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ABSTRACT: In this study, added resistance was evaluated experimentally and numerically in four draft conditions: full load, ballast, and two intermediate conditions between the full load and ballast conditions. A series of towing-tank experiments for ship motion and added resistance in the four draft conditions was carried out in head sea conditions. The ship motion and added resistance were measured for the wavelength to ship length ratios of 0.4–2.0. In the numerical approach, two different seakeeping analyses were adopted: the strip method and Rankine panel method. For the strip method, analytical or empirical corrections were added in the short wave condition. The experimental and numerical results for the heave and pitch motions and the added resistance were compared for the four draft conditions. The numerical motion responses of both approaches showed good agreement with the experimental data. For the added resistance, the Rankine panel method showed reasonable results in all draft conditions. In contrast, the strip method showed poor results except in the full load condition. Based on the comparison of the experimental and numerical results, the potential application of the two numerical methods to various draft conditions was considered.
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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.
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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.
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