• Journal of Ginseng Research
• /
• v.45 no.6
• /
• pp.734-743
• /
• 2021

Background: The underlying mechanisms of the potential tumor-suppressive effects of ginsenoside Rh2 are complex. N6-methyladenosine (m6A) RNA methylation is usually dysregulated in cancer. This study explored the regulatory effect of ginsenoside Rh2 on m6A RNA methylation in cancer. Methods: m6A RNA quantification and gene-specific m6A RIP-qPCR assays were applied to assess total and gene-specific m6A RNA levels. Co-immunoprecipitation, fractionation western blotting, and immunofluorescence staining were performed to detect protein interactions and distribution. QRT-PCR, dual-luciferase, and ChIP-qPCR assays were conducted to check the transcriptional regulation. Results: Ginsenoside Rh2 reduces m6A RNA methylation and KIF26B expression in a dose-dependent manner in some cancers. KIF26B interacts with ZC3H13 and CBLL1 in the cytoplasm of cancer cells and enhances their nuclear distribution. KIF26B inhibition reduces m6A RNA methylation level in cancer cells. SRF bound to the KIF26B promoter and activated its transcription. SRF mRNA m6A abundance significantly decreased upon KIF26B silencing. SRF knockdown suppressed cancer cell proliferation and growth both in vitro and in vivo, the effect of which was partly rescued by KIF26B overexpression. Conclusion: ginsenoside Rh2 reduces m6A RNA methylation via downregulating KIF26B expression in some cancer cells. KIF26B elevates m6A RNA methylation via enhancing ZC3H13/CBLL1 nuclear localization. KIF26B-SRF forms a positive feedback loop facilitating tumor growth.

• Metals and materials international
• /
• v.24 no.6
• /
• pp.1193-1201
• /
• 2018

Dilatometry is a useful technique to obtain experimental data concerning transformation. In this paper, a dilation conversional model was established to calculate carbides fraction in AISI H13 hot-work tool steel based on the measured length changes. After carbides precipitation, the alloy contents in the matrix changed. In the usual models, the content of carbon atoms after precipitation is considered as the only element that affects the lattice constant and the content of the alloy elements such as Cr, Mo, Mn, V are often ignored. In the model introduced in this paper, the alloying elements (Cr, Mo, Mn, V) changes caused by carbides precipitation are incorporated. The carbides were identified using scanning electron microscope and transmission electron microscope. The relationship between lattice constant of carbides and temperature are measured by high-temperature X-ray diffraction. The results indicate that the carbides observed in all specimens cooled at different rates are V-rich MC and Cr-rich $M_{23}C_6$, and most of them are V-rich MC, only very few are Cr-rich $M_{23}C_6$. The model including the effects of substitutional alloying elements shows a good improvement on carbides fraction predictions. In addition, lower cooling rate advances the carbides precipitation for AISI H13 specimens. The results between experiments and mathematical model agree well.

• Journal of Convergence for Information Technology
• /
• v.9 no.8
• /
• pp.110-122
• /
• 2019

IT innovation, cultural revolution based on smart and social networks diversified sharing economy services. Due to the rising of business utilizing the sharing economy concept, it is important to better understand the motivational factors that drive and deterrent sharing economy services in the marketplace. Based on responses from 809 adult users, 3 drivers and 2 deterrents affecting intention to use of sharing economy services were identified. Then this study categorized sharing economy services as three types of segments based on consumer perceptions and subjectivity, and analyzed differencies of perceptions on motivational factors between groups. As a result, redistribution market group has shown meaningful different average scores on economic benefit, sustainability and social risk with other groups. Based on the empirical evidence, this study suggests several propositions for future studies and implications for sharing economy businesses on how to formulate optical strategies and manage users.

• Advances in nano research
• /
• v.15 no.4
• /
• pp.355-366
• /
• 2023

Biological corrosion, a crucial aspect of metal degradation, has received limited attention despite its significance. It involves the deterioration of metals due to corrosion processes influenced by living organisms, including bacteria. Soil represents a substantial threat to pipeline corrosion as it contains chemical and microbial factors that cause severe damage to water, oil, and gas transmission projects. To combat fouling and corrosion, corrosion inhibitors are commonly used; however, their production often involves expensive and hazardous chemicals. Consequently, researchers are exploring natural and eco-friendly alternatives, specifically nano-sized products, as potent corrosion inhibitors. This study aims to environmentally synthesize silver nanoparticles using an extract from Lagoecia cuminoides L and evaluate their effectiveness in preventing biological corrosion of buried pipes in soil. The optimal experimental conditions were determined as follows: a volume of 4 ml for the extract, a volume of 4 ml for silver nitrate (AgNO3), pH 9, a duration of 60 minutes, and a temperature of 60 degrees Celsius. Analysis using transmission electron microscopy confirmed the formation of nanoparticles with an average size of approximately 28 nm, while X-ray diffraction patterns exhibited suitable peak intensities. By employing the Scherer equation, the average particle size was estimated to be around 30 nm. Furthermore, antibacterial studies revealed the potent antibacterial activity of the synthesized silver nanoparticles against both aerobic and anaerobic bacteria. This property effectively mitigates the biological corrosion caused by bacteria in steel pipes buried in soil.

• Journal of Advanced Technology Convergence
• /
• v.2 no.4
• /
• pp.43-48
• /
• 2023

Globally, there is a collaborative effort to achieve global carbon neutrality in response to climate change. In the case of South Korea, greenhouse gas emissions are rapidly increasing, presenting an urgent situation that requires resolution. In this context, this study developed a thermal energy collection device named a 'steam trap' and created an AI model capable of predicting future electricity usage by collecting energy usage data through steam traps. The average accuracy of electricity usage prediction with this AI model was 96.7%, demonstrating high precision. Consequently, the AI model enables the prediction and management of days with high electricity consumption and identifies which facilities contribute to elevated power usage. Future research aims to optimize energy consumption efficiency through efficient equipment operation using anomaly detection in steam traps and standardizing energy management systems, with the ultimate goal of reducing greenhouse gas emissions.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.47 no.2
• /
• pp.155-167
• /
• 2024

Distribution and logistics industries contribute some of the biggest GDP(gross domestic product) in South Korea and the number of related companies are quarter of the total number of industries in the country. The number of retail tech companies are quickly increased due to the acceleration of the online and untact shopping trend. Furthermore, major distribution and logistics companies try to achieve integrated data management with the fulfillment process. In contrast, small and medium distribution companies still lack of the capacity and ability to develop digital innovation and smartization. Therefore, in this paper, a deep learning-based demand forecasting & recommendation model is proposed to improve business competitiveness. The proposed model is developed based on real sales transaction data to predict future demand for each product. The proposed model consists of six deep learning models, which are MLP(multi-layers perception), CNN(convolution neural network), RNN(recurrent neural network), LSTM(long short term memory), Conv1D-BiLSTM(convolution-long short term memory) for demand forecasting and collaborative filtering for the recommendation. Each model provides the best prediction result for each product and recommendation model can recommend best sales product among companies own sales list as well as competitor's item list. The proposed demand forecasting model is expected to improve the competitiveness of the small and medium-sized distribution and logistics industry.

• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.17
• /
• pp.8003-8008
• /
• 2015

Background: The aim of this study was to investigate whether family history of cancer is associated with head and neck cancer risk in a Chinese population. Materials and Methods: This case-control study included 921 cases and 806 controls. Recruitment was from December 2010 to January 2015 in eight centers in East Asia. Controls were matched to cases with reference to sex, 5-year age group, ethnicity, and residence area at each of the centers. Results: We observed an increased risk of head and neck cancer due to first degree family history of head and neck cancer, but after adjustment for tobacco smoking, alcohol drinking and betel quid chewing the association was no longer apparent. The adjusted OR were 1.10 (95% CI=0.80-1.50) for family history of tobacco-related cancer and 0.96 (95%CI=0.75-1.24) for family history of any cancer with adjustment for tobacco, betel quid and alcohol habits. The ORs for having a first-degree relative with HNC were higher in all tobacco/alcohol subgroups. Conclusions: We did not observe a strong association between family history of head and neck cancer and head and neck cancer risk after taking into account lifestyle factors. Our study suggests that an increased risk due to family history of head and neck cancer may be due to shared risk factors. Further studies may be needed to assess the lifestyle factors of the relatives.

• Asia pacific journal of information systems
• /
• v.22 no.4
• /
• pp.75-99
• /
• 2012

Innovation can come from inside or outside organizations. Recently, organizations have begun turning to external knowledge more often, through various forms of collective intelligence (CI) as collaborative platform to solve complex problems. Several factors facilitate this CI utilization phenomenon. First, with the rapid development of Internet and social media, numerous web applications have become available to millions of the Internet users over the past few decades. Web 2.0 and social media have become innovative web applications that provide an environment for human social interaction and collaboration. Second, the diffusion of simple and easy-to-use technologies that enable users to interact and design web applications without programming skills have led to vast, previously unknown amounts of user-generated content. Finally, the Internet has enabled communities to connect and collaborate, creating a virtual world of CI. In this study, web enabled CI is defined as a composed ability of individuals who are acting as a single cognitive unit to achieve common goals, think reasonably, solve problems, make decisions, carry out complex tasks, and develop creative ideas collectively through participation and collaboration on the web. Although CI plays a critical role in organizational innovation and collaboration, the dubious quality of CI is still problem that is difficult to solve. In general, the quality level of content collected from the crowd is lower than that from professionals. Thus, it is important to identify determinants of CI quality and to analyze the relationship between CI quality and its usefulness. However, there is a lack of empirical study on the quality factors of web-enabled CI. There exist a variety of web enabled CI sites such as Threadless, iStockphoto or InnoCentive, Wikipedia, and Youtube. One of the most successful forms of web-enabled CI is the Wikipedia online encyclopedia, accessible all over the world. Another one example is Naver KnowledgeiN, a typical and popular CI site offering question and answer (Q&A) services. It is necessary to study whether or not different types of CI have a different effect on CI quality and its usefulness. Thus, the purpose of this paper is to answer to following research questions: ${\bullet}$ What determinants are important to CI quality? ${\bullet}$ What is the relationship between CI quality factors and the usefulness of web-enabled CI? ${\bullet}$ Does CI type have a moderating effect on the relationship between CI quality, its determinants, and CI usefulness? Online survey using Google Docs with email and Kakao Talk was conducted for collecting data from Wikipedia and Naver KnowledgeiN users. A totoal of 490 valid responses were collected, where users of Wikipedia were 220 while users of Naver KnowledgeiN were 270. Expertise of contributors, community size, and diversity of contributors were identified as core determinants of perceived CI quality. Perceived CI quality has significantly influenced perceived CI usefulness from a user's perspective. For improving CI quality, it is believed that organizations should ensure proper crowd size, facilitate CI contributors' diversity and attract as many expert contributors as possible. Hypotheses that CI type plays a role of moderator were partially supported. First, the relationship between expertise of contributors and perceived CI quality was different according to CI type. The expertise of contributors played a more important role in CI quality in the case of Q&A services such as Knowledge iN compared to wiki services such as Wikipedia. This implies that Q&A service requires more expertise and experiences in particular areas rather than the case of Wiki service to improve service quality. Second, the relationship between community size and perceived CI quality was different according to CI type. The community size has a greater effect on CI quality in case of Wiki service than that of Q&A service. The number of contributors in Wikipeda is important because Wiki is an encyclopedia service which is edited and revised repeatedly from many contributors while the answer given in Naver Knowledge iN can not be corrected by others. Finally, CI quality has a greater effect on its usefulness in case of Wiki service rather than Q&A service. In this paper, we suggested implications for practitioners and theorists. Organizations offering services based on collective intelligence try to improve expertise of contributeros, to increase the number of contributors, and to facilitate participation of various contributors.

• Journal of Technology Innovation
• /
• v.31 no.3
• /
• pp.39-73
• /
• 2023

The field of Management of Technology(MOT) emerged in response to the need for research management within U.S. public research institutions during the 1960s. Since its inception, it has proliferated significantly, being practiced in more than 809 institutions globally and over 19 institutions in Korea, encompassing both research and educational endeavors. Particularly noteworthy is the substantial investment of government resources, primarily channeled through the Ministry of Industry since 2007, which has expeditiously established a comprehensive framework for cultivating graduate-level MOT expertise, marked by both quantitative and qualitative advancements. The educational curriculum in the realm of Korean MOT deviates from foreign counterparts through distinctive pathways, exemplified by its emphasis on industry practice-oriented educational programs, standardization and isomorphism across different schools, as well as its interconnectedness with proximate academic disciplines. This research systematically undertakes an analysis of the curriculum in Korean MOT graduate schools, thereby ascertaining its intrinsic identity and distinct attributes. In this endeavor, a comprehensive examination of eleven principal MOT textbooks(three in Korean and eight in English) is conducted to delineate the primary content of the curriculum across seven thematic domains. Moreover, the study deliberates on its differentiation from neighboring academic disciplines and the definitional attributes of MOT. Subsequently, this analysis also encompasses nine Korean MOT graduate programs, projecting the seven thematic domains onto their respective curricula. The findings illuminate that within the context of Korean graduate programs, a substantial proportion of the curriculum, amounting to 62.5%, is dedicated to facets encompassing the operational aspects of technology management within corporate contexts, technology management specific to varying industries and technologies, and collaborative endeavors between academia and industry in the form of projects and seminars. Evidently, the Korean approach to technology management education is notably geared towards the cultivation of adept practitioners capable of executing technology management functions at a mid-tier managerial level, aligned with the exigencies of regional industries. Grounded in the analysis of technology management curricula, this study extrapolates implications for the future trajectory of MOT education in Korea, encompassing a consideration of the stages of industrial development. It underscores the necessity to augment the educational curricula pertaining conceptual foundation of technology and innovation, strategic perspectives of technology and innovation, and the socio-economic context of technology management.

• Journal of Microbiology and Biotechnology
• /
• v.27 no.12
• /
• pp.2119-2128
• /
• 2017

Citrinin (CIT) is a toxic secondary metabolite produced by fungi belonging to the Penicillium, Aspergillus, and Monascus spp. This toxin has been detected in many agricultural products. In this study, a strain Y3 with the ability to eliminate CIT was screened and identified as Cryptococcus podzolicus, based on the sequence analysis of the internal transcribed spacer region. Neither uptake of CIT by cells nor adsorption by cell wall was involved in CIT elimination by Cryptococcus podzolicus Y3. The extracellular metabolites of Cryptococcus podzolicus Y3 stimulated by CIT or not showed no degradation for CIT. It indicated that CIT elimination was attributed to the degradation of intracellular enzyme(s). The degradation of CIT by C. podzolicus Y3 was dependent on the type of media, yeast concentration, temperature, pH, and initial concentration of CIT. Most of the CIT was degraded by C. podzolicus Y3 in NYDB medium at 42 h but not in PDB medium. The degradation rate of CIT was the highest (94%) when the concentration of C. podzolicus Y3 was $1{\times}10^8cells/ml$. The quantity of CIT degradation was highest at $28^{\circ}C$, and there was no degradation observed at 3$5^{\circ}C$. The study also showed that acidic condition (pH 4.0) was the most favorable for CIT degradation by C. podzolicus Y3. The degradation rate of CIT increased to 98% as the concentration of CIT was increased to $20{\mu}g/ml$. The toxicity of CIT degradation product(s) toward HEK293 was much lower than that of CIT.