• Journal of Life Science
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• v.31 no.5
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• pp.488-495
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• 2021

The aim of this study was to investigate the possible antioxidant effect of Spirodela polyrhiza (SP) on rats fed a high fat and high cholesterol diet supplemented with either 5% (SPA group) or 10% (SPB group) SP for 4 weeks. The hepatic SOD activity of the HF group significantly decreased compared to that of the N group, but that of the SPA and SPB groups significantly increased. The GPx activity of the SPA and SPB groups in the liver was significantly greater than that of the HF group, and the hepatic catalase activity of the SPA and SPB groups significantly increased compared to the HF group. The hepatic superoxide radical content of the mitochondria and microsomes of the HF group significantly increased compared to that of the N group, but the contents were reduced in the group that took SP powder. The hepatic hydrogen peroxide content in the cytosol and mitochondria of the SP powder group was lower than in the HF group. The carbonyl content in the mitochondria and microsomes of the SPA and SPB groups was significantly lower than in the HF group. The TBARS values in the liver significantly decreased in the SPA and SPB groups. Spirodela polyrhiza was thus effective in reducing oxidative stress by regulating the hepatic antioxidant enzymes and the free radicals in rats fed high fat and high cholesterol diets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.565-576
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• 2021

This study was undertaken to measure changes in the composition of elk velvet antlers, by considering the part and growth days (40th day, 60th day). The collected samples were divided into the tip, upper, middle, and base part by position. Samples were analyzed for moisture, crude protein, crude fat, crude ash, crude fiber, pH, minerals, and fatty acid and amino acid contents. The amounts of crude protein and crude fat were determined to be highest at the tip of the velvet antler by position, whereas dry matter and crude ash were high at the base. Crude protein contents were increased in the upper part but were decreased at the base, when assessed by growth day. Conversely, crude fiber and crude ash were found to be increased at the base by growth day. The pH value was determined to be lower at the tip, but did not differ when evaluated by growth day. Mineral contents (Ca, P, K) differed significantly by growth day in the middle portion of the antler. Saturated fatty acids tended to increase by growth day, whereas unsaturated fatty acids showed a decreasing trend. However, no significant difference was obtained for any of the components. Most amino acids were found to be high in the 60 days velvet antler, except isoleucine (Ile), which showed low levels at day 60. These results provide information on the changes in the composition of antlers, in cases of early cutting.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.42-51
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• 2020

This study was performed to support the 6th forest basic planning by Korea Forest Service as predicting the change of forestland area by the transition of land use type in the future over 35 years in South Korea. It is very important to analyze upcoming forestland area change for future forest planning because forestland plays a basic role to predict forest resources change for afforestation, production and management in the future. Therefore, the transitional interaction between land use types in future of South Korea was predicted in this study using econometrical models based on past trend data of land use type and related variables. The econometrical model based on maximum discounted profits theory for land use type determination was used to estimate total quantitative change by forestland, agricultural land and urban area at national scale using explanatory variables such as forestry value added, agricultural income and population during over 46 years. In result, it was analyzed that forestland area would decrease continuously at approximately 29,000 ha by 2027 while urban area increases in South Korea. However, it was predicted that the forestland area would be started to increase gradually at 170,000 ha by 2050 because urban area was reduced according to population decrement from 2032 in South Korea. We could find out that the increment of forestland would be attributed to social problems such as urban hollowing and localities extinction phenomenon by steep decrement of population from 2032. The decrement and increment of forestland by unbalanced population immigration to major cities and migration to localities might cause many social and economic problems against national sustainable development, so that future strategies and policies for forestland should be established considering such future change trends of land use type for balanced development and reasonable forestland use and conservation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.268-278
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• 2020

Flowering time has been put forward due to the recent abnormally warm winter, which often caused damages of flower buds by late frosts persistently. In the present study, cumulative chill unit and cumulative heat unit of Niitaka pear, which are required for releasing the endogenous dormancy and for flowering after breaking dormancy, respectively, were compared between flowering time prediction models used in South K orea. Observation weather data were collected at eight locations for the recent three years from 2018-2020. The dates of full bloom were also collected to determine the confidence level of models including DVR, mDVR and CD models. It was found that mDVR model tended to have smaller values (8.4%) of the coefficient of variation (cv) of chill units than any other models. The CD model tended to have a low value of cv (17.5%) for calculation of heat unit required to reach flowering after breaking dormancy. The mDVR model had the most accurate prediction of full bloom during the study period compared with the other models. The DVR model usually had poor skills in prediction of full bloom dates. In particular, the error of the DVR model was large especially in southern coastal areas (e.g., Ulju and Sacheon) where the temperature was warm. Our results indicated that the mDVR model had relatively consistent accuracy in prediction of full bloom dates over region and years of interest. When observation data for full bloom date are compiled for an extended period, the full bloom date can be predicted with greater accuracy improving the mDVR model further.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.27-42
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• 2020

Startup accelerators have emerged as new investment entities that help early startups, which are not easy to survive continuously due to lack of funds, commercialization capabilities, and experiences. As their positive performance on early startups and the ecosystem has been proven, the number of early startups which want to receive their investment is also increasing. However, they are vaguely preparing to attract accelerators' investment because they do not have any information on what factors the accelerators consider important. In addition, researches on startup accelerators are also at an early level, so there are no remarkable prior studies on factors that decide on investment. Therefore, this study aims to help startups prepare for investment attraction by looking at what factors are important for accelerators to invest, and to provide meaningful implications to academia. In the preceding study, we derived five upper level categories, 26 lower level accelerators' investment determinants through the qualitative meta-synthesis method, secondary data analysis, observation on US accelerators and in-depth interviews. In this study, we want to derive important implications by deriving priorities of the accelerators' investment determinants. Therefore, we used AHP that are evaluated as the suitable methodology for deriving importance and priority. The analysis results show that accelerators value market-related factors most. This means that startups that are subject to investment by accelerators are early-stage startups, and many companies have not fully developed their products or services. Therefore, market-related factors that can be evaluated objectively seem to be more important than products (or services) that are still ambiguous. Next, it was found that the factors related to the internal workforce of startups are more important. Since accelerators want to develop their businesses together with start-ups and team members through mentoring, ease of collaboration with them is very important, which seems to be important. The overall priority analysis results of the 26 investment determinants show that 'customer needs' and 'founders and team members' understanding of customers and markets' (0.62) are important and high priority factors. The results also show that startup accelerators consider the customer-centered perspective very important. And among the factors related to startups, the most prominent factor was the founder's openness and execution ability. Therefore, it can be confirmed that accelerators consider the ease of collaboration with these startups very important.

• Korean Journal of Heritage: History & Science
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• v.55 no.2
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• pp.82-100
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• 2022

With the crisis of the COVID-19 pandemic and the era of the 4th industrial revolution, archaeological heritage education has entered a new phase. This article responds to the trends in the post-COVID-19 era, seeking ways to develop archaeological heritage education and sustainable strategies necessary in the era of the 4th industrial revolution. The program of archaeological heritage education required in the era of the 4th industrial revolution must cultivate creative talent, solve problems, and improve self-efficacy. It should also draw attention to archaeological heritage maker education. Such maker education should be delivered based on constructivism and be designed by setting specific learning goals in consideration of various age-specific characteristics. Moreover, various ICT-based contents applying VR, AR, cloud, and drone imaging technologies should be developed and expanded, and, above all, ontact digital education(real-time virtual learning) should seek ways to revitalize communities capable of interactive communication in non-face-to-face situations. The development of such ancient heritage content needs to add AI functions that consider learners' interests, learning abilities, and learning purposes while producing various convergent contents from the standpoint of "cultural collage." Online archaeological heritage content education should be delivered following prior learning or with supplementary learning in consideration of motivation or field learning to access the real thing in the future. Ultimately, archaeological ontact education will be delivered using cutting-edge technologies that reflect the current trends. In conjunction with this, continuous efforts are needed for constructive learning that enables discovery and question-exploration.

• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.1
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• pp.89-104
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• 2021

Based on the TF-IDF weighted value that evaluates the importance of words that play a key role, the semantic network analysis(SNA) was conducted on the self-introduction letter of freshman at Korea National College of Agriculture and Fisheries(KNCAF) in 2020. The top three words calculated by TF-IDF weights were agriculture, mathematics, study (Q. 1), clubs, plants, friends (Q. 2), friends, clubs, opinions, (Q. 3), mushrooms, insects, and fathers (Q. 4). In the relationship between words, the words with high betweenness centrality are reason, high school, attending (Q. 1), garbage, high school, school (Q. 2), importance, misunderstanding, completion (Q.3), processing, feed, and farmhouse (Q. 4). The words with high degree centrality are high school, inquiry, grades (Q. 1), garbage, cleanup, class time (Q. 2), opinion, meetings, volunteer activities (Q.3), processing, space, and practice (Q. 4). The combination of words with high frequency of simultaneous appearances, that is, high correlation, appeared as 'certification - acquisition', 'problem - solution', 'science - life', and 'misunderstanding - concession'. In cluster analysis, the number of clusters obtained by the height of cluster dendrogram was 2(Q.1), 4(Q.2, 4) and 5(Q. 3). At this time, the cohesion in Cluster was high and the heterogeneity between Clusters was clearly shown.

• Journal of Life Science
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• v.32 no.7
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• pp.578-587
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• 2022

Korea, as the world's 7^th largest emitter of greenhouse gases, has raised the national greenhouse gas reduction target as international regulations have been strengthened. As it is possible to utilize coastal and marine ecosystems as important nature-based solutions (NbS) for implementing climate change mitigation or adaptation plans, the blue carbon ecosystem is now receiving attention. Blue carbon refers to carbon that is deposited and stored for a long period after carbon dioxide (CO₂) is absorbed as biomass by coastal ecosystems or oceanic ecosystems through photosynthesis. Currently, there are only three blue carbon ecosystems officially recognized by the Intergovernmental Panel on Climate Change (IPCC): mangroves, salt marshes, and seagrasses. However, the results of new research on the high CO₂ sequestration and storage capacity of various new blue carbon sinks, such as seaweeds, microalgae, coral reefs, and non-vegetated tidal flats, have been continuously reported to the academic community recently. The possibility of IPCC international accreditation is gradually increasing through scientific verification related to calculations. In this review, the current status and potential value of seaweeds, seagrass fields, and non-vegetated tidal flats, which are sources of blue carbon on the east coast, are discussed. This paper confirms that seaweed resources are the most effective NbS in the East Sea of Korea. In addition, we would like to suggest the direction of research and development (R&D) and utilization so that new blue carbon sinks can obtain international IPCC certification in the near future.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.723-736
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• 2022

In this study, monthly precipitation forecasting models that can predict up to 12 months in advance were constructed for the Geum River basin, and two statistical techniques, multiple linear regression (MLR) and artificial neural network (ANN), were applied to the model construction. As predictor candidates, a total of 47 climate indices were used, including 39 global climate patterns provided by the National Oceanic and Atmospheric Administration (NOAA) and 8 meteorological factors for the basin. Forecast models were constructed by using climate indices with high correlation by analyzing the teleconnection between the monthly precipitation and each climate index for the past 40 years based on the forecast month. In the goodness-of-fit test results for the average value of forecasts of each month for 1991 to 2021, the MLR models showed -3.3 to -0.1% for the percent bias (PBIAS), 0.45 to 0.50 for the Nash-Sutcliffe efficiency (NSE), and 0.69 to 0.70 for the Pearson correlation coefficient (r), whereas, the ANN models showed PBIAS -5.0~+0.5%, NSE 0.35~0.47, and r 0.64~0.70. The mean values predicted by the MLR models were found to be closer to the observation than the ANN models. The probability of including observations within the forecast range for each month was 57.5 to 83.6% (average 72.9%) for the MLR models, and 71.5 to 88.7% (average 81.1%) for the ANN models, indicating that the ANN models showed better results. The tercile probability by month was 25.9 to 41.9% (average 34.6%) for the MLR models, and 30.3 to 39.1% (average 34.7%) for the ANN models. Both models showed long-term predictability of monthly precipitation with an average of 33.3% or more in tercile probability. In conclusion, the difference in predictability between the two models was found to be relatively small. However, when judging from the hit rate for the prediction range or the tercile probability, the monthly deviation for predictability was found to be relatively small for the ANN models.

• Korean Chemical Engineering Research
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• v.59 no.3
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• pp.345-358
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• 2021

This study focuses on the development of the liquid air production process that uses LNG (liquefied natural gas) cold energy which usually wasted during the regasification stage. The liquid air can be transported to the LNG exporter, and it can be utilized as the cold source to replace certain amount of refrigerant for the natural gas liquefaction. Therefore, the condition of the liquid air has to satisfy the available pressure of LNG storage tank. To satisfy pressure constraint of the membrane type LNG tank, proposed process is designed to produce liquid air at 1.3bar. In proposed process, the air is precooled by heat exchange with LNG and subcooled by nitrogen refrigeration cycle. When the amount of transported liquid air is as large as the capacity of the LNG carrier, it could be economical in terms of the transportation cost. In addition, larger liquid air can give more cold energy that can be used in natural gas liquefaction plant. To analyze the effect of the liquid air production amount, under the same LNG supply condition, the proposed process is simulated under 3 different air flow rate: 0.50 kg/s, 0.75 kg/s, 1.00 kg/s, correspond to Case1, Case2, and Case3, respectively. Each case was analyzed thermodynamically and economically. It shows a tendency that the more liquid air production, the more energy demanded per same mass of product as Case3 is 0.18kWh higher than Base case. In consequence the production cost per 1 kg liquid air in Case3 was $0.0172 higher. However, as liquid air production increases, the transportation cost per 1 kg liquid air has reduced by $0.0395. In terms of overall cost, Case 3 confirmed that liquid air can be produced and transported with $0.0223 less per kilogram than Base case.