• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09a
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• pp.286-286
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• 2006

• Railway Journal
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• v.12 no.2
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• pp.24-29
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• 2009

• Proceedings of the Microbiological Society of Korea Conference
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• 2000.05a
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• pp.37-51
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• 2000

• Bulletin of the Korean Space Science Society
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• 1999.09a
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• pp.28-28
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• 1999

No Abstract, See Full Text

• Proceedings of the Korean Magnestics Society Conference
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• 2007.05a
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• pp.57.1-57.1
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• 2007

• Journal of the Korean Mathematical Society
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• v.29 no.2
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• pp.341-350
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• 1992

• The Magazine of the IEIE
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• v.40 no.2
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• pp.20-31
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• 2013

• BMB Reports
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• v.42 no.7
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• pp.444-449
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• 2009

Different neurodegenerative disorders like prion disease, is caused by protein misfolding conformers. Reverse-transfected cytosolic prion protein (PrP) and PrP expressed in the cytosol have been shown to be neurotoxic. To investigate the possible mechanism of neurotoxicity due to accumulation of PrP in cytosol, a PrP mutant lacking the signal and GPI (CytoPrP) was introduced into the SH-SY5Y cell. MTT and trypan blue assays indicated that the viability of cells expressing CytoPrP was remarkably reduced after treatment of MG-132. Obvious apoptosis phenomena were detected in the cells accumulated with CytoPrP, including loss of mitochondrial transmembrane potential, increase of caspase-3 activity, more annexin V/PI-double positive-stained cells and reduced Bcl-2 level. Moreover, DNA fragmentation and TUNEL assays also revealed clear evidences of late apoptosis in the cells accumulated CytoPrP. These data suggest that the accumulation of CytoPrP in cytoplasm may trigger cell apoptosis, in which mitochondrial relative apoptosis pathway seems to play critical role.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.212-218
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• 2003

State invariant is a property that holds in every reachable state. It can be used not only in understanding and analyzing complex software systems, but it can also be used for system verifications such as checking safety, liveness, and consistency. For these reasons, there are many vital researches for deriving state invariant from finite state machine models. In previous works every reachable state is to be considered to generate state invariant. Thus it is likely to be too complex for the user to understand. This paper seeks to answer the question `how to simplify state invariant\ulcorner`. Since the complexity of state invariant is strongly dependent upon the size of states to be considered, so the smaller the set of states to be considered is, the shorter the length of state invariant is. For doing so, we let the user focus on some interested scopes rather than a whole state space in a model. Computation Tree Logic(CTL) is used to specify scopes in which he/she is interested. Given a scope in CTL, mixed reachability analysis is used to find out a set of states inside it. Obviously, a set of states calculated in this way is a subset of every reachable state. Therefore, we give a weaker, but comprehensible, state invariant.

• Journal of the Korean Ceramic Society
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• v.56 no.2
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• pp.111-129
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• 2019

Recently, all-solid-state batteries (ASSBs) have attracted increasing interest owing to their higher energy density and safety. As the core material of ASSBs, the characteristics of the solid electrolyte largely determine the performance of the battery. Thus far, a variety of inorganic solid electrolytes have been studied, including the NASICON-type, LISICON-type, perovskite-type, garnet-type, glassy solid electrolyte, and so on. The garnet Li₇La₃Zr₂O₁₂ (LLZO) solid electrolyte is one of the most promising candidates because of its excellent comprehensively electrochemical performance. Both, experiments and theoretical calculations, show that cubic LLZO has high room-temperature ionic conductivity and good chemical stability while contacting with the lithium anode and most of the cathode materials. In this paper, the crystal structure, Li-ion transport mechanism, preparation method, and element doping of LLZO are introduced in detail based on the research progress in recent years. Then, the development prospects and challenges of LLZO as applied to ASSBs are discussed.