• KDI Journal of Economic Policy
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• v.12 no.4
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• pp.3-20
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• 1990

The multisector model is designed to analyze and forecast structural change in industrial output, employment, capital and relative price as well as macroeconomic change in aggregate income, interest rate, etc. This model has 25 industrial sectors, containing about 1,300 equations. Therefore, this model is characterized by detailed structural disaggregation at the sectoral level. Individual industries are based on many of the economic relationships in the model. This is what distinguishes a multisector model from a macroeconomic model. Each industry is a behavioral agent in the model for industrial investment, employment, prices, wages, and intermediate demand. The strength of the model lies in the simulating the interactions between different industries. The result of its simulation will be introduced in the next paper. In this paper, we only introduce the structure of the multisector model and the coefficients of the equations. The multisector model is a dynamic model-that is, it solves year by year into the future using its own solutions for earlier years. The development of a dynamic, year-by-year solution allows us to combine the change in structure with a consideration of the dynamic adjustment required. These dynamics have obvious advantages in the use of the multisector model for industrial planning. The multisector model is a medium-term and long-term model. Whereas a short-term model can taken the labor supply and capital stock as given, a long-term model must acknowledge that these are determined endogenously. Changes in the medium-term can be analyzed in the context of long-term structural changes. The structure of this model can be summarized as follow. The difference in domestic and world prices affects industrial structure and the pattern of international trade; domestic output and factor price affect factor demand; factor demand and factor price affect industrial income; industrial income and relative price affect industrial consumption. Technical progress, as measured in terms of total factor productivity and relative price affect input-output coefficients; input-output coefficients and relative price determine the industrial input cost; input cost and import price determine domestic price. The differences in productivity and wage growth among different industries affect the relative price.

• Archives of Plastic Surgery
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• v.32 no.3
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• pp.369-375
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• 2005

Apoptosis is a physiologic or programmed cell death process which is controlled by genes. It is essential for the function and the appropriate development of multicellular organism. It is also thought to be one of the main mechanisms of cell death in ischemic tissues. The effect of prostaglandin $E_1$($PGE_1$) is proven to be useful in the recovery of ischemic changes by inducing vasodilation of peripheral vessels and platelet disaggregation. $PGE_1$ is also known to suppress apoptosis in human liver sinusoidal endothelial cell from ischemia-reperfusion injury. The purpose of this study is to evaluate the effects of $PGE_1$ on the apoptosis in the ischemia reperfusion injury of rat intestine. Thirty Sprague-Dawley rats were used. In control group(N=15), superior mesenteric artery was occluded for 60 minutes and after removing the vessel clamp, it was reperfused for 60 minutes and harvested. In experimental group(N=15), a jejunal flap was also made as in the control group except for the intraarterial administration of the $PGE_1$ right after clamping the artery and removing the clamp. H&E, TUNEL and immunohistochemical stains for p53, bax, and bcl-2 were performed. There were ischemic changes in gross and microscopic findings in both groups. The apoptotic index was significantly lower in the experimental group($1.29{\pm}0.82$(p=0.003)) than in the control group ($2.33{\pm}0.95$). The rat intestinal ischemia apoptosis by ischemia-reperfusion was partly related to the modulating of bcl-2, bax, and p53 expression. Our results indicate that $PGE_1$ suppresses the apoptosis in the ischemic jejunal flap and this effect is probably the result of a increase in expression of bcl-2.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.73-81
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• 2009

While various factors in passenger and freight demand analysis affect on destination choice, a key factor, in general. is an attractiveness measure by size variable (e.g., population. employment etc) in destination zone. In order to measure the attractiveness, some empirical studies suggested that disaggregate gravity model are more suitable than aggregate gravity model. This study proposes that truck travelers trip diary data among Korean commodity flow data could be used to estimate the behaviors of incorporating trip departure time, activity duration and attractiveness in destination. As a result, the main findings of size and distance variables coincide with the conventional gravity model having a positive effect of population variable and a negative effect of distance variable. Due to disaggregate gravity modeling, the unique findings of this study reports that small trucks are more likely to choose short distance and early morning, morning peak and afternoon peak departure time choice. On the other hand, large trucks are more likely to choose long distance and night time departure time choice.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.13-29
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• 2018

This study presented evaluation procedure for selecting appropriate GCMs and downscaling method by focusing on the climate extreme indices suitable for climate change adaptation. The procedure includes six stages of processes as follows: 1) exclusion of unsuitable GCM through raw GCM analysis before bias correction; 2) calculation of the climate extreme indices and selection of downscaling method by evaluating reproducibility for the past and distortion rate for the future period; 3) selection of downscaling method based on evaluation of reproducibility of spatial correlation among weather stations; and 4) MME calculation using weight factors and evaluation of uncertainty range depending on number of GCMs. The presented procedure was applied to 60 weather stations where there are observed data for the past 30 year period on Korea Peninsula. First, 22 GCMs were selected through the evaluation of the spatio-temporal reproducibility of 29 GCMs. Between Simple Quantile Mapping (SQM) and Spatial Disaggregation Quantile Delta Mapping (SDQDM) methods, SQM was selected based on the reproducibility of 27 climate extreme indices for the past and reproducibility evaluation of spatial correlation in precipitation and temperature. Total precipitation (prcptot) and annual 1-day maximum precipitation (rx1day), which is respectively related to water supply and floods, were selected and MME-based future projections were estimated for near-future (2010-2039), the mid-future (2040-2069), and the far-future (2070-2099) based on the weight factors by GCM. The prcptot and rx1day increased as time goes farther from the near-future to the far-future and RCP 8.5 showed a higher rate of increase in both indices compared to RCP 4.5 scenario. It was also found that use of 20 GCM out of 22 explains 80% of the overall variation in all combinations of RCP scenarios and future periods. The result of this study is an example of an application in Korea Peninsula and APCC Integrated Modeling Solution (AIMS) can be utilized in various areas and fields if users want to apply the proposed procedure directly to a target area.

• Molecules and Cells
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• v.42 no.6
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• pp.480-494
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• 2019

Aggregates of disease-causing proteins dysregulate cellular functions, thereby causing neuronal cell loss in diverse neurodegenerative diseases. Although many in vitro or in vivo studies of protein aggregate inhibitors have been performed, a therapeutic strategy to control aggregate toxicity has not been earnestly pursued, partly due to the limitations of available aggregate models. In this study, we established a tetracycline (Tet)-inducible nuclear aggregate (${\beta}23$) expression model to screen potential lead compounds inhibiting ${\beta}23$-induced toxicity. High-throughput screening identified several natural compounds as nuclear ${\beta}23$ inhibitors, including peucedanocoumarin III (PCIII). Interestingly, PCIII accelerates disaggregation and proteasomal clearance of both nuclear and cytosolic ${\beta}23$ aggregates and protects SH-SY5Y cells from toxicity induced by ${\beta}23$ expression. Of translational relevance, PCIII disassembled fibrils and enhanced clearance of cytosolic and nuclear protein aggregates in cellular models of huntingtin and ${\alpha}$-synuclein aggregation. Moreover, cellular toxicity was diminished with PCIII treatment for polyglutamine (PolyQ)-huntingtin expression and ${\alpha}$-synuclein expression in conjunction with 6-hydroxydopamine (6-OHDA) treatment. Importantly, PCIII not only inhibited ${\alpha}$-synuclein aggregation but also disaggregated preformed ${\alpha}$-synuclein fibrils in vitro. Taken together, our results suggest that a Tet-Off ${\beta}23$ cell model could serve as a robust platform for screening effective lead compounds inhibiting nuclear or cytosolic protein aggregates. Brain-permeable PCIII or its derivatives could be beneficial for eliminating established protein aggregates.

• Clinical and Experimental Pediatrics
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• v.48 no.5
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• pp.545-550
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• 2005

Purpose : Newborn brain tissue has to be dissociated into a single cell suspension for flow cytometric analysis of cell death during hypoxia-ischemia. Thus the development of a method to dissociate cells from the brain tissue with least damage and maintenance of membrane and antigen integrity remains the challenge for the in vivo application of this technique. We evaluated the efficacy of mechanical or enzymatic (collagenase or tryspin) methods of brain tissue disaggregation. Methods : The extent of the damage to the plasma membrane and loss of the characteristics of the membrane induced with each dissociation method was determined by comparing the flow cytometric results labeled with both fluorescent annexin V and propidium iodide of the newborn rat pup brain tissue in the control group (n=10) and in the 48-hour after hypoxia-ischemia group (n=10). Results : In the control group, the cell percentage of damaged, apoptotic and necrotic cells of both hemispheres with the mechanical dissociation method was significantly increased compared to the trypsin or collagenase method. In the 48-hour after hypoxia-ischemia group, the cell percentage of apoptotic and necrotic cells of the right hemisphere with the collagenase method significantly increased, and live cells significantly decreased compared to the left hemisphere, control group. Although the same trend was observed, the extent of alterations made with the trypsin method was significantly less compared to the collagenase method. Conclusion : The dissociation of neonatal brain tissue for flow cytometric analysis with collagenase was most efficacious with the least cell damage and preservation of the plasma membrane characteristics.