• Journal of Ginseng Research
• /
• v.41 no.3
• /
• pp.379-385
• /
• 2017

In this study, white ginseng was used as the raw material, which was fermented with Paecilomyces hepiali through solid culture medium, to produce ginsenosides with modified chemical composition. The characteristic chemical markers of the products thus produced were investigated using rapid resolution liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (RRLC-QTOF-MS). Chemical profiling data were obtained, which were then subjected to multivariate statistical analysis for the systematic comparison of active ingredients in white ginseng and fermented ginseng to understand the beneficial properties of ginsenoside metabolites. In addition, the effects of these components on biological activity were investigated to understand the improvements in the phagocytic function of macrophages in zebrafish. According to the established RRLC-QTOF-MS chemical profiling, the contents in ginsenosides of high molecular weight, especially malonylated protopanaxadiol ginsenosides, were slightly reduced due to the fermentation, which were hydrolyzed into rare and minor ginsenosides. Moreover, the facilitation of macrophage phagocytic function in zebrafish following treatment with different ginseng extracts confirmed that the fermented ginseng is superior to white ginseng. Our results prove that there is a profound change in chemical constituents of ginsenosides during the fermentation process, which has a significant effect on the biological activity of these compounds.

• Journal of Microbiology and Biotechnology
• /
• v.16 no.4
• /
• pp.519-523
• /
• 2006

To improve epothilones production and the ratio of epothilone B/A, carbon sources were investigated in flask culture of Sorangium cellulosum. Depending on the initial concentration, starch significantly enhanced cell growth, but the maximum epothilones productivity and the maximum epothilones production (0.3 mg/l day and 2.6 mg/l at 15 g/l starch, respectively) were relatively low compared with cell growth. On the other hand, addition of glycerol did not stimulate cell growth, but epothilone production was increased from 2.81 mg/l to 7.59 mg/l. Addition of glycerol to culture medium resulted in more significant enhancement of the production of epothilone A, whereas epothilone B levels were relatively constant. Furthermore, when sodium propionate was added as a precursor of methylmalonyl-CoA, it resulted in increase of both total epothilones production and epothilone B/A resolution. Maximum epothilone A and B concentrations reached 10.9 mg/l and 8.58 mg/l, respectively, at 5 mM sodium propionate.

• Mycobiology
• /
• v.49 no.4
• /
• pp.434-437
• /
• 2021

In our ongoing search for new secondary metabolites from fungi, a basidiomycete fungus Irpex consors was selected for mycochemical investigation, and three new zwitterionic alkaloids (1-3) and five known compounds (4-8) were isolated from the culture broth (16 l) of I. consors. The culture filtrate was fractionated by a series of column chromatography including Diaion HP-20, silica gel, and Sephadex LH-20, Sep-Pak C₁₈ cartridge, medium pressure liquid chromatography (MPLC), and high pressure liquid chromatography (HPLC) to yield eight compounds (1-8). The structures of the isolated compounds were elucidated by the interpretation of nuclear magnetic resonance (NMR) spectra and high-resolution mass spectrometry (HR-MS). Their antioxidant and antibacterial activities were examined. The zwitterionic structures of three new sesquiterpene alkaloids (1-3) were determined together with five known compounds identified as stereumamide E (4), stereumamide G (5), stereumamide H (6), stereumamide D (7), and sterostrein H (8). This is the first report of the zwitterionic alkaloids in the culture broth of I. consors. Three new zwitterionic alkaloids were named as consoramides A-C (1-3).

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.5
• /
• pp.867-878
• /
• 2021

Recently, there has been active research on smart street lamps that can collect real-time traffic data and provide traffic information by attaching images and radars to road lighting facilities. Smart street light technology can detect, identify, and provide dense information compared to existing technologies. In order to effectively utilize the smart streetlight as a high-resolution information delivery medium, a branch-type operation strategy that is different from the existing centralized operation strategy is required. This study presents dynamic information delivery strategies, release strategies, and their criteria for various purposes in a spatial range, separated by the context before and after the occurrence of smart street lights-based accidents. Through this, it is expected that smart road lighting facilities can be used more effectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.05a
• /
• pp.513-515
• /
• 2014

Ultra High Definition(hereafter UHD), Next-generation video technology, was quickening in the request of many years of the recipient and the authors who have been towards the higher sense of reality. The change of the medium has resulted in a mutation in the detailed content and the point of view overlooking the world as evidenced through the history. Thus the emergence of UHD will also be expected to require to manufacture unique technology. Therefore, this paper, especially in the documentary among the video content, tries to study the changes in the manufacturing process by UHD video technology. Moreover UHD video screen technology such as high resolution tries to analyse for the fitness for purpose of the documentary that transmission of the accuracy and the change from a documentary video production. In addition, I try to explore the improvement in the choice of shooting material expected to be a problem, even for the advance of the work on the second half and backup according to the enormous data. We derive the developmental aspects that UHD video technology in documentary production is brought about by the research plan described above. It is intended to contribute to the development of content production with the development of technology.

• The Bulletin of The Korean Astronomical Society
• /
• v.43 no.2
• /
• pp.38.3-38.3
• /
• 2018

We present the results of high-resolution near-IR spectral mapping toward the Orion KL outflow. In this study, we used the Immersion Grating Infrared Spectrometer (IGRINS) on the 2.7 m Harlan J. Smith Telescope at McDonald Observatory. IGRINS's large wavelength coverage over the H & K bands and high spectral resolving power (R ~ 45,000) allowed us to detect over 35 shock-excited ro-vibrational H2 transitions and to measure directly the gas temperature and velocity of the dense outflows. In our previous study toward the H2 peak 1 region in the Orion KL outflow, we identified 31 outflow fingers from a datacube of the H2 1-0 S(1) $2.122{\mu}m$ line and constructed a three-dimensional map of the fingers. The internal extinction (${\Delta}AV$ > 10 mag) and overall angular spread of the flow argue for an ambient medium with a high density (105 cm-3). In this presentation, we show preliminary results of additional mapping toward a remarkable chain of bows (HH 205 - HH 207) farther from the ejection center, and obtain a more clear view of the shock physics of a single isolated bullet that improves on the knowledge gained from observations of the more complex peak 1 region in our earlier study.

• Journal of Ocean Engineering and Technology
• /
• v.35 no.4
• /
• pp.273-286
• /
• 2021

In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.

• International Journal of Computer Science & Network Security
• /
• v.22 no.2
• /
• pp.214-222
• /
• 2022

Convolutional Neural networks (CNNs) are a category of deep learning networks that have proven very effective in computer vision tasks such as image classification. Notwithstanding, not much has been seen in its use for remote sensing image classification in developing countries. This is majorly due to the scarcity of training data. Recently, transfer learning technique has successfully been used to develop state-of-the art models for remote sensing (RS) image classification tasks using training and testing data from well-known RS data repositories. However, the ability of such model to classify RS test data from a different dataset has not been sufficiently investigated. In this paper, we propose a deep CNN model that can classify RS test data from a dataset different from the training dataset. To achieve our objective, we first, re-trained a ResNet-50 model using EuroSAT, a large-scale RS dataset to develop a base model then we integrated Augmentation and Ensemble learning to improve its generalization ability. We further experimented on the ability of this model to classify a novel dataset (Nig_Images). The final classification results shows that our model achieves a 96% and 80% accuracy on EuroSAT and Nig_Images test data respectively. Adequate knowledge and usage of this framework is expected to encourage research and the usage of deep CNNs for land cover mapping in cases of lack of training data as obtainable in developing countries.

• The Korea Journal of Herbology
• /
• v.34 no.6
• /
• pp.117-124
• /
• 2019

Objective : Broccoli is edible green plant that has a wide variety of health benefits including cancer prevention and cholesterol reduction. However, leaves of broccoli are not eaten and are mostly left as waste. This study was conducted to evaluate the effects of the broccoli leaf extract (BLE) on prostaglandin E₂ (PGE₂) production related to nuclear factor kappa B (NF-κB) signaling in lipopolysaccharide (LPS)-activated macrophages. Methods : BLE was prepared by extracting dried leaf with ethanol. Cell viability was determined by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. PGE₂ and inflammatory cytokines were detected by enzyme-linked immunosorbent assay (ELISA). Expression level of each protein was monitored by Western blot analysis. Results : In LPS-activated Raw264.7 cells, PGE₂ release into culture medium was dramatically enhanced compared to control cells. However, increased PGE₂ was attenuated dose-dependently by treatment with BLE. Inhibition of PGE₂ production by BLE was due to the suppression of cyclooxygenase-2 (COX-2) expression determined by Western blot analysis. BLE also inhibited the production of inflammatory cytokines such as interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α). Inhibition at PGE₂ and cytokine was mediated from inhibition of nuclear translocation of NF-κB due to the repression of inhibitory kappa B alpha (IκBα) phosphorylation and degradation. Conclusion : This study showed that BLE exerted inhibitory activities against PGE₂, which is critical for the initiation and resolution of inflammatory responses, and that inhibition of PGE₂ was mediated by suppression of NF-κB signaling. These results suggest that the waste broccoli leaves could be used for controlling inflammation.

• Journal of Forest and Environmental Science
• /
• v.39 no.3
• /
• pp.167-179
• /
• 2023

The extent of change in the Land use/Land cover (LULC) of Okomu National Park (ONP) and fringe communities was evaluated. High resolution Landsat imagery was used to identify the major vegetation cover/land use systems and changes around the national park and fringe communities while field visits/ground truthing, involving the collection of coordinates of the locations was carried out to ascertain the various land cover/land use types identified on the images, and the extent of change over three-time series (2000, 2010 and 2020). The change detection was analyzed using area calculation, change detection by nature and normalized difference vegetation index (NDVI). The result of the classification and analysis of the LULC Change of ONP and fringe communities revealed an alarming rate of encroachment into the protected area. All the classification features analyzed had notable changes from 2000-2020. The forest, which was the dominant LULC feature in 2000, covering about 66.19% of the area reduced drastically to 36.12% in 2020. Agricultural land increased from 6.14% in 2000 to 34.06% in 2020 while vegetation (degraded land) increased from 27.18% in 2000 to 38.89% in 2020. The magnitude of the change in ONP and surroundings showed the forest lost -247.136 km² (50.01%) to other land cover classes with annual rate change of 10%, implying that 10% of forest land was lost annually in the area for 20 years. The NDVI classification values of 2020 indicate that the increase in medium (399.62 km² ) and secondary high (210.17 km² ) vegetation classes which drastically reduced the size of the high (38.07 km² ) vegetation class. Consequent disappearance of the high forests of Okomu is inevitable if this trend of exploitation is not checked. It is pertinent to explore other forest management strategies involving community participation.