• Microbiology and Biotechnology Letters
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• v.20 no.5
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• pp.519-526
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• 1992

The gene coding for urease of alkalophilic Bacillus pasteurii had been cloned in Escherichia coli previously. The urease protein was purified 63.1-fold by TEAE-cellulose, DEAE-Sephadex A-50, Sephadex G-150 and Sephadex G-200 chromatographies with a 7.3% yield from the sonicated fluid of the E. coli HB1Ol(pBUll) encoding B. pasteurii urease gene. The ureases of E. coli (pBUll) and B. pasteurii possessed as a $K_m$ for urea, 42.1 mM and 40.4 mM, respectively. They hydrolyzed urea with $V_{max}$ of 86.9$\mu$mol/min and 160$\mu$mol/min, respectively. Both ureases were composed with four subunits (Mrs 67,000) and a subunit (Mr 20,000). The molecular weight of both native enzymes was Mr 280,OOO$pm$10,000 determined by gel filtration chromatography and Coomassie blue staining of the subunits. The optimal reaction pH of both ureases were pH 7.5. The ureases were stabled in pH 5.5-10.5. The optimal reaction temperature of both ureases were $60^{\circ}C$, and the ureases were stable for an hour at $50^{\circ}C$, 40min at $60^{\circ}C$ and 10 min at $70^{\circ}C$ The activity of both enzymes were inhibited completely by $Ag^{2+}$, $Hg^{2+}$, $Zn^{2+}$, $Cu^{2+}$, and were inhibited 60% by CoH, 30% by $Fe^{2+}$ and 10% by $Pb^{2+}$. However it was increased by the addition of $Sn^{2+}$, $Mn^{2+}$, $Mg^{2+}$ at concentration of $1{\times}10^{-3}$M. Both ureases were inhibited completely by p-CMB and acetohydroxamic acid. The urease expressed in E. coli (pBU11) was inhibited 70% by SDS. The urease of B. pasteurii was inhibited 40% by hydroxyurea, whereas the recombinant urease of E. coli strain was inhibited 17%. Both enzymes were not inhibited by cyclohexanediaminetetraacetic acid (CDTA) and ethylendiaminetetraacetic acid (EDTA).

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Journal of Animal Science and Technology
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• v.52 no.5
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• pp.427-434
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• 2010

This study was conducted to investigate the growth performance and meat quality improvement according to castration, optimal feeding management and ruminally protected amino acid-enriched fatty acid (RPAAFA) for the unselected Hanwoo bulls in the performance test. Bulls were castrated at approximately 14 months of age. Sixteen Hanwoo steers, 15 months of age and weighing $412.9{\pm}24.9kg$, were distributed into 2 groups. Steers were fed a basal diet supplemented with RPAAFA at 0 g (control) or 100 g (treatment), respectively for 12 months. Steers were slaughtered at 27 months of age. Average daily gain for treatment tended to be higher (p=0.10) than that of control, whereas feed conversion ratio tended to be lower (p=0.07) in treatment than in control. The supplementation of RPAAFA did not affect rib eye area, back fat thickness, meat color, fat color, texture and maturity. The appearance rates of yield 'A' grade and high quality grade ($1^{++}$, $1^+$ and 1) were higher in treatment than in control. The content of moisture, fat, protein and ash in longissimus muscles were similar between control and treatment. The supplementation of RPAAFA did not affect water-holding capacity, oxidation and reduction potential, myoglobin and fatty acid contents in longissimus muscles. Thus, present results indicate that castration, optimal feeding management and RPAAFA may be recommended for improving growth performance and quality grade of the unselected Hanwoo bulls in the performance test.

• Journal of Food Hygiene and Safety
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• v.33 no.3
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• pp.200-206
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• 2018

This study was to investigate the optimal condition of mixture ratio for development of functional food ingredient from Sarcodon aspratus and rice bran. First, $^{\circ}Brix$ was measured along with extraction time. Five kinds of mixtures of Sarcodon aspratus and rice bran (10:0, 7:3, 5:5, 3:7, 0:10) were extracted in $95^{\circ}C$ water over a one-hour period and the extraction yield was evaluated. We further evaluated ${\beta}-glucan$ content, DPPH radical scavenging activity, ferric ion reducing antioxidant power (FRAP), total phenolic content and total flavonoids content. As a result, both Sarcodon aspratus and rice bran showed a constant $^{\circ}Brix$ after 45 minutes of extraction time. The content of ${\beta}-glucan$ was highest in the Sarcodon aspratus and rice bran mixture with a ratio of 3:7. As the ratio of rice bran increased in all mixtures, the antioxidant capacity also increased. In conclusion, to create a functional food ingredient the optimal mixing ratio of Sarcodon aspratus to rice bran is 3:7.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.

• Korean Journal of Microbiology
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• v.54 no.4
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• pp.384-397
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• 2018

The aim of this study is to screen the strains of Bacillus spp. possessing safety, probiotic activity, and so on, which can be utilized as probiotic resource for using the feed and supplement food of companion animal. About 300 isolates were isolated from traditional Korean sauces, four isolates that did not have or produce the six kinds of B. cereus type vomiting and diarrhea toxin genes, ${\beta}$-hemolytic, and three kinds of carcinogenic enzymes were selected. Antibiotic gene retention, cell surface hydrophobicity, antibiotic sensitivity, and glucose utilization were analyzed for four isolates, and finally SRCM 100731 was selected. SRCM 100731 was named as Bacillus amyloliquefaciens SRCM 100731 16S rRNA sequencing analysis, and carried out optimization of cell growth for industrial applications such as pet food and feed. The effects of 14 different components on cell growth were investigated and three significant positive factors, molasses, sodium chloride, and potassium chloride were selected as the main factors based on a Plackett-Burman design. In order to find out optimal concentration on each constituent, we carried out central composite design. The predicted optimized concentrations were 7% molasses, 1.1% sodium chloride, 0.5% potassium chloride. Finally, an overall about 7-fold increase in dry cell weight yield ($12.6625{\pm}0.0658g/L$) was achieved using the optimized medium compared with the non-optimized medium ($1.8273{\pm}0.0214g/L$). This research is expected to be highly utilized in the growing pet industry by establishing optimal cultivation conditions for industrial application as well as screening Bacillus amyloliquefaciens SRCM 100731 as probiotic resource for companion animal.

• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.352-362
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• 2023

Harvest time is one of the most important determining factors of seed quality, especially for species that produce seeds over irregular and long-term periods, such as Larix kaempferi. A cone collection plan must be established to increase seed production efficiency and stable mass production. We investigated seed qualities such as seed efficiency, germination rate, and T₅₀ (germination speed), with 7 or 8 cone collection times at a clonal seed orchard of L. kaempferi in Chungju between 2021 and 2022. A multivariate analysis was then performed for the collected data. In early August, decreases in the moisture contents and browning of cones were observed. These were followed by a decrease in germination rate, with a peak at the end of September, but no clear trend was observed. The later the cones were harvested, the better the seed vigor (T₅₀). However, the seed yield and efficiency decreased owing to increases in seed scattering and the number of insect-damaged seeds. As a result, the optimal time of seed harvest for the seed orchard was in early August. To produce uniform seedlings, insect damage must be reduced through timely control and harvest cones in early September. This shows that the degree of browning and moisture content of cones can be used as indicators of the timing of cone collection in L. kaempferi seed orchards.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.68 no.4
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• pp.304-312
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• 2023

Plant breeding is a time-consuming process, mainly due to the limited annual generational advancement. A speed breeding system, using LED light sources, has been applied to accelerate generational progression in various crops. However, detailed protocols applicable to soybeans are still insufficient. In this study, we report the optimized protocols for a speed breeding system comprising 12 soybean varieties with various maturity ecotypes. We investigated the effects of two light qualities (RGB ratio), three levels of light intensity (PPFD), and two soil conditions on the flowering time and development of soybeans. Our results showed that an increase in the red wavelength of the light spectrum led to a delay in flowering time. Furthermore, as light intensity increased, flowering time, average internode length, and plant height decreased, while the number of nodes, branches, and pods increased. When compared to agronomic soil, horticultural soil resulted in an increase of more than 50% in the number of nodes, branches, and pods. Consequently, the optimal conditions were determined as follows: a 10-hour short-day photoperiod, an equal RGB ratio (1:1:1), light intensity exceeding 1,300 PPFD, and the use of horticultural soil. Under these conditions, the average flowering time was found to be 27.3±2.48 days, with an average seed yield of 7.9±2.67. Thus, the speed breeding systems reduced the flowering time by more than 40 days, compared to the average flowering time of Korean soybean resources (approximately 70 days). By using a controlled growth chamber that is unaffected by external environmental conditions, up to 6 generations can be achieved per year. The use of LED illumination and streamlined facilities further contributes to cost savings. This study highlights the substantial potential of integrating modern crop breeding techniques, such as digital breeding and genetic editing, with generational shortening systems to accelerate crop improvement.

• Microbiology and Biotechnology Letters
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• v.8 no.3
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• pp.181-191
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• 1980

For the purpose of studies on the citric acid production, some experiments were carried out with isolated strains. The results obtained were as follows. 1) The optimal culture media of the strain M-80 in surface culture contained 140g of sucrose, 3.0g of (N $H_4$)$_2$S $O_4$, 1.5g of K $H_2$P $O_4$, 0.2g of MgS $O_4$.7$H_2O$, 3.0mg of F $e^{++}$, 1.0mg of Z $n^{++}$, 0.5N HCI to a pH of 5.0 and distilled water to 1.0 liter; and that of the strain M-315 in surface culture contained 140g of sucrose, 2.0g of N $H_4$N $O_3$, 1.0g of K $H_2$P $O_4$, 0.25g of MgS $O_4$. 7$H_2O$, 2.0mg of F $e^{++}$, 2.0mg of Z $n^{++}$, 0.05mg of C $u^{++}$, 0.5N HCI to a pH of 4.5 and distilled water to 1.0 liter. While that of the strain M-315 in submerged culture contained 140g of sucrose, 2.5g of N $H_4$N $O_3$, 1.5g of K $H_2$P $O_4$, 0.3g of MgS $O_4$. 7$H_2O$, 3.0mg of F $e^{++}$, 0.1mg of C $u^{++}$, 0.5N HCI to a pH of 4.5 and distilled water to 1.0 liter. The optimal temperature and size of inoculum were mostly 28-3$0^{\circ}C$, 10$^{7}$ -10$^{8}$ spores/50ml, respectively. 2) Through the course of citric acid production, the growth of strains had nearly been completed, pH value was rapidly decreased below 2.0 and the content of sugar was also reduced, while the accumulation of citric acid in media was remarkably begun in about 3-4 days. The yields of citric acid generally reached the maximum level in 8-10 days in surface or submerged fermentation process. 3) Methanol was effective citric acid production when they were added to fermentation media. In the case of surface culture, by addition of 2％ (strain M-80), 3％ (strain M-315), the yields of citric acid was increased 6.5％, 20.6%, respectively and 5.0% yield was increased by addition of 3% methanol in submerged culture media of the strain M-315. 4) Chromatography analysis of culture broth after fermentation under optimal culture conditions detected that the majority of acid in media was citric acid. 72.1mg/ml, 98.1mg/ml, of citric acid were determined in surface culture media by strains of M-80, M-315, and 59.8 mg/ml of citric acid was contained in the submerged culture media by the strain M-315. strain M-315.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.133-144
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• 2022

This study was conducted to investigate the cultivation period, adaptive genetic resources, growth and development patterns, and water consumption for rice cultivation in the desert environment of United Arab Emirates (UAE). R esearch on rice cultivation in the desert environment is expected to contribute to resolving food shortages caused by climate change and water scarcity. It was found that the optimal cultivation period of rice was from late November to late April of the following year during which the low temperature occurred at the vegetative growth stage of rice in the UAE. Asemi and FL478 were selected to be candidate cultivars for temperature and day-length conditions in the desert areas as a result of pre-testing genetic resources under reclaimed soil and artificial meteorological conditions. In the desert environment in the UAE, FL478 died before harvest due to the etiolation and poor growth in the early stage of growth. In contrast, Asemi overcame the etiolation in the early stage of growth, which allowed for harvest. The vegetative growth phases of Asemi were from early December to early March of the following year whereas its reproductive growth and ripening phases were from early March to late March and from late March to late April, respectively. The yield of milled rice for Asemi was 763kg/10a in the UAE, which was about 41.8% higher than that in Korea. Such an outcome was likely due to the abundant solar radiation during the reproductive growth and grain filling periods. On the other hand, water consumption during the cultivation period in the UAE was 2,619 ton/10a, which was about three times higher than that in Korea. These results suggest that irrigation technology and development of cultivation methods would be needed to minimize water consumption, which would make it economically viable to grow rice in the UAE. In addition, select on of genetic resources for the UAE desert environments such as minimum etiolation in the early stages of growth would be merited further studies, which would promote stable rice cultivation in the arid conditions.