• Journal of Life Science
• /
• v.23 no.5
• /
• pp.710-720
• /
• 2013

Radiotherapy is commonly used in treating many kinds of cancers which cannot be cured by other therapeutic strategies. However, radiotherapy also induces the damages on the normal tissues. Radiation-induced fibrosis is frequently observed in the patients undergoing radiotherapy, and becomes a major obstacle in the treatment of intrahepatic cancer. Hedgehog (Hh) that is an essential in the liver formation during embryogenesis is not detected in the healthy liver, but activated and modulates the repair process in damaged livers in adult. The expression of Hh increases with the degree of liver damage, regulating the proliferation of hepatic progenitors and hepatic stellate cells (HSC). In addition, Hh induces epithelial-to-mesencymal transition (EMT) and activation of myofibroblasts. In the irradiated livers, up-regulated expression of Hh signaling was associated with proliferation of progenitors, EMT induction, and increased fibrosis. Female-specific expression of Hh leaded to the expansion of progenitors and the accumulation of collagen in the irradiated livers of female mice, indicating that gender disparity in Hh expression may be related with radiation-susceptibility in female. Hence, Hh signaling becomes a novel object of studies for fibrogenesis induced by radiation. However, the absence of the established experimental animal models showing the similar physiopathology with human liver diseases and fibrosis-favorable microenvironment hamper the studies for the radiation-induced fibrosis, providing a few descriptive results. Therefore, further research on the association of Hh with radiation-induced fibrosis can identify the cell and tissue-specific effects of Hh and provides the basic knowledge for underlying mechanisms, contributing to developing therapies for preventing the radiation-induced fibrosis.

• Journal of the Korean Electrochemical Society
• /
• v.23 no.4
• /
• pp.105-112
• /
• 2020

Transition metal oxide, which undergoes a conversion reaction in the negative electrode material for a lithium-ion batteries, has a high specific capacity, but still has several critical problems. In this study, manganese pyrophosphate (Mn₂P₂O₇), nickel pyrophosphate (Ni₂P₂O₇), and carbon composite materials with pyrophosphates as novel negative electrode materials instead of transition metal oxide, are synthesized through simple solid-state reaction. The initial reversible capacity of Mn₂P₂O₇ and Ni₂P₂O₇ are 333 and 340 mAh g^-1, and when the composite materials are composed with carbon, the reversible capacity increases to 433 and 387 mAh g^-1, respectively. The initial Coulombic efficiency is also improved by about 10%. The Mn₂P₂O₇ and carbon composite material has the highest initial capacity and efficiency, and has the best cycle performance. Mn₂P₂O₇ containing polyanion, has a lower specific capacity due to the large mass of polyanion compared to MnO (manganese oxide). However, since Mn₂P₂O₇ shows a voltage curve with a slope, the charging (lithiation) voltage increases from 0.51 to 0.57 V (vs. Li/Li⁺), and the discharge (delithiation) voltage decreases from 1.15 to 1.01 V (vs. Li/Li⁺). Therefore, the voltage efficiency of the cell is improved because the voltage difference between charging and discharging is greatly reduced from 0.64 to 0.44 V, and the operating voltage of the full cell increases because the negative electrode potential is lowered during the discharging process.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.43 no.1
• /
• pp.9-15
• /
• 2014

To characterize novel biologically-active ingredients in traditional Korean soy sauces, polysaccharide fractions were isolated from two different soy sauces made either commercially (CSP-0) or through a traditional Korean process (KTSP-0), after which their intestinal immune-modulating activities were examined. CSP-0 and KTSP-0 showed enhanced production of interleukine-6 (IL-6) in culture supernatant of Peyer's patch cells. However, KTSP-0 activity was more potent than that of CSP-0. Only KTSP-0 increased in vitro immunoglobulin A (IgA) production by Peyer's patch cells in a dose-dependent manner. KTSP-0 also showed the higher bone marrow cell proliferation activity through Peyer's patch cells than that of the CSP-0 group. To investigate the in vivo effects on the intestinal immune system, CSP-0 and KTSP-0 were administered orally to four experimental groups of mice (0.0, 0.5, 1.0, and 5.0 mg/mouse/day, 30 days). Oral administration of CSP-0 and KTSP-0 induced IgA production by Peyer's patch cells and increased IgA excretion into mouse stools in a dose-dependent manner. Peyer's patch cells from the mice administered both CSP-0 and KTSP-0 showed significantly higher IL-6 production than that of the untreated or CSP-0 groups. However, oral administration of KTSP-0 was more effective at the same dosage. KTSP-0 administration augmented IL-6 content in mouse sera, whereas CSP-0 did not show any effect on IL-6 induction. The above data lead us to conclude that the intestinal immune-stimulating activities of polysaccharides from Korean traditional soy sauce are much better than those of commercial ones.

• Journal of Intelligence and Information Systems
• /
• v.27 no.3
• /
• pp.29-56
• /
• 2021

Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.

• Cross-Cultural Studies
• /
• v.53
• /
• pp.103-130
• /
• 2018

The Chilean female writer María Luisa Bombal (1910 - 1980)'s "El ${\acute{a}}rbol$" (The Tree) (1939) tells the process of Brigida's epiphany. Brigida first tried to gain her father's love and failed, and later her husband's love and failed, then tried to substitute that love from men with solace from a tree. At the end of the novel, the epiphany occurs when the tree is cut down. In the present work, I explain the meaning of Brigida's epiphany, by comparing this Chilean short story with the Korean female writer Kim Chaewon(1946 - )'s "Trick of Water: A Kiss with Nothing" (2015). In this Korean short story, Kim insists that a woman who tries to find comfort in life through love with a man is destined to fail. I also examine the errors of the female characters' behaviors in these two short stories that led them to their self-destruction, trying to modify their behaviors in order to be loved by a man and their tendency to consider the man as everything in their life, and not as a part of their life. In order to explain the fated failure of finding comfort in life in the love of a man, I analyze the fleeting characteristic of acquiring an object of desire using Jacques Lacan's "Theory of Desire" and "The Destruction of the Elevated Object into the Dignity of the Thing." Thus, I conclude that women need to acknowledge that comfort in life cannot be found in the love of a man and that they should stop confining themselves to this fictitious characteristic of the dignified object called man.

• Journal of the Society of Cosmetic Scientists of Korea
• /
• v.45 no.2
• /
• pp.185-198
• /
• 2019

Human tissue undergoes aging by the oxidant damage via structural change and its physical properties. The skin aging process is well known and many evaluations have been conducted. However, studies on hair aging were relatively few and thus care for aging hair is difficult. This study aims to fabricate an aging hair and identify anti-aging effect with known ingredient in anti-aging. First of all, physical properties of aging hair of age 60s by physiologically intrinsic factors were compared to those of the hair made by various extrinsic factors such as several chemical reactions and iteration numbers of the treatments. The extrinsic aging hair of this study relates to the less amount of lipid and to the hair of perm treated once accordingly, wherein several physical properties, preferably comprise roughness and tensile strength, present a novel concept of the intrinsic aging hair. The penetration of peptide into the aging hair was leading the extrinsic hair towards more structurally directed a younger hair. In addition to the structural change, the penetration of the peptide enhanced texture and tensile strength of the aging hair. These patterns have been also found in addition of propolis. For the first time, these qualitative studies exhibit that indeed our extrinsic aging hair well describes the anti-aging efficacy as a receptor for a cross-linker and the ingredients of human hair.

• Clean Technology
• /
• v.27 no.3
• /
• pp.232-239
• /
• 2021

In order to develop a novel system named "thermal medium and gas circulation type pyrolysis system," this study was conducted to obtain basic data for process simulation before performing the pyrolysis experiment. Polypropylene (PP) was chosen as model material in the basic pyrolysis experiment instead of waste plastic and fluidized sand (hereinafter referred to as "sand"), and it was used as a heat transfer material in the "thermal medium and gas circulation type pyrolysis system." Ni was impregnated as an active catalyst on the sand to promote catalytic pyrolysis. The basic physical properties of PP were analyzed using a thermogravimetric analyzer, and pyrolysis was performed at 600 ℃ in an N₂ atmosphere to produce liquid oil. The distribution of the carbon number of the liquid oil generated through the catalytic pyrolysis reaction was analyzed using GC/MS. We investigated the effects of varying the pyrolysis space velocity and catalyst amount on the yield of liquid oil and the carbon number distribution of the liquid oil. Using Ni/sand, the yield of liquid oil was increased except with the pyrolysis condition of 10 wt% Ni/sand at a space velocity of 30,000 h^-1, and the composition of C₆ ~ C₁₂ hydrocarbons increased. With increases in the space velocity, higher yields of liquid oil were obtained, but the composition of C₆ ~ C₁₂ hydrocarbons was reduced. With 1 wt% Ni/sand, the oil yield obtained was greater than that obtained with 10 wt% Ni/sand. In summary, when 1 wt% Ni/sand was used at a space velocity of 10,000 h^-1, the oil yield was 60.99 wt% and the composition of C₆ ~ C₁₂ hydrocarbons was highest at 42.06 area%.

• The Mathematical Education
• /
• v.62 no.3
• /
• pp.435-455
• /
• 2023

This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.1-23
• /
• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.

• Tuberculosis and Respiratory Diseases
• /
• v.58 no.1
• /
• pp.31-42
• /
• 2005

Background : Peroxiredoxins (Prxs) are a relatively newly recognized, novel family of peroxidases that reduce $H_2O_2$ and alkylhydroperoxide into water and alcohol, respectively. There are 6 known isoforms of Prxs present in human cells. Normally, Prxs exist in a head-to-tail homodimeric state in a reduced form. However, in the presence of excess $H_2O_2$, it can be oxidized on its catalytically active cysteine site into inactive oxidized forms. This study surveyed the types of the Prx isoforms present in the pulmonary epithelial, macrophage, endothelial, and other cell lines and observed their response to oxidative stress. Methods : This study examined the effect of exogenous, excess $H_2O_2$ on the Prxs of established cell lines originating from the pulmonary epithelium, macrophages, and other cell lines, which are known to be exposed to high oxygen partial pressures or are believed to be subject to frequent oxidative stress, using non-reducing SDS polyacrylamide electrophoresis (PAGE) and 2 dimensional electrophoresis. Result : The addition of excess $H_2O_2$ to the culture media of the various cell-lines caused the immediate inactivation of Prxs, as evidenced by their inability to form dimers by a disulfide cross linkage. This was detected as a subsequent shift to its monomeric forms on the non-reducing SDS PAGE. These findings were further confirmed by 2 dimensional electrophoresis and immunoblot analysis by a shift toward a more acidic isoelectric point (pI). However, the subsequent reappearance of the dimeric Prxs with a comparable, corresponding decrease in the monomeric bands was noted on the non-reducing SDS PAGE as early as 30 minutes after the $H_2O_2$ treatment suggesting regeneration after oxidation. The regenerated dimers can again be converted to the inactivated form by a repeated $H_2O_2$ treatment, indicating that the protein is still catalytically active. The recovery of Prxs to the original dimeric state was not inhibited by a pre-treatment with cycloheximide, nor by a pretreatment with inhibitors of protein synthesis, which suggests that the reappearance of dimers occurs via a regeneration process rather than via the de novo synthesis of the active protein. Conclusion : The cells, in general, appeared to be equipped with an established system for regenerating inactivated Prxs, and this system may function as a molecular "on-off switch" in various oxidative signal transduction processes. The same mechanisms might applicable other proteins associated with signal transduction where the active catalytic site cysteines exist.