• Conservation Science in Museum
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• v.2
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• pp.69-76
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• 2000

This study, a part of scientific analysis of the 23 Neolithic red earthenwares excavated from southeastern coast and islands. We analyzed earthenware through statistical method and hardness analysis of clay, following the analysis of clay composition, its firing temperature, pigment composition and its thickness. Clay composition was analyzed by using ICP-AES and XRF, and then Principal Component Analysis (one of multivariate methods) was used for classification. As a result, clay of the earthenware was classified into 3 groups(Bumbang, Youkjido and other sites). In addition, hardness analysis of pigment and clay based on the depth of earthenware surface showed that pigment layer containing lots of Fe₂O₃ had higher hardness than clay part, which can be interpreted that Fe₂O₃ contributes to raising hardness in case of high temperature firing. The fact that pigment hardness is higher than that of clay part implies that pigment was applied before firing.

• Natural Product Sciences
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• v.17 no.2
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• pp.147-159
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• 2011

A high-performance liquid chromatography-electrospray ionization-tandem mass spectrometric method was developed to determine simultaneously eight marker constituents of Forsythiae fructus, and subsequently applied it to classify its two botanical origins. The marker compounds of Forsythia suspensa were phillyrin, pinoresinol, phillygenin, lariciresinol and forsythiaside; those of F.viridissima were arctiin, arctigenin and matairesinol. Separation of the eight analytes was achieved on a phenyl-hexyl column (150${\times}$2.0 mm i.d., 3 ${\mu}M$) using gradient elution with the mobile phase: (A) 10% acetonitrile in 0.5% acetic acid, (B) 40% aqueous acetonitrile. A few fragment ions specific to the types of lignans, among the product ions generated by collisonally induced dissociation (CID) of molecular ion clusters, such as [M-H]$^-$ or [M+OAc]$^-$ were used not only for fingerprinting analysis but for the quantification of each epimer by using multiple-reaction monitoring mode. It was shown good linearity ($r^2{\geq}$ 0.9998) over the wide range of all analytes; intra- and inter-day precisions (RSD, %) were within 9.14% and the accuracy ranged from 84.3 to 115.1%. The analytical results of 40 drug samples, combined with multivariate statistical analyses - principal component analysis (PCA) and hierarchical cluster analysis (HCA) - clearly demonstrated the classification of the test samples according to their botanical origins. This method would provide a practical strategy for assessing the authenticity or quality of the herbal drug.

• Bulletin of the Korean Chemical Society
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• v.30 no.1
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• pp.137-144
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• 2009

In this study, quantitative and pattern recognition analyses for the quality evaluation of Herba Epimedii using HPLC was developed. For quantitative analysis, five major bioactive constituents, hyperin, epimedin A, epimedin B, epimedin C, and icariin were determined. Analysis was carried out on Capcell pak $C_{18}$ column ($250{\time}4.6$ mm, 5 ${\mu}m$) with a mobile phase of mixture of acetonitrile and 0.1% formic acid, using UV detection at 270 nm. The linear behavior was observed over the investigated concentration range (2-50 ${\mu}g/mL;\;r_2\;>$ 0.99) for all analytes. The intraand inter-day precisions were lower than 4.3% (as a relative standard deviation, RSD) and accuracies between 95.1% and 104.4%. The HPLC analytical method for pattern recognition analysis was validated by repeated analysis of one reference sample. The RSD of intra- and inter-day variation of relative retention time (RRT) and relative peak area (RPA) of the 12 selected common peaks were below 0.8% and 4.7%, respectively. The developed methods were applied to analysis of twenty Herba Epimedii extract samples. Contents of hyperin, epimedin A, epimedin B, epimedin C, and icariin were calculated to be 0$\sim$0.79, 0.69$\sim$1.91, 0.93$\sim$9.58, 0.65$\sim$3.05, and 2.43$\sim$11.8 mg/g dried plant. Principal component analysis (PCA) showed that most samples were clustered together with the reference samples but several apart from the main cluster in the PC score plot, indicating differences in overall chemical composition between two clusters. The present study suggests that quantitative determination of marker compounds combined with pattern-recognition method can provide a comprehensive approach for the quality assessment of herbal medicines.

• Journal of Korean Society on Water Environment
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• v.37 no.2
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• pp.114-127
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• 2021

Water pollution in the lower reaches of the Namhan River is getting worse due to drought and a decrease in water quantity due to climatic changes and hence is affecting the water quality of Paldang Lake. Accordingly, we have used a water quality index (WQI) and statistical analysis in this study to identify the characteristics of the water quality in the lower reaches of the Namhan River, the main causes of water pollution, and tributaries that need priority management. Typically, 10 items (WT, pH, EC, DO, BOD, COD, SS, T-N, T-P, and TOC) were used as the water quality factors for the statistical analysis, and the matrix of data was set as 324 × 10·1. The correlation analysis demonstrated a strong correlation between Chemical Oxygen Demand (COD) and T-P with a high statistical significance (r=0.700, p<0.01). Furthermore, the result of principal component analysis (PCA) revealed that the main factors affecting the change in water quality were T-P and organic substances introduced into the water by rainfall. Based on the Mann-Kendall test, a statistically significant increase in pH was observed in SH-1, DL, SH-2, CM, and BH, along with an increase in WQI in SH-2 and SM. BH was identified as a tributary that needs priority management in the lower reaches of the Namhan River, with a "Somewhat poor" (IV) grade in T-P, "Fair" grade in WQI, and "Marginal" grade in summer.

• Journal of Environmental Health Sciences
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• v.42 no.4
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• pp.280-292
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• 2016

Objectives: The objective of this study was to build COD regression models for the Han River and evaluate water quality. Methods: Water quality data sets for the dry season (as of January) during a four-year period (2012-2015) were collected from the database of the Han River automatic water quality monitoring stations. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR) were used to build five-descriptor COD models. Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) are useful tools for extracting meaningful information. Results: The $r^2$ of the best COD models provided significant high values (> 0.8) between 2012 and 2015. Total organic carbon (TOC) was a surrogate indicator for COD (as COD/TOC) with high reliability ($r^2=0.63$ in 2012, $r^2=0.75$ for 2013, $r^2=0.79$ for 2014 and $r^2=0.85$ for 2015). The ratios of COD/TOC were calculated as 2.08 in 2012, 1.79 in 2013, 1.52 and 1.45 in 2015, indicating that biodegradability in the water body of the Han River was being sustained, thereby further improving water quality. The BOD/COD ratio supported these findings. The cluster analysis revealed higher annual levels of microorganisms and phosphorous at stations along the Hangang-Seoul and Hantangang areas. Nevertheless, the overall water quality over the last four years showed an observable trend toward continuous improvement. These findings also suggest that non-point pollution control strategies should consider the influence of upstreams and downstreams to protect water quality in the Han River. Conclusion: This data analysis procedure provided an efficient and comprehensive tool to interpret complex water quality data matrices. Results from a trend analysis provided much important information about sources and parameters for Han River water quality management.

• Food Science of Animal Resources
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• v.38 no.2
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• pp.362-375
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• 2018

This study proposed a rapid microscopic examination method for pork freshness evaluation by using the self-assembled hyperspectral microscopic imaging (HMI) system with the help of feature extraction algorithm and pattern recognition methods. Pork samples were stored for different days ranging from 0 to 5 days and the freshness of samples was divided into three levels which were determined by total volatile basic nitrogen (TVB-N) content. Meanwhile, hyperspectral microscopic images of samples were acquired by HMI system and processed by the following steps for the further analysis. Firstly, characteristic hyperspectral microscopic images were extracted by using principal component analysis (PCA) and then texture features were selected based on the gray level co-occurrence matrix (GLCM). Next, features data were reduced dimensionality by fisher discriminant analysis (FDA) for further building classification model. Finally, compared with linear discriminant analysis (LDA) model and support vector machine (SVM) model, good back propagation artificial neural network (BP-ANN) model obtained the best freshness classification with a 100 % accuracy rating based on the extracted data. The results confirm that the fabricated HMI system combined with multivariate algorithms has ability to evaluate the fresh degree of pork accurately in the microscopic level, which plays an important role in animal food quality control.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.10a
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• pp.43-43
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• 2018

Mutation breeding by radiation is useful for improving various crop species. Up to now, a total of 170 soybean mutant varieties have been released in the world, which is the second most registered varieties after rice. Despite the economic importance of soybean, there have been no TRAP marker system studies on genetic relationships between/among mutant lines. To develop a strategy of Mutant Diversity Pool (MDP) conservation, a study on the genetic diversity of 210 soybean mutant lines (8 cultivars and 202 mutants) was performed through a TRAP analysis. Sixteen primer combinations amplified a total of 551 fragments. The highest (84.00%) and lowest (32.35%) polymorphism levels were obtained with primers MIR157B + Ga5 and B14G14B + Ga3, respectively. The mean PIC values 0.15 varied among the primer combination ranging from 0.07 in B14G14B + Sal2 to 0.23 in MIR157B + Sa4. Phylogenetic, principal component analysis (PCA) and structure analysis indicated that the 210 lines belong to four groups based on the 16 combination TRAP markers. AMOVA showed 21.0% and 79.0% variations among and within the population, respectively. Overall, the genetic similarity of each cultivar and its mutants were higher than within other mutant populations. Our results suggest that the TRAP marker system may be useful for assessing the genetic diversity among soybean mutants and help to improve our knowledge of soybean mutation breeding.

• Toxicological Research
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• v.34 no.3
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• pp.199-210
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• 2018

Skeletal muscle can be ultrastructurally damaged by eccentric exercise, and the damage causes metabolic disruption in muscle. This study aimed to determine changes in the metabolomic patterns in urine and metabolomic markers in muscle damage after eccentric exercise. Five men and 6 women aged 19~23 years performed 30 min of the bench step exercise at 70 steps per min at a determined step height of 110% of the lower leg length, and stepping frequency at 15 cycles per min. $^1H$ NMR spectral analysis was performed in urine collected from all participants before and after eccentric exercise-induced muscle damage conventionally determined using a visual analogue scale (VAS) and maximal voluntary contraction (MVC). Urinary metabolic profiles were built by multivariate analysis of principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA) using SIMCA-P. From the OPLS-DA, men and women were separated 2 hr after the eccentric exercise and the separated patterns were maintained or clarified until 96 hr after the eccentric exercise. Subsequently, urinary metabolic profiles showed distinct trajectory patterns between men and women. Finally, we found increased urinary metabolites (men: alanine, asparagine, citrate, creatine phosphate, ethanol, formate, glucose, glycine, histidine, and lactate; women: adenine) after the eccentric exercise. These results could contribute to understanding metabolic responses following eccentric exercise-induced muscle damage in humans.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.4
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• pp.315-326
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• 2013

This study investigated the temporal-spatial distribution and variations in water quality parameters (temperature, salinity, pH, DO, COD, SPM, DIN, DIP, silicate, TN, TP, and chlorophyll-a) in the coastal area of Jeju, Korea, adjacent to aquaculture ponds (Aewol-ri, Haengwon-ri, Pyosun-ri, and Ilkwa-ri). Data were collected bimonthly from February 2010 to December 2011. A principal component analysis (PCA) identified three major factors controlling variations in water quality during the sampling period. Aquaculture effluent water led to large changes in nutrient levels. The highest nutrient values were observed during the investigation period. The relatively large increase in organic matter at the sampling stations coupled with sea area runoff events during the summer rainy period. Variation in chlorophyll-a concentration was mainly driven by meteorological factors such as air temperature and rainfall in the coastal areas of Aewol and Haengwon. In the coastal areas of Pyosun and Ilkwa, pollution was caused by anthropogenic factors such as discharge of aquaculture effluent water. High nutrient concentrations at the majority of the coastal stations indicate eutrophication of coastal waters, especially within a distance of 300 m and depth of 10m from drainage channels. Coastal eutrophication driven by aquaculture effluent may be harmful inshore. Events such as eutrophication may potentially influence water pollution in aquaculture ponds when seawater intake is detected because of aquaculture effluent water.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.441-453
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• 2017

This paper described the spatio-temporal distributions in the phytoplankton community, such as species composition, standing crops, and dominant species, from July 2012 to April 2013 in the Coastal Waters of Central South Sea (CWoCSS) of Korea. A total of 87 species of phytoplankton belonging to 52 genera were identified. In particular, diatoms and phytoflagellates comprised more than 62.1% and 37.9% of the total species, respectively. The phytoplankton cell density fluctuated with an annual mean of $7.9{\times}10^4cells{\cdot}L^{-1}$ between the lowest value of $1.0{\times}10^3cells{\cdot}L^{-1}$ in spring and the highest value of $4.5{\times}10^5cells{\cdot}L^{-1}$ in winter. The seasonal succession of the dominant species were Chaetoceros curvisetus, Ch. debilis in summer, Eucampia zodiacus in autumn, E. zodiacus, Thalassiosira curviseriata in winter and Skeletonema costatum -ls (like species), Leptocylindrus danicus in spring. According to principal component analysis, the phytoplankton community of the CWoCSS was characterized by the mixing rate between the freshwater inflow from Somjin River and the seawater of the South Sea, Korea.