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Earthquake safety assessment of an arch dam using an anisotropic damage model for mass concrete
Xinhua Xue,Xingguo Yang 사단법인 한국계산역학회 2014 Computers and Concrete, An International Journal Vol.13 No.5
The seismic safety of concrete dams is one of the important problems in the engineering due to the vast socio-economic disasters which may be caused by collapse of these infrastructures. The accuracy of the risk evaluation associated with these existing dams as well as the efficient design of future dams is highly dependent on a proper understanding of their behaviour due to earthquakes. This paper develops an anisotropic damage model for arch dam under strong earthquakes. The modified Drucker-Prager criterion is adopted as the failure criteria of the dynamic damage evolution of concrete. Some process fields and other necessary information for the safety evaluation are obtained. The numerical results show that the seismic behaviour of concrete dams can be satisfactorily predicted.
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Damage analysis of arch dam under blast loading
Xinhua Xue,Xingguo Yang,Wohua Zhang 사단법인 한국계산역학회 2013 Computers and Concrete, An International Journal Vol.12 No.1
This paper examines the dynamic response of an arch dam subjected to blast loading. A damage model is developed for three dimensional analysis of arch dams. The modified Drucker-Prager criterion is adopted as the failure criteria of the damage evolution in concrete. Then, Xiluodu arch dam serves as an example to simulate the failure behaviors of structures with the proposed model. The results obtained using the proposed model can reveal the reliability degree of the safe operation level of the high arch dam system as well as the degree of potential failure, providing a reliable basis for risk assessment and risk control
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Jinhua Li,Xiaoxing Su,Yinlei Wang,Wei Yang,Yu Pan,Chenggang Su,Xingguo Zhang 한국유전학회 2018 Genes & Genomics Vol.40 No.1
BTB (broad-complex, tramtrack, and bric-abrac) family proteins are characterized by the presence of a protein–protein interaction BTB domain. BTB proteins have diverse functions, including transcriptional regulation, protein degradation, chromatin remodeling, and cytoskeletal regulation. However, little is known about this gene family in tomato (Solanum lycopersicum), the most important model plant for crop species. In this study, 38 BTB genes were identified based on tomato whole-genome sequence. Phylogenetic analysis of BTB proteins in tomato revealed that SlBTB proteins could be divided into at least 4 subfamilies. The SlBTB proteins contains 1–3 BTB domains, and several other types of functional domains, including KCTD (Potassium channel tetramerization domain-containing), the MATH (meprin and TRAF homology), ANK (Ankyrin repeats), NPR1 (nonexpressor of pathogenesis-related proteins1), NPH3 (Nonphototropic Hypocotyl 3), TAZ zinc finger, C-terminal Kelch, Skp1 and Arm (Armadillo/betacatenin- like repeat) domains are also found in some tomato BTB proteins. Moreover, their expression patterns in tissues/ stages, in response to different abiotic stress treatments and hormones were also investigated. This study provides the first comprehensive analysis of BTB gene family in the tomato genome. The data will undoubtedly be useful for better understanding the potential functions of BTB genes, and their possible roles in mediating hormone cross-talk and abiotic stress in tomato as well as in some other relative species.
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Shi-lin Zhang,Gao-jian Wu,Xingguo Yang,Wan-hong Jiang,Jia-wen Zhou 대한토목학회 2018 KSCE JOURNAL OF CIVIL ENGINEERING Vol.22 No.8
The Particle Size Distribution (PSD) properties of dam granular material plays an important role in the construction process ofearth-rock dams, as it can affect the filling quality and structural safety. However, the conventional sieving method employed tocheck the PSD is labor-intensive, time-consuming and not highly accurate. In this study, a digital image-based identification methodis presented for the determination of the PSD of dam granular material, which mainly incorporates image acquisition technology, alarge database and a neural network. Digital Image Processing (DIP) technology is used to recognize the geometric size and gradingcurve of dam granular materials at a small scale, while statistical distribution models are used to determine the characteristicparameters of the grading curve and convert the graphical curve into mathematical variables. Furthermore, a large database and a BPneutral algorithm, which is improved using a genetic algorithm, are introduced as tools to reveal the implicit relationship between theDIP and sieving grading curves to correct the error of identification. A case study for the Changheba Hydropower Station is used toillustrate the implementation details of the presented method. The identification results demonstrate that the presented method canacquire and assess the gradation in spite of a degree of error, which can be decreased when more advanced DIP technologies areexplored, the amount of data in the database is increased, and a more optimized network algorithm is adopted.
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Xu Zhiyang,Zhou Kaixiang,Wang Zhenni,Liu Yang,Wang Xingguo,Gao Tian,Xie Fanfan,Yuan Qing,Gu Xiwen,Liu Shujuan,Xing Jinliang 생화학분자생물학회 2023 Experimental and molecular medicine Vol.55 No.-
Ovarian cancer (OC) is the most lethal gynecologic tumor and is characterized by a high rate of metastasis. Challenges in accurately delineating the metastatic pattern have greatly restricted the improvement of treatment in OC patients. An increasing number of studies have leveraged mitochondrial DNA (mtDNA) mutations as efficient lineage-tracing markers of tumor clonality. We applied multiregional sampling and high-depth mtDNA sequencing to determine the metastatic patterns in advanced-stage OC patients. Somatic mtDNA mutations were profiled from a total of 195 primary and 200 metastatic tumor tissue samples from 35 OC patients. Our results revealed remarkable sample-level and patient-level heterogeneity. In addition, distinct mtDNA mutational patterns were observed between primary and metastatic OC tissues. Further analysis identified the different mutational spectra between shared and private mutations among primary and metastatic OC tissues. Analysis of the clonality index calculated based on mtDNA mutations supported a monoclonal tumor origin in 14 of 16 patients with bilateral ovarian cancers. Notably, mtDNA-based spatial phylogenetic analysis revealed distinct patterns of OC metastasis, in which a linear metastatic pattern exhibited a low degree of mtDNA mutation heterogeneity and a short evolutionary distance, whereas a parallel metastatic pattern showed the opposite trend. Moreover, a mtDNA-based tumor evolutionary score (MTEs) related to different metastatic patterns was defined. Our data showed that patients with different MTESs responded differently to combined debulking surgery and chemotherapy. Finally, we observed that tumor-derived mtDNA mutations were more likely to be detected in ascitic fluid than in plasma samples. Our study presents an explicit view of the OC metastatic pattern, which sheds light on efficient treatment for OC patients.
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