• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1455-1462
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• 2018

As the interests in eco-friendly energy has increased, the interests in Electric Vehicles(EVs) are increasing as well. Moreover, due to the government's economic support for EVs, penetration level of it has rapidly increased. These sharp increases, however, induce various problems in distribution system, such as voltage/frequency variations, peak demand increasement, demand control, etc. To minimize these possible matters, lots of research have conducted. Nevertheless, most of it assumed extremely important factors, such as numbers and charging patterns of EVs. It inevitably results in errors in their research, and thus make it difficult to prevent the possible matters from EVs. In this paper, therefore, we use actual EVs charging data from KEPCO, and analysis and deduction of it were conducted. The simulations were carried out for four aspect(season, region, purpose).

• Journal of Animal Science and Technology
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• v.47 no.1
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• pp.133-140
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• 2005

The aim of this study was to divide vocalizations of sows into general(GVs) and estrus-related vocalizations( EVs) and to find out their phonetic characteristics. Ten sows(Landrace) were recorded using digital video recorders twice daily(06: 00 - 08 : 00h and 17: 00 - 19 : 00h) during the anestrus and estrus periods. The GVs and EVs were divided based on the shapes of spectrum and spectrogram. The GVs and EVs were identified as 5 and 3 types, respectively. Pitch, formant I, formant 2, and formant 3 between GVs and EVs were not significantly different(P> 0.05), whereas intensity(P < 0.001), duration(P < 0.05), and formant 4(P < 0.01) were significantly different. Three parameter groups(Group I : Formant vector alone, Group II: Formant veetor+ parameters from time signal, Group III: Formant vector+parameters from time signal-parameters eliminated by stepwise discriminant analysis backward) were compared by discriminant function analysis. The classification system adopted in the Group II represented the higher discrimination rate than those in other groups(Group I : 76.1 0/0, Group II : 88.1 0/0, Group Ill: 87.3 %). These results suggest that EVs are present and intensity, formant 2, and formant 4 are available parameters for discrimination of EVs in sows.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.11
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• pp.1535-1542
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• 2015

An increasing number of electric vehicles (EVs) in power system affects its reliability in various aspects. Especially under high EV penetration level, new generating units are required to satisfy system's adequacy criterion. Wind power generation is expected to take the major portion of the new units due to environmental and economic issues. In this paper, the system reliability is analyzed using Loss of Load Expectation (LOLE) and Expected Energy Not Served (EENS) under each and both cases of increasing wind power generation and EVs. A probabilistic multi-state modeling method of wind turbine generator under various power output for adequate reliability evaluation is presented as well. EVs are modeled as loads under charging algorithm with Time-Of-Use (TOU) rates in order to incorporate EVs into hour-to-hour yearly load curve. With the expected load curve, the impact of EVs on the system adequacy is analyzed. Simulations show the reliability evaluation of increasing wind power capacity and number of EVs. With this method, system operator becomes capable of measuring appropriate wind power capacity to meet system reliability standard.

• Translational and Clinical Pharmacology
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• v.26 no.3
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• pp.103-110
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• 2018

The human microbiome is known to play an essential role in influencing host health. Extracellular vesicles (EVs) have also been reported to act on a variety of signaling pathways, distally transport cellular components such as proteins, lipids, and nucleic acid, and have immunomodulatory effects. Here we shall review the current understanding of the intersectionality of the human microbiome and EVs in the emerging field of microbiota-derived EVs and their pharmacological potential. Microbes secrete several classes of EVs: outer membrane vesicles (OMVs), membrane vesicles (MVs), and apoptotic bodies. EV biogenesis is unique to each cell and regulated by sophisticated signaling pathways. EVs are primarily composed of lipids, proteins, nucleic acids, and recent evidence suggests they may also carry metabolites. These components interact with host cells and control various cellular processes by transferring their constituents. The pharmacological potential of microbiome-derived EVs as vaccine candidates, biomarkers, and a smart drug delivery system is a promising area of future research. Therefore, it is necessary to elucidate in detail the mechanisms of microbiome-derived EV action in host health in a multi-disciplinary manner.

• Journal of Animal Reproduction and Biotechnology
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• v.37 no.1
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• pp.2-12
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• 2022

Extracellular vesicles (EVs) are nanovesicles that carry bioactive cargoes of proteins, lipids, mRNAs, and miRNAs between living cells. Their role in cellular communication has gained the attention of several research reports globally in the last decade. EVs are critically involved in sperm functions, oocyte functions, fertilization, embryonic development, and pregnancy. The review summarizes the state-of-the-art of EVs research in the diagnostic and therapeutic (theranostic) potentials of the EVs during the pregnancy that might provide a solution for gestational disturbances such as implantation failure, maternal health problems, gestational diabetes, and preeclampsia. EVs can be found in all biological fluids of the fetus and the mother and would provide a non-invasive and excellent tool for diagnostic purposes. Moreover, we provide the current efforts in manufacturing and designing targeted therapeutics using synthetic and semi-synthetic nanovesicles mimicking the natural EVs for efficient drug delivery during pregnancy.

• Journal of Nutrition and Health
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• v.55 no.2
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• pp.240-249
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• 2022

Purpose: Glabridin (GD) is a bio-available isoflavane isolated from the root extract of licorice (Glycyrrhiza glabra L.). It exhibits a variety of pharmacological activities such as anti-inflammatory and anti-oxidant activities. However, extracellular vesicles (EVs) secretion and the anti-cancer mechanism of action remains largely unknown. The present study investigates the anticancer effects of GD by determining the inhibition of EVs secretion in the human breast cancer cell line, MDA-MB-231. Methods: Cell viability, reactive oxygen species (ROS) production, migration, invasion rate, and vascular endothelial growth factor (VEGF) concentration were assessed in MDA-MB-231 cells treated with increasing concentrations of GD (0.1, 1, 5, 10, 20 µM). Subsequently, EV secretion and exosomal DEL-1 protein expression were evaluated to determine the anticancer effects of GD. Results: The results showed that GD significantly inhibited the cell proliferation of MDA-MB-231 cells in a dose- or time-dependent manner. Also, ROS production and apoptosis marker protein cleaved caspase-3 were significantly increased in GD-treated MDA-MB-231, compared to control. Furthermore, GD exposure resulted in significantly decreased not only migration and invasion rates but also the VEGF concentration, thereby contributing to a reduction in angiogenesis. Interestingly, the concentration and number of EVs as well as EV marker proteins, such as CD63 and TSG101, were decreased in GD-treated MDA-MB-231 cells. Markedly, extracellular matrix protein DEL-1 as angiogenesis factor was decreased in EVs from GD-treated MDA-MB-231 cells. Conclusion: This study identifies that the anti-cancer molecular mechanism of GD is exerted via inhibition of angiogenesis and EVs secretion, indicating the potential of GD as a chemotherapeutic agent for breast cancer.

• Transactions of the Korean hydrogen and new energy society
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• v.28 no.3
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• pp.287-294
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• 2017

EVs manufacturers typically target a range of 300 km on a fully charged battery. Many studies have been conducted to improve these disadvantages. As a results, the mileage of EVs is expected to increase significantly. However, as the distance traveled by EVs increases, current test method (SCT) have many difficulties. The biggest problem is that it takes a lot of time to test an EVs and greatly increases the error rate during the test period. In order to solve these problems, this paper discusses the fuel economy test method of EVs for energy efficiency and mileage. The comparison of test methods was achieved by chassis dynamometer test about EVs. These review of test methods are intended to both improve testing efficiency and provide a practical testing methodology that can be easily adapted to accommodate future testing enhancements. In conclusion, the results of MCT mode and SCT mode comparison show similar results within 3 %, confirming that the test method is appropriate. Also, as the CSCM distance becomes shorter in the MCT mode, the mileage becomes longer and the fuel economy becomes lower. As a result, the error from the SCT test results is expected to increase. In order to minimize the error of SCT measurement fuel economy, it is recommended to maximize the CSCM driving distance. However, since the timing of the EOT is not clearly known, it is reasonable to define the allowable range of the CSCE to be within 20 % of the MCT total mileage.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.767-774
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• 2013

The electricity demand and supply could be off balance if several electric vehicles(EVs) were charged at the same time or at peak load times. Therefore, smart grids are necessary to flatten the EVs' electricity demand and to enable EVs to be used as distributed storage devices as electricity demand from EV-charging increases. There are still few quantitative studies on the impact of smart grids on managing EVs' electrical loads. In this study, we analyzed the quantitative impact of smart grids on managing EVs' electrical loads and suggested policy implications. As a result, it is identified that smart grids can manage effectively EVs' impact on electrical grids. The electricity market structure and regulatory framework should support the demonstration and commercialization of smart grid technologies.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.9
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• pp.1577-1582
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• 2016

Now we are facing severe environmental issues such as global warming. Due to these, the concerns about eco-friendly energy have been increased. Kyoto protocol and Copenhagen climate change conference are circumstantial evidence of it. With these trends, the interests for the Electric Vehicles(EVs) which do not emit any harmful gases have gradually been raised. Unfortunately, however, massive connection of EVs to the power system could cause negative impacts such as voltage variations, frequency variations and increase of demand power. To prevent the mentioned issues, KEPCO adopts Time-of-Use(ToU) price for EVs charging. Nevertheless, it is important to verify the propriety of the charging system. In this paper, therefore, we used pre-introduced price elasticity concept to predict possible Demand Response(DR) on charging of EVs. And analyzed possible demand power increase according to various price elasticities. Simulation results show that given ToU based charging system would not enough to control the increase of demand power by EVs on the power system. It is concluded, therefore, additional methods and/or algorithms are required.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.1949-1957
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• 2016

Rapid Expansion of EVs(Electric Vehicles) is inevitable trends, to comply with eco-friendly energy paradigm according to Paris Agreement and to solve the environment problems such as global warming. In this paper, we analyze the limit point of transformer acceptable capacity as the increase of power demand considering EVs supply in the near future. Through the analysis of transformer utilization, we suggest methods to analyze the spare capacity of transformer for the case of optimal efficiency operation and emergency operation respectively. We have the results of 18.4~29% spare capacity for the charging infrastructure to the rated capacity of transformer by analyzing the existing sample apartments. It is analyzed that the acceptable number of EVs is 0.09~0.14 for optimal efficiency operation and 0.06~0.13 for emergency operation. Therefore, it is analyzed the power demand of EV will exceed the existing transformer spare capacity in 7~8 years as the annual growth rate of EVs is prospected 112.5% considering current annual growth rate of EVs and the government EV supply policy.