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RISS 인기검색어
- 검색키워드
- 저자 : Guohua Shen (검색결과 5 건)
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Novel Method for Calculating the Effective Stress Coefficient in a Tight Sandstone Reservoir
Yinghao Shen,Guohua Luan,Haiyong Zhang,Qian Liu,Junjing Zhang,Hongkui Ge 대한토목학회 2017 KSCE JOURNAL OF CIVIL ENGINEERING Vol.21 No.6
Determining the influence of effective stress on rock deformation is essential for geotechnical stability analysis in oil and gas production. There is no universal effective stress coefficient for all rock properties, and different values of effective stress coefficient apply for different physical quantities (Gurevich, 2004). Although the effective stress law and its application is not new, frequently overlooked or misapplied. Hence, a novel method was proposed for measuring and calculating the effective stress coefficient in this work. Firstly, pore compressibility under different confine pressure values was measured using reservoir fluid or experimental fluid. Secondly, effective stress was calculated by comparing pore compressibility under different confine pressure and then, the range of effective stress coefficients was determined eventually. Finally, the reliability of the proposed method was validated via the stresssensitive curves of tight sandstone core samples and by comparing the results with those of two other calculation methods for the effective stress coefficient. This work suggests that the stress-sensitive curves of the two core samples from the same location and with similar physical properties have given similar effective stress coefficient (η = 0.201) calculated using the proposed method, which indicates that the calculation is reasonable. The comparison of the proposed method with other methods also indicate that the proposed technique is reliable.
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Xie Guohua,Dong ping,Chen Hui,Xu Ling,Liu Yi,Ma Yanhui,Zheng Yingxia,Yang Junyao,Zhou Yunlan,Chen Lei,Shen Lisong 생화학분자생물학회 2021 Experimental and molecular medicine Vol.53 No.-
ATF3 has been reported to be dysregulated in various cancers and involved in various steps of tumorigenesis. However, the mechanisms underlying the abnormal expression of ATF3 and its biological function in gastric cancer (GC) have not been well investigated. Here, we report ATF3 as one of the key regulators of GC development and progression. Patients with low ATF3 expression had shorter survival and a poorer prognosis. In vitro and in vivo assays investigating ATF3 alterations revealed a complex integrated phenotype that affects cell growth and migration. Strikingly, high-throughput sequencing and microarray analysis of cells with ATF3 silencing or of ATF3-low GC tissues indicated alterations in the Wnt signaling pathway, focal adhesions and adherens junctions. Mechanistically, the expression of β-catenin and cell migration inducing hyaluronidase 1 (CEMIP) was significantly upregulated in GC cells with downregulated ATF3, which was synergistically repressed by the β-catenin/TCF3 signaling axis and noncoding RNA miR-17-5p and HOXA11-AS. In addition, we found that WDR5 expression was promoted by TCF3 and is involved in miR-17-5p and HOXA11-AS activation in GC cells. Taken together, our findings revealed the mechanism of ATF3 downregulation and its biological role in regulating the expression of Wnt signaling-related genes during GC progression, suggesting new informative biomarkers of malignancy and therapeutic directions for GC patients.
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Cohesion Metrics for Evaluating Semantic Web Ontologies
Lili Liao,Guohua Shen,Zhiqiu Huang,Fei Wang 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.11
With the widespread development of the Semantic Web, large-scale ontologies are being developed in more real-world applications to represent and integrate knowledge and data. There is an increasing need for measuring the cohesion of these ontologies for better understanding, maintenance, reuse and integration. The ontology cohesion metrics proposed in this paper can be used as a very useful complementarity of existing ontology cohesion metrics. Specifically, we first propose a set of evaluation metrics to measure the cohesion of ontologies based on directed acyclic graph. Following the framework for software measurement validation, we then evaluate the effectiveness of the proposed metrics theoretically. Finally, we conduct experiments using a set of classical ontologies; the results show that the proposed metrics are reasonable and effective.
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Research on AADL Model for Qualitative Safety Analysis of Embedded Systems
Yinling Liu,Guohua Shen,Fei Wang,Jia Si,Zi Wang 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.6
As embedded software is taking an important part in safety critical filed, how to ensure the safety of safety-critical software has recently become a research focus. Developing safety-critical and highly reliable systems almost always includes significant emphasis on safety analysis and risk assessment. There have been substantial improvements in automation and formalization of other aspects of critical system engineering. However, safety analysis and risk assessment are still largely manual and informal activities and tool support is limited. In this paper, we propose a qualitative safety analysis method of embedded system based on AADL (Architecture Analysis & Design Language) model. Firstly, we extend the Error Model Annex with the R-FMSE (Risk-based Failure Mode Safety Effect) property to express the failure mode formally. Then, we give a detail illustration for qualitative safety analysis based on AADL model. Thirdly, we give a algorithm to develop a R-FMSE analysis Eclipse plug-in to realize the automation of the method. On using the Isolette system (an infant incubator), a case study is demonstrated the feasibility of this method.
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Weighing the Evidence of Dividend Initiations
Tianyu Zhu,Guohua Ma,Xu-Shen Zhou 사람과세계경영학회 2011 Global Business and Finance Review Vol.16 No.1
This paper analyzes post-event stock performance based on the strength and the weight of evidence of dividend initiations. The strength refers to how extreme the evidence is; the weight refers to how credible the evidence is. Griffin and Tversky’s (1992) experiments show that people are underconfident when presented with low strength and high weight information and overconfident with high strength and low weight information. This study shows that Griffin and Tversky’s results extend to dividend initiation as well. Portfolios with high strength and low weight overreact to dividend announcement, while portfolios with low strength and high weight underreact. The empirical results in this paper show that the strength-weight model can explain the underreaction-overreaction puzzle and suggests that psychological biases may impact stock performance.
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