Institution
Waseda University
Education•Tokyo, 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.
Topics: Catalysis, Large Hadron Collider, Robot, Computer science, Population
Papers published on a yearly basis
Papers
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TL;DR: The results for the 1986 survey are compared in this paper, showing that the Japanese are clearly ahead in the trade-off between flexibility and cost efficiency, while the European and North Americans are not yet seizing the opportunity to cut costs through rapid production and design changes, and are focusing more on traditional cost reduction programmes and the improvement of quality.
Abstract: Over the past 4 years research teams from INSEAD (Fontainebleau), Boston University and Waseda University (Tokyo) have administered a yearly survey on the manufacturing strategy of the large manufacturers of the three industrialized regions of the world In this paper the results for the 1986 survey are compared One of the most striking results of that year's survey is the emphasis some of the more advanced manufacturers put on their efforts to overcome the trade-off between flexibility and cost efficiency In particular for the Japanese respondents these attempts become clear Europeans and North Americans are not yet seizing the opportunity to cut costs through rapid production and design changes, and are focusing more on traditional cost reduction programmes and the improvement of quality This might mean that they are preparing the basis on which they can built to obtain added value from flexible automation If this is the case then the Japanese are clearly ahead
464 citations
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13 Sep 2019
TL;DR: Transformer as mentioned in this paper is an emergent sequence-to-sequence model which achieves state-of-the-art performance in neural machine translation and other natural language processing applications, such as automatic speech recognition (ASR), speech translation (ST), and text to speech (TTS).
Abstract: Sequence-to-sequence models have been widely used in end-to-end speech processing, for example, automatic speech recognition (ASR), speech translation (ST), and text-to-speech (TTS). This paper focuses on an emergent sequence-to-sequence model called Transformer, which achieves state-of-the-art performance in neural machine translation and other natural language processing applications. We undertook intensive studies in which we experimentally compared and analyzed Transformer and conventional recurrent neural networks (RNN) in a total of 15 ASR, one multilingual ASR, one ST, and two TTS benchmarks. Our experiments revealed various training tips and significant performance benefits obtained with Transformer for each task including the surprising superiority of Transformer in 13/15 ASR benchmarks in comparison with RNN. We are preparing to release Kaldi-style reproducible recipes using open source and publicly available datasets for all the ASR, ST, and TTS tasks for the community to succeed our exciting outcomes.
464 citations
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TL;DR: The first application of hydrogen-terminated surfaces as electron devices is presented in this article for the metal-semiconductor field effect transistor (MSE transistor), where the surface states of (1 1 1) and (0 0 1) were discussed.
462 citations
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TL;DR: In this article, the Gamma-ray Burst Monitor (GBM) and Large Area Telescope (LAT) instruments on-board the Fermi observatory were used to observe the long gamma-ray burst, GRB 090902B.
Abstract: We report on the observation of the bright, long gamma-ray burst (GRB), GRB 090902B, by the Gamma-ray Burst Monitor (GBM) and Large Area Telescope (LAT) instruments on-board the Fermi observatory. ...
462 citations
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TL;DR: The structure of the HSA-hemin-myristate complex (PDB ID 1o9x) reveals the key polar and hydrophobic interactions that determine the hemin-binding specificity of HSA.
Abstract: Human serum albumin (HSA) is an abundant plasma protein that binds a wide variety of hydrophobic ligands including fatty acids, bilirubin, thyroxine and hemin. Although HSA-heme complexes do not bind oxygen reversibly, it may be possible to develop modified HSA proteins or heme groups that will confer this ability on the complex. We present here the crystal structure of a ternary HSA-hemin-myristate complex, formed at a 1:1:4 molar ratio, that contains a single hemin group bound to subdomain IB and myristate bound at six sites. The complex displays a conformation that is intermediate between defatted HSA and HSA-fatty acid complexes; this is likely to be due to low myristate occupancy in the fatty acid binding sites that drive the conformational change. The hemin group is bound within a narrow D-shaped hydrophobic cavity which usually accommodates fatty acid; the hemin propionate groups are coordinated by a triad of basic residues at the pocket entrance. The iron atom in the centre of the hemin is coordinated by Tyr161. The structure of the HSA-hemin-myristate complex (PDB ID 1o9x) reveals the key polar and hydrophobic interactions that determine the hemin-binding specificity of HSA. The details of the hemin-binding environment of HSA provide a structural foundation for efforts to modify the protein and/or the heme molecule in order to engineer complexes that have favourable oxygen-binding properties.
458 citations
Authors
Showing all 24378 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yusuke Nakamura | 179 | 2076 | 160313 |
Yoshio Bando | 147 | 1234 | 80883 |
Charles Maguire | 142 | 1197 | 95026 |
Kazunori Kataoka | 138 | 908 | 70412 |
Senta Greene | 134 | 1346 | 90697 |
Intae Yu | 134 | 1372 | 89870 |
Kohei Yorita | 131 | 1389 | 91177 |
Wei Xie | 128 | 1281 | 77097 |
Susumu Kitagawa | 125 | 809 | 69594 |
Leon O. Chua | 122 | 824 | 71612 |
Jun Kataoka | 121 | 603 | 54274 |
S. Youssef | 120 | 683 | 65110 |
Katsuhiko Mikoshiba | 120 | 866 | 62394 |
Yusuke Yamauchi | 117 | 1000 | 51685 |
Teruo Okano | 117 | 476 | 47081 |