Identification of Thermoduric Leuconostoc mesenteroides BD5H That Can Grow at Over 42℃

권오식,이삼빈 계명대학교 자연과학연구소 2017 Quantitative Bio-Science Vol.36 No.1

Lactic acid bacteria was isolated from Chonggak and Baechu kimchi and characterized by a sugar fermentation analysis. Leuconostoc strains (1B12, BD5H and CH5H) growing at 40℃ were isolated and compared with L. mesenteroides subsp. mesenteroides KCTC 3722 grown at a mesophilic temperature (30℃). Among these, L. mesenteroides BD5H could grow at 42℃ (pH 4.70±0.02) and could still grow at 43℃ (pH 5.51±0.04), which indicates that is a thermoduric bacterial strain. In the fermentation of pentose, all strains had exactly the same patterns of fermentation, except L. mesenteroides CH5H, which could not ferment ribose (pH 5.92±0.04). These strains had significantly different abilities to ferment galactose, with only L. mesenteroides BD5H capable of active galactose fermentation (pH 4.94±0.03). All strains failed to ferment rhamnose compared to other hexoses (p<0.001). L. mesenteroides BD5H could ferment cellobiose (4.42± 0.02), while the remaining strains could not. L. mesenteroides BD5H could ferment raffinose (pH 4.66±0.07), but not melezitose. These fermentation characteristics are typical of L. mesenteroides. Interestingly L. mesenteroides BD5H could ferment amygdalin (pH 4.82±0.04), while other strains could not (p<0.001). Furthermore L. mesenteroides BD5H could ferment salicin (pH 4.77±0.15), while the other strains could not. According to 16S rRNA sequence analysis using primers 785F and 907R, all tested strains were L. mesenteroides, with 99~100% identity. Significant differences were observed between these strains in their ability to ferment carbohydrates, which enabled better differentiation than that afforded by 16S rRNA sequence analysis. Carbohydrate fermentation analysis allowed for subspecies-level identification of L. mesenteroides isolated from Baechu and Chonggak kimchi.

A New Coordinate Transformation between Inertial Reference Frames S and S′

김군찬 계명대학교 자연과학연구소 2013 Quantitative Bio-Science Vol.32 No.2

This paper introduces a new coordinate transformation between the two inertial reference frames S and S′, where S′is moving at velocity v relative to S and with the occurrence of an event by which an object starts to move with velocity u′relative to S′. It is assumed that the origin O′of the frame S′coincides with origin O of the first frame S at t=t′=0. The transformation is formulated as t=t′, x=x′+vt), where =1/+vu′/c). We show that using this transformation, the wave equation for electromagnetic waves in frame S′has the same form as that in S. This result thus shows that there exists a transformation with absolute time (t=t′) which conforms to the relativity principle. A strong implication on the time dilation of a moving object is also discussed.

Multivariate Bias Correction for Climate Simulation Data, with Application to Precipitation Extremes in Korea

홍주영,김태윤,박정수 계명대학교 자연과학연구소 2019 Quantitative Bio-Science Vol.38 No.2

Much of knowledge on future climate change depends on projections from the simulation codes with global circulation models (GCMs) and regional climate models (RCMs). But even state-of-art simulation codes still have a rather coarse resolution and and are substantially biased compared to real-world climate. In an attempt to remove systematic biases between simulation model output and real observations, a variety of statistical bias correction (BC) methods has been developed. The methods are classified to univariate and multivariate ones. This study reviews these techniques with more emphasis on recently advanced multivariate methods. These includes delta change approach, quantile mapping, quantile delta mapping, empirical copula bias correction, multivariate quantile delta mapping and multivariate stochastic BC with optimal transport function. An application of multivariate BC method to annual daily extreme rainfall in Korea peninsula is presented. We applied an ensemble prediction with generalized extreme value distribution (GEVD) to the data obtained as simulated by the coupled model intercomparison project phase six (CMIP6) models. Simulation data under three RCP (Representative Concentration Pathway) scenarios, namely RCP 2.6, RCP 4.5 and RCP 8.5, are employed. The 20-year and 50-year return levels and return periods relative to the reference years (1973-2014) are estimated for two future periods, namely period 1 (2021-2050) and period 2 (2061-2099).

An Investment Strategy to Integrate the KOSDAQ150 Index and Bitcoin Using the Rough Set Theory

Min Kyung Park,Yeonji Choi,Jaeyun Kim,Kyong Joo Oh 계명대학교 자연과학연구소 2021 Quantitative Bio-Science Vol.40 No.1

Bitcoin, the most representative cryptocurrency, and the KOSDAQ150 index have a higher proportion of individual investors than the other financial products. As they present great investment opportunities, both are found to be highly volatile as well as high-risk financial products. Based on the correlation between the two products, this study proposes a more stable and a higher rate of return trading model for trading the KOSDAQ150 index alongside Bitcoin, enabling the investors to make sound and stable investments. The study utilizes the rough set theory for the development of the investment strategy. In conclusion, it was possible to achieve higher rates of return when trading the KOSDAQ150 index and Bitcoin together than when trading Bitcoin alone. The study demonstrates how the trading of Bitcoin allows for a longterm and a stable investment.

A Comparative Analysis of Two Different Wastewater Treatment Processes in Actual Wastewater Treatment Plants

배헌균 계명대학교 자연과학연구소 2018 Quantitative Bio-Science Vol.37 No.1

In this study, two different wastewater treatment systems, a conventional activated sludge process and pure oxygen activated sludge process, used at a municipal wastewater treatment facility in California were investigated. Their BOD and NH3 removal efficiencies, sludge productions, and economic efficiencies were compared. The BOD removal efficiency of the conventional activated sludge process (92.4~95.4%) is similar to that of the pure oxygen activated sludge process (91.9~96.2%). Further, both processes showed poor NH3 removal efficiencies; 9~18% for the conventional activated sludge process and 0~11.1% for the pure oxygen activated sludge process. Such poor NH3 removal efficiencies are probably because these processes are optimized for BOD removal. The pure oxygen activated sludge process produced 2~3 times more sludge than the conventional activated sludge process. The pure oxygen activated sludge process was slightly more economically efficient than the conventional activated sludge process (saved about 0.3 million $/yr).

Comparative Analysis of Antioxidant Activity in Almond and Pistachio Seeds

Lu Lu Wang,노광수 계명대학교 자연과학연구소 2014 Quantitative Bio-Science Vol.33 No.1

In order to compare the antioxidant activity of almond and pistachio seeds, total flavonoid content, total polyphenol content, ABTS free radical scavenging activity, and DPPH electron donating activity were measured. In case of almond seed, the highest value of the total flavonoid content and the total polyphenol content was observed from hot water extracts, while the highest values were observed from 100% methanol extracts in pistachio seed. Total flavonoid content was higher in almond than in pistachio seed, and the total polyphenol content was higher in pistachio seed. ABTS free radical scavenging activity of both almond and pistachio seeds were observed to be highest from hot water extracts, and it is higher in pistachio than in almond seed for all solvent extracts. Higher DPPH free radical scavenging activity was observed from hot water extracts rather than other solvent extracts in both almond and pistachio seeds. DPPH free radical scavenging activity was higher than ABTS free radical scavenging activity. In consequence, almond and pistachio seeds showed antioxidant activity, and these two nuts are worth being utilized as natural antioxidants in many fields.

Long-term Changes in Climate Factors and Food Supply in Korea: Focused on Fishery Products

김종규 계명대학교 자연과학연구소 2022 Quantitative Bio-Science Vol.41 No.1

This study aimed to investigate the impact of climatic factors on the offshore fishery catches in Korea over the past three decades and their effect on the fishery product supply. It focused on seven major fish species popular in Korean side dishes. The study data were entirely obtained from the official statistics of Korea. Data analyses, such as trend analysis and regression analysis, were done using SPSS software package. Over the last 30 years (1981 to 2010), cold-water fish species, such as Alaska/walleye pollock, have almost disappeared; however, catches of warm-water species, such as anchovy and squid, have greatly increased (p< 0.05). During the study period, the sea surface temperature (SST) and air temperature of Korea significantly increased (p< 0.05). The per capita annual consumption of fishery products in 2010 was much higher than that of 1981; however, the self-sufficiency ratio declined remarkably. Changes in catches due to SST changes strongly affected consumer prices of fish species such as Alaska/walleye pollock, while consumer price index (CPI) of Pacific saury was representative of the overall CPI for living. The results indicate that the fish species caught have changed during the long period because of the rise of air temperature and SST. These results warn that fish catches will change more due to ocean warming around the Korean peninsula. If the Korean fishery product consumption steadily increases, it would lead to a rise in its fishery prices (fishflation).

Bias-correction of Reanalysis Data and Missing Value Estimation for Extreme Precipitation Across Asia

박혜빈,박정수,홍주영 계명대학교 자연과학연구소 2022 Quantitative Bio-Science Vol.41 No.1

So-called reanalysis data are useful for climatic data analysis. However, some reanalysis data, such as APHRODITE (Asia Precipitation Highly Resolved Observational Data Integration Towards Evaluation), have biases in their mean and variance, especially for extreme rainfall. Undeniably, it needs further analysis for improvement. This study applies a multivariate bias- correction method to Korea, southern China, Philippines, and Thailand to realize this improvement. Our focus in this study is the annual maximum daily precipitation (AMP1). After correcting APHRODITE data over grids, we construct a time series of the AMP1 observations for some locations with no observational records by applying the so-called back- interpolation technique. This technique is also used to estimate missing values in the AMP1 series. This method is illustrated in some cities in North Korea and the Philippines.

1,6-Disubstituted-1H-benzo[d]imidazol-2(3H)-one Derivatives as PIM Kinase Inhibitors

추현승,정승익,Hong, Victor Sukbong,이진호 계명대학교 자연과학연구소 2022 Quantitative Bio-Science Vol.41 No.1

PIM proteins, which are proto-oncogenic serine/threonine kinases that are highly expressed in hematological malignancies and solid cancers, are potential molecular targets for anticancer drugs. 1H-Benzo[d]imidazol-2(3H)-one is a key structure in drug discovery, and several of its analogues have been developed as therapeutics. 1,6-Disubstituted-1H- benzo[d]imidazol-2(3H)-one derivatives were synthesized and evaluated in terms of their inhibitory activities against all three PIM kinases. Systematic structural modifications of benzo[d]imidazol-2-one at the 1- and 6-positions led to the discovery of pan-PIM inhibitors represented by 9. The binding modes of the synthesized compounds and the effects of the substituents on the selectivities among the PIM kinase isoforms were studied to confirm 1,6-disubstituted-1H- benzo[d]imidazol-2(3H)-one as a scaffold for use in the discovery of PIM kinase inhibitors.

Integrated Analytic Methodology Using Visual Image and Meta-Data for Product Recommendation

이용학,오재훈,양승민,김성환 계명대학교 자연과학연구소 2022 Quantitative Bio-Science Vol.41 No.1

Because the big data industry holds a significant position nowadays, Meta-Data has been adopted rapidly in various fields. In this paper, we introduce a model that exploits Meta-Data consisting of numerous production data to extract features using a pretrained deep learning model with image and text information. Thus, we can build a relational model between the production data to realize a recommendation system. Regarding the dataset, we determined that combining both image and text data is better than using one type of data to achieve a more accurate prediction from the relational model. Concerning the condition of two mixed languages (English and Korean), the method produces a satisfactory result. According to the relational model of the two products, we can design a recommendation system that suggests products that would be of interest to consumers.