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Institution

National Institute of Advanced Industrial Science and Technology

GovernmentTsukuba, Ibaraki, Japan
About: National Institute of Advanced Industrial Science and Technology is a government organization based out in Tsukuba, Ibaraki, Japan. It is known for research contribution in the topics: Catalysis & Thin film. The organization has 22114 authors who have published 65856 publications receiving 1669827 citations. The organization is also known as: Sangyō Gijutsu Sōgō Kenkyū-sho.
Topics: Catalysis, Thin film, Carbon nanotube, Hydrogen, Laser


Papers
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Journal ArticleDOI
TL;DR: In this article, N-methyl-N-propylpiperidinium bis(trifluoromethanesulfonyl)imide is the most promising candidate as the electrolyte base.

687 citations

Journal ArticleDOI
TL;DR: The KI oxidation dosimetry using 0.1 moldm(-3) KI solution as a standard method to calibrate the sonochemical efficiency of an individual reaction system is proposed.

684 citations

Journal ArticleDOI
TL;DR: Theoretical modeling of the electronic structures indicates that the reduction of the effective mass at the valence band maximum (VBM) with decreasing sheet thickness enhances the carrier mobility of the GaS nanosheets, contributing to the high photocurrents.
Abstract: The first GaS nanosheet-based photodetectors are demonstrated on both mechanically rigid and flexible substrates. Highly crystalline, exfoliated GaS nanosheets are promising for optoelectronics due to strong absorption in the UV–visible wavelength region. Photocurrent measurements of GaS nanosheet photodetectors made on SiO2/Si substrates and flexible polyethylene terephthalate (PET) substrates exhibit a photoresponsivity at 254 nm up to 4.2 AW–1 and 19.2 AW–1, respectively, which exceeds that of graphene, MoS2, or other 2D material-based devices. Additionally, the linear dynamic range of the devices on SiO2/Si and PET substrates are 97.7 dB and 78.73 dB, respectively. Both surpass that of currently exploited InGaAs photodetectors (66 dB). Theoretical modeling of the electronic structures indicates that the reduction of the effective mass at the valence band maximum (VBM) with decreasing sheet thickness enhances the carrier mobility of the GaS nanosheets, contributing to the high photocurrents. Double-pea...

680 citations

Journal ArticleDOI
TL;DR: The structural model suggests that water molecules, which were observed in the vicinity of highly conserved residues and in the retinal pocket, regulate the activity of rhodopsin-like GPCRs and spectral tuning in visual pigments, respectively.
Abstract: Activation of G protein-coupled receptors (GPCRs) is triggered and regulated by structural rearrangement of the transmembrane heptahelical bundle containing a number of highly conserved residues. In rhodopsin, a prototypical GPCR, the helical bundle accommodates an intrinsic inverse-agonist 11-cis-retinal, which undergoes photo-isomerization to the all-trans form upon light absorption. Such a trigger by the chromophore corresponds to binding of a diffusible ligand to other GPCRs. Here we have explored the functional role of water molecules in the transmembrane region of bovine rhodopsin by using x-ray diffraction to 2.6 A. The structural model suggests that water molecules, which were observed in the vicinity of highly conserved residues and in the retinal pocket, regulate the activity of rhodopsin-like GPCRs and spectral tuning in visual pigments, respectively. To confirm the physiological relevance of the structural findings, we conducted single-crystal microspectrophotometry on rhodopsin packed in our three-dimensional crystals and show that its spectroscopic properties are similar to those previously found by using bovine rhodopsin in suspension or membrane environment.

675 citations

Book ChapterDOI
24 Sep 2012
TL;DR: A regularization approach is proposed that is applicable to any prediction algorithm with probabilistic discriminative models and applied to logistic regression and empirically show its effectiveness and efficiency.
Abstract: With the spread of data mining technologies and the accumulation of social data, such technologies and data are being used for determinations that seriously affect individuals' lives. For example, credit scoring is frequently determined based on the records of past credit data together with statistical prediction techniques. Needless to say, such determinations must be nondiscriminatory and fair in sensitive features, such as race, gender, religion, and so on. Several researchers have recently begun to attempt the development of analysis techniques that are aware of social fairness or discrimination. They have shown that simply avoiding the use of sensitive features is insufficient for eliminating biases in determinations, due to the indirect influence of sensitive information. In this paper, we first discuss three causes of unfairness in machine learning. We then propose a regularization approach that is applicable to any prediction algorithm with probabilistic discriminative models. We further apply this approach to logistic regression and empirically show its effectiveness and efficiency.

673 citations


Authors

Showing all 22289 results

NameH-indexPapersCitations
Takeo Kanade147799103237
Ferenc A. Jolesz14363166198
Michele Parrinello13363794674
Kazunari Domen13090877964
Hideo Hosono1281549100279
Hideyuki Okano128116967148
Kurunthachalam Kannan12682059886
Shaobin Wang12687252463
Ajit Varki12454258772
Tao Zhang123277283866
Ramamoorthy Ramesh12264967418
Kazuhito Hashimoto12078161195
Katsuhiko Mikoshiba12086662394
Qiang Xu11758550151
Yoshinori Tokura11785870258
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202367
2022265
20213,064
20203,389
20193,257
20183,181