• Korean Journal of Food Science and Technology
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• v.26 no.1
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• pp.81-87
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• 1994

Two different trypsin inhibitors, TRTI-1 and TRTI-2, were purified to near homogenity from Trichosanthes kirilowii root, by $0{\sim}90%$ saturated ammonium sulfate salting out, DEAE-Sephacel ion exchange chromatography, Sephadex G-50 gel filtration chromatography and trypsin-affinity chromatography. The molecular weight of TRTI-1 and TRTI-2 were estimated to be about 5,000 Da and 24,000 Da, respectively, by gel filtration and must be monomer and homodimer since they contain 4,000 Da and 10,000 Da each on SDS-polyacrylamide gel electrophoresis. TRTI-1 was stable after heating for at least 2 hr at $100^{\circ}C$ but TRTI-2 was completely inactivated after heating for 10 min at $90^{\circ}C$. When Bz-dl-Arg-pNA was used as a substrate of TPCK-treated trypsin, half-maximal inhibitions of TRTI-1 and TRTI-2 were observed at $0.8\;{\mu}M$ and 6\;${\mu}M$, repectively. Both TRTI-1 and TRTI-2 inhibited the hydrolysis of trypsin competitively and Km values were $0.97\;{\mu}M$ and $0.63\;{\mu}M$, respectively. Both TRTI-1 and TRTI-2 specifically inhibited trypsin but they did not inhibit other proteases tested, chymotrypsin, papain, elastase, collagenase, thermolysin, Nagarase, pepsin, and thrombin.

• Journal of Korean Society of Rural Planning
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• v.21 no.3
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• pp.171-179
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• 2015

The objectives of this research have been focussed on 1) developing prediction techniques for the flash flood and landslide based on rainfall prediction data in agricultural area and 2) developing an integrated forecasting system for the abrupt disasters using USN based real-time disaster sensing techniques. This study contains following steps to achieve the objective; 1) selecting rainfall prediction data, 2) constructing prediction techniques for flash flood and landslide, 3) developing USN and communication network protocol for detecting the abrupt disaster suitable for rural area, & 4) developing mobile application and SMS based early warning service system for local resident and tourist. Local prediction model (LDAPS, UM1.5km) supported by Korean meteorological administration was used for the rainfall prediction by considering spatial and temporal resolution. NRCS TR-20 and infinite slope stability analysis model were used to predict flash flood and landslide. There are limitations in terms of communication distance and cost using Zigbee and CDMA which have been used for existing disaster sensors. Rural suitable sensor-network module for water level and tilting gauge and gateway based on proprietary RF network were developed by consideration of low-cost, low-power, and long-distance for communication suitable for rural condition. SMS & mobile application forecasting & alarming system for local resident and tourist was set up for minimizing damage on the critical regions for abrupt disaster. The developed H/W & S/W for integrated abrupt disaster forecasting & alarming system was verified by field application.

• Korean Journal of Microbiology
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• v.51 no.1
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• pp.68-74
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• 2015

Based on the genomic analysis of Thermococcus pacificus P-4, we identified a putative GH1 ${\beta}$-glucosidase-encoding gene (Tpa-glu). The gene revealed a 1,464 bp encoding 487 amino acid residues, and the deduced amino acid residues exhibited 77% identity with Pyrococcus furiosus ${\beta}$-glucosidase (accession no. NP_577802). The gene was cloned and expressed in Escherichia coli system. The recombinant protein was purified by metal affinity chromatography and characterized. Tpa-Glu showed optimum activity at pH 7.5 and $75^{\circ}C$, and thermostability with a half life of 6 h at $90^{\circ}C$. Tpa-Glu exhibited hydrolyzing activity against various pNP-glycopyranosides, with kcat/Km values in the order of pNP-${\beta}$-glucopyranoside, pNP-${\beta}$-galactopyranoside, pNP-${\beta}$-mannopyranoside, and pNP-${\beta}$-xylopyranoside. In addition, the enzyme exhibited exo-hydrolyzing activity toward ${\beta}$-1,3-linked polysaccharide (laminarin) and ${\beta}$-1,3- and ${\beta}$-1,4-linked oligosaccharides. This is the first description of an enzyme from hyperthermophilic archaea that displays exo-hydrolyzing activity toward ${\beta}$-1,3-linked polysaccharides and could be applied in combination with ${\beta}$-1,3-endoglucanase for saccharification of laminarin.

• Journal of the Korean Society of Food Science and Nutrition
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• v.21 no.1
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• pp.54-59
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• 1992

The characteristics of endogenous and exogenous ${\beta}-galactosidase\;({\beta}-Galase)$ produced from L. acidophilus were investigated as one of the serial studies on the fermentation of Chinese cabbage kimchi using L. acidophilus. Apparent molecular weight of endogenous and exogenous of the ${\beta}-Galase$ were investigated to be 550,000 and 740,000 daltons by the method of gel filtration and Km values of the both enzymes were 1.67mg/ml, 1.33mg/ml and $V_{max}$ were $8.5\;{\mu}\;mol/mg/30min.$, $2.65\;{\mu}\;mol/ml/30min.$, respectively. The optimum pH of the enzymes were 7 and 8, respectively. The optimum temperatures and salt concentrations of the both enzyme were the same and appeared to $30^{\circ}C$and$4{\sim}5%$, respectively. The activities of the endogenous and exogenous ${\beta}-Galase$ were decreased by increasing of temperature from $60^{\circ}C$to$90^{\circ}C$ and the decreasing rate of the enzyme activities on the processing of the heating times showed high at first 2 minutes of heating.

• Journal of Aquaculture
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• v.19 no.4
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• pp.275-280
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• 2006

Effect of the various sources of dietary additives on growth, body composition and shell color of abalone Haliotis discus hannai was investigated for 16 weeks. Forty juvenile abalone averaging 13.5 g were randomly stocked into 21 of 50 L plastic rectangular containers each. Eight kinds of additives were prepared for this study: four commercially available microalgae [Haeatococcus (Hae), Isochrysis galbana (Iso), Shizochytrium (Sch) and Spirulina (Spi)], three crustacean meals [krill meal (KM), shrimp head meal (Shm) and red crab meal (Rcm)], and green tea by-product (Gre). In addition, dry sea tangle (Dst), Laminaria japonica, as a control, was prepared. Casein, dextrin and a mixture corn oil and fish oil was protein, carbohydrate and lipid sources, respectively, in the experimental diets. The 2% each additive was included into the experimental diets. The experimental diets were fed to abalone once a day at the ratio of $1.5{\sim}2.0%$ total biomass of abalone with a little leftover throughout the 16-week feeding trial. Survival of abalone was not significantly (P>0.05) affected by the experimental diets. However, weight gain of abalone fed the all experimental diets containing the various sources of additives was significantly (P<0.05) higher than that of abalone fed the Dst diet. Weight gain of abalone fed the Spi diet was highest and Shi, KM and Iso diets in order. Shell length and the ratio of soft body weight to body weight of abalone was not significantly (P>0.05) affected by the experimental diets. However, shell width of abalone fed the all experimental diets containing the various sources of additives was significantly (P<0.05) higher than that of abalone fed the Dst diet. The shell color of abalone fed the Spi diet was improved the most distinctively and similar to that of natural abalone. Therefore, it can be concluded that the experimental diets with the various sources of additives (microalgae and crustacean meals) was effective to improve growth of abalone and dietary inclusion of Spirulina was most effective to improve shell color of abalone.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1053-1066
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• 2020

Sulfur dioxide (SO₂) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO₂ can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO₂ crucial. In South Korea, SO₂ monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO₂ concentrations. Thus, this research estimated spatially continuous ground-level SO₂ concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO₂ estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO₂ concentrations based on the proposed model agreed with the general seasonality of SO₂ and the temporal patterns of emission sources.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.597-605
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• 2014

The continuous observations for atmospheric aerosols were conducted during 3 years (2009 to 2011) by using Gwangju Institute of Science and Technology (GIST) multi-wavelength Raman lidar at Gwangju, Korea ($35.10^{\circ}N$, $126.53^{\circ}E$). The aerosol depolarization ratios calculated from lidar data were used to identify the Asian dust layer. The optical properties of Asian dust layer were different according to its vertical distribution. In order to investigate the difference between the optical properties of each individual dust layers, the transport pathway and the transport altitude of Asian dust were analyzed by Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. We consider that the variation of optical properties were influenced not only their transport pathway but also their transport height when it passed over anthropogenic pollution source regions in China. The lower particle depolarization ratio values of $0.12{\pm}0.01$, higher lidar ratio of $67{\pm}9sr$ and $68{\pm}9sr$ at 355 nm and 532 nm, respectively, and higher ${\AA}ngstr\ddot{o}m$ exponent of $1.05{\pm}0.57$ which are considered as the optical properties of pollution were found. In contrast with this, the higher particle depolarization ratio values of $0.21{\pm}0.09$, lower lidar ratio of $48{\pm}5sr$ and $46{\pm}4sr$ at 355 nm and 532 nm, respectively, and lower ${\AA}ngstr\ddot{o}m$ exponent of $0.57{\pm}0.24$ which are considered as the optical properties of dust were found. We found that the degree of mixing of anthropogenic pollutant aerosols in mixed Asian dust govern the variation of optical properties of Asian dust and it depends on their altitude when it passed over the polluted regions over China.

• Current Research on Agriculture and Life Sciences
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• v.4
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• pp.55-64
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• 1986

Polyphenol oxidase in japanese pear (Pyrus communis var. mansamkil) was isolated, partially purified and its some properties were investigated. Polyacrylamide disc gel electrophoresis indicated two bands with polyphenol oxidase activity in the extract from acetone dry powder of par flesh. These two polyphenol oxidases (PPO A and PPO B) were purified through acetone precipitation and diethylaminoethyl cellulose column chromatography. PPO A and B were purified 7.8 fold and 8.7 fold by the present procedure, respectively. The Rm values of partially purified PPO A and B were estimated to be 0.58 and 0.68, respectively. The optimum temp, and pH of PPO A activity were $33^{\circ}C$ and pH 7.0, while those of PPO B were $30^{\circ}C$ and pH 4.2, respectively. Two PPO were unstable over the temperature of $60^{\circ}C$. The substrate specificity of pear PPO showed high affinity toward o-diphenolic compounds, especially catechol in PPO A and chlorogenic acid in PPO B, but inactive toward m-diphenol, p-diphenol and monophenols. PPO A showed affinity toward the trihydroxyphenolic compound. $Zn^{{+}{+}}$ activated the PPO A activity but $Fe^{{+}{+}}$ inhibited PPO B activity, while $Fe^{{+}{+}}$ and $Zn^{{+}{+}}$ activated the PPO B activity, while $Fe^{{+}{+}}$ and $Zn^{{+}{+}}$ activated the PPO B activity but $K^+$, $Mg^{{+}{+}}$, $Ca^{{+}{+}}$ and $Hg^{{+}{+}}$ inhibited at 10mM concentration. $Cu^{{+}{+}}$ activated the enzyme action at low concentrations but inhibited at high concentration. Inhibition studies indicated that L-ascorbic acid, L-cysteine and thiourea were most potent. The Km values of PPO A and PPO B for catechol were 20mM and 14.3mM, respectively.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.959-974
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• 2021

Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the possibility as a new water quality index which simultaneously contains optical information of water quality parameters has been suggested. In thisstudy, Ocean Colour-Climate Change Initiative (OC-CCI) based 4 km FUI was spatially downscaled to the resolution of 500 m using the Geostationary Ocean Color Imager (GOCI) data and Random Forest (RF) machine learning. Then, the RF-derived FUI was examined in terms of its correlation with various water quality parameters measured in coastal areas and its spatial distribution and seasonal characteristics. The results showed that the RF-derived FUI resulted in higher accuracy (Coefficient of Determination (R²)=0.81, Root Mean Square Error (RMSE)=0.7784) than GOCI-derived FUI estimated by Pitarch's OC-CCI FUI algorithm (R²=0.72, RMSE=0.9708). RF-derived FUI showed a high correlation with five water quality parameters including Total Nitrogen, Total Phosphorus, Chlorophyll-a, Total Suspended Solids, Transparency with the correlation coefficients of 0.87, 0.88, 0.97, 0.65, and -0.98, respectively. The temporal pattern of the RF-derived FUI well reflected the physical relationship with various water quality parameters with a strong seasonality. The research findingssuggested the potential of the high resolution FUI in coastal water quality management in the Korean Peninsula.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.707-723
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• 2022

Although satellite-based sea surface temperature (SST) is advantageous for monitoring large areas, spatiotemporal data gaps frequently occur due to various environmental or mechanical causes. Thus, it is crucial to fill in the gaps to maximize its usability. In this study, daily SST composite fields with a resolution of 4 km were produced through a two-step machine learning approach using polar-orbiting and geostationary satellite SST data. The first step was SST reconstruction based on Data Interpolate Convolutional AutoEncoder (DINCAE) using multi-satellite-derived SST data. The second step improved the reconstructed SST targeting in situ measurements based on light gradient boosting machine (LGBM) to finally produce daily SST composite fields. The DINCAE model was validated using random masks for 50 days, whereas the LGBM model was evaluated using leave-one-year-out cross-validation (LOYOCV). The SST reconstruction accuracy was high, resulting in R² of 0.98, and a root-mean-square-error (RMSE) of 0.97℃. The accuracy increase by the second step was also high when compared to in situ measurements, resulting in an RMSE decrease of 0.21-0.29℃ and an MAE decrease of 0.17-0.24℃. The SST composite fields generated using all in situ data in this study were comparable with the existing data assimilated SST composite fields. In addition, the LGBM model in the second step greatly reduced the overfitting, which was reported as a limitation in the previous study that used random forest. The spatial distribution of the corrected SST was similar to those of existing high resolution SST composite fields, revealing that spatial details of oceanic phenomena such as fronts, eddies and SST gradients were well simulated. This research demonstrated the potential to produce high resolution seamless SST composite fields using multi-satellite data and artificial intelligence.