論文 - 山本　詠士

Universal relation between instantaneous diffusivity and radius of gyration of proteins in aqueous solution

E Yamamoto, T Akimoto, A Mitsutake, R Metzler

arXiv preprint arXiv:2009.06829 126 （ 12 ）  2020年

ISSN  0031-9007

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Phase-change Janus particles with switchable dual properties

R Soma, B Nakayama, M Kuwahara, E Yamamoto, T Saiki

Applied Physics Letters 117 (22), 221601 117 （ 22 ）  2020年

ISSN  0003-6951

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Separation of water-alcohol mixtures using carbon nanotubes under an electric field

Winarto, Yamamoto Eiji, Yasuoka Kenji

PHYSICAL CHEMISTRY CHEMICAL PHYSICS 21 （ 28 ） 15431 - 15438 2019年07月

ISSN  1463-9076

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Highly bright and stable NIR-BRET with blue-shifted coelenterazine derivatives for deep-tissue imaging of molecular events in vivo

R Nishihara, R Paulmurugan, T Nakajima, E Yamamoto, A Natarajan, ...

Theranostics 9 (9), 2646 9 （ 9 ） 2646 - 2661 2019年

ISSN  1838-7640

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Rapid Assembly of Colloidal Crystals under Laser Illumination on a GeSbTe Substrate

K Yamaguchi, E Yamamoto, R Soma, B Nakayama, M Kuwahara, T Saiki

Langmuir 35 （ 19 ） 6403 - 6408 2019年

ISSN  0743-7463

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Separation of water–alcohol mixtures using carbon nanotubes under an electric field

E Yamamoto, K Yasuoka

Physical Chemistry Chemical Physics 21 (28), 15431-15438 2019年

Molecular Dynamic Simulations to Probe Water Permeation Pathways of GPCRs

K Tomobe, E Yamamoto, K Yasuoka

G Protein-Coupled Receptor Signaling, 21-30 1947   21 - 30 2019年

ISSN  1064-3745

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Selectivity of Carbon Nanotubes under An Electric Field on Transferring Water–Alcohol Mixtures

E Yamamoto, K Yasuoka

IOP Conference Series: Materials Science and Engineering 494 (1), 012099 2019年

Why is the environment important for decision making? Local reservoir model for choice-based learning

Naruse M., Yamamoto E., Nakao T., Akimoto T., Saigo H., Okamura K., Ojima I., Northoff G., Hori H.

PLoS ONE （PLoS ONE）  13 （ 10 ）  2018年10月

ISSN  1932-6203

　概要を見る

© 2018 Naruse et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Decision making based on behavioral and neural observations of living systems has been extensively studied in brain science, psychology, neuroeconomics, and other disciplines. Decision-making mechanisms have also been experimentally implemented in physical processes, such as single photons and chaotic lasers. The findings of these experiments suggest that there is a certain common basis in describing decision making, regardless of its physical realizations. In this study, we propose a local reservoir model to account for choicebased learning (CBL). CBL describes decision consistency as a phenomenon where making a certain decision increases the possibility of making that same decision again later. This phenomenon has been intensively investigated in neuroscience, psychology, and other related fields. Our proposed model is inspired by the viewpoint that a decision is affected by its local environment, which is referred to as a local reservoir. If the size of the local reservoir is large enough, consecutive decision making will not be affected by previous decisions, thus showing lower degrees of decision consistency in CBL. In contrast, if the size of the local reservoir decreases, a biased distribution occurs within it, which leads to higher degrees of decision consistency in CBL. In this study, an analytical approach for characterizing local reservoirs is presented, as well as several numerical demonstrations. Furthermore, a physical architecture for CBL based on single photons is discussed, and the effects of local reservoirs are numerically demonstrated. Decision consistency in human decisionmaking tasks and in recruiting empirical data is evaluated based on the local reservoir. This foundation based on a local reservoir offers further insights into the understanding and design of decision making.

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Water permeation through the internal water pathway in activated GPCR rhodopsin.

K Tomobe, E Yamamoto, K Kholmurodov, K Yasuoka

PloS one 12 (5), e0176876 12 （ 5 ）  2017年

ISSN  1932-6203

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Effects of temperature, concentration, and isomer on the hydration structure in monosaccharide solutions

K Tomobe, E Yamamoto, M Yasui, K Yasuoka

Physical Chemistry Chemical Physics 19 (23), 15239-15246 19 （ 23 ） 15239 - 15246 2017年

ISSN  1463-9076

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Dynamic interactions between a membrane binding protein and lipids induce fluctuating diffusivity

E Yamamoto, T Akimoto, AC Kalli, K Yasuoka, MSP Sansom

Science Advances 3, e1601871 3 （ 1 ）  2017年

ISSN  2375-2548

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Detection of transition times from single-particle-tracking trajectories

T Akimoto, E Yamamoto

Physical Review E 96 (5), 052138 96 （ 5 ）  2017年

ISSN  2470-0045

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Computational and theoretical approaches for studies of a lipid recognition protein on biological membranes

E Yamamoto

Biophysics and Physicobiology 14, 153-160 14   153 - 160 2017年

ISSN  2189-4779

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Origin of the blueshift of water molecules at interfaces of hydrophilic cyclic compounds

K Tomobe, E Yamamoto, D Kojić, Y Sato, M Yasui, K Yasuoka

Science Advances 3 (12), e1701400 3 （ 12 ）  2017年

ISSN  2375-2548

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Water Molecules in a Carbon Nanotube under an Applied Electric Field at Various Temperatures and Pressures

E Yamamoto, K Yasuoka

Water 9 (7), 473 9 （ 7 ）  2017年

ISSN  2073-4441

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1/f fluctuation and water permeation of aquaporins

E Yamamoto, K Yasuoka

Kobunshi 65 (4), 175-176 2016年

Distributional behaviors of time-averaged observables in the Langevin equation with fluctuating diffusivity: Normal diffusion but anomalous fluctuations

T Akimoto, E Yamamoto

Physical Review E 93 (6), 062109 93 （ 6 ）  2016年

ISSN  2470-0045

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Distributional behavior of diffusion coefficients obtained by single trajectories in annealed transit time model

T Akimoto, E Yamamoto

Journal of Statistical Mechanics: Theory and Experiment 2016 (12), 123201 2016年

ISSN  1742-5468

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Instability of buried hydration sites increases protein subdomains fluctuations in the human prion protein by the pathogenic mutation T188R

K Tomobe, E Yamamoto, T Akimoto, M Yasui, K Yasuoka

AIP Advances 6 (5), 055324 6 （ 5 ）  2016年

ISSN  2158-3226

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