Study on the Social Adaptation of Chinese Children with Down Syndrome

Yan-xia Wang,Shan-shan Mao,Chun-hong Xie,Yu-feng Qin,Zhi-wei Zhu,Jian-ying Zhan,Jie Shao,Rong Li,Zheng-yan Zhao 연세대학교의과대학 2007 Yonsei medical journal Vol.48 No.3

Optimization of variable blank holder force based on a sharing niching RBF neural network and an improved NSGA-II algorithm

Yan-Min Xie,Wei Tang,Fei Zhang,Bei-Bei Pan,Yaopeng Yue,Meiqiang Feng 한국정밀공학회 2019 International Journal of Precision Engineering and Vol.20 No.2

Variable blank holder force (VBHF) is an important process parameter in sheet metal forming. The purpose of this study is to propose a sharing niching radial basis function (SNRBF) neural network for VBHF optimization. Two methods are put forward to improve the prediction accuracy of a RBF neural network. (1) A RBF neural network is trained by a sharing niching technique to achieve global optimal nodes. (2) In Latin hypercube design, Spearman correlation analysis is employed to decrease sample correlation. In addition, in order to improve the performance of the non-dominated sorting genetic algorithm (NSGA-II), excellent individuals in each class of non-dominated individuals are selected by employing immune operators. Based on the Spearman correlation analysis and the Latin hypercube method, training samples are generated and numerical simulations are performed for a double C part. The surrogate models between VBHF and forming quality are constructed by a SNRBF neural network. The Pareto frontier solutions are achieved by employing the improved NSGA-II algorithm. Grey relational analysis is applied to determine the optimal VBHF loading trajectory. The results show decreased wrinkles in the optimized forming part and greater uniformity in the plastic deformation by employing the optimized VBHF, thereby leading to improvement in the forming quality of the double C.

Transcriptional Analysis of 10 Selected Genes in a Model of Penicillin G Induced Persistence of Chlamydophila psittaci in HeLa Cells

( Yan Qun Hu ),( Li Li Chen ),( Chuan Wang ),( Ya Feng Xie ),( Zhi Xi Chen ),( Liang Zhuan Liu ),( Ze Hong Su ),( Yi Mou Wu ) 한국미생물 · 생명공학회 2015 Journal of microbiology and biotechnology Vol.25 No.8

Chlamydophila psittaci is an important intracellular pathogen. Persistent infection is an important state of the host-parasite interaction in this chlamydial infection, which plays a significant role in spreading the organism within animal populations and in causing chronic chlamydiosis and serious sequelae. In this study, a C. psittaci persistent infection cell model was induced by penicillin G, and real-time quantitative PCR was used to study the transcriptional levels of 10 C. psittaci genes (dnaA, dnaK, ftsW, ftsY, grpE, rpsD, incC, omcB, CPSIT_0846, and CPSIT_0042) in acute and penicillin-G-induced persistent infection cultures. Compared with the acute cultures, the penicillin-G-treated cultures showed a reduced chlamydial inclusion size and a significantly decreased number of elementary body particles. Additionally, some enlarged aberrant reticulate body particles were present in the penicillin- G-treated cultures but not the acute ones. The expression levels of genes encoding products for cell division (FtsW, FtsY) and outer membrane protein E encoding gene (CPSIT_0042) were downregulated (p < 0.05) from 6 h post-infection onward in the persistent infection cultures. Also from 6 h post-infection, the expression levels of DnaA, DnaK, IncC, RpsD, GrpE, and CPSIT_0846 were upregulated (p < 0.05); however, the expression level of OmcB in the persistent infection was almost the same as that in the acute infection (p > 0.05). These results provide new insight regarding molecular activities that accompany persistence of C. psittaci, which may play important roles in the pathogenesis of C. psittaci infection.

A Generalized Hidden Markov Model and Its Applications in Recognition of Cutting States

Feng-Yun Xie,You-Min Hu,Bo Wu,Yan Wang 한국정밀공학회 2016 International Journal of Precision Engineering and Vol.17 No.11

In the traditional hidden Markov model (HMM) for statistical learning and classification, aleatory uncertainty because of randomness and epistemic uncertainty that is due to the lack of knowledge are not differentiated. In this paper, a generalized hidden Markov model (GHMM) in the context of generalized interval probability theory is proposed. The parameters of GHMM are in the form of generalized interval probability, which provides a concise representation for the two kinds of uncertainty simultaneously. The generalized versions of the forward-backward, Viterbi, and Baum-Welch algorithms in GHMM are developed. The proposed algorithms take advantage of the algebraic property in the generalized interval probability. These algorithms provide an efficient approach to train the GHMM. The trained GHMM is used for state recognition with the criterion of maximum log-likelihood. A case study on recognizing the cutting states in manufacturing processes is provided to demonstrate the application of GHMM. The interval forms of the cutting signal are considered as the inputting of GHMM. The cutting states are recognized based on the learning algorithm of GHMM. With the two uncertainty components quantified, the reliability of GHMM in state recognition is superior to that of HMM.

An Efficient Parallel Infilling Strategy and Its Application in Sheet Metal Forming

Yan-Min Xie,Yuan-Heng Guo,Fei Zhang,Yue-Peng Yue,Mei-Qiang Feng,Jiang-Bo Zhao 한국정밀공학회 2020 International Journal of Precision Engineering and Vol.21 No.8

Infilling strategies play an important role in kriging based optimization, especially when computationally expensive simulations are involved. In order to improve the efficiency of constructing a high-precision kriging model, an improved expected improvement criterion (IEI) and a parallel infilling strategy are proposed based on the maximum expected improvement (EI) criterion. In the proposed parallel infilling strategy, new sample points are generated by employing IEI criterion coupled with EI criterion. During the improved sampling process, redundant and pseudo sample are deleted in order to avoid failure of constructing a kriging model. An improved weighted particle swarm optimization (WPSO) algorithm is proposed to improve optimization efficiency. The proposed parallel infilling strategy is applied to nonlinear function optimization and variable blank holder force (VBHF) optimization in a double-c stamped part. Based on the LHD and software DYNAFORM, kriging models between the VBHF and forming quality are constructed. Compared with the initial kriging models, the meat relative error of kriging models with the proposed parallel infilling strategy for the wrinkling and average thinning rate are reduced by 95% and 55%, respectively. The optimal VBHF is obtained by the WPSO. The results show that, cracking has been completely eliminated and wrinkling has been decreased, greatly improving the forming quality of the double-c stamped part.

Austenite Grain Growth Behavior of 30BF Steel Before Rough Rolling

Yong‑feng Chen,Jian‑bo Xie,Yan‑xin Wu,Jian‑xun Fu 대한금속·재료학회 2019 METALS AND MATERIALS International Vol.25 No.4

To investigate the eff ect of heat treatment on the grain size of austenite in 30BF steel, the comparisons of the morphologiesand sizes of austenite grains between heating samples were made with a high-temperature electric resistance furnace, andthe austenite growth models were built with method of mathematics. The results show that most grains in original specimenwith the sizes below 70 μm uniformly distributed. At a heating rate ( v ) of 10 °C/s, the grain size ( d ) value under a certain time( t ) increased by 60–100 μm with raising temperature ( T ) from 850 to 1100 °C, whereas the d value under a certain T merelyincreased by 70–120 μm with raising time to 60 min. Under v = 0.1 °C/s, T = 850 °C, and t = 0 s, the occupied ratio of grainswith sizes of 40–50 μm was 0.165, whereas at 900 °C, the occupied ratio was 0.125. The evolutions of ln (d5.8− d5.80 ) with1/ T were in negative linear correlations, whereas the ln (d5.8− d5.80 ) with ln t were in positive linear correlations. To sum up,the grain growth behavior of steel was elucidated.

Transfer function modeling of structural vibration of complex aerospace structures based on finite element analysis

Xin Feng Wu,Yongjun Lei,Daokui Li,Yan Xie 대한기계학회 2013 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.27 No.5

An approach to establish the transfer function of complex aerospace structures to express their structural vibration behavior through finite element modeling is proposed. The fundamental idea of the approach is to characterize the vibrations of complicated structures through the transfer function model for an advanced control system design, while the parameters of the model are identified from the response data obtained through finite element analysis. The proposed method comprises four steps, namely, finite element modeling and validation, data preparation based on the finite element analysis, parameter identification of the transfer function, and model validation,and is presented from both frequency and time domains. The developed approach is applied to a cantilever beam, a strap-on launch vehicle,and a local part of the aerospace structure to demonstrate the method’s effectiveness and satisfactory performance.

Computed-Tomography-Determined Sarcopenia is a Useful Imaging Biomarker for Predicting Postoperative Outcomes in Elderly Colorectal Cancer Patients

Hailun Xie,Yizhen Gong,Jiaan Kuang,Ling Yan,Guotian Ruan,Shuangyi Tang,Feng Gao,Jialiang Gan 대한암학회 2020 Cancer Research and Treatment Vol.52 No.3

Purpose This study aimed to establish whether computed tomography (CT)–determined sarcopenia is a useful imaging biomarker for postoperative outcome in elderly colorectal cancer (CRC) patients, and construct sarcopenia-based nomograms to predict individual outcomes after surgery. Materials and Methods CT imaging data of 298 elderly CRC patients who underwent surgery in 2012-2014 were retrospectively analyzed. Skeletal muscle mass was determined by CT, and sarcopenia was diagnosed based on the optimal cutoff value determined by X-tile program. The correlation between sarcopenia and risk of preoperative nutrition and postoperative complications was evaluated. A Cox proportional hazards model was used to determine survival predictors. Sarcopenia-based nomograms were developed based on multivariate analysis, and calibrated using concordance index and calibration curves. Results A total 132 patients (44.3%) had sarcopenia based on the optimum cutoff values (29.9 cm2/m2 for women and 49.5 cm2/m2 for men). Sarcopenia was an independent risk factor for preoperative nutrition (p < 0.001; odds ratio [OR], 3.405; 95% confidence interval [CI], 1.948 to 5.954) and postoperative complications (p=0.008; OR, 2.192; 95% CI, 1.231 to 3.903). Sarcopenia was an independent predictor for poor progression-free survival (p < 0.001; hazard ratio [HR], 2.175; 95% CI, 1.489 to 3.179) and overall survival (p < 0.001; HR, 2.524; 95% CI, 1.721 to 3.703). Based on multivariate analysis, we produced four nomograms that had better predictive performance. Conclusion CT-determined sarcopenia is a useful imaging biomarker for predicting preoperative nutritional risk, postoperative complications, and long-term outcomes in elderly CRC patients. The sarcopenia-based nomograms can provide a scientific basis for guiding therapeutic schedule and follow-up strategies.

Genome‑wide association analysis of salt tolerance QTLs with SNP markers in maize (Zea mays L.)

Yonghong Xie,Yan Feng,Qi Chen,Feike Zhao,Shuijuan Zhou,Ying Ding,Xianliang Song,Ping Li,Baohua Wang 한국유전학회 2019 Genes & Genomics Vol.41 No.10

Background Salt-tolerant breeding of maize has great significance to the development and utilization of saline–alkaline soil and the maintenance of grain security. Genome-wide association study (GWAS) has been widely used in maize genetics and breeding. Objective To discover new salt-tolerant genes in maize by association analysis, which can provide technical supports for the innovation and genetic improvement of salt-tolerant germplasm resources in maize. Methods Totally 150 maize inbred lines were genotyped with a high-density chip. GWAS was carried out to identify the significant single nucleotide polymorphisms (SNPs) which were associated with maize salt tolerance. Totally 34,972 SNPs with high quality and diversity were selected from 56,110 SNP markers, which were distributed on 10 chromosomes of maize. The GLM algorithm in TASSEL5.2 was used to analyze the five traits related to salt tolerance. Results Using a strict LOD threshold of 4.5, totally 7 SNP loci were identified, which were significantly correlated with plant height change rate and fresh weight change rate. The high density fingerprints of 150 inbred lines were clustered by TASSEL5.2 software to construct genetic clustering map to estimate the genetic distance and the subgroups. The 150 maize inbred lines were divided into two groups: SS group and NSS group, and the SNP loci of the salt-tolerant index showed difference in chromosome distribution. Based on previous studies, we screened 8 candidate genes for salt tolerance in maize and four of them were further validated by real-time quantitative PCR. Conclusion Totally 7 SNP loci and 8 candidate genes related to salt tolerance in maize were identified, which will be of special value in molecular breeding of salt-tolerant maize.

Proposals for flexural capacity prediction method of externally prestressed concrete beam

Wu-Tong Yan,Liang-Jiang Chen,Bing Han,Feng Wei,Hui-Bing Xie,Jia-Ping Yu 국제구조공학회 2022 Structural Engineering and Mechanics, An Int'l Jou Vol.83 No.3

Flexural capacity prediction is a challenging problem for externally prestressed concrete beams (EPCBs) due to the unbonded phenomenon between the concrete beam and external tendons. Many prediction equations have been provided in previous research but typically ignored the differences in deformation mode between internal and external unbonded tendons. The availability of these equations for EPCBs is controversial due to the inconsistent deformation modes and ignored secondorder effects. In this study, the deformation characteristics and collapse mechanism of EPCB are carefully considered, and the ultimate deflected shape curves are derived based on the simplified curvature distribution. With the compatible relation between external tendons and the concrete beam, the equations of tendon elongation and eccentricity loss at ultimate states are derived, and the geometric interpretation is clearly presented. Combined with the sectional equilibrium equations, a rational and simplified flexural capacity prediction method for EPCBs is proposed. The key parameter, plastic hinge length, is emphatically discussed and determined by the sensitivity analysis of 324 FE analysis results. With 94 collected laboratory-tested results, the effectiveness of the proposed method is confirmed, and comparisons with the previous formulas are made. The results show the better prediction accuracy of the proposed method for both stress increments and flexural capacity of EPCBs and the main reasons are discussed.