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RISS 인기검색어
- 검색키워드
- 저자 : ( Donghao Zhao ) (검색결과 4 건)
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Guizhong Tian,Zhengyu Ma,Donghao Zhao,Honggen Zhou,Xuwen Jing,Zhancheng Xie,Guochao Li 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.6
The residual stresses (RS) generated during the thermal processing processes such as casting and heat treatment is one of the fundamental causes of irreversible deformation of diesel engine bodies (DEBs). However, previous studies only focused on the RS generated from casting or the effect of annealing heat treatment on the RS in castings unilaterally, and the analytical results were far from the actual conditions. Therefore, this paper proposes a comprehensive research method to consider the whole dynamic evolution of the casting from the RS generated by casting to the stress relief by heat treatment. Numerical simulation of DEBs casting process is carried out by PROCAST, and the results of casting RS obtained from the simulation are imported into ABAQUS, and then numerical simulation of annealing heat treatment is carried out for the DEB casting model with casting RS, so as to realize the analysis of dynamic evolution of RS from casting to heat treatment.
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Dong, Wei-Wei,Zhao, Jinhua,Zhong, Fei-Liang,Zhu, Wen-Jing,Jiang, Jun,Wu, Songquan,Yang, Deok-Chun,Li, Donghao,Quan, Lin-Hu The Korean Society of Ginseng 2017 Journal of Ginseng Research Vol.41 No.4
Background: In general, after Panax ginseng is administered orally, intestinal microbes play a crucial role in its degradation and metabolization process. Studies on the metabolism of P. ginseng by microflora are important for obtaining a better understanding of their biological effects. Methods: In vitro biotransformation of P. ginseng extract by rat intestinal microflora was investigated at $37^{\circ}C$ for 24 h, and the simultaneous determination of the metabolites and metabolic profile of P. ginseng saponins by rat intestinal microflora was achieved using LC-MS/MS. Results: A total of seven ginsenosides were detected in the P. ginseng extract, including ginsenosides Rg1, Re, Rf, Rb1, Rc, Rb2, and Rd. In the transformed P. ginseng samples, considerable amounts of deglycosylated metabolite compound K and Rh1 were detected. In addition, minimal amounts of deglycosylated metabolites (ginsenosides Rg2, F1, F2, Rg3, and protopanaxatriol-type ginsenosides) and untransformed ginsenosides Re, Rg1, and Rd were detected at 24 h. The results indicated that the primary metabolites are compound K and Rh1, and the protopanaxadiol-type ginsenosides were more easily metabolized than protopanaxatriol-type ginsenosides. Conclusion: This is the first report of the identification and quantification of the metabolism and metabolic profile of P. ginseng extract in rat intestinal microflora using LC-MS/MS. The current study provided new insights for studying the metabolism and active metabolites of P. ginseng.
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Biotransformation of Panax ginseng extract by rat intestinal microflora
Wei-Wei Dong,Jinhua Zhao,Fei-Liang Zhong,Wen-Jing Zhu,Jun Jiang,Songquan Wu,Deok-Chun Yang,Donghao Li,Lin-Hu Quan 고려인삼학회 2017 Journal of Ginseng Research Vol.41 No.4
Background: In general, after Panax ginseng is administered orally, intestinal microbes play a crucial role in its degradation and metabolization process. Studies on the metabolism of P. ginseng by microflora are important for obtaining a better understanding of their biological effects. Methods: In vitro biotransformation of P. ginseng extract by rat intestinal microflora was investigated at 37C for 24 h, and the simultaneous determination of the metabolites and metabolic profile of P. ginseng saponins by rat intestinal microflora was achieved using LCeMS/MS. Results: A total of seven ginsenosides were detected in the P. ginseng extract, including ginsenosides Rg1, Re, Rf, Rb1, Rc, Rb2, and Rd. In the transformed P. ginseng samples, considerable amounts of deglycosylated metabolite compound K and Rh1 were detected. In addition, minimal amounts of deglycosylated metabolites (ginsenosides Rg2, F1, F2, Rg3, and protopanaxatriol-type ginsenosides) and untransformed ginsenosides Re, Rg1, and Rd were detected at 24 h. The results indicated that the primary metabolites are compound K and Rh1, and the protopanaxadiol-type ginsenosides were more easily metabolized than protopanaxatriol-type ginsenosides. Conclusion: This is the first report of the identification and quantification of the metabolism and metabolic profile of P. ginseng extract in rat intestinal microflora using LCeMS/MS. The current study provided new insights for studying the metabolism and active metabolites of P. ginseng.
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Smart Anti-jamming Mobile Communication for Cloud and Edge-Aided UAV Network
( Zhiwei Li ),( Yu Lu ),( Zengguang Wang ),( Wenxin Qiao ),( Donghao Zhao ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.12
The Unmanned Aerial Vehicles (UAV) networks consisting of low-cost UAVs are very vulnerable to smart jammers that can choose their jamming policies based on the ongoing communication policies accordingly. In this article, we propose a novel cloud and edge-aided mobile communication scheme for low-cost UAV network against smart jamming. The challenge of this problem is to design a communication scheme that not only meets the requirements of defending against smart jamming attack, but also can be deployed on low-cost UAV platforms. In addition, related studies neglect the problem of decision-making algorithm failure caused by intermittent ground-to-air communication. In this scheme, we use the policy network deployed on the cloud and edge servers to generate an emergency policy tables, and regularly update the generated policy table to the UAVs to solve the decision-making problem when communications are interrupted. In the operation of this communication scheme, UAVs need to offload massive computing tasks to the cloud or the edge servers. In order to prevent these computing tasks from being offloaded to a single computing resource, we deployed a lightweight game algorithm to ensure that the three types of computing resources, namely local, edge and cloud, can maximize their effectiveness. The simulation results show that our communication scheme has only a small decrease in the SINR of UAVs network in the case of momentary communication interruption, and the SINR performance of our algorithm is higher than that of the original Q-learning algorithm.
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