• KIPS Transactions on Computer and Communication Systems
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• v.1 no.3
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• pp.193-204
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• 2012

This paper specifies a low-cost global mobility management architecture and protocol procedure called LC-$GM^2$, which is based on Proxy Mobile IPv6. In LC-$GM^2$, mobility management is performed by the network entity. The benefit is the elimination of the wireless link data delivery tunnel overhead between a mobile node and the access router. To compare with the well-known Hierarchical Mobile IPv6 mobility management protocol and GPMIP, the location update, packet delivery, and total cost functions generated by a mobile node during its average domain residence time are formulated for each protocol based on Fluid-flow mobility model. Then, the impacts of various system parameters on the cost functions are analyzed. The analytical results indicate that the proposed global mobility management protocol can guarantee lower total costs.

• Proceedings of the Korean Society of Applied Pharmacology
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• 2008.04a
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• pp.5-20
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• 2008

GLP-1-based drugs (GLP-1 analogues and DPP IV inhibitors) and incretin mimetics are currently one of the most exciting classes of agents for type II diabetes. GLP-1, a gut peptide, is an incretin that potentiates glucose-dependent insulin release from the pancreas, slows GI-transit and stimulates the proliferation of beta-cells. DPP IV inhibitors act like incretins by inhibiting DPP IV which inactivates GLP-1. LC15-0133 is a competitive, reversible DPP IV inhibitor ($IC_{50}$ = 24 nM, Ki=0.247 nM) with excellent selectivity over other critical human proteases such as DPP II, DPP 8, elastase, trypsin. and urokinase. LC15-0133 showed long half-life and good bioavailability in rats and dogs. Inhibition of plasma DPP IV activity by LC15-0133 was kept more than 50% 24 hours after oral dosing in rats and dogs at 0.1 mg/kg and 0.02 mg/kg, respectively. The Minimum effective doses of LC15-0133 were 0.01 mg/kg for lowering blood glucose excursion during oral glucose tolerance test and 0.1 mg/kg for increasing glucose-induced GLP-1 response in C57BL/6 mice. Repeat oral administration of LC15-0133 for 1 month delayed the progression to diabetes and reduced HbA1c levels in a dose-dependent manner in Zucker Diabetic Fatty rats. In conclusion, LC15-0133 is a novel, potent, selective and orally active DPP IV inhibitor and showed an excellent blood glucose lowering effects in various animal models.

• Herbal Formula Science
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• v.21 no.1
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• pp.36-50
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• 2013

Objectives : To clarify the possible effect of Lycium chinese Mill (LC)., Morus alba L (MA)., and Lycium chinese Mill. +Morus alba L. (LC+MA), we have examined their influence on the development of pulmonary eosinophilic inflammation in the asthmatic murine model. Methods : Female Balb/c mice (5weeks) were immunized on two different days (21 days and 7 days before inhalational exposure) by intraperitonial injections of 0.2ml alum-precipitated Ag containing $100{\mu}g$ of OVA bound to 4 mg of aluminum hydroxide in PBS. Seven days after the second sensitization, mice were exposed to aerosolized ovalbumin for 30 minutes/day on 3 days/week for 8 weeks (at a flow rate of 250 L/min, 2.5% ovalbumin in normal saline) and, LC, MA, and LC+MA (500 mg/kg) were orally administered 3 times per a week for 8 weeks. Results : The suppressive effect of LC, MA, and LC+MA were demonstrated by the accumulation of eosinophills into airways, with the reduction of eosinophil, total lung leukocytes numbers. These were correlated with the marked reduction of IL-5, IL-13 and IL-4 levels in the BALF and serum. OVA-specific IgE levels were also decreased in serum and BAL from these mice. LC, MA, and LC+MA decreased eosinophil CCR3 expression and CD11b expression in lung cells. Conclusions : These results indicate that LC, MA, and LC+MA have high inhibitory effects on airway inflammation and hyper-responsiveness in the asthmatic murine model. The suppression of IL-5, IgE, eosinophil CCR3 expression and CD11b expression, and the increase of IFN-${\gamma}$ production in BALF seem to contribute to this effect. Hence, the results indicated that LC, MA, and LC+MA could act as a immuno-modulator which possesses anti-inflammatory and anti-asthmatic property by modulating the imbalance between Th1 and Th2 cytokines.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.2
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• pp.131-138
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• 2007

In this paper, a novel nonlinear control method of the CVCF(constant voltage and constant frequency) output voltage for the three-phase PWM inverter with LC output filters is proposed. A nonlinear modeling including the output LC filters is linearized by feedback linearization theory, the controllers of which can be designed based on a linear control theory. It is applied to the DC/AC power conversion of the PWM inverter for stand-alone wind power generation system. It has been verified by the experimental results that the proposed control scheme gives high dynamic responses at load variation as well as a zero steady-state error.

• Nuclear Engineering and Technology
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• v.22 no.2
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• pp.151-158
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• 1990

The new discrete elements method (DEM) is applied to the one-group neutron transport equation in one-dimensional slab geometry. The fixed source and the criticality problems are treated and three spatial differencing schemes (the DD, the SC, -and the LC schemes) are tested to determine the most computationally efficient in the DEM. In all cases, the accuracy of the results obtained from the DEM shows an improvement over that obtained from the standard discrete ordinates calculations. And the LC scheme gives the most accurate results in the DEM.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.9
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• pp.825-830
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• 2009

Pharmaceutical compounds enter the water environment through the diverse pathways. Because their concentration in the water environment was frequently detected in the level of ppt to ppb, the monitoring system should be optimized as much as possible for finding appropriate management policies and technical solutions. One Factor At a Time (OFAT) approach approximating the response with a single variable has been preferred for the optimization of LC-MS/MS operational conditions. However, it is common that variables in analytical instruments are interdependent. Therefore, the best condition could be found by using the statistical optimization method changing multiple variables at a time. In this research, response surface analysis (RSA) was applied to the LC-MS/MS analysis of emerging antibiotic compound, sulfamethoxazole, for the best sensitivity. In the screening test, fragmentation energy and collision voltage were selected as independent variables. They were changed simultaneously for the statistical optimization and a polynomial equation was fit to the data set. The correlation coefficient, $R^2$ valuerepresented 0.9947 and the error between the predicted and observed value showed only 3.41% at the random condition, fragmentation energy of 60 and collision voltage of 17 eV. Therefore, it was concluded that the model derived by RSA successfully predict the response. The optimal conditions identified by the model were fragmentation energy of 116.6 and collision voltage of 10.9 eV. This RSA can be extensively utilized for optimizing conditions of solid-phase extraction and liquid chromatography.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.3
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• pp.262-276
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• 2018

Models to predict Leaf Wetness Duration (LWD) were evaluated using the observed meteorological and dew data at the 11 citrus orchards in Jeju, South Korea from 2016 to 2017. The sensitivity and the prediction accuracy were evaluated with four models (i.e., Number of Hours of Relative Humidity (NHRH), Classification And Regression Tree/Stepwise Linear Discriminant (CART/SLD), Penman-Monteith (PM), Deep-learning Neural Network (DNN)). The sensitivity of models was evaluated with rainfall and seasonal changes. When the data in rainy days were excluded from the whole data set, the LWD models had smaller average error (Root Mean Square Error (RMSE) about 1.5hours). The seasonal error of the DNN model had the similar magnitude (RMSE about 3 hours) among all seasons excluding winter. The other models had the greatest error in summer (RMSE about 9.6 hours) and the lowest error in winter (RMSE about 3.3 hours). These models were also evaluated by the statistical error analysis method and the regression analysis method of mean squared deviation. The DNN model had the best performance by statistical error whereas the CART/SLD model had the worst prediction accuracy. The Mean Square Deviation (MSD) is a method of analyzing the linearity of a model with three components: squared bias (SB), nonunity slope (NU), and lack of correlation (LC). Better model performance was determined by lower SB and LC and higher NU. The results of MSD analysis indicated that the DNN model would provide the best performance and followed by the PM, the NHRH and the CART/SLD in order. This result suggested that the machine learning model would be useful to improve the accuracy of agricultural information using meteorological data.

• Journal of Marine Life Science
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• v.4 no.2
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• pp.45-52
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• 2019

Polycyclic aromatic hydrocarbons (PAHs) are persistent and commonly detected in marine ecosystem. They coexist with a various contaminants including heavy metals in real environment, but most studies have been still focused on single effects of these contaminants to aquatic organisms. In this study, the single and combined effects of benzy[a]pyrene (B[a]P) and HgCl₂ were investigated in the brackish water flea, Diaphanosoma celebensis. For combined effect study, three mixtures A (3:7), B (5:5), and C (7:3) of benzy[a]pyrene (B[a]P) and HgCl₂ were determined by 48 h - LC₅₀ values of single exposure. Combined effects of both chemicals were estimated by concentration addition (CA) model and independent action (IA) model. As results, 48 h - LC₅₀ values of benzy[a]pyrene (B[a]P) and HgCl₂ was 25.75 ㎍ l^-1 and 3.6 ㎍ l^-1, respectively. TU values of mixture A, B, and C were 1.06, 0.83, and 0.96, respectively, indicating additive effects of mixtures using CA model. This study will be helpful as basic data for understanding the combined effects of contaminants in marine environment.

• Analytical Science and Technology
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• v.34 no.6
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• pp.241-250
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• 2021

Calibration curves are essential in quantitative methods and for improving the accuracy of analyte measurements in biological samples. In this study, a statistical analysis model built in the R language (The R Foundation for Statistical Computing) was used to identify a set of weighting factors and regression models based on a stepwise selection criteria. An LC-MS/MS method was used to detect the presence of urinary methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹ -tetrahydrocannabinol in a sample set. Weighting factors for the calibration curves were derived by calculating the heteroscedasticity of the measurements, where the presence of heteroscedasticity was determined via variance tests. The optimal regression model and weighting factor were chosen according to the sum of the absolute percentage relative error. Subsequently, the order of the regression model was calculated using a partial variance test. The proposed statistical analysis tool facilitated selection of the optimal calibration model and detection of methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹-tetrahydrocannabinol in urine. Thus, this study for the selection of weighting and the use of a complex regression equation may provide insights for linear and quadratic regressions in analytical and bioanalytical measurements.

• Journal of Life Science
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• v.26 no.4
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• pp.387-397
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• 2016

The purpose of this study was to determine if heat shock proteins are involved in autophagy in skeletal muscle. We used the autophagy flux strategy, which is an LC3 II/p62 turnover assay conducted with and without an autophagy inhibitor, to determine whether 17-DMAG (an Hsp90 inhibitor/Hsp72 activator) stimulates autophagy in skeletal muscle. We treated C2C12 cells with 17-DMAG (500 nM) for 24 hr with and without the autophagy inhibitor (Bafilomycin A1, 200 ng/ml), and we injected C57BL/6 mice i.p. with 17-DMAG (10 mg/kg) daily for 7 days with and without colchicine as an autophagy inhibitor (0.4 mg/kg/day, administered on the last 2 days). C2C12 myotubes and tibialis anterior muscles were harvested for analysis of mTOR-dependent autophagy signaling pathway proteins and autophagic marker proteins (p62 and LC3 II) by Western blot analysis. The blots showed that 17-DMAG upregulated hsp72 and decreased Akt protein levels and S6 phosphorylation in C2C12 cells. However, an in vitro autophagic flux assay demonstrated that 17-DMAG did not increase LC3 II and p62 protein concentrations to a greater extent than Bafilomycin A1 treatment alone. Similarly, 17-DMAG increased Hsp72 protein levels and decreased the expression of Akt and the phosphorylation of S6 in mouse skeletal muscle. However, unlike the response seen in C2C12 myotubes, the p62 protein levels were significantly decreased in 17-DMAG-treated mouse skeletal muscle (~50%; p<0.05). The LC3 II protein levels in 17-DMAG-treated mice were increased ~2-fold more when degradation was inhibited by colchicine (p<0.01). This suggests that 17-DMAG stimulates basal autophagy in skeletal muscle but is not found in C2C12 myotubes.