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- SourceAvailable from: Kyung-Duck Suh[Show abstract] [Hide abstract]
ABSTRACT: In this paper, a hybrid artificial neural network (ANN) model is constructed to estimate the stability number of rock armor using the experimental data of Van der Meer (1988). Among the eleven input parameters in the experiment, the six parameters each of which is well distributed in a certain range are transformed into six principal components (PCs) by using a principal component analysis (PCA), which are then used as the input variables of the ANN. The remaining five parameters that vary among several different values (e.g. number of waves of 1000 or 3000) are directly used as the input variables of the ANN. Since the orthogonality of the PCs prevents the duplication of information by separating the variables into several independent components while maintaining the critical information in them, the hybrid ANN model combined with the PCA gives better results compared with the conventional ANN models.Procedia Engineering 12/2015; 116(1):149-154. DOI:10.1016/j.proeng.2015.08.276
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ABSTRACT: Progression to metastasis is the leading cause of most cancer-related mortality; however, much remains to be understood about what facilitates the spread of tumor cells. In the present study, we describe a novel pathway in breast cancer that regulates epithelial-to-mesenchymal transition (EMT), motility, and invasiveness. We examined nuclear factor I-C (NFI-C) expression in MCF10A human breast epithelial cells, MCF7 non-invasive breast cancer cells, and MDA-MB231 invasive breast cancer cells by real-time PCR and western blotting. To investigate the loss- and gain-function of NFI-C, we determined whether NFI-C regulated KLF4 expression by real-time PCR, western blotting, and promoter assay. To understand the biological functions of NFI-C, we observed cell invasion, migration, adhesion in human tumor cells by transwell assay, wound healing assay, quantitative RT-PCR, cell adhesion assay, western blotting, and immunohistochemistry. We identified the downstream factors of NFI-C, such as KLF4 and E-cadherin, which play roles in EMT. NFI-C is expressed in normal mammary gland or noninvasive breast cancer cells with epithelial characteristics. NFI-C overexpression induced expression of KLF4 and E-cadherin, but not Slug, in breast cancer cells. NFI-C bound directly to the KLF4 promoter and stimulated KLF4 transcriptional activity, thereby regulating E-cadherin expression during tumorigenesis. Cells overexpressing NFI-C maintained their epithelial differentiation status, which could drive mesenchymal-epithelial transition (MET) via the NFI-C-KLF4-E-cadherin axis in breast cancer cells. Consequently, NFI-C suppressed EMT, migration, and invasion in breast cancer cells. Our study reveals a novel signaling pathway that is important during breast cancer tumorigenesis: the NFI-C-KLF4-E-cadherin pathway. The results indicate the important role of NFI-C in regulating KLF4 during tumorigenesis.BMC Cancer 12/2015; 15(1):1118. DOI:10.1186/s12885-015-1118-z
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ABSTRACT: The effective cross sections (XSs) in the direct whole core calculation code nTRACER are evaluated by the equivalence theory-based resonance-integral-table method using the WIMS-based library as an alternative to the subgroup method. The background XSs, as well as the Dancoff correction factors, were evaluated by the enhanced neutron-current method. A method, with pointwise microscopic XSs on a union-lethargy grid, was used for the generation of resonance-interference factors (RIFs) for mixed resonant absorbers. This method was modified by the intermediate-resonance approximation by replacing the potential XSs for the non-absorbing moderator nuclides with the background XSs and neglecting the resonance-elastic scattering. The resonance-escape probability was implemented to incorporate the energy self-shielding effect in the spectrum. The XSs were improved using the proposed method as compared to the narrow resonance infinite mass-based method. The RIFs were improved by 1% in 235U, 7% in 239Pu, and >2% in 240Pu. To account for thermal feedback, a new feature was incorporated with the interpolation of pre-generated RIFs at the multigroup level and the results compared with the conventional resonance-interference model. This method provided adequate results in terms of XSs and k-eff. The results were verified first by the comparison of RIFs with the exact RIFs, and then comparing the XSs with the McCARD calculations for the homogeneous configurations, with burned fuel containing a mixture of resonant nuclides at different burnups and temperatures. The RIFs and XSs for the mixture showed good agreement, which verified the accuracy of the RIF evaluation using the proposed method. The method was then verified by comparing the XSs for the virtual environment for reactor application-benchmark pin-cell problem, as well as the heterogeneous pin cell containing burned fuel with McCARD. The method works well for homogeneous, as well as heterogeneous configurations.Nuclear Engineering and Technology 10/2015; DOI:10.1016/j.net.2015.09.001
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