• Bulletin of Food Technology
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• v.26 no.3
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• pp.258-265
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• 2013

• Biomolecules & Therapeutics
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• v.31 no.1
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• pp.89-96
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• 2023

Uric acid produced by guanine deaminase (GDA) is involved in photoaging and hyperpigmentation. Reactive oxygen species (ROS) generated by uric acid plays a role in photoaging. However, the mechanism by which uric acid stimulates melanogenesis in GDA-overexpressing keratinocytes is unclear. Keratinocyte-derived paracrine factors have been identified as important mechanisms of ultraviolet-induced melanogenesis. Therefore, the role of paracrine melanogenic growth factors in GDA-induced hypermelanosis mediated by uric acid was examined. The relationships between ROS and these growth factors were examined. Primary cultured normal keratinocytes overexpressed with wild type or mutant GDA and those treated with xanthine or uric acid in the presence or absence of allopurinol, H₂O₂, or N-acetylcysteine (NAC) were used in this study. Intracellular and extracellular bFGF and SCF levels were increased in keratinocytes by wild type, but not by loss-of-function mutants of GDA overexpression. Culture supernatants from GDA-overexpressing keratinocytes stimulated melanogenesis, which was restored by anti-bFGF and anti-SCF antibodies. Allopurinol treatment reduced the expression levels of bFGF and SCF in both GDA-overexpressing and normal keratinocytes exposed to exogenous xanthine; the exogenous uric acid increased their expression levels. H₂O₂-stimulated tyrosinase expression and melanogenesis were restored by NAC pretreatment. However, H₂O₂ or NAC did not upregulate or downregulate bFGF or SCF, respectively. Overall, uric acid could be involved in melanogenesis induced by GDA overexpression in keratinocytes via bFGF and SCF upregulation not via ROS generation.

• Bulletin of the Korean Chemical Society
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• v.35 no.1
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• pp.39-44
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• 2014

Glass discs functionalized with alkynyl (GDA) terminated monolayers were prepared and incubated in $AgNO_3$ solution (GDA-Ag). The modified functional glass surfaces were characterized by X-ray photoelectron microscopy (XPS). The potential of GDA and GDA-Ag as antimicrobial surfaces was investigated. Anti-microbial efficacies of GDA against Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, Bacillus cereus, and Candida albicans was relatively low ranging from 4.67 to 17.00%. However, the GDA-Ag was very effective and its antimicrobial efficacy ranged from 99.90 to 99.99% against the same set of microbial strains except for C. albicans where it was 95.50%. The durability of the Ag bonded to the terminal alkynyl groups was studied by placing the GDA-Ag in PBS buffer solution (pH 7.4) for two weeks. Initially, the silver release was relatively fast, with 40.05 ppb of silver released in first 24 h followed by a very slow and constant release. To study the potential of GDA-Ag for medical applications, in vitro cytotoxicity of GDA-Ag against Human Embryonic Kidney 293 (HEK293) cell lines was studied using WST-assay. The cytotoxicity of the GDA-Ag was very low (5%) and was almost comparable to the control (blank glass disc) indicating that GDA-Ag has a promising potential for medical applications.

• Korean Architects
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• s.480
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• pp.36-41
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• 2009

• Korean Architects
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• s.645
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• pp.38-43
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• 2023

• Journal of Electrical Engineering and Technology
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• v.5 no.4
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• pp.646-652
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• 2010

This paper investigates a method to improve the breakdown voltage characteristics of a gas discharge arrester (GDA) for a surge suppressor. The middle electrode is inserted between two terminal electrodes. Voltage application to the electrode synchronized and amplified by the impulse voltage decreases spark overvoltage from 45% to 57.6%. The decrease is caused by higher voltage slope, as opposed to applied impulse voltage (by 5.5 to 6.2 times). In addition, the GDA model using ATP-Draw was used to analyze the operation characteristics of GDAs. The test and simulation results agree to within 2% when the trigger source was used.

• The Korean Journal of Community Living Science
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• v.24 no.3
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• pp.327-342
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• 2013

The purposes of this study were to explore consumer preference for the types of nutrition label of cereal products and to identify some influencing factors on purchase intention and choice probability of nutrition-labeled products. First, most of the respondents preferred the nutrition fact panel with traffic light-GDA(TL-GDA), while the nutrition fact panel only type and the nutrition fact panel with front-of-package(FOP) type were preferred by few respondents. However, consumers evaluated higher for TL-GDA type and FOP symbol type, while the nutrition fact panel only type was evaluated much lower. Second, consumer preference for label types was partially related with 'eating breakfast' and consumer evaluations of the types of labels for the nutrition fact panel only and the nutrition fact panel with FOP were found to be significantly different by gender. Lastly, both purchase intention and choice probability for nutrition-labeled products were found to be significantly influenced by information search and product attitude. In addition, choice probability was found to be significantly influenced by individual characteristics such as gender and grade. It is necessary to find the relationship between nutrition labels and consumer response as this can help consumers make a better choice of food as well as providing some useful information on consumers to the related parties such as companies and consumer organizations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.125-130
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• 2018

Linear discriminant analysis is a statistical analysis method that is generally used for dimensionality reduction of the feature vectors or for class classification. However, in the case of a data set that cannot be linearly separated, it is possible to make a linear separation by mapping a feature vector into a higher dimensional space using a nonlinear function. This method is called generalized discriminant analysis or kernel discriminant analysis. In this paper, we carried out target classification experiments with active sonar target signals available on the Internet using both liner discriminant and generalized discriminant analysis methods. Experimental results are analyzed and compared with discussions. For 104 test data, LDA method has shown correct recognition rate of 73.08%, however, GDA method achieved 95.19% that is also better than the conventional MLP or kernel-based SVM.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.39-58
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• 2019

This study performed the dam watershed storm runoff modeling using GPM(Global Precipitation Measurement) satellite rain and KIMSTORM2(KIneMatic wave STOrm Runoff Model 2) distributed model. For YongdamDam watershed(930㎢), three heavy rain events of 25th August 2014, 11th September 2017, and 26th June 2018 were selected and tested for 4 cases of spatial rainfalls such as (a) Kriging interpolated data using ground observed data at 7 stations, (b) original GPM data, (c) GPM corrected by CM(Conditional Merging), and GPM corrected by GDA(Geographical Differential Analysis). For the 4 kinds of data(Kriging, GPM, CM-GPM, and GDA-GPM), the KIMSTORM2 was calibrated respectively using the observed flood discharges at 3 water level gauge stations(Cheoncheon, Donghyang, and Yongdam) with parameters of initial soil moisture contents, stream Manning's roughness coefficient, and effective hydraulic conductivity. The total average Nash-Sutcliffe efficiency(NSE) for the 3 events and 3 stations was 0.94, 0.90, 0.94, and 0.94, determination coefficient(R²) was 0.96, 0.92, 0.97 and 0.96, the volume conservation index(VCI) was 1.03, 1.01, 1.03 and 1.02 for Kriging, GPM, CM-GPM, and GDA-GPM applications respectively. The CM-GPM and GDA-GPM showed better results than the original GPM application for peak runoff and runoff volume simulations, and they improved NSE, R², and VCI results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1390-1403
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• 2016

Facial expression recognition (FER) plays a very significant role in computer vision, pattern recognition, and image processing applications such as human computer interaction as it provides sufficient information about emotions of people. For video-based facial expression recognition, depth cameras can be better candidates over RGB cameras as a person's face cannot be easily recognized from distance-based depth videos hence depth cameras also resolve some privacy issues that can arise using RGB faces. A good FER system is very much reliant on the extraction of robust features as well as recognition engine. In this work, an efficient novel approach is proposed to recognize some facial expressions from time-sequential depth videos. First of all, efficient Local Binary Pattern (LBP) features are obtained from the time-sequential depth faces that are further classified by Generalized Discriminant Analysis (GDA) to make the features more robust and finally, the LBP-GDA features are fed into Hidden Markov Models (HMMs) to train and recognize different facial expressions successfully. The depth information-based proposed facial expression recognition approach is compared to the conventional approaches such as Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Linear Discriminant Analysis (LDA) where the proposed one outperforms others by obtaining better recognition rates.