• Journal of Life Science
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• v.27 no.12
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• pp.1445-1451
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• 2017

Mitochondria play a central role in energy generation by using electron transport coupled with oxidative phosphorylation. They also participate in other important cellular functions including metabolism, apoptosis, signaling, and reactive oxygen species production. Therefore, mitochondrial dysfunction is known to contribute to a variety of human diseases. Furthermore, there are various inherited diseases of energy metabolism due to mitochondrial DNA (mtDNA) mutations. Unfortunately, therapeutic options for these inherited mtDNA diseases are extremely limited. In this regard, mitochondrial replacement techniques are taking on increased importance in developing a clinical approach to inherited mtDNA diseases. In this study, green fluorescence protein (GFP)-tagged mitochondria were isolated by differential centrifugation from a mammalian cell line. Using microinjection technique, the isolated GFP-tagged mitochondria were then transferred to bovine oocytes that were triggered for early development. During the early developmental period from bovine oocytes to blastocysts, the transferred mitochondria were observed using fluorescent microscopy. The microinjected mitochondria were dispersed rapidly into the cytoplasm of oocytes and were passed down to subsequent cells of 2-cell, 4-cell, 8-cell, morula, and blastocyst stages. Together, these results demonstrate a successful in vitro transfer of isolated mitochondria to oocytes and provide a model for mitochondrial replacement implicated in inherited mtDNA diseases and animal cloning.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.1
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• pp.5-15
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• 2001

For estimating paddy field area with Landsat TM images, two dates, May 31, 1991 (transplanting stage) and August 19, 1991 (heading stage) were selected by the data analysis of digital numbers considering rice cropping calendar. Four different estimating methods (1) rule-based classification method, (2) supervised classification(maximum likelihood), (3) unsupervised classification (ISODATA, No. of class:15), (4) unsupervised classification (ISODATA, No. of class:20) were examined. Paddy field area was estimated to 7291.19 ha by non-classification method. In comparison with topographical map (1:25,000), accuracy far paddy field area was 92%. A new image stacked by 10 layers, Landsat TM band 3,4,5, RVI, and wetness in May 31,1991 and August 19,1991 was made to estimate paddy field area by both supervised and unsupervised classification method. Paddy field was classified to 9100.98 ha by supervised classification. Error matrix showed 97.2% overall accuracy far training samples. Accuracy compared with topographical map was 95%. Unsupervised classifications by ISODATA using principal axis. Paddy field area by two different classification number of criteria were 6663.60 ha and 5704.56 ha and accuracy compared with topographical map was 87% and 82%. Irrespective of the estimating methods, paddy fields were discriminated very well by using two-date Landsat TM images in May 31,1991 (transplanting stage) and August 19,1991 (heading stage). Among estimation methods, rule-based classification method was the easiest to analyze and fast to process.

• Korean Journal of Food Science and Technology
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• v.32 no.5
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• pp.1002-1008
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• 2000

The purpose of this study was to provide the fundamental information for establishing the database needed to estimate total intakes of trans fatty acids in Korea. The amounts of trans fatty acids contained in 164 samples including 25 samples of margarines, 21 samples of shortenings, 19 samples of vegetable salad and cooking oils, 53 samples of confectionery products, 18 samples of bakery products, 19 samples of dairy products, and 9 samples of animal fats and meats were analyzed by capillary gas liquid chromatography. The average amounts of trans fatty acids in those foods were calculated and expressed as gram per one serving. Then, the average daily intakes of trans fatty acids per capita were estimated using the analyzed amounts of trans fatty acids and the amount of yearly production for those foods. The amounts of trans fatty acids per 100 g of lipids were $2.11{\sim}33.83%$ (14.66% on average) in margarines, $1.47{\sim}44.48%$ (14.21% on average) in shortenings, $0.18{\sim}3.82$ (1.54% on average) in vegetable salad and cooking oils, $0{\sim}45.81%$ (10.92% on average) in confectionery products, $0{\sim}18.32%$ (7.87% on average) in bakery products, $0.90{\sim}4.54%$ (2.27% on average) in dairy products, and $0.61{\sim}6.07%$ (2.24% on average) in animal fats and meats. Major isomers of trans fatty acid in the sample foods were $C_{18:1}$ and $C_{18:2}$. As a result, the korean average daily intake of trans fatty acids in korea was estimated to be 2.3 g per capita. The amounts of trans fatty acids consumed from each selected food were as follows: 0.35 g from margarines, 0.57 g from shortenings, 0.11 g from vegetable salad and cooking oils, 0.65 g from confectionery products, 0.07 g from bakery products, 0.14 g from dairy products and 0.21 g from animal fats and meats.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1177-1186
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• 2021

As the Arctic melt ponds play an important role in determining the interannual variation of the sea ice extent and changes in the Arctic environment, it is crucial to monitor the Arctic melt ponds with high accuracy. Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), which is the NASA's latest altimeter satellite based on the green laser (532 nm), observes the global surface elevation. When compared to the CryoSat-2 altimetry satellite whose along-track resolution is 250 m, ICESat-2 is highly expected to provide much more detailed information about Arctic melt ponds thanks to its high along-track resolution of 70 cm. The basic products of ICESat-2 are the surface height and the number of reflected photons. To aggregate the neighboring information of a specific ICESat-2 photon, the segments of photons with 10 m length were used. The standard deviation of the height and the total number of photons were calculated for each segment. As the melt ponds have the smoother surface than the sea ice, the lower variation of the height over melt ponds can make the melt ponds distinguished from the sea ice. When the melt ponds were extracted, the number of photons per segment was used to classify the melt ponds covered with open-water and specular ice. As photons are much more absorbed in the water-covered melt pondsthan the melt ponds with the specular ice, the number of photons persegment can distinguish the water- and ice-covered ponds. As a result, the suggested melt pond detection method was able to classify the sea ice, water-covered melt ponds, and ice-covered melt ponds. A qualitative analysis was conducted using the Sentinel-2 optical imagery. The suggested method successfully classified the water- and ice-covered ponds which were difficult to distinguish with Sentinel-2 optical images. Lastly, the pros and cons of the melt pond detection using satellite altimetry and optical images were discussed.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1339-1348
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• 2021

In accordance with the River Law, the basic river maintenance plan is established every 5-10 years with a considerable national budget for domestic rivers, and various river surveys such as the river section required for HEC-RAS simulation for flood level calculation are being conducted. However, river survey data are provided only in the form of a pdf report to the River Management Geographic Information System (RIMGIS), and the original data are distributedly owned by designers who performed the river maintenance plan in CAD format. It is a situation that the usability for other purposes is considerably lowered. In addition, when using surveyed CAD-type cross-sectional data for HEC-RAS, tools such as 'Dream' are used, but the reality is that time and cost are almost as close as manual work. In this study, RAUT (River Information Auto Upload Tool), a tool that can solve these problems, was developed. First, the RAUT tool attempted to automate the complicated steps of manually inputting CAD survey data and simulating the input data of the HEC-RAS one-dimensional model used in establishing the basic river plan in practice. Second, it is possible to directly read CAD survey data, which is river spatial information, and automatically upload it to the river spatial information DB based on the standard data model (ArcRiver), enabling the management of river survey data in the river maintenance plan at the national level. In other words, if RIMGIS uses a tool such as RAUT, it will be able to systematically manage national river survey data such as river section. The developed RAUT reads the river spatial information CAD data of the river maintenance master plan targeting the Jeju-do agar basin, builds it into a mySQL-based spatial DB, and automatically generates topographic data for HEC-RAS one-dimensional simulation from the built DB. A pilot process was implemented.

• Korean Journal of Food Science and Technology
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• v.53 no.2
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• pp.195-203
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• 2021

Aureobasidium pullulans, a black yeast, produces pullulan, a linear α-glucan composed of maltotriose repeating units linked by α(1→6)-glycosidic linkages. Pullulan can be widely used in food, cosmetic, and biotechnology industries. In this study, we isolated eight strains of A. pullulans from Forsythia koreana, Magnolia kobus DC., Spiraea prunifolia var. simpliciflora, Cornus officinalis, Cerasus, and Hippophae rhamnoides. Among them, A. pullulans MR was selected as the best pullulan producer. The effects of a carbon source, a nitrogen source, and pH on pullulan production were examined. The optimal cultivation conditions for pullulan production by A. pullulans MR were determined by response surface methodology as 15% sucrose, 0.4% soy peptone, and an initial pH of 7 at 26℃. Under these conditions, the predicted pullulan production was 47.6 g/L, which was very close to the experimental data (48.9 g/L).

• Korean Journal of Mineralogy and Petrology
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• v.35 no.2
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• pp.111-123
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• 2022

Carbonate green rust (CGR) and sulfate green rust (SGR) commonly occur in nature. In this study, CGR and SGR were synthesized through co-precipitation, and their formation mechanisms and physicochemical properties were investigated. X-ray diffraction (XRD) and Rietveld refinement showed both CGR and SGR with layered double hydroxide structure were successfully synthesized without any secondary phases under each synthetic condition. Refined structural parameters (unit cell) for two green rusts were a (=b) = 3.17 Å and c = 22.52 Å for CGR and a (=b) = 5.50 Å and c = 10.97 Å for SGR with the crystallite size 57.8 nm in diameter from (003) reflection and 40.1 nm from (001) reflections, respectively. Scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDS) results showed that both CGR and SGR had typical hexagonal plate-like crystal morphologies but their chemical composition is different in the content of C and S. In addition, Fourier transform infrared (FT-IR) spectroscopy analysis revealed that carbonate (CO₃^2-) and sulfate (SO₄^2-) molecules were occupied as interlayer anions of CGR and SGR, respectively. These SEM/EDS and FT-IR results were in good agreement with XRD results. Changes in the solution chemistry (i.e., pH, Eh and residual iron concentrations (Fe(II):Fe(III)) of the mixed solution) were observed as a function of the injection time of hydroxyl ion (OH^-) into the iron solution. Three different stages were observed in the formation of both CGR and SGR; precursor, intermediator, and green rust in the formation of both CGR and SGR. This study provides co-precipitation methods for CGR and SGR in a way of the stable synthesis. In addition, our findings for the formation mechanisms of the two green rusts and their physicochemical properties will provide crucial information with researches and industrials in utilizing green rust.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.4
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• pp.409-421
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• 2022

Achieving a highly resolved spatial distribution of Mn-bearing minerals and elements in the natural ferromanganese nodules can provide detailed knowledge of the temporal variations of geochemical conditions affecting the formation processes of nodules. While a recent study utilizing Raman spectroscopy has reported the changes in the manganate mineral phases with growth for spherical nodules from the Arctic Sea, the distributions of minerals and elements in the nodules from the shallow Arctic Sea with non-spherical forms have not yet fully elucidated. Here, we reported the micro-laser Raman spectra with varying data acquisition points along three different profiles from the center to the outermost rim of the non-spherical ferromanganese nodules collected from the East Siberian Sea (~73 m). The elemental distributions in the nodule (such as Mn, Fe, etc.) were also investigated by energy dispersive X-ray spectroscopy (EDS) analysis to observe the internal structure and mineralogical details. Based on the microscopic observation, the internal structures of a non-spherical nodule can be divided into three different regions, which are sediment-rich core, iron-rich substrate, and Mn-Fe layers. The Raman results show that the Mn-bearing mineral phases vary with the data acquisition points in the Mn-Fe layer, suggesting the changes in the geochemical conditions during nodule formation. In addition, we also observe that the mineral composition and structural characteristics depend on the profile direction from the core to the rim. Particularly, the Raman spectra obtained along one profile show the lack of Fe-(oxy)hydroxides and the noticeably high crystallinity of Mn-bearing minerals such as birnessite and todorokite. On the other hand, the spectra obtained along the other two profiles present the presence of significant amount of amorphous or poorly-ordered Fe-bearing minerals and the low crystallinity of Mn-bearing minerals. These results suggest that the diagenetic conditions varied with the different growth directions. We also observed the presence of halite in several layers in the nodule, which can be evidence of the alteration of seawater after nodule formation. The current results can provide the opportunity to obtain detailed knowledge of the formation process and geochemical environments recorded in the natural non-spherical ferromanganese nodule.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.263-286
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• 2022

This study acquires NBA statistical information for a total of 32 years from 1990 to 2022 using web crawling, observes variables of interest through exploratory data analysis, and generates related derived variables. Unused variables were removed through a purification process on the input data, and correlation analysis, t-test, and ANOVA were performed on the remaining variables. For the variable of interest, the difference in the mean between the groups that advanced to the playoffs and did not advance to the playoffs was tested, and then to compensate for this, the average difference between the three groups (higher/middle/lower) based on ranking was reconfirmed. Of the input data, only this year's season data was used as a test set, and 5-fold cross-validation was performed by dividing the training set and the validation set for model training. The overfitting problem was solved by comparing the cross-validation result and the final analysis result using the test set to confirm that there was no difference in the performance matrix. Because the quality level of the raw data is high and the statistical assumptions are satisfied, most of the models showed good results despite the small data set. This study not only predicts NBA game results or classifies whether or not to advance to the playoffs using machine learning, but also examines whether the variables of interest are included in the major variables with high importance by understanding the importance of input attribute. Through the visualization of SHAP value, it was possible to overcome the limitation that could not be interpreted only with the result of feature importance, and to compensate for the lack of consistency in the importance calculation in the process of entering/removing variables. It was found that a number of variables related to three points and errors classified as subjects of interest in this study were included in the major variables affecting advancing to the playoffs in the NBA. Although this study is similar in that it includes topics such as match results, playoffs, and championship predictions, which have been dealt with in the existing sports data analysis field, and comparatively analyzed several machine learning models for analysis, there is a difference in that the interest features are set in advance and statistically verified, so that it is compared with the machine learning analysis result. Also, it was differentiated from existing studies by presenting explanatory visualization results using SHAP, one of the XAI models.