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        Research on self-propulsion simulation of a polar ship in a brash ice channel based on body force model

        Xie Chang,Zhou Li,Ding Shifeng,Lu Mingfeng,Zhou Xu 대한조선학회 2023 International Journal of Naval Architecture and Oc Vol.15 No.-

        Main engine power prediction is important for polar ships operating in brash ice channels, which is one of the most important concerns of shipowners. Self-propulsion simulation is an efficient method to predict the developed power. At present, such models as the discretized propeller model (DPM) and the body force model (BFM) are used for self-propulsion simulation. However, these models are often limited to open water. There is little research on self-propulsion calculations in ice-infested water. This paper presents the BFM to carry out selfpropulsion simulations in a brash ice channel. Research on simulation strategy for open water performance based on the BFM is carried out. Ship–ice–water interactions are simulated using computational fluid dynamicsdiscrete element method (CFD-DEM) coupling method. Both loaded and ballast conditions are considered in the model-scale self-propulsion simulations. Numerical results based on the BFM are compared with the simulation results based on the DPM, as well as model test results. Ship–propeller–ice interactions and propeller suction effects are also compared with photographs taken at an ice tank test. The results show that the differences of the developed power based on the BFM for both loaded and ballast conditions are 8.94% and 15.25%, respectively. The prediction accuracies of the developed power based on the BFM for both loaded and ballast conditions are 1.56% and 7.01%, respectively; lower than those based on the DPM. However, the computation efficiency based on the BFM is 12 times higher than that based on the DPM. To conclude, the proposed BFM could be used as an effective means to calculate the developed power and to evaluate the trend of hull-line optimization at the development stage.

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        Genomic Characteristics and the Potential Clinical Implications in Oligometastatic Non–Small Cell Lung Cancer

        Rongxin Liao,Kehong Chen,Jinjin Li,Hengqiu He,Guangming Yi,Mingfeng Huang,Rongrong Chen,Lu Shen,Xiaoyue Zhang,Zaicheng Xu,Zhenzhou Yang,Yuan Peng 대한암학회 2023 Cancer Research and Treatment Vol.55 No.3

        Purpose Oligometastatic non–small cell lung cancer (NSCLC) patients have been increasingly regarded as a distinct group that could benefit from local treatment to achieve a better clinical outcome. However, current definitions of oligometastasis are solely numerical, which are imprecise because of ignoring the biological heterogeneity caused by genomic characteristics. Our study aimed to profile the molecular alterations of oligometastatic NSCLC and elucidate its potential difference from polymetastasis. Materials and Methods We performed next-generation sequencing to analyze tumors and paired peripheral blood from 77 oligometastatic and 21 polymetastatic NSCLC patients to reveal their genomic characteristics and assess the genetic heterogeneity. Results We found ERBB2, ALK, MLL4, PIK3CB, and TOP2A were mutated at a significantly lower frequency in oligometastasis compared with polymetastasis. EGFR and KEAP1 alterations were mutually exclusive in oligometastatic group. More importantly, oligometastasis has a unique significant enrichment of apoptosis signaling pathway. In contrast to polymetastasis, a highly enriched COSMIC signature 4 and a special mutational process, COSMIC signature 14, were observed in the oligometastatic cohort. According to OncoKB database, 74.03% of oligometastatic NSCLC patients harbored at least one actionable alteration. The median tumor mutation burden of oligometastasis was 5.00 mutations/Mb, which was significantly associated with smoking, DNA damage repair genes, TP53 mutation, SMARCA4 mutation, LRP1B mutation, ABL1 mutation. Conclusion Our results shall help redefine oligometastasis beyond simple lesion enumeration that will ultimately improve the selection of patients with real oligometastatic state and optimize personalized cancer therapy for oligometastatic NSCLC.

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