Task-based Intercultural Language Teaching in EFL Classroom

Wang Ge 아시아영어교육학회 2004 The Journal of Asia TEFL Vol.1 No.2

Development and linkage mapping of unigene-derived microsatellite markers in <i>Brassica rapa</i> L.

Ge, Yu,Ramchiary, Nirala,Wang, Tao,Liang, Cui,Wang, Na,Wang, Zhe,Choi, Su-Ryun,Lim, Yong Pyo,Piao, Zhong Yun Japanese Society of Breeding 2011 Breeding science Vol.61 No.2

<P><I>Brassica rapa</I> plants are highly important as vegetables, sources of oilseeds and fodder crop. Here, we developed 450 unigene derived microsatellite (UGMS) markers in <I>B. rapa</I> using unigenes downloaded from the National Center for Biotechnology Information database. Of the 450 UGMS primer pairs, 428 (95.1%) produced repeatable and reliable amplifications of expected size in at least one parental line of <I>B. rapa</I>, and 70 UGMS markers gave 72 polymorphic loci between the two contrasting parental lines. Cross-species transferability analysis of these 70 polymorphic UGMS markers in five other cultivated <I>Brassica</I> species showed varying transferability rates ranging from 82.9% in <I>B. nigra</I> to 97.1% in <I>B. juncea</I> and <I>B. napus</I>, and overall 53 UGMS markers amplified targets in all five species. The <I>B. rapa</I> linkage map was constructed using the 72 UGMS polymorphic loci and 154 previously developed SSRs. The newly developed UGMS markers and linkage map in this study would help in future studies to better understand the organization and evolution of <I>Brassica</I> genomes with respect to unigenes, in addition to mapping, tagging and cloning of economically important trait QTL/gene(s) and marker-assisted breeding in <I>Brassica</I> crops.</P>

Blood lipids and all-cause mortality among old people: the Chinese Longitudinal Healthy Longevity Survey 2008-2018

Wang Rongxi,Yu Xiaoyue,Wang Zhiqiang,Liu Yujie,Chen Hui,Liu Shangbin,XU CHENG,Chen Yingjie,Xia Danni,Ge Xin,Chang Ruijie,Xu Gang,Xiang Mi,Wang Ying,Shen Tian,Hu Fan,Cai Yong 한국역학회 2022 Epidemiology and Health Vol.44 No.-

OBJECTIVES: Proper blood lipid levels are essential for survival in older adults, but inconsistent relationships have been reported between blood lipids and all-cause mortality in the elderly. METHODS: This retrospective longitudinal study analyzed data from 1,067 Chinese older adults enrolled in the Chinese Longitudinal Healthy Longevity Survey collected in 2008 and followed up until death or December 31, 2018. The outcome was allcause mortality. Multivariate Cox regression analyses were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) with stratification by age (60-80, 80-100, or ≥ 100 years) for further analysis. The survival probability according to lipid profile quartiles was calculated using Kaplan-Meier curves and the log-rank test. RESULTS: The participants’ mean age was 84.84 years, and 57.0% were female. In total, 578 individuals died, and 277 were lost to follow-up. The mean total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) levels were higher among those who died than among those who survived. Participants in the second HDL-C quartile and the highest LDL-C and triglyceride (TG) quartiles had 28% higher, 23% lower, and 49% lower risks of all-cause mortality, respectively. After further adjustment, the associations remained except for HDL-C, and additional associations were observed between all-cause mortality and the third TC and LDL-C quartiles and the second TG quartile (HR, 1.44; 95% CI, 1.01 to 2.06; HR, 0.68; 95% CI, 0.49 to 0.94; HR, 0.79; 95% CI, 0.62 to 0.99, respectively). CONCLUSIONS: Older adults should maintain an LDL-C level of 1.91-2.47 mmol/L and a TG level of no less than 1.66 mmol/L.

A review of experimental methods for characterising composite viscosities of continuous fibre-reinforced polymer composites

Wang Jinhuo,Han Yang,Ge Xiaohong,Qi Zhengbing,Zhao Jun,Wang Rongwen,Wu Huawei,Han Taiping,Sun Shaoxun,Wang Hui,Lin Jia,Liu Yuejun,Kong Xiangsong,Chen Qiming,Zeng Xiangxu 한국유변학회 2023 Korea-Australia rheology journal Vol.35 No.2

Optimisation design of composite structures requires an accurate predictive model for forming behaviour. The simulation process contains a number of model parameters which include transverse and longitudinal viscosities of continuous fibrereinforced viscous composites, fundamental to predicting the shear rheology. Shearing the unidirectional composite along the fibre direction gives a measure of the longitudinal viscosity (LV), whilst shearing across or transverse to the fibre direction gives a measure of the transverse viscosity (TV). Numerous experimental work was conducted in the past to measure these two viscosities for various materials. However, conflicting measurements by different test methods were obtained and these apparent discrepancies had not yet been systematically investigated in any single study. This paper reviews previous work on characterisation techniques to further understand the cause of such discrepancy, and hence to improve measurement accuracy, which would benefit future work on theoretical modelling of the composite viscosities and optimisation simulation of composites forming. Some important findings, such as effects of resin-rich areas, contributory factors of elastic effects, non-Newtonian behaviour for composites with Newtonian matrix, aspect ratio and end effects of test samples, geometry effects of fibres and fibre rearrangement during shearing, existence of a mathematical relationship between LV and TV and necessary benchmarking exercise using Newtonian matrix composites, were summarised.

The Risk Factors and Outcomes for Radiological Abnormalities in Early Convalescence of COVID-19 Patients Caused by the SARS-CoV-2 Omicron Variant: A Retrospective, Multicenter Follow-up Study

Wang Hong,Yang Qingyuan,Li Fangfei,Wang Huiying,Yu Jing,Ge Xihong,Gao Guangfeng,Xia Shuang,Xing Zhiheng,Shen Wen 대한의학회 2023 Journal of Korean medical science Vol.38 No.8

Background: The emergence of the severe acute respiratory syndrome coronavirus 2 omicron variant has been triggering the new wave of coronavirus disease 2019 (COVID-19) globally. However, the risk factors and outcomes for radiological abnormalities in the early convalescent stage (1 month after diagnosis) of omicron infected patients are still unknown. Methods: Patients were retrospectively enrolled if they were admitted to the hospital due to COVID-19. The chest computed tomography (CT) images and clinical data obtained at baseline (at the time of the first CT image that showed abnormalities after diagnosis) and 1 month after diagnosis were longitudinally analyzed. Uni-/multi-variable logistic regression tests were performed to explore independent risk factors for radiological abnormalities at baseline and residual pulmonary abnormalities after 1 month. Results: We assessed 316 COVID-19 patients, including 47% with radiological abnormalities at baseline and 23% with residual pulmonary abnormalities at 1-month follow-up. In a multivariate regression analysis, age ≥ 50 years, body mass index ≥ 23.87, days after vaccination ≥ 81 days, lymphocyte count ≤ 1.21 × 10-9/L, interleukin-6 (IL-6) ≥ 10.05 pg/mL and IgG ≤ 14.140 S/CO were independent risk factors for CT abnormalities at baseline. The age ≥ 47 years, presence of interlobular septal thickening and IL-6 ≥ 5.85 pg/mL were the independent risk factors for residual pulmonary abnormalities at 1-month follow-up. For residual abnormalities group, the patients with less consolidations and more parenchymal bands at baseline could progress on CT score after 1 month. There were no significant changes in the number of involved lung lobes and total CT score during the early convalescent stage. Conclusion: The higher IL-6 level was a common independent risk factor for CT abnormalities at baseline and residual pulmonary abnormalities at 1-month follow-up. There were no obvious radiographic changes during the early convalescent stage in patients with residual pulmonary abnormalities.

Susceptibility Loci Associations with Prostate Cancer Risk in Northern Chinese Men

Wang, Na-Na,Xu, Yong,Yang, Kuo,Wei, Dong,Zhang, Yao-Guang,Liu, Ming,Shi, Xiao-Hong,Liang, Si-Ying,Sun, Liang,Zhu, Xiao-Quan,Yang, Yi-Ge,Tang, Lei,Zhao, Cheng-Xiao,Wang, Xin,Chen, Xin,Hui, Juan,Zhang, Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.5

Background: KLK3 gene products, like human prostate-specific antigen (PSA), are important biomarkers in the clinical diagnosis of prostate cancer (PCa). G protein-coupled receptor RFX6, C2orf43 and FOXP4 signaling plays important roles in the development of PCa. However, associations of these genes with PCa in northern Chinese men remain to be detailed. This study aimed to investigate their impact on occurrence and level of malignancy. Methods: All subjects were from Beijing and Tianjin, including 266 cases with prostate cancer and 288 normal individuals as controls. We evaluated associations between clinical covariates (age at diagnosis, prostate specific antigen, Gleason score, tumor stage and aggressive) and 6 candidate PCa risk loci, genotyped by PCR- high resolution melting curve and sequencing methods. Results: Case-control analysis of allelic frequency of PCa associated with PCa showed that one of the 6 candidate risk loci, rs339331 in the RFX6 gene, was associated with reduced risk of prostate cancer (odds ratio (OR) = 0.73, 95% confidence interval (CI) =0.57-0.94, P = 0.013) in northern Chinese men. In addition, subjects with CX (CC+TC) genotypes had a decreased risk for prostrate cancer compared to those carrying the TT homozygote (OR =0.64, 95% CI = 0.45- 0.90, P = 0.008). The TT genotype of 13q22 (rs9600079, T) was associated with tumor stage (P=0.044, OR=2.34, 95% CI=0.94-5.87). Other SNPs were not significantly associated with clinical covariates in prostate cancer (P > 0.05). Conclusions. rs339331 in the RFX6 gene may be associated with prostate cancer as a susceptibility locus in northern Chinese men.

Prediction of Diabetes based on Deep Neural Networks Using MIMIC Clinical Database

Ge Wang(왕격),Inwhee Joe(조인휘) 한국통신학회 2022 한국통신학회 학술대회논문집 Vol.2022 No.2

Diabetes is one of the most chronic diseases worldwide which can cause various kinds of complications like blindness, stroke, heart disease, etc. So the prediction of diabetes is a critical issue that has been discussed for a long time. In this paper, we propose a diabetes prediction model based on deep neural networks. The datasets were retrieved from MIMIC-III and the MIMIC-IV database respectively that include prediction factors like Age, Gender, Glucose, etc. We compared two different Deep Neural Networks(DNN) to evaluate the two datasets, and the experimental results confirmed the effectiveness of our methods with an accuracy of more than 98% in both models.

Image Reconstruction is a New Frontier of Machine Learning

Wang, Ge,Ye, Jong Chu,Mueller, Klaus,Fessler, Jeffrey A. IEEE 2018 IEEE transactions on medical imaging Vol.37 No.6

<P>Over past several years, machine learning, or more generally artificial intelligence, has generated overwhelming research interest and attracted unprecedented public attention. As tomographic imaging researchers, we share the excitement from our imaging perspective [item 1) in the Appendix], and organized this special issue dedicated to the theme of “Machine learning for image reconstruction.” This special issue is a sister issue of the special issue published in May 2016 of this journal with the theme “Deep learning in medical imaging” [item 2) in the Appendix]. While the previous special issue targeted medical image processing/analysis, this special issue focuses on data-driven tomographic reconstruction. These two special issues are highly complementary, since image reconstruction and image analysis are two of the main pillars for medical imaging. Together we cover the whole workflow of medical imaging: from tomographic raw data/features to reconstructed images and then extracted diagnostic features/readings.</P>

An enhancing many-objective evolutionary algorithm using chaotic mapping and solution ranking mechanism for large-scale optimization

Wang Yong,Zhang Qian,Wang Gai-Ge,Hu Zhongyi 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.5

There are many complex optimization problems in the real world, and various evolutionary algorithms are proposed to solve them. Recently, the many-objective evolutionary algorithm using a one-by-one selection strategy (1by1EA) adopts a convergence indicator and a distribution indicator to balance convergence and diversity. However, the algorithm is too random in initialization and the fitness evaluation of solutions in the mating selection is single, which leads to poor performance in solving large-scale problems. Therefore, this paper proposes an improved method called 1by1EA-CHV by using circle chaotic mapping and a solution ranking mechanism based on the hypervolume (HV) indicator. We first map each component of solutions into a certain value space to initialize the population. Then, we calculate the contribution of each partition divided based on HV and apply the aggregation method to guide the reallocation of fitness, which achieves the ranking of solutions by using it before the old calculation method. To validate the performance, experiments compared 1by1EA-CHV with 1by1EA and other seven many-objective algorithms on large-scale functions, and the differences between these algorithms were analyzed statistically by a non-parametric test. The results showed the superiority of 1by1EA-CHV in solving large-scale many-objective optimization problems with up to 2000 decision variables.

Purification and Characterization of Novel Bifunctional Xylanase, Xyn3, Isolated from Aspergillus niger A-25

( Hong Ge Chen ),( Xin Yan ),( Xin Yu Liu ),( Ming Dao Wang ),( Hui Min Huang ),( Xin Cheng Jia ),( Jin An Wang ) 한국미생물생명공학회 2006 Journal of microbiology and biotechnology Vol.16 No.7