• Translational and Clinical Pharmacology
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• v.25 no.2
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• pp.67-73
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• 2017

Glimepiride, a third generation sulfonylurea, is an antihyperglycemic agent widely used to treat type 2 diabetes mellitus. In this study, an untargeted urinary metabolomic analysis was performed to identify endogenous metabolites affected by glimepiride administration. Urine samples of twelve healthy male volunteers were collected before and after administration of 2 mg glimepiride. These samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and then subjected to multivariate data analysis including principal component analysis and orthogonal partial least squares discriminant analysis. Through this metabolomic profiling, we identified several endogenous metabolites such as adenosine 3', 5'-cyclic monophosphate (cAMP), quercetin, tyramine, and urocanic acid, which exhibit significant metabolomic changes between pre- and posturine samples. Among these, cAMP, which is known to be related to insulin secretion, was the most significantly altered metabolite following glimepiride administration. In addition, the pathway analysis showed that purine, tyrosine, and histidine metabolism was affected by pharmacological responses to glimepiride. Together, the results suggest that the pharmacometabolomic approach, based on LC-MS/MS, is useful in understanding the alterations in biochemical pathways associated with glimepiride action.

• Journal of the Korean Society of International Agriculture
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• v.30 no.4
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• pp.320-327
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• 2018

The purpose of this study is to suggest the policy direction for promoting Korean grape, Shine Muscat, export to China. For this, the data were collected from 102 Chinese who live in Guangzhou province. The survey was conducted from Oct 10th to 13th 2017. PLS-SEM model is used to investigate the main factors that cause the Chinese consumers to purchase Korean grape, Shine Muscat. This study finds that the post-evaluation factor is more important to obtain final evaluation and to purchase Korean grape in the future. Thus farmers and research institutes should investigate how to improve the quality for the sweetness and the texture of the grape, reflecting the Chinese consumers' preference.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.249-256
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• 2019

This paper presents an optimization framework of electrical impedance tomography for characterizing electrical conductivity profiles of concrete structures in two dimensions. The framework utilizes a partial-differential-equation(PDE)-constrained optimization approach that can obtain the spatial distribution of electrical conductivity using measured electrical potentials from several electrodes located on the boundary of the concrete domain. The forward problem is formulated based on a complete electrode model(CEM) for the electrical potential of a medium due to current input. The CEM consists of a Laplace equation for electrical potential and boundary conditions to represent the current inputs to the electrodes on the surface. To validate the forward solution, electrical potential calculated by the finite element method is compared with that obtained using TCAD software. The PDE-constrained optimization approach seeks the optimal values of electrical conductivity on the domain of investigation while minimizing the Lagrangian function. The Lagrangian consists of least-squares objective functional and regularization terms augmented by the weak imposition of the governing equation and boundary conditions via Lagrange multipliers. Enforcing the stationarity of the Lagrangian leads to the Karush-Kuhn-Tucker condition to obtain an optimal solution for electrical conductivity within the target medium. Numerical inversion results are reported showing the reconstruction of the electrical conductivity profile of a concrete specimen in two dimensions.

• Journal of Ginseng Research
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• v.43 no.4
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• pp.508-516
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• 2019

Background: Ginsenosides are not only the principal bioactive components but also the important indexes to the quality assessment of Panax ginseng Meyer. Their contents in cultivated ginseng vary with the growth environment and age. The present study aimed at evaluating the significant difference between 36 cultivated ginseng of different cultivation areas and ages based on the simultaneously determined contents of 14 ginsenosides. Methods: A high-performance liquid chromatography (HPLC) coupled with triple quadrupole mass spectrometer (MS) method was developed and used in the multiple reaction-monitoring (MRM) mode (HPLC-MRM/MS) for the quantitative analysis of ginsenosides. Multivariate statistical analysis, such as principal component analysis and partial least squares-discriminant analysis, was applied to discriminate ginseng samples of various cultivation areas and ages and to discover the differentially accumulated ginsenoside markers. Results: The developed HPLC-MRM/MS method was validated to be precise, accurate, stable, sensitive, and repeatable for the simultaneous determination of 14 ginsenosides. It was found that the 3- and 5-yr-old ginseng samples were differentiated distinctly by all means of multivariate statistical analysis, whereas the 4-yr-old samples exhibited similarity to either 3- or 5-yr-old samples in the contents of ginsenosides. Among the 14 detected ginsenosides, Rg1, Rb1, Rb2, Rc, 20(S)-Rf, 20(S)-Rh1, and Rb3 were identified as potential markers for the differentiation of cultivation ages. In addition, the 5-yr-old samples were able to be classified in cultivation area based on the contents of ginsenosides, whereas the 3- and 4-yr-old samples showed little differences in cultivation area. Conclusion: This study demonstrated that the HPLC-MRM/MS method combined with multivariate statistical analysis provides deep insight into the accumulation characteristics of ginsenosides and could be used to differentiate ginseng that are cultivated in different areas and ages.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.208-213
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• 2021

There is a lack of studies comparing the internal quality of fruit with its external quality. However, issues of internal quality of fruit such as internal browning are important. We propose a method of classifying normal apples and internally browned apples using a near-infrared (NIR) non-destructive system. Specifically, we found the optimal wavelength and characteristics of the spectra for determining the internal browning of Fuji apples. The NIR spectra of apples were obtained in the wavelength range of 470-1150 nm. A group of normal apples and a group of internally browned apples were identified using principal component analysis (PCA), and a partial least squares regression (PLSR) analysis was performed to develop and evaluate the discriminant model. The PCA analysis revealed a clear difference between the normal and internally browned apples. From the PLSR, the correlation coefficient of the predictive model without pretreatment was determined to be 0.902 with an RMSE value of 0.157. The correlation coefficient of the predictive model with pretreatment was 0.906 with an RMSE value of 0.154. The results show that this model is suitable for classifying normal and internally browned apples and that it can be applied for the sorting and evaluation of agricultural products for internal and external defects.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.1
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• pp.29-34
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• 2021

Near infrared reflectance spectroscopy (NIRS) is routinely used for the determination of nutrient components of forages. However, little is known about the impact of sample preparation and wavelength on the accuracy of the calibration to predict minerals. This study was conducted to assess the effect of sample preparation and wavelength of near infrared spectrum for the improvement of calibration and prediction accuracy of Calcium (Ca) and Phosphorus (P) in imported hay using NIRS. The samples were scanned in reflectance in a monochromator instrument (680-2,500 nm). Calibration models (n = 126) were developed using partial least squares regression (PLS) based on cross-validation. The optimum calibrations were selected based on the highest coefficients of determination in cross validation (R2) and the lowest standard error of cross-validation (SECV). The highest R2 and the lowest SECV were obtained using oven-dry grinded sample preparation and 1,100-2,500 nm wavelength. The calibration (R2) and SECV were 0.99 (SECV: 468.6) for Ca and 0.91 (SECV: 224.7) for P in mg/kg DM on a dry weight, respectively. Results of this experiment showed the possibility of NIRS method to predict mineral (Ca and P) concentration of imported hay in Korea for routine analysis method to evaluate the feed value.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.1
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• pp.61-66
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• 2022

Sesamin and sesamolin are major lignan components with a wide range of potential biological activities of sesame seeds. Near infrared reflectance spectroscopy (NIRS) is a rapid and non-destructive analysis method widely used for the quantitative determination of major components in many agricultural products. This study was conducted to develop a screening method to determine the lignan contents for sesame breeding. Sesamin and sesamolin contents of 482 sesame samples ranged from 0.03-14.40 mg/g and 0.10-3.79 mg/g with an average of 4.93 mg/g and 1.74 mg/g, respectively. Each sample was scanned using NIRS and calculated for the calibration and validation equations. The optimal performance calibration model was obtained from the original spectra using partial least squares (PLS). The coefficient of determination in calibration (R²) and standard error of calibration (SEC) were 0.963 and 0.861 for sesamin and 0.875 and 0.292 for sesamolin, respectively. Cross-validation results of the NIRS equation showed an R² of 0.889 in the prediction for sesamin and 0.781 for sesamolin and a standard error of cross-validation (SECV) of 1.163 for sesamin and 0.417 for sesamolin. The results showed that the NIRS equation for sesamin and sesamolin could be effective in selecting high lignan sesame lines in early generations of sesame breeding.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.524-539
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• 2022

With the advent of generative artificial intelligence technology, it became possible to create a virtual human, and produce a lecture video only with textual information. It is expected that the virtual human will enhance the efficient production of educational contents and the student's entertainment experience and satisfaction. However, there have been still few studies that have demonstrated the process of how virtual human technology reaches students' satisfaction. Therefore, the purpose of this study is to empirically examine whether the human likeness, which is the main characteristic of a virtual human based on Uncanny Valley theory, affects human experience and satisfaction. In particular, human likeness of the Uncanny Valley theory was subdivided into human likeness in the visual and verbal dimensions, and the process of reaching satisfaction was understood based on the experience economy model. In particular, human similarity in Uncanny Valley theory was classified as similarity in the visual and language levels, and the process of reaching satisfaction based on the experiential economic model was analyzed with a partial least squares structure model equation (PLS-SEM). The survey was conducted online for a panel of office workers at a specialized research institution in China. The results indicate that both the visual and verbal human likeness had a positive effect on experience economy factors (education, entertainment, esthetic, escape), and then these experiential factors had a significant effect on satisfaction. The results also provide some suggestions to consider when designing educational contents by virtual human.

• Korean Journal of Poultry Science
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• v.48 no.4
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• pp.239-253
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• 2021

This study investigates the metabolomic changes in breast and thigh meat from Cobb and Ross 308 chickens regarding the rearing environment. One-day-old Cobb and Ross broilers were raised for 35 days in conventional and animal welfare farms with, amongst others, different floor sizes, stock densities, and ammonia concentrations. One-dimensional ¹H nuclear magnetic resonance, orthogonal partial least squares-discriminant analysis (OPLS-DA), and pathway analyses were performed to analyze the metabolomic properties of broiler meat. For breast meat, only those from the Ross strain could be separated according to the environment in the OPLS-DA plot. Ross breast meat from animal welfare farms showed significantly higher acetate, anserine, creatine, and inosine monophosphate content than those from conventional farms (P<0.05). In contrast, for thigh meat, the Cobb strain was differentiated using OPLS-DA. The contents of five metabolites, such as glucose and lactate, were higher in thigh meat from animal welfare farms; however, nine metabolites, including seven free amino acids, were lower compared to those from conventional farms (P<0.05). Pathway analysis was performed to interpret the biological changes in chicken meat based on environmental factors. The results indicated that the animal welfare environment led to significant changes in four metabolic pathways in Ross breast meat and in 20 metabolic pathways in Cobb thigh meat (P<0.05). In conclusion, the animal welfare environment could influence the metabolomic properties of Ross breast meat and Cobb thigh meat, which may affect the sensory quality of meat.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.45-64
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• 2022

Due to the recent and rapid globalization, logistics outsourcing has expanded globally and is seen as a means of creating a robust logistics system. However, many businesses continue to have difficulties with their logistics outsourcing contracts, which compels them to reinstate the logistics function for internal management. This study aims to investigate how organizational capabilities of logistics service providers (LSPs), notably flexibility, integration, innovation, and technological capabilities, impact on the logistics outsourcing success in Ugandan food processing firms. Using a structured questionnaire survey, cross-sectional data collected from 211 food processing firms in Kampala - Uganda were analyzed by partial least squares-structural equation modeling (PLS-SEM) using SmartPLS 3.3.7 software to examine the theorized relationships. The study findings revealed that whereas the technological and innovation capabilities positively and significantly influence logistics outsourcing success, the effects of flexibility and integration capabilities were insignificant. Additionally, the importance-performance map analysis (IPMA) reveals that the technological capability is a priority capability, followed by the innovation capability if logistics outsourcing success is to be achieved. Conversely, flexibility and integration capabilities are of low priority.