• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.1019-1032
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• 2013

The accurate prediction of future mortality is an important issue due to recent rapid increases in life expectancy. An accurate estimation and prediction of mortality is important to future welfare policies. The optimal selection of a mortality model is important to estimate and predict mortality; however, the period of time series data used is also an important issue. It is essential to understand that the time series data for mortality is short in Korea and the data before 1982 is incomplete. This paper divides the time series of Korean mortality into two sets to compare the parameter estimates of the LC model and LC model with a cohort effect by the period of data used. A modeling and prediction of the mortality index and cohort effect index as well as the evaluation of future life expectancy is conducted. Finally, some suggestions are proposed for the future prediction of mortality.

• 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.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.951-960
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• 2016

Tower insulators in electric power transmission network play a crucial role in preserving the reliability of the system. Electrical utilities frequently face the problem of flashover of insulators due to pollution deposition on their surface. Several research works based on leakage current (LC) measurement has been already carried out in developing diagnostic techniques for these insulators. Since the LC signal is highly intermittent in nature, estimation of pollution severity based on LC signal measurement over a short period of time will not produce accurate results. Reports on the measurement and analysis of LC signals over a long period of time is scanty. This paper attempts to use Random Forest (RF) classifier, which produces accurate results on large data bases, to analyze the pollution severity of high voltage tower insulators. Leakage current characteristics over a long period of time were measured in the laboratory on porcelain insulator. Pollution experiments were conducted at 11 kV AC voltage. Time domain analysis and wavelet transform technique were used to extract both basic features and histogram features of the LC signal. RF model was trained and tested with a variety of LC signals measured over a lengthy period of time and it is noticed that the proposed RF model based pollution severity classifier is efficient and will be helpful to electrical utilities for real time implementation.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.637-653
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• 2018

Rapid aging of the population affects population structure and population aging. Consequently, developed countries have focused on population aging as a major issue in regards to pension sustainability finances as well as health and the elderly welfare system. Mortality projections that result from population structure changes and population aging are increasingly important. This paper compares six mortality models using KOSTAT's life table from 1970 to 2016. The models are rooted in the Lee-Carter (LC) model (Lee and Carter, Journal of the American Statistical Association, 87, 659-671, 1992) and have been modified and improved on the assumptions of the LC model. We examined the improvement process and the check assumption by models in order to find a suitable mortality model for Korea. Korea shows rapid aging and declined mortality rate by age; therefore, it is desirable to estimate and predict mortality from LL&LC-ER models by combining LC-ER, LL, and LC-ER models that reflect the phenomena and modify age-specific mortality patterns without major changes in expected life expectancy.

• Journal of the Korean Society of Clothing and Textiles
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• v.18 no.4
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• pp.524-535
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• 1994

The interaction and detergency between oily soil and surfactant solution were studied Samples used were tristearin, tripalmitin and their mixture as a triglyceride, myristic acid as a fatty acid and sodium dodecyl sulfate (SDS) as surfactant. The results were as follows: 1. The mixtures of model oily soils were formed of eutectic point and their melting point were lower than them of individual oily soils. 2. The formation of liquid crystalline (LC) phase was recognized in the triangle phase diagram for SDS~ water~model oily soil system. The areas of LC phase region were in the order of SHS~ water~myristir acid> SDS~ water~mixture of tristearin, tripalmitin and myristic acid (TS/TP/M)>SDS~water~mixture of tristearin and tripalmitin (TS/TP) 3. The LC phase region expanded to wide concentration range of SDS solution and high concentration range of model oily soil with increasing temperature. Particularity, the LC phase region expanded highly at $30~40^{\circ}C$ but when the temperature was elevated above $40^{\circ}C$, expanding tendency decreased. 4. In the system of myristic acid and TS/TP/M contacted with SDS solution, the LC phase was already formed at $28^{\circ}C$ and the region of the LC phase were expanded with increasing temperature. But in the system of TS/TP contacted with SDS solution, the LC phase was not formed in whole experiment temperature. 5. The detergency of myristic acid was very high ann it was recognized that the formation of the LC phase played an important role in the detergency. The detergency of TS/TP was very for low, but when TS/TF was mixed with myristic acid, the detergency of TS/TP increased. It is supposed that the LC phase was formed butween SDS solution and myristic acid promoted to penetration of SDS solution into the inner parts of TS/TP.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.77-96
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• 2018

A reverse mortgage provides a pension until the death for the insured or last survivor. Long-term risk management is important to estimate the contractual period of a reverse mortgage. It is also necessary to study prediction methods of mortality rates that appropriately reflect the improvement trend of the mortality rate since the extension of the life expectancy, which is the main cause of aging, can have a serious impact on the pension financial soundness. In this study, the Lee-Carter (LC) model reflects the improvement in mortality rates; in addition, multiple life model are also applied to a reverse mortgage. The mortality prediction method by the traditional LC model has shown a dramatic improvement in the mortality rate; therefore, this study suggests mortality projection based on the projection of the skewness for the mortality that has been applied to appropriately reflect the improvement trend of the mortality rate. This paper calculates monthly payments using future mortality rates based on the projection of the skewness of the mortality. As a result, the mortality rates based on this method less reflect the mortality improvement effect than the mortality rates based on a traditional LC model and a larger pension amount is calculated. In conclusion, this method is useful to forecast future mortality trend results in a significant reduction of longevity risk. It can also be used as a risk management method to pay appropriate monthly payments and prevent insufficient payment due to overpayment by the issuing institution and the guarantee institution of the reverse mortgage.

• Communications for Statistical Applications and Methods
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• v.28 no.3
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• pp.233-250
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• 2021

This paper studies if the accuracies of mortality models (LC model vs. 4-parametric model) are aggravated if a mortality structure changes due to the impact of COVID-19. LC model (LCM) uses dimension reduction for fitting to the log mortality matrix so that the performance of the dimension reduction method may not be good when the matrix structure changes. On the other hand, 4-parametric factor model (4-PFM) is designed to use factors for fitting to log mortality data by age groups so that it would be less affected by the change of the mortality structure. In fact, the forecast accuracies of LCM are better than those of 4-PFM when life-tables are used whereas those of 4-PFM are better when the mortality structure changes. Thus this result shows that 4-PFM is more reliable in performance to the structural changes of the mortality. To support the accuracy changes of LCM the functional aspect is explained by computing eigenvalues produced by singular vector decomposition

• Toxicological Research
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• v.31 no.4
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• pp.331-337
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• 2015

Synthetic pyrethroids (SPs) are the most common pesticides which are recently used for indoor pest control. The widespread use of SPs has resulted in the increased exposure to wild animals and humans. Recently, some SPs are suspected as endocrine disrupting chemicals (EDCs) and have been assessed for their potential estrogenicity by adopting various analyzing assays. In this study, we examined the estrogenic effects of lambda-cyhalothrin (LC) and cypermethrin (CP), the most commonly used pesticides in Korea, using BG-1 ovarian cancer cells expressing estrogen receptors (ERs). To evaluate the estrogenic activities of two SPs, LC and CP, we employed MTT assay and reverse-transcription polymerase chain reaction (RT-PCR) in LC or CP treated BG-1 ovarian cancer cells. In MTT assay, LC ($10^{-6}M$) and CP ($10^{-5}M$) significantly induced the growth of BG-1 cancer cells. LC or CP-induced cell growth was antagonized by addition of ICI 182,720 ($10^{-8}M$), an ER antagonist, suggesting that this effect appears to be mediated by an ER-dependent manner. Moreover, RT-PCR results showed that transcriptional level of cyclin D1, a cell cycle-regulating gene, was significantly up-regulated by LC and CP, while these effects were reversed by co-treatment of ICI 182,780. However, p21, a cyclin D-ckd-4 inhibitor gene, was not altered by LC or CP. Moreover, $ER{\alpha}$ expression was not significantly changed by LC and CP, while down-regulated by E2. Finally, in xenografted mouse model transplanted with human BG-1 ovarian cancer cells, E2 significantly increased the tumor volume compare to a negative control, but LC did not. Taken together, these results suggest that LC and CP may possess estrogenic potentials by stimulating the growth of BG-1 ovarian cancer cells via partially ER signaling pathway associated with cell cycle as did E2, but this estrogenic effect was not found in in vivo mouse model.

• Computers and Concrete
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• v.32 no.6
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• pp.577-594
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• 2023

Engineered cementitious composites with calcined clay limestone cement (LC³-ECC) as a kind of green, low-carbon and high toughness concrete, has recently received significant investigation. However, the complicated relationship between potential influential factors and LC³-ECC compressive strength makes the prediction of LC³-ECC compressive strength difficult. Regarding this, the machine learning-based prediction models for the compressive strength of LC³-ECC concrete is firstly proposed and developed. Models combine three novel meta-heuristic algorithms (golden jackal optimization algorithm, butterfly optimization algorithm and whale optimization algorithm) with support vector regression (SVR) to improve the accuracy of prediction. A new dataset about LC³-ECC compressive strength was integrated based on 156 data from previous studies and used to develop the SVR-based models. Thirteen potential factors affecting the compressive strength of LC³-ECC were comprehensively considered in the model. The results show all hybrid SVR prediction models can reach the Coefficient of determination (R²) above 0.95 for the testing set and 0.97 for the training set. Radar and Taylor plots also show better overall prediction performance of the hybrid SVR models than several traditional machine learning techniques, which confirms the superiority of the three proposed methods. The successful development of this predictive model can provide scientific guidance for LC³-ECC materials and further apply to such low-carbon, sustainable cement-based materials.

• Journal of Microbiology and Biotechnology
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• v.34 no.9
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• pp.1810-1818
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• 2024

Autophagy is essential for regulating hair growth. Accordingly, we developed autophagy activator ICP5249 (pentasodium tetracarboxymethyl palmitoyl dipeptide) and investigated its potential role in hair growth. We evaluated its effect on hair growth using in vitro human dermal papilla cells (hDPCs) culture model, human hair follicles (hHFs) organ culture model, and telogenic mouse model. ICP5249 increased hDPCs proliferation and alkaline phosphatase (ALP) expression. It also increased microtubule-associated protein (MAP) light chain 3-II (LC3-II) expression and AMP-activated protein kinase α (AMPKα) and unc-51-like kinase 1 (ULK1) phosphorylation in hDPCs. ICP5249 extended the length of hHFs and increased LC3-II please revised from LC3 II to LC3-II in all manuscript expression. Consistently, ICP5249 also significantly increased hair growth area, dermis thickness, and anagen and telogen ratio in telogenic mice. Furthermore, it upregulated Ki-67 and LC3-II expression and AMPKα phosphorylation on the mice's dorsal skin. To investigate whether AMPK regulates ICP5249-induced hair growth, following treatment with the compound C, AMPK inhibitor, the activity of ICP5249 was evaluated. The effects of ICP5249 on hair growth were assessed following pretreatment with the AMPK inhibitor compound C. The results showed that compound C suppressed ICP5249-mediated proliferation and hair inductivity in hDPCs. Additionally, compound C inhibited ICP5249-mediated hair growth area, dermis thickness, anagen and telogen ration, and LC3-II expression in mice, suggesting that ICP5249 promotes hair growth by modulating autophagy, with AMPKα playing a regulatory role in this process. Taken together, we demonstrate that ICP5249 has the potential as an ingredient for improving hair growth.