• Journal of The Korean Society of Inherited Metabolic disease
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• v.24 no.1
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• pp.1-9
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• 2024

Mitochondrial Encephalomyopathy with Lactic Acidosis and Stroke-like episode (MELAS) is a rare maternally inherited disorder primarily caused by mutations in mitochondrial DNA, notably the m.3243A>G mutation in the MT-TL1 gene. This mutation impairs mitochondrial function crucial for cellular energy production, particularly in high-energy-demanding organs such as the brain and muscles. MELAS manifests as recurrent stroke-like episodes, seizures, diabetes mellitus, cardiomyopathy, and other multisystemic symptoms that are often present in childhood. The diagnosis combines genetic testing, clinical evaluation, and neuroimaging, with elevated lactate levels and characteristic magnetic resonance imaging (MRI) findings as key indicators. Treatment focuses on symptomatic management and enhancement of mitochondrial function through L-arginine, coenzyme Q10, high-dose vitamins, and taurine supplementation. Studies have identified additional genetic variants linked to MELAS, including mutations in POLG and other mitochondrial genes, further complicating the genetic landscape. Emerging therapies, particularly gene therapy and mitochondria-targeting drugs, offer promising avenues for addressing the underlying genetic defects and improving mitochondrial functioning. Furthermore, ongoing studies continue to enhance our understanding and management of MELAS, with the aim of reducing its burden and improving patient outcomes and quality of life. This review summarizes the current knowledge on the genetics, clinical features, diagnosis, and treatment of MELAS, highlighting the latest advancements and future directions for therapeutic interventions.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.101-123
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• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.

• Journal of Plant Biotechnology
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• v.29 no.4
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• pp.265-275
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• 2002

Flavonoid biosynthesis is one of the most extensively studied areas in the secondary metabolism. Due to the study of flavonoid metabolism in diverse plant system, the pathways become the best characterized secondary metabolites and can be excellent targets for metabolic engineering. These flavonoid-derived secondary metabolites have been considerably divergent functional roles: floral pigment, anticancer, antiviral, antitoxin, and hepatoprotective. Three species have been significant for elucidating the flavonoid metabolism and isolating the genes controlling the flavonoid genes: maize (Zea mays), snapdragon (Antirrhinum majus) and petunia (Prtunia hybrida). Recently, many genes involved in biosynthesis of flavonoid have been isolated and characterized using mutation and recombinant DNA technologies including transposon tagging and T-DNA tagging which are novel approaches for the discovery of uncharacterized genes. Metabolic engineering of flavonoid biosynthesis was approached by sense or antisense manipulation of the genes related with flavonoid pathway, or by modified expression of regulatory genes. So, the use of a variety of experimental tools and metabolic engineering facilitated the characterization of the flavonoid metabolism. Here we review recent progresses in flavonoid metabolism: confirmation of genes, metabolic engineering, and applications in the industrial use.

• The Korean Journal of Air & Space Law and Policy
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• v.28 no.1
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• pp.3-54
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• 2013

Nowadays, major advanced countries in aviation technology are putting their effort to develop commercial and civil Unmanned Aircraft System(UAS) due to its highly promising market demand in the future. The market scale of commercial and civil UAS is expected to increase up to approximately 8.8 billon U.S. dollars by the year 2020. The usage of commercial and civil UAS covers various areas such as remote sensing, relaying communications, pollution monitoring, fire detection, aerial reconnaissance and photography, coastline monitoring, traffic monitoring and control, disaster control, search and rescue, etc. With the introduction of UAS, changes need to be made on current Air Traffic Management Systems which are focused mainly manned aircrafts to support the operation of UAS. Accordingly, the legislation for the UAS operation should be followed. Currently, ICAO's Unmanned Aircraft System Study Group(UASSG) is leading the standardization process of legislation for UAS operation internationally. However, some advanced countries such as United States, United Kingdom, Australia have adopted its own legislation. Among these countries, United States is most forth going with President Obama signing a bill to integrate UAS into U.S. national airspace by 2015. In case of Korea, legislation for the unmanned aircraft system is just in the beginning stage. There are no regulations regarding the operation of unmanned aircraft in Korea's domestic aviation law except some clauses regarding definition and permission of the unmanned aircraft flight. However, the unmanned aircrafts are currently being used in military and under development for commercial use. In addition, the Ministry of Land, Infrastructure and Transport has a ambitious plan to develop commercial and civil UAS as Korea's most competitive area in aircraft production and export. Thus, Korea is in need of the legislation for the UAS operation domestically. In this regards, I personally think that Korea's domestic legislation for UAS operation will be enacted focusing on following 12 areas : (1)use of airspace, (2)licenses of personnel, (3)certification of airworthiness, (4)definition, (5)classification, (6)equipments and documents, (7)communication, (8)rules of air, (9)training, (10)security, (11)insurance, (12)others. Im parallel with enacting domestic legislation, korea should contribute to the development of international standards for UAS operation by actively participating ICAO's UASSG.

• Clean Technology
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• v.10 no.2
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• pp.73-87
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• 2004

In most of industrial fields, cleaning is employed for removing soils on their products or parts. Halogenated cleaning agents such as CFC-113, 1,1,1-TCE(1,1,1-trichloroethane), MC(methylene chloride) and TCE (trichloroethylene) have been used as cleaning ones in most of companies in the world since their excellent performance of cleaning ability and good material compatibility. However, CFC-113 and 1,1,1-TCE which are ozone destruction substances are not used any more in the advanced countries because of the which are ozone destruction substances are not used any more in the advanced countries because of the Montreal protocol. MC and TCE are now used restrictively at small part of industrial fields in most of countries since they are known to be hazardous or carcinogenic materials. Thus, it is indispensible that the alternative cleaning agents which are environmental-friendly and safe, and show good cleaning ability should be developed or utilized for replacement of the halogenated cleaning agents. Aqueous/semi-aqueous cleaning agents are evaluated to be promising alternative ones among various alternatives in environmental and economical view point. In this study, commercially available 12 aqueous and 6 semi-aqueous cleaning agents were selected and their physical properties, cleaning abilities, rinsing abilities and recycling of contaminated rinse water were measured and analyzed. Aqueous cleaning agents with higher wetting index showed better cleaning ability compared with those with lower wetting index. However wetting index did not have any correlation with cleaning ability in semi-aqueous cleaning agents. It was observed that soil concentration in aqueous and semi-aqueous cleaning agents should be maintained below the certain concentrations which depend on types of clearing agents. More than 70% soils in contaminated rinse water by some of aqueous and semi-aqueous clearing agents could be separated by simple settling method. This means that some cleaning agents with high oil-water separation efficiency will be effiective for recycling oil-contaminated rinse water. It was found that contaminated rinse water with aqueous agents was purified easiy by ultrafiltration method with PAN membrane of 30 kDa.

• 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.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.83-105
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• 2016

Measuring an individual's subjective wellbeing in an accurate, unobtrusive, and cost-effective manner is a core success factor of the wellbeing support system, which is a type of medical IT service. However, measurements with a self-report questionnaire and wearable sensors are cost-intensive and obtrusive when the wellbeing support system should be running in real-time, despite being very accurate. Recently, reasoning the state of subjective wellbeing with conventional sentiment analysis and unstructured data has been proposed as an alternative to resolve the drawbacks of the self-report questionnaire and wearable sensors. However, this approach does not consider contextual polarity, which results in lower measurement accuracy. Moreover, there is no sentimental word net or ontology for the subjective wellbeing area. Hence, this paper proposes a method to extract keywords and their contextual polarity representing the subjective wellbeing state from the unstructured text in online websites in order to improve the reasoning accuracy of the sentiment analysis. The proposed method is as follows. First, a set of general sentimental words is proposed. SentiWordNet was adopted; this is the most widely used dictionary and contains about 100,000 words such as nouns, verbs, adjectives, and adverbs with polarities from -1.0 (extremely negative) to 1.0 (extremely positive). Second, corpora on subjective wellbeing (SWB corpora) were obtained by crawling online text. A survey was conducted to prepare a learning dataset that includes an individual's opinion and the level of self-report wellness, such as stress and depression. The participants were asked to respond with their feelings about online news on two topics. Next, three data sources were extracted from the SWB corpora: demographic information, psychographic information, and the structural characteristics of the text (e.g., the number of words used in the text, simple statistics on the special characters used). These were considered to adjust the level of a specific SWB. Finally, a set of reasoning rules was generated for each wellbeing factor to estimate the SWB of an individual based on the text written by the individual. The experimental results suggested that using contextual polarity for each SWB factor (e.g., stress, depression) significantly improved the estimation accuracy compared to conventional sentiment analysis methods incorporating SentiWordNet. Even though literature is available on Korean sentiment analysis, such studies only used only a limited set of sentimental words. Due to the small number of words, many sentences are overlooked and ignored when estimating the level of sentiment. However, the proposed method can identify multiple sentiment-neutral words as sentiment words in the context of a specific SWB factor. The results also suggest that a specific type of senti-word dictionary containing contextual polarity needs to be constructed along with a dictionary based on common sense such as SenticNet. These efforts will enrich and enlarge the application area of sentic computing. The study is helpful to practitioners and managers of wellness services in that a couple of characteristics of unstructured text have been identified for improving SWB. Consistent with the literature, the results showed that the gender and age affect the SWB state when the individual is exposed to an identical queue from the online text. In addition, the length of the textual response and usage pattern of special characters were found to indicate the individual's SWB. These imply that better SWB measurement should involve collecting the textual structure and the individual's demographic conditions. In the future, the proposed method should be improved by automated identification of the contextual polarity in order to enlarge the vocabulary in a cost-effective manner.

• Geophysics and Geophysical Exploration
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• v.9 no.1
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• pp.67-72
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• 2006

Injection of $CO_2$ into underground saline formations, due to their large storage capacity, is probably the most promising approach for the reduction of $CO_2$ emissions into the atmosphere. $CO_2$ storage must be carefully planned and monitored to ensure that the $CO_2$ is safely retained in the formation for periods of at least thousands of years. Seismic methods, particularly for offshore reservoirs, are the primary tool for monitoring the injection process and distribution of $CO_2$ in the reservoir over time provided that reservoir properties are favourable. Seismic methods are equally essential for the characterisation of a potential trap, determining the reservoir properties, and estimating its capacity. Hence, an assessment of the change in seismic response to $CO_2$ storage needs to be carried out at a very early stage. This must be revisited at later stages, to assess potential changes in seismic response arising from changes in fluid properties or mineral composition that may arise from chemical interactions between the host rock and the $CO_2$. Thus, carefully structured modelling of the seismic response changes caused by injection of $CO_2$ into a reservoir over time helps in the design of a long-term monitoring program. For that purpose we have developed a Graphical User Interface (GUI) driven rock physics simulator, designed to model both short and long-term 4D seismic responses to injected $CO_2$. The application incorporates $CO_2$ phase changes, local pressure and temperature changes. chemical reactions and mineral precipitation. By incorporating anisotropic Gassmann equations into the simulator, the seismic response of faults and fractures reactivated by $CO_2$ can also be predicted. We show field examples (potential $CO_2$ sequestration sites offshore and onshore) where we have tested our rock physics simulator. 4D seismic responses are modelled to help design the monitoring program.

• The Korean Journal of Air & Space Law and Policy
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• v.30 no.2
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• pp.3-36
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• 2015

As of end of 2014, the population engaging in aviation activities for leisure has reached approximately 13 million, where approximately 356 cases involve a general aircraft, 200 cases involve light aircraft, and 636 cases involve an ULM. The industry for leisure has become a very promising industry in line with rapidly rising living standards which are expected to further increase in the future. The demand for such services is expected to increase over time. The purpose of this paper is to review the development and site selection of airfields in anticipation of these developments in the industry. While the government also has experience in the review of airfield location and candidate sites, it is not the government that carries out the actual construction. As such, the feasibility of the site needs to be verified in terms of actual construction. This study identified factors for Site Selection of factors through a review of related documents and existing research reports. A questionnaire was also used to collect the views of experts in the field, which was then analyzed. The Research model was confirmed in the layered form for an AHP analysis. The factors for Site Selection were identified as the technical / operational factors and economic / political elements for a two-stage configuration. The third step consisted of technical and operational elements. The final step is was constructed a total of 11 elements (weather, surface conditions, obstacle limitation surface, airspace conditions, operating procedures, noise problems, environmental issues, availability of facilities, construction and investment costs, contribution to the local economy, accessibility, demand / the proximity of demand). The surveys are conducted for more than 10 General and light aircraft pilots, professionals, and instructor. The analysis results showed a higher level in the technical / operating elements (73.2%) in the first step, while the next step sawa higher level of the operational elements (30.9%) than the other. The factors for Site Selection were any particular elements did not appear high, the weather conditions (17.5%), noise problems (19.8%), the proximity of demand (6%), accessibility (5.7%), environmental issues (11.1%), availability of facilities (8%), airspace conditions (7.9%), obstacle limitation surface (12%), construction and investment costs (4.2%) and to operating procedures (4.9%), contribution to the local economy (3.8%).

• Resources Recycling
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• v.29 no.2
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• pp.55-61
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• 2020

Selective catalytic reduction (SCR) has been a promising technology to reduce the air pollution caused by nitrogen oxides (NOx) in several industries. The consumption of SCR catalysts increases every year as technology evolves, however those have a limited lifespan and usually end up in landfills after they deactivate. Currently, the most widely used catalyst for and stationary applications is V₂O₅-WO₃/TiO₂ which can contain around 50% wt V₂O₅ and 7-10% wt of WO₃. The vast uses for both vanadium and tungsten and the worldwide interest in recycling methods that allow for the extraction of metals from secondary sources represent the major motivation for this research. The extraction time, pH dependency, extraction concentration studies were carried out using Aliquat 336 in exxol D80 as the extractant. It was determined that to optimize the extraction of both metals 30min of contact time with an organic phase containing 0.5mol/L of Aliquat 336 are needed at a slightly acidic pH (~5.0). In addition, counter McCabe-Thiele studies allowed us to determine that one stage is necessary for the removal of 99% of vanadium while 2 stages are necessary for the extraction of tungsten and counter current simulations proved that the theoretical approach was correct.