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Institution

Tohoku University

EducationSendai, Japan
About: Tohoku University is a education organization based out in Sendai, Japan. It is known for research contribution in the topics: Magnetization & Population. The organization has 72116 authors who have published 170791 publications receiving 3941714 citations. The organization is also known as: Tōhoku daigaku.


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Journal ArticleDOI
TL;DR: In this paper, a two-step annealing process has been used to produce samples with large variations in structural parameters such as boundary spacing, misorientation angle and dislocation density.

492 citations

Journal ArticleDOI
Daniele S. M. Alves1, Nima Arkani-Hamed, S. Arora2, Yang Bai1, Matthew Baumgart3, Joshua Berger4, Matthew R. Buckley5, Bart Butler1, Spencer Chang6, Spencer Chang7, Hsin-Chia Cheng6, Clifford Cheung8, R. Sekhar Chivukula9, Won Sang Cho10, R. Cotta1, Mariarosaria D'Alfonso11, Sonia El Hedri1, Rouven Essig12, Jared A. Evans6, Liam Fitzpatrick13, Patrick J. Fox5, Roberto Franceschini14, Ayres Freitas15, James S. Gainer16, James S. Gainer17, Yuri Gershtein2, R. N.C. Gray2, Thomas Gregoire18, Ben Gripaios19, J.F. Gunion6, Tao Han20, Andy Haas1, P. Hansson1, JoAnne L. Hewett1, Dmitry Hits2, Jay Hubisz21, Eder Izaguirre1, Jared Kaplan1, Emanuel Katz13, Can Kilic2, Hyung Do Kim22, Ryuichiro Kitano23, Sue Ann Koay11, Pyungwon Ko24, David Krohn25, Eric Kuflik26, Ian M. Lewis20, Mariangela Lisanti27, Tao Liu11, Zhen Liu20, Ran Lu26, Markus A. Luty6, Patrick Meade12, David E. Morrissey28, Stephen Mrenna5, Mihoko M. Nojiri, Takemichi Okui29, Sanjay Padhi30, Michele Papucci31, Michael Park2, Myeonghun Park32, Maxim Perelstein4, Michael E. Peskin1, Daniel J. Phalen6, Keith Rehermann33, Vikram Rentala34, Vikram Rentala35, Tuhin S. Roy36, Joshua T. Ruderman27, Veronica Sanz37, Martin Schmaltz13, S. Schnetzer2, Philip Schuster38, Pedro Schwaller39, Pedro Schwaller16, Pedro Schwaller40, Matthew D. Schwartz25, Ariel Schwartzman1, Jing Shao21, J. Shelton41, David Shih2, Jing Shu10, Daniel Silverstein1, Elizabeth H. Simmons9, Sunil Somalwar2, Michael Spannowsky7, Christian Spethmann13, Matthew J. Strassler2, Shufang Su34, Shufang Su35, Tim M. P. Tait34, Brooks Thomas42, Scott Thomas2, Natalia Toro38, Tomer Volansky8, Jay G. Wacker1, Wolfgang Waltenberger43, Itay Yavin44, Felix Yu34, Yue Zhao2, Kathryn M. Zurek26 
TL;DR: A collection of simplified models relevant to the design of new-physics searches at the Large Hadron Collider (LHC) and the characterization of their results is presented in this paper.
Abstract: This document proposes a collection of simplified models relevant to the design of new-physics searches at the Large Hadron Collider (LHC) and the characterization of their results. Both ATLAS and CMS have already presented some results in terms of simplified models, and we encourage them to continue and expand this effort, which supplements both signature-based results and benchmark model interpretations. A simplified model is defined by an effective Lagrangian describing the interactions of a small number of new particles. Simplified models can equally well be described by a small number of masses and cross-sections. These parameters are directly related to collider physics observables, making simplified models a particularly effective framework for evaluating searches and a useful starting point for characterizing positive signals of new physics. This document serves as an official summary of the results from the 'Topologies for Early LHC Searches' workshop, held at SLAC in September of 2010, the purpose of which was to develop a set of representative models that can be used to cover all relevant phase space in experimental searches. Particular emphasis is placed on searches relevant for the first similar to 50-500 pb(-1) of data and those motivated by supersymmetric models. This note largely summarizes material posted at http://lhcnewphysics.org/, which includes simplified model definitions, Monte Carlo material, and supporting contacts within the theory community. We also comment on future developments that may be useful as more data is gathered and analyzed by the experiments.

491 citations

Journal ArticleDOI
TL;DR: Both filler morphology and filler loading influenced flexural strength, flexural modulus, hardness, and fracture toughness of contemporary composites.
Abstract: Statement of Problem Little information exists regarding the filler morphology and loading of composites with respect to their effects on selected mechanical properties and fracture toughness Purpose The objectives of this study were to: (1) classify commercial composites according to filler morphology, (2) evaluate the influence of filler morphology on filler loading, and (3) evaluate the effect of filler morphology and loading on the hardness, flexural strength, flexural modulus, and fracture toughness of contemporary composites Material and Methods Field emission scanning electron microscopy/energy dispersive spectroscopy was used to classify 3 specimens from each of 14 commercial composites into 4 groups according to filler morphology The specimens (each 5 × 25 × 15 mm) were derived from the fractured remnants after the fracture toughness test Filler weight content was determined by the standard ash method, and the volume content was calculated using the weight percentage and density of the filler and matrix components Microhardness was measured with a Vickers hardness tester, and flexural strength and modulus were measured with a universal testing machine A 3-point bending test (ASTM E-399) was used to determine the fracture toughness of each composite Data were compared with analysis of variance followed by Duncan's multiple range test, both at the P Results The composites were classified into 4 categories according to filler morphology: prepolymerized, irregular-shaped, both prepolymerized and irregular-shaped, and round particles Filler loading was influenced by filler morphology Composites containing prepolymerized filler particles had the lowest filler content (25% to 51% of filler volume), whereas composites containing round particles had the highest filler content (59% to 60% of filler volume) The mechanical properties of the composites were related to their filler content Composites with the highest filler by volume exhibited the highest flexural strength (120 to 129 MPa), flexural modulus (12 to 15 GPa), and hardness (101 to 117 VHN) Fracture toughness was also affected by filler volume, but maximum toughness was found at a threshold level of approximately 55% filler volume Conclusion Within the limitations of this study, the commercial composites tested could be classified by their filler morphology This property influenced filler loading Both filler morphology and filler loading influenced flexural strength, flexural modulus, hardness, and fracture toughness (J Prosthet Dent 2002;87:642-9)

490 citations

Journal ArticleDOI
TL;DR: Directional selectivity was found in all the cue, preparatory, and movement-related responses in the supplementary motor area and the rostral part of macaque monkey.
Abstract: 1. The rostromesial agranular frontal cortex of macaque monkey (Macaca fuscata), traditionally defined as the supplementary motor area (SMA), was studied using various physiological techniques to d...

490 citations

Journal ArticleDOI
21 May 2004-Science
TL;DR: Size-dependent development of the hydrogen bond network structure in largesized clusters of protonated water, H+(H2O)n, was probed by infrared spectroscopy of OH stretches by demonstrating that the chain structures at small sizes develop into two-dimensional net structures and then into nanometer-scaled cages.
Abstract: Size-dependent development of the hydrogen bond network structure in largesized clusters of protonated water, H+(H2O)n (n = 4 to 27), was probed by infrared spectroscopy of OH stretches. Spectral changes with cluster size demonstrate that the chain structures at small sizes (n ≲ 10) develop into two-dimensional net structures (∼10

489 citations


Authors

Showing all 72477 results

NameH-indexPapersCitations
John Q. Trojanowski2261467213948
Aaron R. Folsom1811118134044
Marc G. Caron17367499802
Masayuki Yamamoto1711576123028
Kenji Watanabe1672359129337
Rodney S. Ruoff164666194902
Frederik Barkhof1541449104982
Takashi Taniguchi1522141110658
Yoshio Bando147123480883
Thomas P. Russell141101280055
Ali Khademhosseini14088776430
Marco Colonna13951271166
David H. Barlow13378672730
Lin Gu13086856157
Yoichiro Iwakura12970564041
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023162
2022754
20216,412
20206,426
20196,076
20185,898