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Institution

Waseda University

EducationTokyo, Japan
About: Waseda University is a education organization based out in Tokyo, Japan. It is known for research contribution in the topics: Catalysis & Large Hadron Collider. The organization has 24220 authors who have published 46859 publications receiving 837855 citations. The organization is also known as: Waseda daigaku & Sōdai.


Papers
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Journal ArticleDOI
Georges Aad1, Brad Abbott2, Jalal Abdallah3, S. Abdel Khalek4  +2870 moreInstitutions (169)
TL;DR: The performance of the ATLAS muon reconstruction during the LHC run withpp collisions at s=7–8 TeV in 2011–2012 is presented, focusing mainly on data collected in 2012.
Abstract: This paper presents the performance of the ATLAS muon reconstruction during the LHC run with pp collisions at root s = 7-8 TeV in 2011-2012, focusing mainly on data collected in 2012. Measurements ...

305 citations

Journal ArticleDOI
TL;DR: An overview of the identification, pathology, diagnosis and virulence factors of E. tarda in fish is provided, and recent strategies for developing vaccines against edwardsiellosis are described.
Abstract: Edwardsiella tarda is one of the serious fish pathogens, infecting both cultured and wild fish species. Research on edwardsiellosis has revealed that E. tarda has a broad host range and geographic distribution, and contains important virulence factors that enhance bacterial survival and pathogenesis in hosts. Although recent progress in edwardsiellosis research has enabled the development of numerous, highly effective vaccine candidates, these efforts have not been translated into a commercialized vaccine. The present review aims to provide an overview of the identification, pathology, diagnosis and virulence factors of E. tarda in fish, and describe recent strategies for developing vaccines against edwardsiellosis. The hope is that this presentation will be useful not only from the standpoint of understanding the pathogenesis of E. tarda, but also from the perspective of facilitating the development of effective vaccines.

303 citations

Journal ArticleDOI
01 Sep 2008-ReCALL
TL;DR: The results are discussed in terms of the readiness of learners to undertake mobile-based language learning activities, and the issues having an effect on the establishment of the mobile phone as a language learning tool.
Abstract: While the use of mobile devices for language learning has sparked the interest of an increasing number of researchers in recent years (e.g., Aizawa & Kiernan, 2003; Thornton & Houser, 2005), our knowledge of learners' preferences for the mobile platform and their usage patterns remains limited. Are learners prepared to use mobile phones for performing language learning activities, or is there still a preference for desktop computer environments? Do learners make attempts to use mobile phones and then opt for a desktop computer instead? When and where do those learners who choose to use mobile phones use them, and why do they choose them? The current study investigated 75 learners of English at a Japanese university who were assigned vocabulary learning activities which they could choose to complete on either a mobile phone or desktop computer. It sought to determine their intentions to use mobile phones for language learning if other options were available, to compare this with their actual usage patterns, and to determine when and why learners used mobile phones. Learner attitudes and preferences were elicited through a post-survey, and usage patterns were determined through analysis of detailed server logs. The results are discussed in terms of the readiness of learners to undertake mobile-based language learning activities, and the issues having an effect on the establishment of the mobile phone as a language learning tool.

302 citations

Journal ArticleDOI
A. A. Abdo1, A. A. Abdo2, Markus Ackermann3, Marco Ajello3  +189 moreInstitutions (37)
TL;DR: In this paper, the Fermi Large Area Telescope (LAT) was used to detect a source positionally coincident with the young supernova remnant (SNR) RX J1713.7-3946.
Abstract: We present observations of the young Supernova remnant (SNR) RX J1713.7-3946 with the Fermi Large Area Telescope (LAT). We clearly detect a source positionally coincident with the SNR. The source is extended with a best-fit extension of 0.55$^{\circ} \pm 0.04^{\circ}$ matching the size of the non-thermal X-ray and TeV gamma-ray emission from the remnant. The positional coincidence and the matching extended emission allows us to identify the LAT source with the supernova remnant RX J1713.7-3946. The spectrum of the source can be described by a very hard power-law with a photon index of $\Gamma = 1.5 \pm 0.1$ that coincides in normalization with the steeper H.E.S.S.-detected gamma-ray spectrum at higher energies. The broadband gamma-ray emission is consistent with a leptonic origin as the dominant mechanism for the gamma-ray emission.

302 citations

Journal ArticleDOI
Georges Aad1, T. Abajyan2, Brad Abbott3, Jalal Abdallah4  +2885 moreInstitutions (169)
TL;DR: In this article, the electron reconstruction and identification efficiencies of the ATLAS detector at the LHC have been evaluated using proton-proton collision data collected in 2011 at TeV and corresponding to an integrated luminosity of 4.7 fb.
Abstract: Many of the interesting physics processes to be measured at the LHC have a signature involving one or more isolated electrons. The electron reconstruction and identification efficiencies of the ATLAS detector at the LHC have been evaluated using proton-proton collision data collected in 2011 at TeV and corresponding to an integrated luminosity of 4.7 fb. Tag-and-probe methods using events with leptonic decays of and bosons and mesons are employed to benchmark these performance parameters. The combination of all measurements results in identification efficiencies determined with an accuracy at the few per mil level for electron transverse energy greater than 30 GeV.

302 citations


Authors

Showing all 24378 results

NameH-indexPapersCitations
Yusuke Nakamura1792076160313
Yoshio Bando147123480883
Charles Maguire142119795026
Kazunori Kataoka13890870412
Senta Greene134134690697
Intae Yu134137289870
Kohei Yorita131138991177
Wei Xie128128177097
Susumu Kitagawa12580969594
Leon O. Chua12282471612
Jun Kataoka12160354274
S. Youssef12068365110
Katsuhiko Mikoshiba12086662394
Yusuke Yamauchi117100051685
Teruo Okano11747647081
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202380
2022237
20212,348
20202,467
20192,368
20182,289