Publish in OALib Journal

ISSN: 2333-9721

APC: Only $99


Any time

2019 ( 43 )

2018 ( 384 )

2017 ( 390 )

2016 ( 403 )

Custom range...

Search Results: 1 - 10 of 37286 matches for " Jun Sugiyama "
All listed articles are free for downloading (OA Articles)
Page 1 /37286
Display every page Item
Imprints of the Metrically-coupled Dilaton on Density Perturbations in Inflationary Cosmology
Takeshi Chiba,Naoshi Sugiyama,Jun'ichi Yokoyama
Physics , 1997, DOI: 10.1016/S0550-3213(98)00412-X
Abstract: Spectra of density perturbations produced during chaotic inflation are calculated, taking both adiabatic and isocurvature modes into account in a class of scalar-tensor theories of gravity in which the dilaton is metrically coupled. Comparing the predicted spectrum of the cosmic microwave background radiation anisotropies with the one observed by the COBE-DMR we calculate constraints on the parameters of these theories, which turn out to be stronger by an order-of-magnitude than those obtained from post-Newtonian experiments.
Penta-quark baryon from the QCD Sum Rule
Jun Sugiyama,Takumi Doi,Makoto Oka
Physics , 2003, DOI: 10.1016/j.physletb.2003.12.018
Abstract: Exotic penta-quark baryon with strangeness +1, \Theta^+, is studied in the QCD sum rule approach. We derive sum rules for the positive and negative parity baryon states with J=1/2 and I=0. It is found that the standard values of the QCD condensates predict a negative parity \Theta^+ of mass \simeq 1.5 GeV, while no positive parity state is found. We stress the roles of chiral-odd condensates in determining the parity and mass of \Theta^+.
Effect of Void Network on CMB Anisotropy
Nobuyuki Sakai,Naoshi Sugiyama,Jun'ichi Yokoyama
Physics , 1997, DOI: 10.1086/306550
Abstract: We study the effect of a void network on the CMB anisotropy in the Einstein-de Sitter background using Thompson &Vishniac's model. We consider comprehensively the Sacks-Wolfe effect, the Rees-Sciama effect and the gravitational lensing effect. Our analysis includes the model of primordial voids existing at recombination, which is realized in some inflationary models associated with a first-order phase transition. If there exist primordial voids whose comoving radius is larger than $\sim10h^{-1}$Mpc at recombination, not only the Sachs-Wolfe effect but also the Rees-Sciama effect is appreciable even for multipoles $l\lsim1000$ of the anisotropy spectrum. The gravitational lensing effect, on the other hand, slightly smoothes the primary anisotropy; quantitatively, our results for the void model are similar to the previous results for a CDM model. All the effects, together, would give some constraints on the configuration or origin of voids with high-resolution data of the CMB anisotropy.
Least-Squares Independence Regression for Non-Linear Causal Inference under Non-Gaussian Noise
Makoto Yamada,Masashi Sugiyama,Jun Sese
Statistics , 2011,
Abstract: The discovery of non-linear causal relationship under additive non-Gaussian noise models has attracted considerable attention recently because of their high flexibility. In this paper, we propose a novel causal inference algorithm called least-squares independence regression (LSIR). LSIR learns the additive noise model through the minimization of an estimator of the squared-loss mutual information between inputs and residuals. A notable advantage of LSIR over existing approaches is that tuning parameters such as the kernel width and the regularization parameter can be naturally optimized by cross-validation, allowing us to avoid overfitting in a data-dependent fashion. Through experiments with real-world datasets, we show that LSIR compares favorably with a state-of-the-art causal inference method.
Effects of Propofol on Glutamate-Induced Calcium Mobilization in Presynaptic Boutons of Rat Hippocampal Neurons  [PDF]
Shinichi Ito, Noriko Karube, Hitomi Sugiyama, Jun Hirokawa, Seiko Kitahara, Takeshi Yokoyama
Open Journal of Anesthesiology (OJAnes) , 2016, DOI: 10.4236/ojanes.2016.63005
Abstract: Recent reports have suggested that various general anesthetics affect presynaptic processes in the central nervous system. However, characterizations of the influence of intravenous anesthetics on neurotransmitter release from presynaptic nerve terminals (boutons) are insufficient. Because the presynaptic calcium concentration ([Ca2+]pre) regulates neurotransmitter release, we investigate the effects of the intravenous anesthetic propofol on neurotransmitter release by measuring [Ca2+]pre in the presynaptic boutons of individual dissociated hippocampal neurons. Brain slices were prepared from Sprague–Dawley rats (10 - 14 days of age). The hippocampal CA1 area was isolated with a fire-polished glass pipette, which vibrated horizontally to dissociate hippocampal CA1 neurons along with their attached presynaptic boutons. Presynaptic boutons were visualized under a confocal laser scanning microscope after staining with FM1-43 dye, and [Ca2+]pre was measured using fluo-3 AM dye. Glutamate (3 – 100 μM) administration increased [Ca2+]pre in Ca2+- containing external solution in a concentration-dependent manner. Propofol (3 – 30 μM) dose-dependently suppressed this glutamate (30 μM)-induced increase in [Ca2+]pre in boutons attached to dendrites, but not to the soma or base of the dendritic tree. The large majority of excitatory synapses on CA1 neurons are located on dendritic spines; therefore, propofol may affect glutamate-induced Ca2+ mobilization in excitatory, but not inhibitory, presynaptic boutons. Propofol may possibly have some effect on glutamate-regulated neurotransmitter release from excitatory presynaptic nerve terminals through inhibiting the increase in [Ca2+]pre induced by glutamate.
Food Flavor Perception as Expressed via Sensory Spectrograph  [PDF]
Naomi Sano, Ayaka Miyamoto, Mao Igasaki, Shiori Itoh, Haruna Ohkaji, Yoshie Yamagata, Jun Kayashita, Sumi Sugiyama, Yoshiaki Sugawara
Psychology (PSYCH) , 2016, DOI: 10.4236/psych.2016.72025
Abstract: In our previous studies, we examined the relationship between changes in mood, verbal (semantic) behavior, and non-verbal (skin temperature) activity induced by inhalation of essential oil fragrances, as well as linalool and its enantiomers. Sensory evaluation was a key component of these studies. We have found that perceived sensory attributes reported by participants can be represented via sensory spectrograph: A bar graph where the mean of the impression is plotted against descriptors of the setting for the semantic impression. In this paper, we present our latest attempts at assessing the taste of food using a sensory spectrograph. We conducted two studies: One in which participants assessed the taste of cookies with or without bean curd lees and one in which participants evaluated the taste of Miso soup and Sumashi soup as a function of salty concentration and soup stock consistency.
Model-Based Policy Gradients with Parameter-Based Exploration by Least-Squares Conditional Density Estimation
Syogo Mori,Voot Tangkaratt,Tingting Zhao,Jun Morimoto,Masashi Sugiyama
Computer Science , 2013,
Abstract: The goal of reinforcement learning (RL) is to let an agent learn an optimal control policy in an unknown environment so that future expected rewards are maximized. The model-free RL approach directly learns the policy based on data samples. Although using many samples tends to improve the accuracy of policy learning, collecting a large number of samples is often expensive in practice. On the other hand, the model-based RL approach first estimates the transition model of the environment and then learns the policy based on the estimated transition model. Thus, if the transition model is accurately learned from a small amount of data, the model-based approach can perform better than the model-free approach. In this paper, we propose a novel model-based RL method by combining a recently proposed model-free policy search method called policy gradients with parameter-based exploration and the state-of-the-art transition model estimator called least-squares conditional density estimation. Through experiments, we demonstrate the practical usefulness of the proposed method.
Efficient Sample Reuse in Policy Gradients with Parameter-based Exploration
Tingting Zhao,Hirotaka Hachiya,Voot Tangkaratt,Jun Morimoto,Masashi Sugiyama
Computer Science , 2013,
Abstract: The policy gradient approach is a flexible and powerful reinforcement learning method particularly for problems with continuous actions such as robot control. A common challenge in this scenario is how to reduce the variance of policy gradient estimates for reliable policy updates. In this paper, we combine the following three ideas and give a highly effective policy gradient method: (a) the policy gradients with parameter based exploration, which is a recently proposed policy search method with low variance of gradient estimates, (b) an importance sampling technique, which allows us to reuse previously gathered data in a consistent way, and (c) an optimal baseline, which minimizes the variance of gradient estimates with their unbiasedness being maintained. For the proposed method, we give theoretical analysis of the variance of gradient estimates and show its usefulness through extensive experiments.
Sufficient Component Analysis for Supervised Dimension Reduction
Makoto Yamada,Gang Niu,Jun Takagi,Masashi Sugiyama
Statistics , 2011,
Abstract: The purpose of sufficient dimension reduction (SDR) is to find the low-dimensional subspace of input features that is sufficient for predicting output values. In this paper, we propose a novel distribution-free SDR method called sufficient component analysis (SCA), which is computationally more efficient than existing methods. In our method, a solution is computed by iteratively performing dependence estimation and maximization: Dependence estimation is analytically carried out by recently-proposed least-squares mutual information (LSMI), and dependence maximization is also analytically carried out by utilizing the Epanechnikov kernel. Through large-scale experiments on real-world image classification and audio tagging problems, the proposed method is shown to compare favorably with existing dimension reduction approaches.
Possibility to Realize the Brain-Computer Interface from the Quantum Brain Model Based on Superluminal Particles  [PDF]
Takaaki Musha, Toshiki Sugiyama
Journal of Quantum Information Science (JQIS) , 2011, DOI: 10.4236/jqis.2011.13015
Abstract: R. Penrose and S. Hameroff have proposed an idea that the brain can attain high efficient quantum computation by functioning of microtubular structure of neurons in the cytoskelton of biological cells, including neurons of the brain. But Tegmark estimated the duration of coherence of a quantum state in a warm wet brain to be on the order of 10>–13
Page 1 /37286
Display every page Item

Copyright © 2008-2017 Open Access Library. All rights reserved.