Nature of Controlling Stake, R&D Investment and Corporate Performance-Based on Empirical Data of Listed Companies in China

Zhang Guiling 보안공학연구지원센터 2016 International Journal of u- and e- Service, Scienc Vol.9 No.2

This article makes an empirical analysis on influence of R&D investment on corporate performance under different nature of controlling stake by applying multivariate regression analysis and ordinary least square and taking China A-share listed companies as samples. The study finds that for the whole sample enterprises and non-state-controlled enterprises, current and last R&D investment have significant positive influence on corporate performance; for state-controlled enterprises, current and last R&D investment have positive influence on corporate performance but not significant.

Study on Influencing Factors for Investment Strategy of Chinese Cultural Industry

Zhang Guiling 보안공학연구지원센터 2016 International Journal of u- and e- Service, Scienc Vol.9 No.10

This paper analyzes relations of influence of the four factors, including corporate external financing capacity, governance mechanism, systems and talents environment, on longsighted investment strategy for cultural industry using the least square method of regression analysis by data samples. The study finds enhancing corporate external financing capacity, improving its governance mechanism, optimizing its systems and talents environment for a competitive promotion and a strategic investment transformation from shortsighted to longsighted for culture industry.

Real-time Evaluation Mechanism Based on Double Evidence Classification of User Behavior

Jiale Zhang,Guiling Zhang,Xiufang Zhang 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.12

With the development of trusted network, the research of trusted evaluation mechanism of user behavior is a hotpot in the network security. In order to solve the problems of subjectivity, limitations and static in traditional trusted network user behavior evaluation models, we have to find a real-time and dynamic evaluation method for user behavior. In this paper, the authors construct a real-time evaluation mechanism based on double evidence classification of user behavior (DEC-UB). The evaluation mechanism includes the process classification and characteristic classification of user behavior evidence, which makes the user behavior evidence of any time can be directly involved in the trust evaluation, and the evaluation result is more comprehensive and accurate. Simulation experiments have evaluated the three kinds of user behaviors based on the DEC-UB, and compared them with the other two kinds of trust evaluation methods of user behavior, the results show that the proposed methods can evaluate the user's behavior comprehensively, accurately and dynamically in complex network environments, and the results are more realistic.

Fecal Microbiota Transplantation (FMT) Alleviates Experimental Colitis in Mice by Gut Microbiota Regulation

Zhang Wanying,Zou Guiling,Li Bin,Du Xuefei,Sun Zhe,Sun Yu,Jiang Xiaofeng 한국미생물·생명공학회 2020 Journal of microbiology and biotechnology Vol.30 No.8

Inflammatory bowel disease (IBD) is an increasing global burden and a predisposing factor to colorectal cancer. Although a number of treatment options are available, the side effects could be considerable. Studies on fecal microbiota transplantation (FMT) as an IBD intervention protocol require further validation as the underlying mechanisms for its attenuating effects remain unclear. This study aims to demonstrate the ameliorative role of FMT in an ulcerative colitis (UC) model induced by dextran sulfate sodium (DSS) and elucidate its relative mechanisms in a mouse model. It was shown that FMT intervention decreased disease activity index (DAI) levels and increased the body weight, colon weight and colon length of experimental animals. It also alleviated histopathological changes, reduced key cytokine expression and oxidative status in the colon. A down-regulated expression level of genes associated with NF-κB signaling pathway was also observed. The results of 16S rRNA gene sequencing showed that FMT intervention restored the gut microbiota to the pattern of the control group by increasing the relative abundance of Firmicutes and decreasing the abundances of Bacteroidetes and Proteobacteria. The relative abundances of the genera Lactobacillus, Butyricicoccus, Lachnoclostridium, Olsenella and Odoribacter were upregulated but Helicobacter, Bacteroides and Clostridium were reduced after FMT administration. Furthermore, FMT administration elevated the concentrations of SCFAs in the colon. In conclusion, FMT intervention could be suitable for UC control, but further validations via clinical trials are recommended.

Analysis and simulation of micro-groove generation process in ultrasonic elliptical vibration turning

Chen Zhang,Kornel F. Ehmann,Yingguang Li,Guiling Shi 한국생산제조학회 2014 한국생산제조시스템학회 학술발표대회 논문집 Vol.2014 No.9(2)

Graph Theory-based Approach for Partial Topology Identification of Stochastic Multi-group Models With Multiple Dispersal

Chunmei Zhang,Dan Xia,Huiling Chen,Guiling Chen 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.9

This paper is mainly concerned with partial topology identification of stochastic multi-group models with multiple dispersals (SMGMMD) by adaptive pinning control. By using a graph-theoretic approach and adaptive synchronization techniques, some sufficient criteria for partial topology identification of SMGMMD with time delay are obtained. Meanwhile, the partial topological structures of SMGMMD without time delay and the whole topological structures of SMGMMD can also be identified successfully. Finally, coupled Lorenz systems with time delay are identified to demonstrate the feasibility and effectiveness of theoretical results.

Preparation of N-Doped Graphene by Hydrothermal Method and Interpretation of N-Doped Mechanism

Yan Shang,Huizhu Xu,Mingyue Li,Guiling Zhang 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2017 NANO Vol.12 No.2

Nitrogen-doped graphene (NG) was generated by hydrothermal method, using GO as the raw material and formamide as the reducing-doping source. The composite material was characterized by Fourier transform infrared (FTIR) spectrum, X-ray diffraction (XRD) spectrum, X-ray photoelectron spectroscopy (XPS). The results showed that Nitrogen was successfully doped in the graphene. Through regulating the reaction temperature, time and the ratio of graphite oxide and formamide, the different nitrogen contents were obtained, the highest nitrogen content was 5.67%. NG was also synthesized by urea or ammonia, characterizing by XPS. The characterization results showed that for taking urea and ammonia as nitrogen source, pyrrolic-N was the main form of nitrogen existing, taking formamide as a nitrogen, pyridinic-N was the main form of nitrogen existing. Based on these experimental results by different nitrogen source, the N-doped graphene mechanism was interpreted.

Characterization of the Hormone and Stress-Induced Expression of FaRE1 Retrotransposon Promoter in Strawberry

pinghe,Yue Ma,Hongyan Dai,Linguang Li,Yuexue Liu,He Li,Guiling Zhao,Zhihong Zhang 한국식물학회 2012 Journal of Plant Biology Vol.55 No.1

Retrotransposons are the most abundant mobile elements in the plant genome and seem to play an important role in genome reorganization induced by environmental challenges. Their success in this function depends on the ability of their promoters to regulate plant adaptation to biotic and abiotic stresses. In this study, the promoter region of FaRE1 was amplified in the strawberry genome, and promoter::GUS fusion was constructed. We produced transgenic strawberry plants carrying FaRE1 promoter::GUS-fusion genes, and monitored GUS reporter activity. Histochemical and fluorimetric GUS analysis these plants showed the characteristics of the FaRE1 promoter were activated by either hormones treatments with ABA, NAA,and 2,4-D or cold stress. In addition, we found the GUS reporter was activated in the leaves of transgenic strawberry plants using 5-azaC. These results suggest that the promoter of FaRE1 may act as different signal transduction pathways,allowing FaRE1 retrotransposon to be activated in response to multiples challenges.

Feasibility of a Clinical-Radiomics Model to Predict the Outcomes of Acute Ischemic Stroke

Zhou Yiran,Wu Di,Yan Su,Xie Yan,Zhang Shun,Lv Wenzhi,Qin Yuanyuan,Liu Yufei,Liu Chengxia,Lu Jun,Li Jia,Zhu Hongquan,Liu Weiyin Vivian,Liu Huan,Zhang Guiling,Zhu Wenzhen 대한영상의학회 2022 Korean Journal of Radiology Vol.23 No.8

Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses. Results: Age, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825–0.910) in the training cohort and 0.890 (0.844–0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness. Conclusion: The clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcome