• Journal of Ginseng Research
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• v.48 no.1
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• pp.59-67
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• 2024

Background: Alzheimer's disease (AD) has memory impairment associated with aggregation of amyloid plaques and neurofibrillary tangles in the brain. Although anti-amyloid β (Aβ) protein antibody and chemical drugs can be prescribed in the clinic, they show adverse effects or low effectiveness. Therefore, the development of a new drug is necessarily needed. We focused on the cognitive function of Panax ginseng and tried to find active ingredient(s). We isolated panaxcerol D, a kind of glycosyl glyceride, from the non-saponin fraction of P. ginseng extract. Methods: We explored effects of acute or sub-chronic administration of panaxcerol D on cognitive function in scopolamine- or Aβ_25-35 peptide-treated mice measured by several behavioral tests. After behavioral tests, we tried to unveil the underlying mechanism of panaxcerol D on its cognitive function by Western blotting. Results: We found that pananxcerol D reversed short-term, long-term and object recognition memory impairments. The decreased extracellular signal-regulated kinases (ERK) or Ca²⁺/calmodulin-dependent protein kinase II (CaMKII) in scopolamine-treated mice was normalized by acute administration of panaxcerol D. Glial fibrillary acidic protein (GFAP), caspase 3, NF-kB p65, synaptophysin and brainderived neurotrophic factor (BDNF) expression levels in Aβ_25-35 peptide-treated mice were modulated by sub-chronic administration of panaxcerol D. Conclusion: Pananxcerol D could improve memory impairments caused by cholinergic blockade or Aβ accumulation through increased phosphorylation level of ERK or its anti-inflammatory effect. Thus, panaxcerol D as one of non-saponin compounds could be used as an active ingredient of P. ginseng for improving cognitive function.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.307-321
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• 2024

This paper delves into the critical assessment of predicting sidewall displacement in underground caverns through the application of nine distinct machine learning techniques. The accurate prediction of sidewall displacement is essential for ensuring the structural safety and stability of underground caverns, which are prone to various geological challenges. The dataset utilized in this study comprises a total of 310 data points, each containing 13 relevant parameters extracted from 10 underground cavern projects located in Iran and other regions. To facilitate a comprehensive evaluation, the dataset is evenly divided into training and testing subset. The study employs a diverse array of machine learning models, including recurrent neural network, back-propagation neural network, K-nearest neighbors, normalized and ordinary radial basis function, support vector machine, weight estimation, feed-forward stepwise regression, and fuzzy inference system. These models are leveraged to develop predictive models that can accurately forecast sidewall displacement in underground caverns. The training phase involves utilizing 80% of the dataset (248 data points) to train the models, while the remaining 20% (62 data points) are used for testing and validation purposes. The findings of the study highlight the back-propagation neural network (BPNN) model as the most effective in providing accurate predictions. The BPNN model demonstrates a remarkably high correlation coefficient (R2 = 0.99) and a low error rate (RMSE = 4.27E-05), indicating its superior performance in predicting sidewall displacement in underground caverns. This research contributes valuable insights into the application of machine learning techniques for enhancing the safety and stability of underground structures.

• Geomechanics and Engineering
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• v.37 no.5
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• pp.475-498
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• 2024

The prediction of the susceptibility of soil to liquefaction using a limited set of parameters, particularly when dealing with highly unbalanced databases is a challenging problem. The current study focuses on different ensemble learning classification algorithms using highly unbalanced databases of results from in-situ tests; standard penetration test (SPT), shear wave velocity (V_s) test, and cone penetration test (CPT). The input parameters for these datasets consist of earthquake intensity parameters, strong ground motion parameters, and in-situ soil testing parameters. liquefaction index serving as the binary output parameter. After a rigorous comparison with existing literature, extreme gradient boosting (XGBoost), bagging, and random forest (RF) emerge as the most efficient models for liquefaction instance classification across different datasets. Notably, for SPT and V_s-based models, XGBoost exhibits superior performance, followed by Light gradient boosting machine (LightGBM) and Bagging, while for CPT-based models, Bagging ranks highest, followed by Gradient boosting and random forest, with CPT-based models demonstrating lower G_mean(error), rendering them preferable for soil liquefaction susceptibility prediction. Key parameters influencing model performance include internal friction angle of soil (ϕ) and percentage of fines less than 75 µ (F₇₅) for SPT and V_s data and normalized average cone tip resistance (q_c) and peak horizontal ground acceleration (a_max) for CPT data. It was also observed that the addition of V_s measurement to SPT data increased the efficiency of the prediction in comparison to only SPT data. Furthermore, to enhance usability, a graphical user interface (GUI) for seamless classification operations based on provided input parameters was proposed.

• Korean Journal of Soil Science and Fertilizer
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• v.36 no.4
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• pp.200-209
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• 2003

Distribution coefficient ($K_d$) is an universal parameter estimating cadmium partition for a soil-water-crop system in agricultural lands. This study was performed to find some factors affecting soil-water partition coefficients for cadmium in some Korean soils. The distribution coefficients ($K_d$) of cadmium for the 15 series of agricultural soils were measured at quasi-steady state in the pH ranges from 2 to 11. The adsorption data of the selected soils showed a linear relationship between log $K_d$ and pH, which was well agreed with theoretically expected results ; $log\;K_d=0.6339pH+0.5532(r^2=0.70^{**})$. Normalization of the partition coefficients were performed in a range of pH 3.5 ~ 8.5 to minimize adverse effects of Al dissolution, cationic competition, and organic matter dissolution. The $K_d$-om, partition coefficients normalized for organic matter, improved this linearity to the pH of soils. The values of $K_d$-om measured from the field samples were significantly correlated with those of $K_d$ predicted from the sorption-edge experimental data ($r^2=0.68^{**}$).

• The Korea Journal of Herbology
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• v.22 no.2
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• pp.45-50
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• 2007

objectives: We investigated the moisturizing and cooling effects of the cosmetic product with Scrophularia Buergeriana, Poria Cocos, Lonicera Japonica, Portulaca Oleracea and Ginko Biloba extract on human skin by using non-invasive instrument. Methods: We measured physiological effects after volunteers(female, n=5) applied the cosmetic product containing the extract of oriental herbs. The forearm skin moisturization was measured with $Corneometer^{\circledR}$ CM825 after 15min, 3hr, and 6hr. The forearm skin surface roughness was with Scanning electron microscopy after 15min, and 6hr. The face skin temperatures cooling and microcirculation effects were measured with ThermaCAMTM PM525 and LDl-Periscan PlM II after 15min, and 30min. Results: The forearm skin moisturization was imcreased 108% after 15min. The forearm skin surface roughness was decreased significantly after 15min. The face skin temperatures were cooling down to $30.7^{\circ}C$. The face skin microcirculation effect was normalized time-dependently. Conclusions: We concluded that cosmetic product containing the extract of Scrophularia Buergeriana, Poria Cocos, Lonicera Japonica, Portulaca Oleracea and Ginko Biloba had a moisturization effect and improving the surface roughness, temperature and microcirculation on the human skin.

• Science of Emotion and Sensibility
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• v.23 no.2
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• pp.3-12
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• 2020

The purpose of this work is to suggest the optimal color temperature, which induces a sense of comfort for autonomous vehicle users through the analysis of biosignal using electroencephalography (EEG) and photoplethysmography (PPG). To achieve this purpose, we applied lighting with a color temperature of 3000 K, 4000 K, 5000 K, and 6000 K to the autonomous driving environment. We experimented in a laboratory equipped with a graphic driving simulator. The experimental procedure is as follows: 1) stabilization (5 min). 2) Uchida-Kraepelin test (3 min). 3) Automatic driving + lighting (3 min). This procedure was repeated four times under different color temperatures. We performed frequency analysis on a collected time-series data and calculated the power value for each frequency band through power spectrum analysis. In the case of EEG, we analyzed α- and β-waves, which are indicators of stability and arousal, respectively. In the case of PPG, we analyzed the sympathetic nervous system activity. To reduce deviations between the subjects, we normalized the data before analysis. The result of the first analysis revealed that α-wave increased only at 5000 K, while the β-wave increased at almost all color temperatures. In addition, in the case of PPG, sympathetic nervous system activity (SNSA) increased under driving conditions. The result of the second analysis revealed that the difference between β-wave and SNSA is insignificant. In conclusion, the increase in α-waves showed that EEG was most stable at 5000 K. The results of this study can be applied to the upcoming autonomous driving era to induce high driver satisfaction. Furthermore, this approach could eventually lead to the acceptance of autonomous vehicles by suggesting a positive effect of autonomous driving.

• Journal of Ginseng Research
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• v.44 no.6
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• pp.799-807
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• 2020

Background: The skin acts as a barrier to protect organisms against harmful exogenous agents. Compound K (CK) is an active metabolite of ginsenoside Rb1, Rb2 and Rc, and researchers have focused on its skin protective efficacy. In this study, we hypothesized that increased expression of the serine protease inhibitor Kazal type-5 (SPINK5) may improve skin barrier function. Methods: We screened several ginsenosides to increase SPINK5 gene promoter activity using a transactivation assay and found that CK can increase SPINK5 expression. To investigate the protective effect of CK on the skin barrier, RT-PCR and Western blotting were performed to investigate the expression levels of SPINK5, kallikrein 5 (KLK5), KLK7 and PAR2 in UVB-irradiated HaCaT cells. Measurement of transepidermal water loss (TEWL) and histological changes associated with the skin barrier were performed in a UVB-irradiated mouse model and a 1-chloro-2,4-dinitrobenzene (DNCB)-induced atopic dermatitis-like model. Results: CK treatment increased the expression of SPINK5 and decreased the expression of its downstream genes, such as KLKs and PAR2. In the UVB-irradiated mouse model and the DNCB-induced atopic dermatitis model, CK restored increased TEWL and decreased hydration and epidermal hyperplasia. In addition, CK normalized the reduced SPINK5 expression caused by UVB or DNCB, thereby restoring the expression of the proteins involved in desquamation to a level similar to normal. Conclusions: Our data showed that CK contributes to improving skin-barrier function in UVB-irradiated and DNCB-induced atopic dermatitis-like models through SPINK5. These results suggest that therapeutic attempts with CK might be useful in treating barrier-disrupted diseases.

• Tuberculosis and Respiratory Diseases
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• v.73 no.6
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• pp.320-324
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• 2012

A 55-year-old woman was admitted for an elevated serum carbohydrate antigen-125 (CA-125) level, and a left pleural effusion, which were detected at a routine health examination. Computed tomography of the chest was performed upon admission, revealing extensive bilateral paratracheal and mediastinal lymph node enlargement with a massive left-sided pleural effusion. Subsequent analysis of the pleural fluid demonstrated consistency with an exudate, no evidence of malignant cells, and a normal adenosine deaminase. However, the pleural fluid and serum CA-125 levels were 2,846.8 U/mL and 229.5 U/mL, respectively. A positron emission tomography did not reveal any primary focus of malignancy. Finally, a surgical mediastinoscopic biopsy of several mediastinal lymph nodes was performed, revealing non-necrotizing granulomas, consistent with sarcoidosis. After a month of treatment of prednisolone, the left pleural effusion had resolved, and after 2 months the serum CA-125 level was normalized.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.393-407
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• 2012

This study focuses on the correction of topographic effects caused by a combination of solar elevation and azimuth, and topographic relief in single optical remote sensing imagery, and by a combination of changes in position of the sun and topographic relief in comparative analysis of multi-temporal imageries. For the Jeju Island, Republic of Korea, where Mt. Halla and various cinder cones are located, a Landsat 7 ETM+ imagery and ASTER GDEM data were used to normalize the topographic effects on the imagery, using two topographic normalization methods: cosine correction assuming a Lambertian condition and assuming a non-Lambertian c-correction, with kernel sizes of $3{\times}3$, $5{\times}5$, $7{\times}7$, and $9{\times}9$ pixels. The effects of each correction method and kernel size were then evaluated. The c-correction with a kernel size of $7{\times}7$ produced the best result in the case of a land area with various land-cover types. For a land-cover type of forest extracted from an unsupervised classification result using the ISODATA method, the c-correction with a kernel size of $9{\times}9$ produced the best result, and this topographic normalization for a single land cover type yielded better compensation for topographic effects than in the case of an area with various land-cover types. In applying the relative radiometric normalization to topographically normalized three multi-temporal imageries, more invariant spectral reflectance was obtained for infrared bands and the spectral reflectance patterns were preserved in visible bands, compared with un-normalized imageries. The results show that c-correction considering the remaining reflectance energy from adjacent topography or imperfect atmospheric correction yielded superior normalization results than cosine correction. The normalization results were also improved by increasing the kernel size to compensate for vertical and horizontal errors, and for displacement between satellite imagery and ASTER GDEM.

• The Journal of the Petrological Society of Korea
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• v.9 no.2
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• pp.84-98
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• 2000

Daejeon-sa basalt in the Mt. Juwang area composed of 12 basalt flows alternate with 9 peperites and each basalt and peperite has the variety of thickness. Peperites yielded in Daejeon-sa basalt are mixed of basalt with reddish shale, of which textural type is globular peperite. Basalts yielded in Daejeon-sa basalt are massive basalt without vesicule, although sometimes vesicules are founded in upper within a flow unit. The basalt has mainly pseudomorph of olivine as phenocryst, and also plagioclase and clinopyroxene phenocryst. Matrix is mainly subophitic texture. The plotting result on the TAS diagram shows these basalts belong to the sub-alkaline, and it can be subdivided into calc-alkaline series on the basis of the diagram of Si02 vs. K20 and of alkali index vs. A1203 diagram. According to plots of wt.% oxides vs. wt.% MgO, abundances of A1203 and CaO increase with decreasing MgO while F ~ dOecre~ase . With decreasing MgO compatible elements decrease while incompatible elements increase. In spider diagram of MORB-normalized trace element patterns, HFS elements are nearly similiar with MORB, but LIL elements are enriched. Especially, contents of Ce, F: and Sm are enriched but Nb is depleted. In the chondrite-normalized REE patterns light REEs are enriched than heavy REEs. Tectomagmatic discrimination diagrams shows basalts in the study area are formed in the tectonomagmatic environment of subduction zone under continental margin. This result accord with characters of chemical composition mentioned above. Cr vs. Y diagram and CeM, vs. Ce diagram show that the primary magma of the basalts may formed by the about 15% partial melting of garnet-peridotite in the mantle wedge. After then, Daejeon-sa basalts may formed from evolved magma undergone mainly olivine fractional crystallization and contarnination of crustal materials before eruption.