• Journal of Life Science
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• v.20 no.11
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• pp.1691-1696
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• 2010

Neohesperidin is a natural new nutrition sweetener, widely existing in plants of dry citrus peel, which can be derived from extraction. Since the sweetness is 1,300-1,500 times greater than that of sugar, neohesperidin are widely used in fruit juices, wines, beverages, bakeries and pharmaceutical formulations, and are particularly suitable for consumption by diabetic patients. However, the yield of extraction from citrus peel waste is very low. In this study optimal yield conditions were determinedusing response surface methodology (RSM) in order to increase the neohesperidin extraction yield. The critical factors for maximum extraction yield were selected extraction pressure ($x_1$), extraction time ($x_2$), and concentration of ethanol ($x_3$). As a result, the extraction yield was improved when the extracting pressure increased. The extraction yield also increased in a time-dependent manner. When adding ethanol as an assistance solvent to the supercritical carbon dioxide, extraction yield was increased as more ethanol concentration was added. Finally, the extraction yield of neohesperidin was improved to about 162.22% compared to ethanol extraction as a conventional method.

• Journal of Life Science
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• v.25 no.7
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• pp.810-818
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• 2015

We analyzed whether lactic acid bacteria could control the expression of IL-4 and IL-13 in activated mast cells and whether these bacteria could inhibit the activity of transcription factors such as GATA-1, GATA-2, NF-AT1, NF-AT2, and NF-κB p65. We previously described a technique for identification of lactic acid bacteria with anti-atopy functionality by confirming increased expression of CD4+/CD25+/foxp3+ in T cells. We also confirmed that a double-culture method increased the antibacterial activity of these lactic acid bacteria against Staphylococcus aureus (S. aureus). In the present study, we characterized the effect of lactic acid bacteria cultured by this double-culture method on inhibition of allergic inflammatory reactions of RBL-2H3 mast cells, a cellular model of atopic dermatitis. The strongest anti-allergic effects of the lactic acid bacteria were seen in the following order: Lactococcus lactis broth cultured with medium containing Lactobacillus plantarum culture supernatant > Lc. lactis > Lc. lactis broth cultured with medium containing Lb. plantarum culture supernatant > Lb. plantarum. Thus, Lc. lactis cultured in medium containing Lb. plantarum culture supernatant had the strongest inhibitory effect on the differentiation of mast cells during allergic reactions, which may be mediated through the selective regulation of expression of relevant genes.

• Korean Journal of Microbiology
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• v.54 no.3
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• pp.175-187
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• 2018

Myxobacteria produce diverse secondary metabolites for predation, self-defense, intercellular signaling, and other unknown functions. Many secondary metabolites isolated from myxobacteria show pharmaceutically useful bioactivity such as anticancer, antibacterial, and antifungal activities with a unique mechanism of action. Therefore, a large number of myxobacterial strains have been isolated globally and many bioactive compounds have been purified from them. However, 16S rRNA database analysis indicates that there are far more types of myxobacterial species in the wild than have ever been isolated, and genome sequence analysis suggests that each myxobacterium is capable of producing much more metabolites than already known. In this article, the current status of studies on the secondary metabolites from myxobacteria, their biosynthetic genes, biological functions, and transcriptional regulatory factors governing gene expression were reviewed.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.1-21
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• 2021

As the global business environment changes, uncertainties in technology development and market needs increase, and competition among companies intensifies, interests and demands for R&D activities of individual companies are increasing. In order to cope with these environmental changes, R&D companies are strengthening R&D investment as one of the means to enhance the qualitative competitiveness of R&D while paying more attention to facility investment. As a result, facilities or R&D investment elements are inevitably a burden for R&D companies to bear future uncertainties. It is true that the management strategy of increasing investment in R&D as a means of enhancing R&D capability is highly uncertain in terms of corporate performance. In this study, the structural factors that influence the R&D capabilities of companies are explored in terms of technology management capabilities, R&D capabilities, and corporate classification attributes by utilizing data mining techniques, and the characteristics these individual factors present according to the level of R&D capabilities are analyzed. This study also showed cluster analysis and experimental results based on evidence data for all domestic R&D companies, and is expected to provide important implications for corporate management strategies to enhance R&D capabilities of individual companies. For each of the three viewpoints, detailed evaluation indexes were composed of 7, 2, and 4, respectively, to quantitatively measure individual levels in the corresponding area. In the case of technology management capability and R&D capability, the sub-item evaluation indexes that are being used by current domestic technology evaluation agencies were referenced, and the final detailed evaluation index was newly constructed in consideration of whether data could be obtained quantitatively. In the case of corporate classification attributes, the most basic corporate classification profile information is considered. In particular, in order to grasp the homogeneity of the R&D competency level, a comprehensive score for each company was given using detailed evaluation indicators of technology management capability and R&D capability, and the competency level was classified into five grades and compared with the cluster analysis results. In order to give the meaning according to the comparative evaluation between the analyzed cluster and the competency level grade, the clusters with high and low trends in R&D competency level were searched for each cluster. Afterwards, characteristics according to detailed evaluation indicators were analyzed in the cluster. Through this method of conducting research, two groups with high R&D competency and one with low level of R&D competency were analyzed, and the remaining two clusters were similar with almost high incidence. As a result, in this study, individual characteristics according to detailed evaluation indexes were analyzed for two clusters with high competency level and one cluster with low competency level. The implications of the results of this study are that the faster the replacement cycle of professional managers who can effectively respond to changes in technology and market demand, the more likely they will contribute to enhancing R&D capabilities. In the case of a private company, it is necessary to increase the intensity of input of R&D capabilities by enhancing the sense of belonging of R&D personnel to the company through conversion to a corporate company, and to provide the accuracy of responsibility and authority through the organization of the team unit. Since the number of technical commercialization achievements and technology certifications are occurring both in the case of contributing to capacity improvement and in case of not, it was confirmed that there is a limit in reviewing it as an important factor for enhancing R&D capacity from the perspective of management. Lastly, the experience of utility model filing was identified as a factor that has an important influence on R&D capability, and it was confirmed the need to provide motivation to encourage utility model filings in order to enhance R&D capability. As such, the results of this study are expected to provide important implications for corporate management strategies to enhance individual companies' R&D capabilities.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.23-30
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• 2019

The purpose of this study is to find out the structure of the substance that affects antidiabetic using the candidate drug information for diabetes treatment. A quantitative structure activity relationship model based on machine learning method was constructed and major molecular descriptors were determined for each experimental data variables from coefficient values using a partial least squares algorithm. The results of the analysis of the molecular access system fingerprint data reflecting the candidate drug structure information were higher than those of the in vitro data analysis in terms of goodness-of-fit, and the major molecular expression factors affecting the antidiabetic effect were also variously derived. If the proposed method is applied to the new drug development environment, it is possible to reduce the cost for conducting candidate screening experiment and to shorten the search time for new drug development.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.374-390
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• 2021

Growth and yield of field vegetable crops would be affected by climate conditions, which cause a relatively large fluctuation in crop production and consumer price over years. The yield prediction system for these crops would support decision-making on policies to manage supply and demands. The objectives of this study were to compile literatures related to onion and garlic and to perform data-mining analysis, which would shed lights on the development of crop models for these major field vegetable crops in Korea. The literatures on crop growth and yield were collected from the databases operated by Research Information Sharing Service, National Science & Technology Information Service and SCOPUS. The keywords were chosen to retrieve research outcomes related to crop growth and yield of onion and garlic. These literatures were analyzed using text mining approaches including word cloud and semantic networks. It was found that the number of publications was considerably less for the field vegetable crops compared with rice. Still, specific patterns between previous research outcomes were identified using the text mining methods. For example, climate change and remote sensing were major topics of interest for growth and yield of onion and garlic. The impact of temperature and irrigation on crop growth was also assessed in the previous studies. It was also found that yield of onion and garlic would be affected by both environment and crop management conditions including sowing time, variety, seed treatment method, irrigation interval, fertilization amount and fertilizer composition. For meteorological conditions, temperature, precipitation, solar radiation and humidity were found to be the major factors in the literatures. These indicate that crop models need to take into account both environmental and crop management practices for reliable prediction of crop yield.

• Journal of the Korean Geophysical Society
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• v.9 no.4
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• pp.321-331
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• 2006

Recently, runoff characteristics of urban area are changing because of the increase of impervious area by rapidly increasing of population and industrialization, urbanization. It needs to extract the accurate topologic and hydrologic parameters of watershed in order to manage water resource efficiently. Thus, this study developed more precise input data and more improved parameter estimating procedures using GIS(Geographic Information System) and GA(Genetic Algorithm). For these purposes, XP-SWMM (EXPert-Storm Water Management Model) was used to simulate the urban runoff. The model was applied to An-Yang stream basin that is a typical Korean urban stream basin with several tributaries. The rules for parameter estimation were composed and applied based on quantity parameters that are investigated through the sensitivity analysis. GA algorithm is composed of these rules and facts. The conditions of urban flows are simulated using the rainfall-runoff data of the study area. The data of area, slope, width of each subcatchment and length, slope of each stream reach were acquired from topographic maps, and imperviousness rate, land use types, infiltration capacities of each subcatchment from land use maps, soil maps using GIS. Also we gave the management scheme of urbanization runoff using XP-SWMM. The parameters are estimated by GA from sensitivity analysis which is performed to analyze the runoff parameters.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.10
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• pp.947-955
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• 2010

Most oil and gas reservoirs, which have some light hydrocarbon components, show sensitive phase behavior in response to changes in the composition of the internal fluid. When evaluating and developing plans for oil and gas fields, flash calculation, PVT analysis, and saturation-property calculation are necessary for analyzing reservoir characteristics and pipeline flows. In general, the determination of saturation properties such as dew point and bubble point is considered a difficult task because of the poor convergence of the calculation methods. In this study, several new initial-value-guessing methods and root-finding methods are proposed; parametric analysis were carried out to verify the improvement in convergence. Finally, these new ideas and methods were successfully applied to the new GUI based multi-phase behavior simulator.

• Journal of Plant Biotechnology
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• v.47 no.4
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• pp.337-344
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• 2020

Plant growth-promoting microorganisms promote plant growth by supplying nutrients to roots and interacting with the intrinsic factors in plants through volatile organic compounds (VOCs). In this study, we evaluated the effect of UOS, plant growth-promoting fungi (PGPF) isolated from previous study, on the growth of Nicotiana tabacum L. var Xanthi nc. Phylogenetic analysis and GC-MS were used to identify the fungal species and the VOCs emitted by the UOS, respectively. The fresh weight of UOS-treated Nicotiana tabacum L. was 3.8 and 4.2-fold higher than that of the control groups grown in vertical and I-plates, respectively. Moreover, in the UOS-treated plants, the length of the primary root was half and the number of lateral roots were twice compared to those in control plants. The UOS was identified as Phoma sp. by studying spore and mycelial morphology and using phylogenetic analysis. GC-MS revealed that the VOC emitted by the UOS was hexamethylcyclotrisiloxane (D3). These results suggest that the UOS of Phoma sp. influences plant growth and root development through D3. We expect this UOS and its VOC, D3 to be utilized in the future to increase growth and enhance yield for other plants.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.274-284
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• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.