Hamiltonian decomposition for bulk and surface states

We demonstrate that a tight-binding Hamiltonian with nearest- and next-nearest-neighbor hopping integrals can be decomposed into bulk and boundary parts in a general lattice system. The Hamiltonian decomposition reveals that next nearest-neighbor hopping causes sizable changes in the energy spectrum of surface states even if the correction to the energy spectrum of bulk states is negligible. By applying the Hamiltonian decomposition to edge states in graphene systems, we show that the next nearest-neighbor hopping stabilizes the edge states.Comment: 5 pages, 4 figure

ジグザグ端グラフェン・ナノリボンの完全伝導チャネルに対する位相緩和効果に関する数値的研究

広島大学(Hiroshima University)博士(理学)Doctor of Sciencedoctora

Metabolic syndrome, adiponectin and fat ROS

The metabolic syndrome, a cluster of insulin resistance, elevated blood pressure, and atherogenic dyslipidemia, is a common basis of atherosclerosis. Accumulation of intra-abdominal visceral fat stands upstream of the metabolic syndrome. Adipose tissue expresses a variety of genes for bioactive secretory proteins conceptualized as adipocytokines. We discovered a novel adipose-specific protein named adiponectin from human fat cDNAs. Adiponectin circulates in the plasma and its serum level is decreased in visceral fat accumulation. Results of experimental and clinical researches have demonstrated that hypoadiponectinemia underlies the pathogenesis of multiple diseases related to visceral fat accumulation, including atherosclerosis, hypertension, cardiac failure, insulin resistance, diabetes, hepatic steatosis, inflammatory bowel disease, and cancers. Recently, we revealed fat-derived reactive oxygen species (fat ROS) as an upstream factor in the development of hypoadiponectinemia and metabolic syndrome. Intervention targeting visceral fat accumulation, hypoadiponectinemia and fat ROS should be the way to therapeutically tackle the metabolic syndrome.Biomedical Reviews 2006; 17: 1-10

nsPEFs induce the ISR via ROS-mediated HRI activation

The integrated stress response (ISR) is one of the most important cytoprotective mechanisms and is integrated by phosphorylation of the α subunit of eukaryotic translation initiation factor 2 (eIF2α). Four eIF2α kinases, heme-regulated inhibitor (HRI), double-stranded RNA-dependent protein kinase (PKR), PKR-like endoplasmic reticulum kinase (PERK), and general control nonderepressible 2 (GCN2), are activated in response to several stress conditions. We previously reported that nanosecond pulsed electric fields (nsPEFs) are a potential therapeutic tool for ISR activation. In this study, we examined which eIF2α kinase is activated by nsPEF treatment. To assess the responsible eIF2α kinase, we used previously established eIF2α kinase quadruple knockout (4KO) and single eIF2α kinase-rescued 4KO mouse embryonic fibroblast (MEF) cells. nsPEFs 70 ns in duration with 30 kV/cm electric fields caused eIF2α phosphorylation in wild-type (WT) MEF cells. On the other hand, nsPEF-induced eIF2α phosphorylation was completely abolished in 4KO MEF cells and was recovered by HRI overexpression. CM-H2DCFDA staining showed that nsPEFs generated reactive oxygen species (ROS), which activated HRI. nsPEF-induced eIF2α phosphorylation was blocked by treatment with the ROS scavenger N-acetyl-L-cysteine (NAC). Our results indicate that the eIF2α kinase HRI is responsible for nsPEF-induced ISR activation and is activated by nsPEF-generated ROS

Comparative study of path nomalizations for path prediction

This paper disccusses two methods on normalization of a sample path for predicting paths of a pedestrian by using eigenspace. A path of a person is defined as a sequence of successive coordinates of the person over frames and represented the path as a vector with 2M elements of M number of coordinates. A problem of their prediction is that the method is based on subspace. To make a subspace from sample paths, all paths need to be normalized and resampled such that a path vector has the same number of elements. Because different sample paths have different number of frames. In this paper, we apply a normalization method using DP matching and discuss results of two predictions : resampling and DP

Comparative study of path nomalizations for path prediction

The 14th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2008), Slide ; Place : Beppu, Oita, Japan ; Date : January 23-26, 200

On methods for taking pedstrians' paths for prediction

第9回IEEE広島支部学生シンポジウム(HISS), ポスター ; 開催場所:鳥取 ; 開催日:2007年11月24-25