Blood lipids are important risk factors for coronary artery disease (CAD). Here we perform an exome-wide association study by genotyping 12,685 Chinese, using a custom Illumina HumanExome BeadChip, to identify additional loci influencing lipid levels. Single-variant association analysis on 65,671 single nucleotide polymorphisms reveals 19 loci associated with lipids at exome-wide significance (P<2.69 × 10−7), including three Asian-specific coding variants in known genes (CETP p.Asp459Gly, PCSK9 p.Arg93Cys and LDLR p.Arg257Trp). Furthermore, missense variants at two novel loci—PNPLA3 p.Ile148Met and PKD1L3 p.Thr429Ser—also influence levels of triglycerides and low-density lipoprotein cholesterol, respectively. Another novel gene, TEAD2, is found to be associated with high-density lipoprotein cholesterol through gene-based association analysis. Most of these newly identified coding variants show suggestive association (P<0.05) with CAD. These findings demonstrate that exome-wide genotyping on samples of non-European ancestry can identify additional population-specific possible causal variants, shedding light on novel lipid biology and CAD.
The cyclic void growth model (CVGM) is a micro-mechanical fracture model that has been used to assess ultra-low cycle fatigue (ULCF) of steel structures in recent years. However, owing to the stress triaxiality range and contingency of experimental results, low goodness of fit is sometimes obtained when calibrating the model damage degradation parameter, resulting in poor prediction. In order to improve the prediction accuracy of the CVGM model, a model parameter calibration method is proposed. In the research presented in this paper, tests were conducted on circular notched specimens that provided different magnitudes of stress triaxiality. The comparative analysis was carried out between experimental results and predicted results. The results indicate that the number of cycles and the equivalent plastic strain to ULCF fracture initiation by the CVGM model calibrated by the proposed method agree well with the experimental results. The proposed parameter calibration method greatly improves prediction accuracy compared to the previous method.
Cyclic void growth model (CVGM) and continuum damage mechanics (CDM) model are suitable for predicting the damage of ultra-low-cycle fatigue (ULCF) theoretically. However, studies on the prediction of ultra-low-cycle fatigue (ULCF) damage is lacking. To determine which method is better, we used the two methods to predict the damage of ULCF. Firstly, uniaxial tensile and large strain cycle tests were performed on the base metal, weld metal and heat-affected zone and the material parameters were calibrated respectively. The uniaxial plastic strain threshold and toughness parameter of weld metal were minimum, and the dispersion was maximum. The finite element models of the base metal and weld specimens were established based on the calibrated parameters, and the ULCF damage was predicted. Compared with the CVGM model, the CDM model can predict the fatigue life and the relationships among the fatigue and fracture lives, the post-fracture path and the number of cycles to initial damage. The parameter calibration is simple. CDM is superior to CVGM in predicting the ULCF damage of steel and its weld joints.
In the native language of Tibet preparatory students, pronunciation assimilation is a very common phenomenon, and if it is brought into Chinese, it will lead to incorrect pronunciation. In order to study and analyze this pronunciation, Chinese learning students carry out the experimental tests in Tibet preparatory. This paper proposes a software testing method to obtain pronunciation error prediction analysis curves, and the reliability of the data was analyzed by using the two methods of theoretical analysis and software calculation, but it is not easy to find the phenomenon of pronunciation assimilation in Chinese. The native language and Chinese in Tibet are compared by using theoretical analysis method, the pronunciation errors of the students are predicted in Chinese learning, and then this paper has been focused on the emergence of partial error. Through the experimental data analysis, it is found that tone pronunciation are often replaced by Chinese learners with other tones, so teachers should strengthen the training and improve the accuracy of pronunciation in teaching.
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