Structure design of the ship pedestal based on topology optimization

The optimization study of the ship pedestal structure is of great significance to the lightweight and the anti-shock performance of the ship. Therefore, the TOSCA software is used to design the ship pedestal in topology optimization. of a ship's pedestal. By setting the load, determining the objective function, selecting the constraints, and selecting the optimization region, the topology-optimized pedestal structure is obtained. Then, the structure was redesigned to determine the final structure of the pedestal. Finally, compared with the traditional pedestal for modal and anti-shock performance, it is verified that the designed pedestal in this paper has improved performance over the traditional one

A knee-point-based evolutionary algorithm using weighted subpopulation for many-objective optimization

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Among many-objective optimization problems (MaOPs), the proportion of nondominated solutions is too large to distinguish among different solutions, which is a great obstacle in the process of solving MaOPs. Thus, this paper proposes an algorithm which uses a weighted subpopulation knee point. The weight is used to divide the whole population into a number of subpopulations, and the knee point of each subpopulation guides other solutions to search. Besides, Additionally, the convergence of the knee point approach can be exploited, and the subpopulation-based approach improves performance by improving the diversity of the evolutionary algorithm. Therefore, these advantages can make the algorithm suitable for solving MaOPs. Experimental results show that the proposed algorithm performs better on most test problems than six other state-of-the-art many-objective evolutionary algorithms

Deep Learning Approach for Automated Thickness Measurement of Epithelial Tissue and Scab using Optical Coherence Tomography

Significance: In order to elucidate therapeutic treatment to accelerate wound healing, it is crucial to understand the process underlying skin wound healing, especially re-epithelialization. Epidermis and scab detection is of importance in the wound healing process as their thickness is a vital indicator to judge whether the re-epithelialization process is normal or not. Since optical coherence tomography (OCT) is a real-time and non-invasive imaging technique that can perform a cross-sectional evaluation of tissue microstructure, it is an ideal imaging modality to monitor the thickness change of epidermal and scab tissues during wound healing processes in micron-level resolution. Traditional segmentation on epidermal and scab regions was performed manually, which is time-consuming and impractical in real-time.Aim: Develop a deep-learning-based skin layer segmentation method for automated quantitative assessment of the thickness of in-vivo epidermis and scab tissues during a time course of healing within a murine model.Approach: Five convolution neural networks (CNN) were trained using manually labelled epidermis and scab regions segmentation from 1000 OCT B-scan images (assisted by its corresponding angiographic information). The segmentation performance of five segmentation architectures were compared qualitatively and quantitatively for validation set.Results: Our results show higher accuracy and higher speed of the calculated thickness compared with human experts. The U-Net architecture represents a better performance than other deep neural network architectures with a 0.894 at F1-score, 0.875 at mean IOU, 0.933 at dice similarity coefficient, and 18.28 μm at an average symmetric surface distance. Furthermore, our algorithm is able to provide abundant quantitative parameters of the wound based on its corresponding thickness mapping in different healing phases. Among them, normalized epidermis thickness is recommended as an essential hallmark to describe the re-epithelialization process of the mouse model.Conclusions: The automatic segmentation and thickness measurements within different phases of wound healing data demonstrates that our pipeline provides a robust, quantitative, and accurate method for serving as a standard model for further research into effect of external pharmacological and physical factors

Associations of IL-4, IL-4R, and IL-13 Gene Polymorphisms in Coal Workers' Pneumoconiosis in China: A Case-Control Study

Background: The IL-4, IL-4 receptor (IL4R), and IL-13 genes are crucial immune factors and may influence the course of various diseases. In the present study, we investigated the association between the potential functional polymorphisms in IL-4, IL-4R, and IL-13 and coal workers ’ pneumoconiosis (CWP) risk in a Chinese population. Methods: Six polymorphisms (C-590T in IL-4, Ile50Val, Ser478Pro, and Gln551Arg in IL-4R, C-1055T and Arg130Gln in IL-13) were genotyped and analyzed in a case-control study of 556 CWP and 541 control subjects. Results: Our results revealed that the IL-4 CT/CC genotypes were associated with a significantly decreased risk of CWP (odd

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements