A New Approach for Evaluating Stability and Deformation of Earthstructure in Earthquake

A new procedure for determining the shear strength of sand for slope stability analysis. An earthquake is proposed together with a simplified procedure for predicting deformation in earthquake. The proposed method is based on the advanced total stress method and uses undrained strength of sand with consideration on strength anisotropy. Soil parameters required in the use of proposed method as well as for deformation prediction are indicated and then results of stability and deformation analyses with the proposed method are presented for a revetment constructed on a silty sand on Tokyo Bay together with 1) field and laboratory tests results, 2) results with the method currently authorized in Japan and 3) field behaviour of this revetment in the Chiba-Tohooki earthquake of 1987

Body mass index and colorectal cancer risk : A Mendelian randomization study

Traditional observational studies have reported a positive association between higher body mass index (BMI) and the risk of colorectal cancer (CRC). However, evidence from other approaches to pursue the causal relationship between BMI and CRC is sparse. A two-sample Mendelian randomization (MR) study was undertaken using 68 single nucleotide polymorphisms (SNPs) from the Japanese genome-wide association study (GWAS) and 654 SNPs from the GWAS catalogue for BMI as sets of instrumental variables. For the analysis of SNP-BMI associations, we undertook a meta-analysis with 36 303 participants in the Japanese Consortium of Genetic Epidemiology studies (J-CGE), comprising normal populations. For the analysis of SNP-CRC associations, we utilized 7636 CRC cases and 37 141 controls from five studies in Japan, and undertook a meta-analysis. Mendelian randomization analysis of inverse-variance weighted method indicated that a one-unit (kg/m2) increase in genetically predicted BMI was associated with an odds ratio of 1.13 (95% confidence interval, 1.06-1.20; P value <.001) for CRC using the set of 68 SNPs, and an odds ratio of 1.07 (1.03-1.11, 0.001) for CRC using the set of 654 SNPs. Sensitivity analyses robustly showed increased odds ratios for CRC for every one-unit increase in genetically predicted BMI. Our MR analyses strongly support the evidence that higher BMI influences the risk of CRC. Although Asians are generally leaner than Europeans and North Americans, avoiding higher BMI seems to be important for the prevention of CRC in Asian populations

A genome-wide association study on meat consumption in a Japanese population : the Japan Multi-Institutional Collaborative Cohort study

Recent genome-wide association studies (GWAS) on the dietary habits of the Japanese population have shown that an effect rs671 allele was inversely associated with fish consumption, whereas it was directly associated with coffee consumption. Although meat is a major source of protein and fat in the diet, whether genetic factors that influence meat-eating habits in healthy populations are unknown. This study aimed to conduct a GWAS to find genetic variations that affect meat consumption in a Japanese population. We analysed GWAS data using 14 076 participants from the Japan Multi-Institutional Collaborative Cohort (J-MICC) study. We used a semi-quantitative food frequency questionnaire to estimate food intake that was validated previously. Association of the imputed variants with total meat consumption per 1000 kcal energy was performed by linear regression analysis with adjustments for age, sex, and principal component analysis components 1–10. We found that no genetic variant, including rs671, was associated with meat consumption. The previously reported single nucleotide polymorphisms that were associated with meat consumption in samples of European ancestry could not be replicated in our J-MICC data. In conclusion, significant genetic factors that affect meat consumption were not observed in a Japanese population

A Genome-wide Association Study on Confection Consumption in a Japanese Population- The Japan Multi-Institutional Collaborative Cohort study.

Differences in individual eating habits may be influenced by genetic factors, in addition to cultural, social, or environmental factors. Previous studies suggested that genetic variants within sweet taste receptor genes family were associated with sweet taste perception and the intake of sweet foods. The aim of this study was to conduct a genome-wide association study (GWAS) to find genetic variations that affect confection consumption in a Japanese population. We analyzed GWAS data on sweets consumption using 14,073 participants from the Japan Multi-Institutional Collaborative Cohort study. We used a semi-quantitative food frequency questionnaire to estimate food intake that was validated previously. Association of the imputed variants with sweets consumption was performed by linear regression analysis with adjustments for age, sex, total energy intake and principal component analysis components 1 to 3. Furthermore, the analysis was repeated adjusting for alcohol intake (g/day) in addition to the above-described variables. We found 418 single nucleotide polymorphisms (SNPs) located in 12q24 that were associated with sweets consumption. SNPs with the 10 lowest P-values were located on nine genes including at the BRAP, ACAD10, and ALDH2 regions on 12q24.12-13. After adjustment for alcohol intake, no variant was associated with sweets intake with genome-wide significance. In conclusion, we found a significant number of SNPs located on 12q24 genes that were associated with sweets intake before adjustment for alcohol intake. However, all of them lost statistical significance after adjustment for alcohol intake

Extension of the operational regime of the LHD towards a deuterium experiment

As the finalization of a hydrogen experiment towards the deuterium phase, the exploration of the best performance of hydrogen plasma was intensively performed in the large helical device. High ion and electron temperatures, Ti and Te, of more than 6 keV were simultaneously achieved by superimposing high-power electron cyclotron resonance heating onneutral beam injection (NBI) heated plasma. Although flattening of the ion temperature profile in the core region was observed during the discharges, one could avoid degradation by increasing the electron density. Another key parameter to present plasma performance is an averaged beta value $\left\langle \beta \right\rangle$ . The high $\left\langle \beta \right\rangle$ regime around 4% was extended to an order of magnitude lower than the earlier collisional regime. Impurity behaviour in hydrogen discharges with NBI heating was also classified with a wide range of edge plasma parameters. The existence of a no impurity accumulation regime, where the high performance plasma is maintained with high power heating  >10 MW, was identified. Wide parameter scan experiments suggest that the toroidal rotation and the turbulence are the candidates for expelling impurities from the core region

Distortion Model Based on Word Sequence Labeling for Statistical Machine Translation

This article proposes a new distortion model for phrase-based statistical machine translation. In decoding, a distortion model estimates the source word position to be translated next (subsequent position; SP) given the last translated source word position (current position; CP). We propose a distortion model that can simultaneously consider the word at the CP, the word at an SP candidate, the context of the CP and an SP candidate, relative word order among the SP candidates, and the words between the CP and an SP candidate. These considered elements are called rich context. Our model considers rich context by discriminating label sequences that specify spans from the CP to each SP candidate. It enables our model to learn the effect of relative word order among SP candidates as well as to learn the effect of distances from the training data. In contrast to the learning strategy of existing methods, our learning strategy is that the model learns preference relations among SP candidates in each sentence of the training data. This leaning strategy enables consideration of all of the rich context simultaneously. In our experiments, our model had higher BLUE and RIBES scores for Japanese-English, Chinese-English, and German-English translation compared to the lexical reordering models