1, Han Sang Kim3, Linda Bojmar4, Linda Bojmar5, Linda Bojmar1, Kofi Ennu Gyan1, Michele Cioffi1, Jonathan M. Hernandez6, Jonathan M. Hernandez1, Jonathan M. Hernandez7, Constantinos P. Zambirinis6, Constantinos P. Zambirinis1, Gonçalo Rodrigues8, Gonçalo Rodrigues1, Henrik Molina9, Søren Heissel9, Milica Tesic Mark9, Loïc Steiner10, Loïc Steiner1, Alberto Benito-Martin1, Serena Lucotti1, Angela Di Giannatale1, Katharine Offer1, Miho Nakajima1, Caitlin Williams1, Laura Nogués11, Laura Nogués1, Fanny A. Pelissier Vatter1, Ayako Hashimoto2, Ayako Hashimoto1, Ayako Hashimoto12, Alexander E. Davies13, Daniela Freitas8, Daniela Freitas1, Candia M. Kenific1, Yonathan Ararso1, Weston Buehring1, Pernille Lauritzen1, Yusuke Ogitani1, Kei Sugiura12, Kei Sugiura2, Naoko Takahashi2, Maša Alečković14, Kayleen A. Bailey1, Joshua S. Jolissant1, Joshua S. Jolissant6, Huajuan Wang1, Ashton Harris1, L. Miles Schaeffer1, Guillermo García-Santos15, Guillermo García-Santos1, Zoe Posner1, Vinod P. Balachandran6, Yasmin Khakoo6, G. Praveen Raju16, Avigdor Scherz17, Irit Sagi17, Ruth Scherz-Shouval17, Yosef Yarden17, Moshe Oren17, Mahathi Malladi6, Mary Petriccione6, Kevin C. De Braganca6, Maria Donzelli6, Cheryl Fischer6, Stephanie Vitolano6, Geraldine P. Wright6, Lee Ganshaw6, Mariel Marrano6, Amina Ahmed6, Joe DeStefano6, Enrico Danzer6, Michael H.A. Roehrl6, Norman J. Lacayo18, Theresa C. Vincent5, Theresa C. Vincent19, Martin R. Weiser6, Mary S. Brady6, Paul A. Meyers6, Leonard H. Wexler6, Srikanth R. Ambati6, Alexander J. Chou6, Emily K. Slotkin6, Shakeel Modak6, Stephen S. Roberts6, Ellen M. Basu6, Daniel Diolaiti19, Benjamin A. Krantz19, Benjamin A. Krantz6, Fatima Cardoso20, Amber L. Simpson6, Michael F. Berger6, Charles M. Rudin6, Diane M. Simeone19, Maneesh Jain21, Cyrus M. Ghajar22, Surinder K. Batra21, Ben Z. Stanger23, Jack D. Bui24, Kristy A. Brown1, Vinagolu K. Rajasekhar6, John H. Healey6, Maria de Sousa1, Maria de Sousa8, Kim Kramer6, Sujit Sheth1, Jeanine Baisch1, Virginia Pascual1, Todd E. Heaton6, Michael P. La Quaglia6, David J. Pisapia1, Robert E. Schwartz1, Haiying Zhang1, Yuan Liu6, Arti Shukla25, Laurence Blavier26, Yves A. DeClerck26, Mark A. LaBarge27, Mina J. Bissell28, Thomas C. Caffrey21, Paul M. Grandgenett21, Michael A. Hollingsworth21, Jacqueline Bromberg6, Jacqueline Bromberg1, Bruno Costa-Silva20, Héctor Peinado11, Yibin Kang14, Benjamin A. Garcia23, Eileen M. O'Reilly6, David P. Kelsen6, Tanya M. Trippett6, David R. Jones6, Irina Matei1, William R. Jarnagin6, David Lyden1 
20 Aug 2020-Cell
TL;DR: EVP proteins can serve as reliable biomarkers for cancer detection and determining cancer type, and a panel of tumor-type-specific EVP proteins in TEs and plasma are defined, which can classify tumors of unknown primary origin.

565 citations


Authors

Showing all 46967 results

NameH-indexPapersCitations
Matthew Meyerson194553243726
Yury Gogotsi171956144520
Masayuki Yamamoto1711576123028
H. Eugene Stanley1541190122321
Takashi Taniguchi1522141110658
Shu-Hong Yu14479970853
Kazunori Kataoka13890870412
Osamu Jinnouchi13588586104
Hector F. DeLuca133130369395
Shlomo Havlin131101383347
Hiroyuki Iwasaki131100982739
Kazunari Domen13090877964
Hideo Hosono1281549100279
Hideyuki Okano128116967148
Andreas Strasser12850966903
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202388
2022358
20213,457
20203,695
20193,783
20183,531