• Journal of Food Hygiene and Safety
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• v.21 no.4
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• pp.213-217
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• 2006

The halophilic bacterium Vibrio vulnificus is known to be a foodborne pathogen that causes septicemia in human. V. vulnificus infection is characterized by the high fatality rates and the primary attack against a person who have underlying diseases such as liver cirrhosis. However, there is no effective treatment for V. vulnificus septicemia except for classical treatments such as antibiotics. Recently, it has been known that lipoprotein (LDL) plays a major role in the protection against infection and inflammation. Consequently in this paper we analyzed the effects of LDL on V. vulnificus septicemia. We purified V. vulnificus cytolysin, a major virulent factor of V. vulnificus infection and measured inhibitory effects of mouse serum, cholesterol, and LDL on its hemolytic activity. Next experiments were performed to investigate whether LDL has a protective role against septicemia induced by V. vulnificus in mice. Intraperitoneal injection of LDL (1mg as protein) into mice 3hr before V. vulnificus $(1\times10^6\;CFU)$ injection, and V. vulnificus -induced lethality was determined. For the determination the relationship between LDL or cholesterol and prognosis, we determined serum levels of cholesterol and lipoprotein from V. vulnificus septicemia patients (n=15) who had visited the Chonbuk National University Hospital in Chonju. V. vulnificus cytolysin -induced hemolysis of mice erythrocytes was completely inhibited by serum, cholesterol, and low-density lipoprotein. V. vulnificus- induced lethality of mice injected with LDL showed only 40% compared to 100% of control. In survival groups (n=4) of V. vulnificus septicemia patients (n=15), their serum LDL and cholesterol revealed normal levels ($153.3{\pm}40.7,\;LDL;\;190.8{\pm}16.3$, Total cholesterol). However, in death groups (n=11) showed very low levels ($35.6{\pm}13.9,\;LDL;\;59.2{\pm}15.1$, Total cholesterol). Our study indicates that cholesterol and LDL are a prognosis indicator of V. vulnificus septicemia as well as an inhibitor of virulent action of V. vulnificus cytolysin. We suggested that the serum levels of cholesterol or LDL would be major index in the treatment and prevention of V. vulnificus septicemia.

• Research in Plant Disease
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• v.26 no.4
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• pp.264-271
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• 2020

We have developed a simultaneous diagnostic method that can identify both the species of thrips and tomato spotted wilt virus (TSWV) that are problematic in chrysanthemum plants. This is a method of amplifying DNA by performing reverse transcription-polymerase chain reaction by simultaneously adding primers specific to TSWV coat protein (N) gene and primers specific to the internal transcribed spacer 2 region of Frankliniella occidentalis and F. intonsa using total nucleic acid extracted from one thrips. The sizes of DNA fragments for TSWV, F. occidentalis, and F. intonsa were 777, 287, and 367 bp, respectively. These results showed species identification of thrips and whether thrips carrying TSWV can be simultaneously confirmed. Further usefulness of the simultaneous diagnostic method was made from greenhouse survey at chrysanthemum greenhouses in Taean (Chungcheongnam-do) and Changwon (Gyeongsangnam-do) to investigate the identification of thrips species and the rate of thrips carrying TSWV. Of thrips collected from the greenhouses, 83.7% thrips was F. occidentalis and 72.9% F. occidentalis carried TSWV in Taean. Similarly, the diagnostic method showed that 92.2% thrips was F. occidentalis and 84.0% F. occidentalis carried TSWV in Changwon. These results confirm that F. occidentalis is a dominant thrips species and the thrips species plays a crucial role in the transmission of TSWV in chrysanthemum plants in the greenhouses. Taken together, this study showed a simple diagnostic method for thrips identification and epidemiological studies of the timing and spread of TSWV through thrips in chrysanthemum greenhouses in South Korea.

• Korean Chemical Engineering Research
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• v.60 no.4
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• pp.588-593
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• 2022

Terephthalaldehyde (TPA) is introduced as a cross liker to enhance electron transfer of hemin-based cathodic catalyst consisting of polyethyleneimine (PEI), carbon nanotube (CNT) for hydrogen peroxide reduction reaction (HPRR). In the cyclic voltammetry (CV) test with 10 mM H₂O₂ in phosphate buffer solution (pH 7.4), the current density for HPRR of the suggested catalyst (CNT/PEI/hemin/PEI/TPA) shows 0.2813 mA cm^-2 (at 0.2 V vs. Ag/AgCl), which is 2.43 and 1.87 times of non-cross-linked (CNT/PEI/hemin/PEI) and conventional cross liker (glutaraldehyde, GA) used catalyst (CNT/PEI/hemin/PEI/GA), respectively. In the case of onset potential for HPRR, that of CNT/PEI/hemin/PEI/TPA is observed at 0.544 V, while those of CNT/PEI/hemin/PEI and CNT/PEI/hemin/PEI/GA are 0.511 and 0.471 V, respectively. These results indicate that TPA plays a role in facilitating electron transfer between the electrodes and substrates due to the π-conjugated cross-linking bonds, whereas conventional GA cross-linker increases the overpotential by interrupting electron and mass transfer. Electrochemical impedance spectroscopy (EIS) results also display the same tendency. The charge transfer resistance (R_ct) of CNT/PEI/hemin/PEI/TPA decreases about 6.2% from that of CNT/PEI/hemin/PEI, while CNT/PEI/hemin/PEI/GA shows the highest R_ct. The polarization curve using each catalyst also supports the superiority of TPA cross liker. The maximum power density of CNT/PEI/hemin/PEI/TPA (36.34±1.41 μWcm^-2) is significantly higher than those of CNT/PEI/hemin/PEI (27.87±0.95 μWcm^-2) and CNT/PEI/hemin/PEI/GA (25.57±1.32 μWcm^-2), demonstrating again that the cathode using TPA has the best performance in HPRR.

• (The) Research of the performance art and culture
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• no.39
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• pp.325-355
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• 2019

On June 12, 1791, the old bachelor Kim Hee-jip and the old lady Shin Deok-bin's Daughter get married. The wedding ceremony is a state-led so-called 'virgin virgin bachelor's marriage project'. At that time, the king ordered the recorder to record the case, which is called . The private sector also made it into a work, which is the Chinese drama written by LeeOk(李鈺). was created with the purpose of praising the king, and it inserted entertainment elements into it, so it had a frame of plays, but it did not have a performance in mind from the beginning. LeeOk uses different styles in each of the four acts. He tried to soothe his boredom by setting tales and proverbs in Acts 1 and 2, Pansori in Act 3, and drama in Act 4. In 1918, BaekDooYong(白斗鏞) published DongSangGiChan[東床記纂], which is combines drama and Yadam . In previous studies, these two were perceived as different works, but the two rooms were closely linked: the link was 'someone recognize me[知 己]'. He understood the table of contents made by Lee as 'JaeHyun(才賢)', 'deokhye(德慧)', 'Kwontaek(眷澤)', 'Bokyeon(福 緣)' respectively, and recorded the version of the yadam that fits it in . From acts 1 to 4, Baek contained his desire in it by constructing 'someone recognizes me → I recognize someone → do good things[積善] → blessings[餘慶]'. This is why we can't comprehend and as completely different works.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.201-219
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• 2023

ESG (Environment, Social, Governance) is becoming the core of the interest of today's entrepreneurs concerning about the earth crisis. Numerous studies are going on these days about the importance of ESG, but most of them seem confined to the introductory level. This study concentrates on "ESG education" that will teach the learners how to put various ESG ideas into practice, knowing that the earth crisis would not be overcome without actual practice of those ideas. First, elementary and junior·senior high school, professors in university and educational consultants in the field designed educational programs and related content materials under "ESG entrepreneurship education" integrated with ESG and Entrepreneurship education, which have been implemented previously. Participatory learning methods are converged with the program. The researcher analyzed the learning effects in depth after implementing the programs in the education field. Thus, this study first examined the effects of key variables of ESG educational program i.e., ESG entrepreneurship education, student participatory learning, and team-based learning on creative problem-solving and social value recognition with an essential variant of ESG educational programs and identified the relations to creative problem-solving and social value recognition. Besides, this study investigated the moderating effects of school atmosphere, and teachers' enthusiasm, regarding traits of educational programs and social value recognition. Findings indicate that sub variants of the traits of educational programs i.e., ESG entrepreneurship education, student participatory learning, and team-based learning significantly affect creative problem-solving skills and social value recognition and that creative problem-solving impacts social value recognition. In addition, teachers' enthusiasm has moderating effects between traits of educational programs and social value recognition. This study provides content-program learning methods that can be practically applied in education, emphasizing practice in ESG in elementary and junior·senior high school education. Implications suggest that ESG entrepreneurship education and active participatory learning affect social value recognition and that teachers' enthusiasm plays a significant role in education.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.131-148
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• 2023

The purpose of this study is to investigate the effects of entrepreneurial environment and entrepreneurial competency on entrepreneurial intention by setting degree of self-determination as a moderating variable for pre-entrepreneur of agriculture industry. The entrepreneurial environment was divided into perceived support and perceived barriers, and the sub-variables of entrepreneurial competence were set as creativity, problem solving, communication, marketing, and business plan. 253 questionnaires were used for empirical analysis. The results of the analysis using SPSS v25.0 and Process macro v4.2 are as follows. First, the perceived support and perceived barriers of the entrepreneurial environment have a significant effect on entrepreneurial intention. Creativity, problem solving, marketing and business plan of entrepreneurial competency have a significant effect on entrepreneurial intention, but the effect of communication was non-significant. Second, the degree of self-determination did not moderate the relationship between perceived support, barriers and entrepreneurial intention. This means that the level of self-determination may not have a significant effect on the relationship between entrepreneurial environment and entrepreneurial intention. Third, the degree of self-determination was found to moderate the relationship between creativity, problem solving, communication, marketing and business plan of entrepreneurial competency and entrepreneurial intention. Specifically, as the degree of self-determination increases, the size of the influence of creativity, problem solving, marketing, and business plan on entrepreneurial intention plays a role of strengthening in a positive direction. On the other hand, as the degree of self-determination increases, the degree of self-determination, which weakens the relationship between communication and entrepreneurial intention. Future research will require exploration of other factors that can explain entrepreneurial environment and entrepreneurial capacity, and follow-up studies are needed to analyze the moderated mediating effects through conditional process models that include new mediating and moderating variables.

• Korean Journal of Clinical Laboratory Science
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• v.56 no.3
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• pp.236-247
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• 2024

The human leukocyte antigen (HLA) system, which is part of the major histocompatibility complex (MHC) plays a vital role in immune responses by differentiating between itself and foreign cells and antigens. The significant diversity of alleles affects disease susceptibility and immune responses within different populations. Specifically, the HLA-A and HLA-DRB1 alleles are associated with various immune-related diseases, and understanding the frequency and haplotype associations of these alleles is vital for genetic and immunological research. To investigate the distribution of these characteristics in Koreans, we isolated peripheral blood mononuclear cells (PBMCs) from blood samples donated by volunteers at the Seoul Central Blood Bank and performed HLA typing on 790 samples. Our study found that the HLA-A and HLA-DRB1 alleles are widely distributed within the Korean population, with HLA-A^*24:02 (21.7%) and HLA-DRB1*09:01 (9.9%) being the most frequent. Significant haplotype associations between specific HLA-A and HLA-DRB1 alleles were identified using the Chi-square test, suggesting that certain genetic combinations may influence disease onset. This insight could contribute to the development of predictive and preventative strategies for various diseases. The unique genetic characteristics of the Korean population highlight the importance of studying the HLA allele and the haplotype distributions in this group as key indicators for understanding disease susceptibility.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.59-83
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• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.

• Journal of Global Scholars of Marketing Science
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• v.19 no.1
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• pp.37-46
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• 2009

The Census Bureau of the Department of Commerce announced in May 2008 that U.S. retail e-commerce sales for 2006 reached $ 107 billion, up from $ 87 billion in 2005 - an increase of 22 percent. From 2001 to 2006, retail e-sales increased at an average annual growth rate of 25.4 percent. The explosive growth of E-Commerce has caused profound changes in marketing channel relationships and structures in many industries. Despite the great potential implications for both academicians and practitioners, there still exists a great deal of uncertainty about the impact of the Internet channel introduction on distribution channel management. The purpose of this study is to investigate how the ownership of the new Internet channel affects the existing channel members and consumers. To explore the above research questions, this study conducts well-controlled mathematical experiments to isolate the impact of the Internet channel by comparing before and after the Internet channel entry. The model consists of a monopolist manufacturer selling its product through a channel system including one independent physical store before the entry of an Internet store. The addition of the Internet store to this channel system results in a mixed channel comprised of two different types of channels. The new Internet store can be launched by the independent physical store such as Bestbuy. In this case, the physical retailer coordinates the two types of stores to maximize the joint profits from the two stores. The Internet store also can be introduced by an independent Internet retailer such as Amazon. In this case, a retail level competition occurs between the two types of stores. Although the manufacturer sells only one product, consumers view each product-outlet pair as a unique offering. Thus, the introduction of the Internet channel provides two product offerings for consumers. The channel structures analyzed in this study are illustrated in Fig.1. It is assumed that the manufacturer plays as a Stackelberg leader maximizing its own profits with the foresight of the independent retailer's optimal responses as typically assumed in previous analytical channel studies. As a Stackelberg follower, the independent physical retailer or independent Internet retailer maximizes its own profits, conditional on the manufacturer's wholesale price. The price competition between two the independent retailers is assumed to be a Bertrand Nash game. For simplicity, the marginal cost is set at zero, as typically assumed in this type of study. In order to explore the research questions above, this study develops a game theoretic model that possesses the following three key characteristics. First, the model explicitly captures the fact that an Internet channel and a physical store exist in two independent dimensions (one in physical space and the other in cyber space). This enables this model to demonstrate that the effect of adding an Internet store is different from that of adding another physical store. Second, the model reflects the fact that consumers are heterogeneous in their preferences for using a physical store and for using an Internet channel. Third, the model captures the vertical strategic interactions between an upstream manufacturer and a downstream retailer, making it possible to analyze the channel structure issues discussed in this paper. Although numerous previous models capture this vertical dimension of marketing channels, none simultaneously incorporates the three characteristics reflected in this model. The analysis results are summarized in Table 1. When the new Internet channel is introduced by the existing physical retailer and the retailer coordinates both types of stores to maximize the joint profits from the both stores, retail prices increase due to a combination of the coordination of the retail prices and the wider market coverage. The quantity sold does not significantly increase despite the wider market coverage, because the excessively high retail prices alleviate the market coverage effect to a degree. Interestingly, the coordinated total retail profits are lower than the combined retail profits of two competing independent retailers. This implies that when a physical retailer opens an Internet channel, the retailers could be better off managing the two channels separately rather than coordinating them, unless they have the foresight of the manufacturer's pricing behavior. It is also found that the introduction of an Internet channel affects the power balance of the channel. The retail competition is strong when an independent Internet store joins a channel with an independent physical retailer. This implies that each retailer in this structure has weak channel power. Due to intense retail competition, the manufacturer uses its channel power to increase its wholesale price to extract more profits from the total channel profit. However, the retailers cannot increase retail prices accordingly because of the intense retail level competition, leading to lower channel power. In this case, consumer welfare increases due to the wider market coverage and lower retail prices caused by the retail competition. The model employed for this study is not designed to capture all the characteristics of the Internet channel. The theoretical model in this study can also be applied for any stores that are not geographically constrained such as TV home shopping or catalog sales via mail. The reasons the model in this study is names as "Internet" are as follows: first, the most representative example of the stores that are not geographically constrained is the Internet. Second, catalog sales usually determine the target markets using the pre-specified mailing lists. In this aspect, the model used in this study is closer to the Internet than catalog sales. However, it would be a desirable future research direction to mathematically and theoretically distinguish the core differences among the stores that are not geographically constrained. The model is simplified by a set of assumptions to obtain mathematical traceability. First, this study assumes the price is the only strategic tool for competition. In the real world, however, various marketing variables can be used for competition. Therefore, a more realistic model can be designed if a model incorporates other various marketing variables such as service levels or operation costs. Second, this study assumes the market with one monopoly manufacturer. Therefore, the results from this study should be carefully interpreted considering this limitation. Future research could extend this limitation by introducing manufacturer level competition. Finally, some of the results are drawn from the assumption that the monopoly manufacturer is the Stackelberg leader. Although this is a standard assumption among game theoretic studies of this kind, we could gain deeper understanding and generalize our findings beyond this assumption if the model is analyzed by different game rules.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.95-112
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• 2021

In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.