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Melanogenesis regulatory constituents from Premna serratifolia wood collected in Myanmar

  • WOO, SO-YEUN
    • Proceedings of the Plant Resources Society of Korea Conference
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    • 2019.04a
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    • pp.21-22
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    • 2019
  • Melanin is a mixture of pigmented biopolymers synthesized by epidermal melanocytes that determine the skin, eye, and hair colors. Melanocytes produce two different kinds of melanin, eumelanin (dark brown/black insoluble pigments found in dark skin and dark hair and pheomelanin (lighter red/yellow). The biological role of melanin is to prevent skin damage by ultraviolet (UV) radiation. However, the overproduction or deficiency of melanin synthesis could lead to serious dermatological problems, which include melasma, melanoderma, lentigo, and vitiligo. Therefore, regulating melanin production is important to prevent the pigmentation disorders. Myanmar has a rich in natural resources. However, the chemical constituents of these natural resources in Myanmar have not been fully investigated. In the effort to search for compounds with anti-melanin deposition activity from Myanmar natural resources, five plants were collected in Myanmar. Extracts of these collected five plants were tested for anti-melanin deposition activity against a mouse melanoma cell line (B16-F10) induced with ${\alpha}$-melanocyte-stimulating hormone (${\alpha}$-MSH) and 3-isobutyl-1-methylxanthine (IBMX), and their anti-melanin deposition activities were compared with the positive control, arbutin. Among the tested extracts, the CHCl3 extracts of the Premna serratifolia (syn: P. integrifolia) wood showed anti-melanin deposition activities with IC50 values of $81.3{\mu}g/mL$. Hence, this study aims to identify secondary metabolites with anti-melanin deposition activity from P. serratifolia wood of Myanmar. P. serratifolia belongs to the Verbenaceae family and is widely distributed in near western sea coast from South Asia to South East Asia, which include India, Malaysia, Vietnam, Cambodia, and Sri Lanka. People in Tanintharyi region located in the southern part of Myanmar utilize the P. serratifolia, Sperethusa crenulata, Naringi crenulata, and Limonia acidissima as Thanaka, traditional cosmetics in Myanmar. Thanaka is applied in the form of paste onto skins to make it smooth and clear, as well as to prevent wrinkles, skin aging, excessive facial oil, pimples, blackheads, and whiteheads. However, the chemical constituents responsible for their cosmetic properties are yet to be identified. Moreover, the chemical constituents of P. serratifolia was almost uncharacterized. Investigation of the P. serratifolia chemical constituents is thus an attractive endeavor to discover new anti-melanin deposition active compounds. The investigation of the chemical constituents of the active CHCl3 extract of P. serratifolia led to isolation of four new lignoids, premnan A (1), premnan B (2), taungtangyiol C (3), and 7,9-dihydroxydolichanthin B (4), together with premnan C (5) (assumed to be an artifact), one natural newlignoid,(3R,4S)-4-(1,3-benzodioxol-5-ylcarbonyl)-3-[(R)-1-(1,3-benzo dioxol-5-yl)-1-hydroxy methyl]tetrahydro-2-furanone (6), and five known compounds (7-11)1,2). The structures of all isolated compounds were determined on the basis of their spectroscopic data and by comparison with the reported literatures. The absolute configurations of 1-3 and 5 were also determined by optical rotation and circular dichroism (CD) data analyses1). The anti-melanin deposition activities of all the isolated compounds were evaluated against B16-F10 cell line. 7,9-Dihydroxydolichanthin B (4) and ($2{\alpha},3{\alpha}$)-olean-12-en-28-oic acid (11) showed strong anti-melanin deposition activities with IC50 values of 18.4 and $11.2{\mu}M$, respectively, without cytotoxicity2). On the other hand, compounds 1-3, 5, and 7 showed melanogenesis enhancing activities1). To better understand their anti-melanin deposition mechanism, the effects of 4 and 11 on tyrosinase activities were investigated. The assay indicated that compounds 4 and 11 did not inhibit tyrosinase. Furthermore, we also examined the mRNA expression of microphthalmia-associated transcription factor (MITF), tyrosinase (TYR), tyrosinase-related protein-1 (TRP-1), and tyrosinase-related protein-2 (TRP-2). Compounds 4 and 11 down-regulated the expression of Tyr and Mitf mRNAs, respectively. Although the P. serratifolia wood has been used as traditional cosmetics in Myanmar for centuries, there are no scientific evidences to support its effectiveness as cosmetics. Investigation of the anti-melanin deposition activity of the chemical constituents of P. serratifolia thus provided insight into the effectiveness of the P. serratifolia wood as a cosmetic agent.

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Research Trend Analysis Using Bibliographic Information and Citations of Cloud Computing Articles: Application of Social Network Analysis (클라우드 컴퓨팅 관련 논문의 서지정보 및 인용정보를 활용한 연구 동향 분석: 사회 네트워크 분석의 활용)

  • Kim, Dongsung;Kim, Jongwoo
    • Journal of Intelligence and Information Systems
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    • v.20 no.1
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    • pp.195-211
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    • 2014
  • Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

An Intelligent Decision Support System for Selecting Promising Technologies for R&D based on Time-series Patent Analysis (R&D 기술 선정을 위한 시계열 특허 분석 기반 지능형 의사결정지원시스템)

  • Lee, Choongseok;Lee, Suk Joo;Choi, Byounggu
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.79-96
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    • 2012
  • As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

The Influence of Store Environment on Service Brand Personality and Repurchase Intention (점포의 물리적 환경이 서비스 브랜드 개성과 재구매의도에 미치는 영향)

  • Kim, Hyoung-Gil;Kim, Jung-Hee;Kim, Youn-Jeong
    • Journal of Global Scholars of Marketing Science
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    • v.17 no.4
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    • pp.141-173
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    • 2007
  • The study examines how the environmental factors of store influence service brand personality and repurchase intention in the service environment. The service industry has been experiencing the intensified competition with the industry's continuous growth and the influence from rapid technological advancement. Under the circumstances, it has become ever more important for the brand competitiveness to be distinctively recognized against competition. A brand needs to be distinguished and differentiated from competing companies because they are all engaged in the similar environment of the service industry. The differentiation of brand achievement has become increasingly important to highlight certain brand functions to include emotional, self-expressive, and symbolic functions since the importance of such functions has been further emphasized in promoting consumption activities. That is the recent role of brand personality that has been emphasized in the service industry. In other words, customers now freely and actively express their personalities or egos in consumption activities, taking an important role in construction of a brand asset. Hence, the study suggests that it is necessary to disperse the recognition and acknowledgement that the maintenance of the existing customers contributes more to boost repurchase intention when it is compared to the efforts to create new customers, particularly in the service industry. Meanwhile, the store itself can offer a unique environment that may influence the consumer's purchase decision. Consumers interact with store environments in the process of,virtually, all household purchase they make (Sarel 1981). Thus, store environments may encourage customers to purchase. The roles that store environments play are to provide informational cues to customers about the store and goods and communicate messages to stimulate consumers' emotions. The store environments differentiate the store from competing stores and build a unique service brand personality. However, the existing studies related to brand in the service industry mostly concentrated on the relationship between the quality of service and customer satisfaction, and they are mostly generalized while the connective studies focused on brand personality. Such approaches show limitations and are insufficient to investigate on the relationship between store environment and brand personality in the service industry. Accordingly, the study intends to identify the level of contribution to the establishment of brand personality made by the store's physical environments that influence on the specific brand characteristics depending on the type of service. The study also intends to identify what kind of relationships with brand personality exists with brand personality while being influenced by store environments. In addition, the study intends to make meaningful suggestions to better direct marketing efforts by identifying whether a brand personality makes a positive influence to induce an intention for repurchase. For this study, the service industry is classified into four categories based on to the characteristics of service: experimental-emotional service, emotional -credible service, credible-functional service, and functional-experimental service. The type of business with the most frequent customer contact is determined for each service type and the enterprise with the highest brand value in each service sector based on the report made by the Korea Management Association. They are designated as the representative of each category. The selected representatives are a fast-food store (experimental-emotional service), a cinema house (emotional-credible service), a bank (credible-functional service), and discount store (functional-experimental service). The survey was conducted for the four selected brands to represent each service category among consumers who are experienced users of the designated stores in Seoul Metropolitan City and Gyeonggi province via written questionnaires in order to verify the suggested assumptions in the study. In particular, the survey adopted 15 scales, which represent each characteristic factor, among the 42 unique characteristics developed by Jennifer Aaker(1997) to assess the brand personality of each service brand. SPSS for Windows Release 12.0 and LISREL were used in the analysis of data verification. The methodology of the structural equation model was used for the study and the pivotal findings are as follows. 1) The environmental factors ware classified as design factors, ambient factors, and social factors. Therefore, the validity of measurement scale of Baker et al. (1994) was proved. 2) The service brand personalities were subdivided as sincerity, excitement, competence, sophistication, and ruggedness, which makes the use of the brand personality scales by Jennifer Aaker(1997) appropriate in the service industry as well. 3) One-way ANOVA analysis on the scales of store environment and service brand personality showed that there exist statistically significant differences in each service category. For example, the social factors were highest in discount stores, while the ambient factors and design factors were highest in fast-food stores. The discount stores were highest in the sincerity and excitement, while the highest point for banks was in the competence and ruggedness, and the highest point for fast-food stores was in the sophistication, The consumers will make a different respond to the physical environment of stores and service brand personality that are inherent to the corresponding service interface. Hence, the customers will make a different decision-making when dealing with different service categories. In this aspect, the relationships of variables in the proposed hypothesis appear to work in a different way depending on the exposed service category. 4) The store environment factors influenced on service brand personalities differently by category of service. The factors of store's physical environment are transferred to a brand and were verified to strengthen service brand personalities. In particular, the level of influence on the service brand personality by physical environment differs depending on service category or dimension, which indicates that there is a need to apply a different style of management to a different service category or dimension. It signifies that there needs to be a brand strategy established in order to positively influence the relationship with consumers by utilizing an appropriate brand personality factor depending on different characteristics by service category or dimension. 5) The service brand personalities influenced on the repurchase intention. Especially, the largest influence was made in the sophistication dimension of service brand personality scale; the unique and characteristically appropriate arrangement of physical environment will make customers stay in the service environment for a long time and will lead to give a positive influence on the repurchase intention. 6) The store environment factors influenced on the repurchase intention. Particularly, the largest influence was made on the social factors of store environment. The most intriguing finding is that the service factor among all other environment factors gives the biggest influence to the repurchase intention in most of all service types except fast-food stores. Such result indicates that the customers pay attention to how much the employees try to provide a quality service when they make an evaluation on the service brand. At the same time, it also indicates that the personal factor is directly transmitted to the construction of brand personality. The employees' attitude and behavior are the determinants to establish a service brand personality in the process of enhancing service interface. Hence, there should be a reinforced search for a method to efficiently manage the service staff who has a direct contact with customers in order to make an affirmative improvement of the customers' brand evaluation at the service interface. The findings suggest several managerial implications. 1) Results from the empirical study indicated that store environment factors have a strong positive impact on a service brand personality. To increase customers' repurchase intention of a service brand, the management is required to effectively manage store environment factors and create a friendly brand personality based on the corresponding service environment. 2) Mangers and researchers must understand and recognize that the store environment elements are important marketing tools, and that brand personality influences on consumers' repurchase intention. Based on such result of the study, a service brand could be utilized as an efficient measure to achieve a differentiation by enforcing the elements that are most influential among all other store environments for each service category. Therefore, brand personality established involving various store environments will further reinforce the relationship with customers through the elevated brand identification of which utilization to induce repurchase decision can be used as an entry barrier. 3) The study identified the store environment as a component of service brand personality for the store's effective communication with consumers. For this, all communication channels should be maintained with consistency and an integrated marketing communication should be executed to efficiently approach to a larger number of customers. Mangers and researchers must find strategies for aligning decisions about store environment elements with the retailers' marketing and store personality objectives. All ambient, design, and social factors need to be orchestrated so that consumers can take an appropriate store personality. In this study, the induced results from the previous studies were extended to the service industry so as to identify the customers' decision making process that leads to repurchase intention and a result similar to those of the previous studies. The findings suggested several theoretical and managerial implications. However, the situation that only one service brand served as the subject of analysis for each service category, and the situation that correlations among store environment elements were not identified, as well as the problem of representation in selection of samples should be considered and supplemented in the future when further studies are conducted. In addition, various antecedents and consequences of brand personality must be looked at in the aspect of the service environment for further research.

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