• Journal of the Korean Society for Library and Information Science
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• v.46 no.4
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• pp.119-146
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• 2012

In this study, the concept of 'Musim' presented by Baegun Hwasang was analyzed from the viewpoint of a bibliography. Major findings are as follows: First, it is reasonable to translate 'Musim' into Korean to mean (1) 'free from cares', (2) 'there is noting called a heart', and (3) 'no anxieties' according to the context of praises. Second, Musim by Baegun means 'calm mind without any trembles in ordinary times', 'unload any worries', and 'the spirit of awakening'. Such concepts of Musim agree with the praises of 'Awakening by seeing through a person's own heart' presented by Dalma Josa, and 'Unloading any worries' presented by Buddha. Therefore it is understood that Musim is the mental state of 'being free from cares which seek and hold', and Baegun Hwasang presents his experiential awakening 'by keeping his mind calm without any trembles in ordinary times, unloading any worries, and freeing himself from cares'. Third, it is confirmed that Musim by Baegun when compared with the praises presented by 'Gwageo 7 Buls' and 'Seocheon 6 Josas' in Jikji, firmly holds the ideas of Buddha's 'Unloading any worries' and Seocheon Josa's 'Neutral perspective based on double negations'. Therefore, Baegun Hwasang's 'Musimseon' which especially emphasizes 'Musim' is the method of meditation which most clearly inherited the nature of Dalma Seonjong or Yukjo Hyeneung, and Imjejong's meditation.

• Journal of Microbiology and Biotechnology
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• v.18 no.3
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• pp.410-416
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• 2008

The gene SfXyn10, which encodes a protease-resistant xylanase, was isolated using colony PCR screening from a genomic library of a feather-degrading bacterial strain Streptomyces fradiae var. k11. The full-length gene consists of 1,437bp and encodes 479 amino acids, which includes 41 residues of a putative signal peptide at its N terminus. The amino acid sequence shares the highest similarity (80%) to the endo-1,4-${\beta}$-xylanase from Streptomyces coelicolor A3, which belongs to the glycoside hydrolase family 10. The gene fragment encoding the mature xylanase was expressed in Escherichia coli BL21 (DE3). The recombinant protein was purified to homogeneity by acetone precipitation and anion-exchange chromatography, and subsequently characterized. The optimal pH and temperature for the purified recombinant enzyme were 7.8 and $60^{\circ}C$, respectively. The enzyme showed stability over a pH range of 4.0-10.0. The kinetic values on oat spelt xylan and birchwood xylan substrates were also determined. The enzyme activity was enhanced by $Fe^{2+}$ and strongly inhibited by $Hg^{2+}$ and SDS. The enzyme also showed resistance to neutral and alkaline proteases. Therefore, these characteristics suggest that SfXyn10 could be an important candidate for protease-resistant mechanistic research and has potential applications in the food industry, cotton scouring, and improving animal nutrition.

• Proceedings of the Microbiological Society of Korea Conference
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• 2001.11a
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• pp.16-25
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• 2001

A genomic library of biphenyl-degrading strain Comamonas sp. SMN4 was constructed by using the cosmid vector pWE15 and introduced into Escherichia coli. Of 1,000 recombinant clones tested, two clones that expressed 2,3-dihydroxybiphenyl 1,2-dioxygenase activity were found (named pNB 1 and pNB2). From pNB1 clone, subclone pNA210, demonstrated 2,3-dihydroxybiphenyl 1,2-dioxygenase activity, is isolated. 2,3-Dihydroxybiphenyl 1,2-dioxygenase (23DBDO, BphC) is an extradiol-type dioxygenase that involved in third step of biphenyl degradation pathway. The nucleotide sequence of the Comamonas sp. SMN4 gene bphC, which encodes 23DBDO, was cloned into a plasmid pQE30. The His-tagged 23DBDO produced by a recombinant Escherichia coli, SG 13009 (pREP4)(pNPC), and purified with a Ni-nitrilotriacetic acid resin affinity column using the His-bind Qiagen system. The His-tagged 23DBDO construction was active. SDS-PAGE analysis of the purified active 23DBDO gave a single band of 32 kDa; this is in agreement with the size of the bphC coding region. The 23DBDO exhibited maximum activity at pH 9.0. The CD data for the pHs, showed that this enzyme had a typical a-helical folding structures at neutral pHs ranged from pH 4.5 to pH 9.0. This structure maintained up to pH 10.5. However, this high stable folding strucure was converted to unfolded structure in acidic region (pH 2.5) or in high pH (pH 12.0). The result of CD spectra observed with pH effects on 23DBDO activity, suggested that charge transition by pH change have affected change of conformational structure for 23DBDO catalytic reaction. The $K_m$ for 2,3-dihydroxybiphenyl, 3-metylcatechol, 4-methylcatechol and catechol was 11.7 $\mu$M, 24 $\mu$M, 50 mM and 625 $\mu$M.

• Korean Journal of Agricultural Science
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• v.46 no.1
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• pp.67-78
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• 2019

The purpose of this study was to predict the water quality using the RNN (recurrent neutral network) and LSTM (long short-term memory). These are advanced forms of machine learning algorithms that are better suited for time series learning compared to artificial neural networks; however, they have not been investigated before for water quality prediction. Three water quality indexes, the BOD (biochemical oxygen demand), COD (chemical oxygen demand), and SS (suspended solids) are predicted by the RNN and LSTM. TensorFlow, an open source library developed by Google, was used to implement the machine learning algorithm. The Okcheon observation point in the Geum River basin in the Republic of Korea was selected as the target point for the prediction of the water quality. Ten years of daily observed meteorological (daily temperature and daily wind speed) and hydrological (water level and flow discharge) data were used as the inputs, and irregularly observed water quality (BOD, COD, and SS) data were used as the learning materials. The irregularly observed water quality data were converted into daily data with the linear interpolation method. The water quality after one day was predicted by the machine learning algorithm, and it was found that a water quality prediction is possible with high accuracy compared to existing physical modeling results in the prediction of the BOD, COD, and SS, which are very non-linear. The sequence length and iteration were changed to compare the performances of the algorithms.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.8-8
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• 2019

The stringent response (SR) is characterized as a bacterial defense mechanism in response to various growth-inhibiting stresses. It is activated by accumulation of a small nucleotide regulator, (p)ppGpp, and induces global changes in bacterial transcription and translation. Recent work from our group has shown that (p)ppGpp plays a critical role in virulence and survival in Vibrio cholerae. The genes, relA and relV, are involved in the production of (p)ppGpp, while the spoT gene encodes an enzyme that hydrolyzes it in V. cholerae. A mutant strain defective in (p)ppGpp production (i.e. ${\Delta}relA{\Delta}relV{\Delta}spoT$ mutant) lost the ability to produce cholera toxin (CT) and lost their viability due to uncontrolled production of organic acids, when grown with extra glucose. In contrast, the ${\Delta}relA{\Delta}spoT$ mutant, a (p)ppGpp overproducer strain, produced enhanced level of CT and exhibited better growth in glucose supplemented media via glucose metabolic switch from organic fermentation to acetoin, a neutral fermentation end product, fermentation. These findings indicates that (p)ppGpp, in addition to its well-known role as a SR mediator, positively regulates CT production and maintenance of growth fitness in V. cholerae. This implicates SR as a promising drug target, inhibition of which may possibly downregulate V. cholerae virulence and survival fitness. Therefore, we screened a chemical library and identified a compound that induces medium acidification (termed iMAC) and thereby loss of wild type V. cholerae viability under glucose-rich conditions. Further, we present a potential mechanism by which the compound inhibits (p)ppGpp accumulation. Together, these results indicate that iMAC treatment causes V. cholerae cells to produce significantly less (p)ppGpp, an important regulator of the bacterial virulence and survival response, and further suggesting that it has a therapeutic potential to be developed as a novel antibacterial agent against cholera.

• Clinics in Shoulder and Elbow
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• v.27 no.1
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• pp.88-107
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• 2024

The aim of this systematic review was to collect evidence on the following 10 technical aspects of glenoid baseplate fixation in reverse total shoulder arthroplasty (rTSA): screw insertion angles; screw orientation; screw quantity; screw length; screw type; baseplate tilt; baseplate position; baseplate version and rotation; baseplate design; and anatomical safe zones. Five literature libraries were searched for eligible clinical, cadaver, biomechanical, virtual planning, and finite element analysis studies. Studies including patients >16 years old in which at least one of the ten abovementioned technical aspects was assessed were suitable for analysis. We excluded studies of patients with: glenoid bone loss; bony increased offset-reversed shoulder arthroplasty; rTSA with bone grafts; and augmented baseplates. Quality assessment was performed for each included study. Sixty-two studies were included, of which 41 were experimental studies (13 cadaver, 10 virtual planning, 11 biomechanical, and 7 finite element studies) and 21 were clinical studies (12 retrospective cohorts and 9 case-control studies). Overall, the quality of included studies was moderate or high. The majority of studies agreed upon the use of a divergent screw fixation pattern, fixation with four screws (to reduce micromotions), and inferior positioning in neutral or anteversion. A general consensus was not reached on the other technical aspects. Most surgical aspects of baseplate fixation can be decided without affecting fixation strength. There is not a single strategy that provides the best outcome. Therefore, guidelines should cover multiple surgical options that can achieve adequate baseplate fixation.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.47-72
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• 2022

This study aims to understand the trends of subjects related to real estate policies and public's emotional opinion on the policies. Two keywords related to real estate policies such as "real estate policy" and "real estate measure" were used to collect tweets created from February 25, 2008 to August 31, 2021. A total of 91,740 tweets were collected and we applied sentiment analysis and dynamic topic modeling to the final preprocessed and categorized data of 18,925 tweets. Sentiment analysis and dynamic topic model analysis were conducted for a total of 18,925 posts after preprocessing data and categorizing them into supply, real estate tax, interest rate, and population variance. Keywords of each category are as follows: the supply categories (rental housing, greenbelt, newlyweds, homeless, supply, reconstruction, sale), real estate tax categories (comprehensive real estate tax, acquisition tax, holding tax, multiple homeowners, speculation), interest rate categories (interest rate), and population variance categories (Sejong, new city). The results of the sentiment analysis showed that one person posted on average one or two positive tweets whereas in the case of negative and neutral tweets, one person posted two or three. In addition, we found that part of people have both positive as well as negative and neutral opinions towards real estate policies. As the results of dynamic topic modeling analysis, negative reactions to real estate speculative forces and unearned income were identified as major negative topics and as for positive topics, expectation on increasing supply of housing and benefits for homeless people who purchase houses were identified. Unlike previous studies, which focused on changes and evaluations of specific real estate policies, this study has academic significance in that it collected posts from Twitter, one of the social media platforms, used emotional analysis, dynamic topic modeling analysis, and identified potential topics and trends of real estate policy over time. The results of the study can help create new policies that take public opinion on real estate policies into consideration.

• Korean Journal of Microbiology
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• v.48 no.2
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• pp.125-133
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• 2012

Anaerobic digestion is an alternative method to digest food wastes and to produce methane that can be used as a renewable energy source. We investigated bacterial and archaeal community structures in a three-stage methane production process using food wastes with concomitant wastewater treatment. The three-stage methane process is composed of semianaerobic hydrolysis/acidogenic, anaerobic acidogenic, and strictly anaerobic methane production steps in which food wastes are converted methane and carbon dioxide. The microbial diversity was determined by the nucleotide sequences of 16S rRNA gene library and quantitative real-time PCR. The major eubacterial population of the three-stage methane process was belonging to VFA-oxidizing bacteria. The archaeal community consisted mainly of two species of hydrogenotrophic methanogen (Methanoculleus). Family Picrophilaceae (Order Thermoplasmatales) was also observed as a minor population. The predominance of hydrogenotrophic methanogen suggests that the main degradation pathway of this process is different from the classical methane production systems that have the pathway based on acetogenesis. The domination of hydrogenotrophic methanogen (Methanoculleus) may be caused by mesophilic digestion, neutral pH, high concentration of ammonia, short HRT, and interaction with VFA-oxidizing bacteria (Tepidanaerobacter etc.).

• Journal of the Korean Society for information Management
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• v.28 no.3
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• pp.335-353
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• 2011

This study examines how and which direction respondents who participated in 5-point Likert scale surveys change their initial responses when they are given an identical second survey after certain treatments. The research employs three identical questionnaires (first, second and third surveys) to analyze survey results based on group differences, kinds of treatment, survey purposes, and response change direction and the degree. This paper concludes that, first, it is significant that specialist groups do not change their initial responses compared to a general librarian group. Second, there are no differences by survey purpose; however, participants tend to change their initial responses by others' opinions rather than by previous use experiences. Third, participants who initially answered positively tend not to change their responses, and most participants who answered negatively change their initial responses in a positive direction. Fourth, when there are changes, participants change their initial responses by less than two points, and most of them change by one point. Finally, the hypothesis that middle responses change most and that participants who respond at both ends do not change their opinion was rejected by the finding that participants who answered on the negative end tend to change their initial responses in a positive direction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.830-860
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• 2022

[Introduction] Nowadays, many companies are shifting their businesses online due to the growing trend among customers to buy and shop online, as people prefer online purchasing products. [Problem] Users share a vast amount of information about products, making it difficult and challenging for the end-users to make certain decisions. [Motivation] Therefore, we need a mechanism to automatically analyze end-user opinions, thoughts, or feelings in the social media platform about the products that might be useful for the customers to make or change their decisions about buying or purchasing specific products. [Proposed Solution] For this purpose, we proposed an automated SentiDecpective approach, which classifies end-user reviews into negative, positive, and neutral sentiments and identifies deceptive crowd-users rating information in the social media platform to help the user in decision-making. [Methodology] For this purpose, we first collected 11781 end-users comments from the Amazon store and Flipkart web application covering distant products, such as watches, mobile, shoes, clothes, and perfumes. Next, we develop a coding guideline used as a base for the comments annotation process. We then applied the content analysis approach and existing VADER library to annotate the end-user comments in the data set with the identified codes, which results in a labelled data set used as an input to the machine learning classifiers. Finally, we applied the sentiment analysis approach to identify the end-users opinions and overcome the deceptive rating information in the social media platforms by first preprocessing the input data to remove the irrelevant (stop words, special characters, etc.) data from the dataset, employing two standard resampling approaches to balance the data set, i-e, oversampling, and under-sampling, extract different features (TF-IDF and BOW) from the textual data in the data set and then train & test the machine learning algorithms by applying a standard cross-validation approach (KFold and Shuffle Split). [Results/Outcomes] Furthermore, to support our research study, we developed an automated tool that automatically analyzes each customer feedback and displays the collective sentiments of customers about a specific product with the help of a graph, which helps customers to make certain decisions. In a nutshell, our proposed sentiments approach produces good results when identifying the customer sentiments from the online user feedbacks, i-e, obtained an average 94.01% precision, 93.69% recall, and 93.81% F-measure value for classifying positive sentiments.