http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Dian-Qing Li (검색결과 10 건)
- 무료
- 기관 내 무료
- 유료
-
Dian-Qing Li,Shui-Hua Jiang,Yong-Gang Cheng,Chuang-Bing Zhou 국제구조공학회 2013 Structural Engineering and Mechanics, An Int'l Jou Vol.45 No.5
This paper aims to compare three collocation point methods associated with the odd order stochastic response surface method (SRSM) in a systematical and quantitative way. The SRSM with the Hermite polynomial chaos is briefly introduced first. Then, three collocation point methods, namely the point method, the root method and the without origin method underlying the odd order SRSMs are highlighted. Three examples are presented to demonstrate the accuracy and efficiency of the three methods. The results indicate that the condition that the Hermite polynomial information matrix evaluated at the collocation points has a full rank should be satisfied to yield reliability results with a sufficient accuracy. The point method and the without origin method are much more efficient than the root method, especially for the reliability problems involving a large number of random variables or requiring complex finite element analysis. The without origin method can also produce sufficiently accurate reliability results in comparison with the point and root methods. Therefore, the origin often used as a collocation point is not absolutely necessary. The odd order SRSMs with the point method and the without origin method are recommended for the reliability analysis due to their computational accuracy and efficiency. The order of SRSM has a significant influence on the results associated with the three collocation point methods. For normal random variables, the SRSM with an order equaling or exceeding the order of a performance function can produce reliability results with a sufficient accuracy. The order of SRSM should significantly exceed the order of the performance function involving strongly non-normal random variables.
-
System Reliability Analysis of Rock Slope Stability Involving Correlated Failure Modes
Dian-Qing Li,Shui-Hua Jiang,Yi-Feng Chen,Chuang-Bing Zhou 대한토목학회 2011 KSCE JOURNAL OF CIVIL ENGINEERING Vol.15 No.8
This paper aims to propose a systematic quantitative method for system reliability evaluation of rock slope with plane failure involving multiple correlated failure modes. A probabilistic fault tree approach is presented to model system reliability of rock slope. An n-dimensional equivalent reliability method is employed to perform the system reliability analysis of the slope involving multiple correlated failure modes. Reliability sensitivity analyses at three different levels, namely, the single limit state function level, single failure mode level, and system reliability level, are carried out to study the effect of variables on reliability. An example is presented to demonstrate the validity and capability of the proposed approach. The results indicate that the system reliability of rock slope involving multiple correlated failure modes can be evaluated efficiently using the proposed approach. The system probability of failure is overestimated if the correlations between different failure modes are ignored. The relative importance of different failure modes to the system reliability can differ considerably. The sensitivity coefficients of basic random variables strongly depend on the selected sensitivity analysis level. The system reliability is sensitive to the location of the tension crack and the percentage of the tension crack filled with water.
-
Li, Dian-Qing,Jiang, Shui-Hua,Cheng, Yong-Gang,Zhou, Chuang-Bing Techno-Press 2013 Structural Engineering and Mechanics, An Int'l Jou Vol.45 No.5
This paper aims to compare three collocation point methods associated with the odd order stochastic response surface method (SRSM) in a systematical and quantitative way. The SRSM with the Hermite polynomial chaos is briefly introduced first. Then, three collocation point methods, namely the point method, the root method and the without origin method underlying the odd order SRSMs are highlighted. Three examples are presented to demonstrate the accuracy and efficiency of the three methods. The results indicate that the condition that the Hermite polynomial information matrix evaluated at the collocation points has a full rank should be satisfied to yield reliability results with a sufficient accuracy. The point method and the without origin method are much more efficient than the root method, especially for the reliability problems involving a large number of random variables or requiring complex finite element analysis. The without origin method can also produce sufficiently accurate reliability results in comparison with the point and root methods. Therefore, the origin often used as a collocation point is not absolutely necessary. The odd order SRSMs with the point method and the without origin method are recommended for the reliability analysis due to their computational accuracy and efficiency. The order of SRSM has a significant influence on the results associated with the three collocation point methods. For normal random variables, the SRSM with an order equaling or exceeding the order of a performance function can produce reliability results with a sufficient accuracy. The order of SRSM should significantly exceed the order of the performance function involving strongly non-normal random variables.
-
-
Jiang, Shui-Hua,Li, Dian-Qing,Zhou, Chuang-Bing,Zhang, Li-Min Techno-Press 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.49 No.1
The stochastic response surface method (SRSM) and the response surface method (RSM) are often used for structural reliability analysis, especially for reliability problems with implicit performance functions. This paper aims to compare these two methods in terms of fitting the performance function, accuracy and efficiency in estimating probability of failure as well as statistical moments of system output response. The computational procedures of two response surface methods are briefly introduced first. Then their capabilities are demonstrated and compared in detail through two examples. The results indicate that the probability of failure mainly reflects the accuracy of the response surface function (RSF) fitting the performance function in the vicinity of the design point, while the statistical moments of system output response reflect the accuracy of the RSF fitting the performance function in the entire space. In addition, the performance function can be well fitted by the SRSM with an optimal order polynomial chaos expansion both in the entire physical and in the independent standard normal spaces. However, it can be only well fitted by the RSM in the vicinity of the design point. For reliability problems involving random variables with approximate normal distributions, such as normal, lognormal, and Gumbel Max distributions, both the probability of failure and statistical moments of system output response can be accurately estimated by the SRSM, whereas the RSM can only produce the probability of failure with a reasonable accuracy.
-
Shui-Hua Jiang,Dian-Qing Li,Chuang-Bing Zhou,Li-Min Zhang 국제구조공학회 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.49 No.1
The stochastic response surface method (SRSM) and the response surface method (RSM) are often used for structural reliability analysis, especially for reliability problems with implicit performance functions. This paper aims to compare these two methods in terms of fitting the performance function, accuracy and efficiency in estimating probability of failure as well as statistical moments of system output response. The computational procedures of two response surface methods are briefly introduced first. Then their capabilities are demonstrated and compared in detail through two examples. The results indicate that the probability of failure mainly reflects the accuracy of the response surface function (RSF) fitting the performance function in the vicinity of the design point, while the statistical moments of system output response reflect the accuracy of the RSF fitting the performance function in the entire space. In addition, the performance function can be well fitted by the SRSM with an optimal order polynomial chaos expansion both in the entire physical and in the independent standard normal spaces. However, it can be only well fitted by the RSM in the vicinity of the design point. For reliability problems involving random variables with approximate normal distributions, such as normal, lognormal, and Gumbel Max distributions, both the probability of failure and statistical moments of system output response can be accurately estimated by the SRSM, whereas the RSM can only produce the probability of failure with a reasonable accuracy.
-
-
Dou, Xue,Wang, Ren-Ben,Yan, Hong-Jiang,Jiang, Shu-Mei,Meng, Xiang-Jiao,Zhu, Kun-Li,Xu, Xiao-Qing,Mu, Dian-Bin Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.6
Objective: The objective of this study was to identify clinical predictive factors for tumor response after neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). Methods: All factors were evaluated in 88 patients with LARC treated with nCRT. After a long period of 4-8 weeks of chemoradiotherapy, 3 patients achieved clinical complete response (cCR) and thus aggressive surgery was avoided, and the remaining 85 patients underwent a curative-intent operation. The response to nCRT was evaluated by tumor regression grade (TRG) system. Results: There were 32 patients (36.4%) with good tumor regression (TRG 3-4) and 56 (63.6%) with poor tumor regression (TRG 0-2). Lymphocyte counts and ratios were higher in good response cases (P=0.01, 0.03, respectively) while neutrophil ratios and N/L ratios were higher in poor response cases (P=0.04, 0.02, respectively). High lymphocyte ratios before nCRT and good tumor regression (TRG3-4) were significantly associated with improved 5-year disease-free survival (P<0.05). Pretreatment nodal status was also significantly associated with 5-year disease-free survival and 5-year overall survival (P<0.05). Multivariate analysis confirmed that the pretreatment lymphocyte ratio and lymph nodal status were independent prognostic factors. Conclusion: Our study suggested that LARC patients with high lymphocyte ratios before nCRT would have good tumor response and high 5-year DFS and OS.
-
Liu, Fen,Wei, Wen-Qiang,Cormier, Robert T.,Zhang, Shu-Tian,Qiao, You-Lin,Li, Xin-Qing,Zhu, Sheng-Tao,Zhai, Yan-Chun,Peng, Xiao-Xia,Yan, Yu-Xiang,Wu, Li-Juan,He, Dian,He, Yan Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.4
Background: The prostaglandin-endoperoxide synthase 2 (PTGS2) and phospholipase A2 group IIA (PLA2G2A) genes encode enzymes that are involved in arachidonic acid and prostaglandin biosynthesis. Dysregulation of both genes is associated with inflammation and carcinogenesis, including esophageal squamous cell carcinoma (ESCC). We therefore hypothesized that there is an association between single nucleotide polymorphisms (SNPs) in these genes and susceptibility to ESCC. Methods: We performed a gene-wide tag SNP-based association study to examine the association of SNPs in PTGS2 and PLA2G2A with ESCC in 269 patients and 269 healthy controls from Taihangshan Mountain, Henan and Hebei Provinces, the rural area of China which has the highest incidence of esophageal cancer in the world. Thirteen tag SNPs in PLA2G2A and 4 functional SNPs in PTGS2 were selected and genotyped using a high-throughput Mass Array genotyping platform. Results: We found a modest increased risk of ESCC in subjects with the PTGS2 rs12042763 AA genotype (OR=1.23; 95% CI, 1.00-3.04) compared with genotype GG. For PLA2G2A, a decreased risk of ESCC was observed in subjects with the rs11677 CT (OR=0.51, 95%CI, 0.29-0.85) or TT genotype (OR=0.51, 95%CI, 0.17-0.96) or the T carriers (CT+TT) (OR=0.52, 95%CI, 0.31-0.85) when compared with the CC genotype. Also for PLA2G2A, rs2236771 C allele carriers were more frequent in the control group (P=0.02). Subjects with the GC (OR=0.55, 95%CI, 0.33-0.93) or CC genotype (OR=0.38, 95% CI, 0.16-0.94) or the C carriers (GC+CC) (OR=0.52, 95%CI, 0.32-0.85) showed a negative association with ESCC susceptibility. Conclusions: Our results suggest that PTGS2 and PLA2G2A gene polymorphisms may modify the risk of ESCC development.
-
Dou, Xue,Wang, Ren-Ben,Meng, Xiang-Jiao,Yan, Hong-Jiang,Jiang, Shu-Mei,Zhu, Kun-Li,Xu, Xiao-Qing,Chen, Dong,Song, Xian-Rang,Mu, Dian-Bin Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.2
Objective: The purpose of this study was to examine the role of programmed cell death 4 (PDCD4) expression in predicting tumor response to neoadjuvant chemoradiotherapy and outcomes for patients with locally advanced rectal cancer. Methods: Clinicopathological factors and expression of PDCD4 were evaluated in 92 patients with LARC treated with nCRT. After the completion of therapy, 4 cases achieved clinical complete response (cCR), and thus the remaining 88 patients underwent a standardized total mesorectal excision procedure. There were 38 patients (41.3%) with a good response (TRG 3-4) and 54 (58.7%) with a poor one (TRG 0-2). Results: Immunohistochemical staining analyses showed that patients with high expression of PDCD4 were more sensitive to nCRT than those with low PDCD4 expression (P=0.02). High PDCD4 expression before nCRT and good response (TRG3-4) were significantly associated with improved 5-year disease-free survival and 5-year overall survival (P<0.05). Multivariate analysis demonstrated that the pretreatment PDCD4 expression was an independent prognostic factor. Conclusion: Our study demonstrated that high expression of PDCD4 protein is a useful predictive factor for good tumor response to nCRT and good outcomes in patients with LARC.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
