• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.25 no.4
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• pp.81-96
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• 2020

Berthlot's reaction spectrophotometric method is generally used for the analysis of dissolved ammonium in seawater, but in recent years, a fluorescence method using an orthophthaldialdehyde-sulfite (OPA) fluorescent reagent is actively used internationally. In this study, we investigated the effects of the detection limit between the analysis methods, the reagent refractive index inherent in the spectrophotometric method, and the use of different calibration curves to understand the cause of the difference in dissolved ammonium concentration (about 0.31 𝜇M) observed in the seawater samples and a nutrient reference material between two institutions (KIOST (spectrophotometric method, one-order linear regression gradient only), Australia CSIRO (fluorescence method, quadratic formula)) conducted onboard the Australian R/V Investigator in 2017. The method detection limit (0.063 𝜇M) and the reagent refractive index background value (0.054 𝜇M) of the spectrophotometric method measured in this study could explain the difference in dissolved ammonium concentration values of the two institutes about 20% and 17%, respectively. However, when the concentration of the calibration curve of the spectrophotometric method was calculated using the same quadratic as the fluorescence method or the slope and intercept of linear regression, the difference in the dissolved ammonium concentration between the two institutions was reduced to less than the detection limit of the spectrophotometric method. Therefore, the difference in the concentration of dissolved ammonium between the two institutions, found in the nutrient reference materials and the seawater field sample during the international onboard nutrient inter-comparison experiment, may be attributed to be the effect of the different calibration curves used in the two methods rather than the effect of the difference in two analytical methods. When comparing the dissolved ammonium data from seawater samples in the future, it is recommended to pay attention to the information on the baseline, number of standard solutions, and calibration curve used in the analysis.

• Journal of Animal Science and Technology
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• v.49 no.5
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• pp.633-638
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• 2007

This study was conducted to determine the protein requirement level in growing Jindo dog through nitrogen balance experiment. Twelve female dogs aged 18～20 weeks old were allotted one of 3 dietary treatments containing 21, 23 and 25% of crude protein. Average daily gain of dogs fed experimental diets containing 21, 23 and 25% of crude protein were 65.42, 79.58 and 99.17g/d, respectively, and there was a significant difference between 21 and 25% of crude protein treatments(p<0.05). Retained nitrogen were calculated 0.74, 0.96 and 1.31g/kgBW.75/d for dogs fed diets containing 21, 23 and 25% of crude protein, respectively, and were significantly higher(p<0.05) in dogs fed 25% of crude protein diet then those of other dogs. A quadratic regression equation was calculated between nitrogen intake(x) and nitrogen retention(y); y=-2.519x2+12.79x-14.79, and it was found a significantly(p<0.05) higher regression coefficient of 0.782. From the above equation, it was estimated maintenance requirement of crude protein for growing Jindo dog is 11.25g/kg BW.75/d.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.9
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• pp.1314-1322
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• 2017

Objective: This experiment investigated the effect of dietary net energy (NE) concentrations on growth performance and NE intake of growing gilts. Methods: Five diets were formulated to contain 9.6, 10.1, 10.6, 11.1, and 11.6 MJ NE/kg, respectively. A metabolism trial with 10 growing pigs (average body weight [BW] = $15.9{\pm}0.24kg$) was conducted to determine NE concentrations of 5 diets based on French and Dutch NE systems in a $5{\times}5$ replicated Latin square design. A growth trial also was performed with five dietary treatments and 12 replicates per treatment using 60 growing gilts (average BW = $15.9{\pm}0.55kg$) for 28 days. A regression analysis was performed to predict daily NE intake from the BW of growing gilts. Results: Increasing NE concentrations of diets did not influence average daily gain and average daily feed intake of growing gilts. There was a quadratic relationship (p = 0.01) between dietary NE concentrations and feed efficiency (G:F), although the difference in G:F among treatment means was relatively small. Regression analysis revealed that daily NE intake was linearly associated with the BW of growing gilts. The prediction equations for NE intake with the BW of growing gilts were: NE intake (MJ/d) = $1.442+(0.562{\times}BW,kg)$, $R^2=0.796$ when French NE system was used, whereas NE intake (MJ/d) = $1.533+(0.614{\times}BW,kg)$, $R^2=0.810$ when Dutch NE system was used. Conclusion: Increasing NE concentrations of diets from 9.6 to 11.6 MJ NE/kg have little impacts on growth performance of growing gilts. Daily NE intake can be predicted from the BW between 15 and 40 kg in growing gilts.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.687-693
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• 2015

Using 378,086 lactation records on dairy cattle, environmental factors influencing acetone and ${\beta}$-hydroxybutyrate acid contents in raw milk which are used as ketosis diagnosis indicator traits were analyzed in this experiment. Significance testing was conducted on farm, lactation stage, parity, milking time and month of age by traits. The results of this experiment indicated that there was a highly significant (p < 0.01) difference in all factors and lactation stage was the most significant factor. Linear regression coefficients of month of age on daily milk yields and acetone and ${\beta}$-hydroxybutyrate acid contents were all positive, while their quadratic linear regression coefficients were negative. Least square means for milk yield at second lactation stage (36~65 days) was 19.06kg which was higher than that of late lactation stage by 6.51kg. Least square means for acetone and ${\beta}$-hydroxybutyrate acid contents at the first lactation stage (5~35 days) were highest (0.1929mM/L and 0.0742mM/L, respectively), and there was a trend that they decreased as the milking progressed, but increased slightly at the late stage of milking. However, least square means for acetone and ${\beta}$-hydroxybutyrate acid contents at the first parity were 0.1414mM/L and 0.0522mM/L, respectively, which were higher than the average milk yield after the second parity. Least square means for acetone and ${\beta}$-hydroxybutyrate acid contents of PM milk yield (0.1372mM/L and 0.0534mM/L, respectively) were higher than those of AM milk yield collectively.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.5
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• pp.35-43
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• 2016

In order to understand rotation behavior of high strength steel endplate connections under fire, this study is compared with existing studies conducted using FEA program. Eurocode 3 presents the three failure modes according to the prediction of bending resistance moment. The parameters of analysis model are temperature, thickness and steel materials of endplate. The rotation stiffness, and bending resistance moment are analyzed according to the parameters. The change of rotation stiffness and bending resistance moment are analyzed about the parameters, regression equations are suggested the change of high strength steel endplate connections. Consequently, the regression equations were proposed as the linear and quadratic equation. The moment ratio of high strength steel under fire was more reduced than the carbon steel, and was small effect about the thickness. When the high strength steel under fire was compared with at ambient temperature, the slope of initial rotation stiffness reduced, the increment ratio of moment was slow, and the change of plastic rotation stiffness wasn't effect by the thickness increase.

• Journal of Bio-Environment Control
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• v.27 no.4
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• pp.326-331
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• 2018

Crop growth models are useful tools for understanding and integrating knowledge about crop growth. Models for predicting plant height, net photosynthesis rate, and plant growth of quinoa (Chenopodium quinoa Willd.) as a leafy vegetable in a closed-type plant factory system were developed using empirical model equations such as linear, quadratic, non-rectangular hyperbola, and expolinear equations. Plant growth and yield were measured at 5-day intervals after transplanting. Photosynthesis and growth curve models were calculated. Linear and curve relationships were obtained between plant heights and days after transplanting (DAT), however, accuracy of the equation to estimate plant height was linear equation. A non-rectangular hyperbola model was chosen as the response function of net photosynthesis. The light compensation point, light saturation point, and respiration rate were 29, 813 and $3.4{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, respectively. The shoot fresh weight showed a linear relationship with the shoot dry weight. The regression coefficient of the shoot dry weight was 0.75 ($R^2=0.921^{***}$). A non-linear regression was carried out to describe the increase in shoot dry weight of quinoa as a function of time using an expolinear equation. The crop growth rate and relative growth rate were $22.9g{\cdot}m^{-2}{\cdot}d^{-1}$ and $0.28g{\cdot}g^{-1}{\cdot}d^{-1}$, respectively. These models can accurately estimate plant height, net photosynthesis rate, shoot fresh weight, and shoot dry weight of quinoa.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.5
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• pp.391-400
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• 2017

Italian ryegrass (IRG) is one of the fastest growing grasses available to farmers. It offers rapid establishment and starts growing early in the following spring and has fast regrowth after defoliation. So, IRG can be utilized as the dominant/single species of grass used in a farming system, or to play a role as a large producing pasture and sacrificial paddock. The objective of this study was to develop the use of unmanned aerial vehicle (UAV) for the evaluation of feed value of IRG. For this study, UAV imagery was taken on the Nonsan regions two times during the IRG growing season. We analyzed the relationships between $NDVI_{UAV}$ and feed value parameters such as fresh matter yield, dry matter yield, acid detergent fiber (ADF), neutral detergent fiber (NDF), total digestible nutrient (TDN) and crude protein at the season of harvest. Correlation analysis between $NDVI_{UAV}$ and feed value parameters of IRG revealed that $NDVI_{UAV}$ correlated well with crude protein (r = 0.745), and fresh matter yield (r = 0.655). According to the relationship, the variation of $NDVI_{UAV}$ was significant to interpret feed value parameters of IRG. Eight different regression models such as Linear, Logarithmic, Inverse, Quadratic, Cubic, Power, S, and Exponential model were used to estimate IRG feed value parameters. The S and exponential model provided more accurate results to predict fresh matter yield and crude protein than other models based on coefficient of determination, p- and F-value. The spatial distribution map of feed values in IRG plot was in strong agreement with the field measurements in terms of geographical variation and relative numerical values when $NDVI_{UAV}$ was applied to regression equation. These lead to the result that the characteristics of variations in feed value of IRG according to $NDVI_{UAV}$ were well reflected in the model.

• Journal of Nutrition and Health
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• v.54 no.1
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• pp.116-128
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• 2021

Purpose: The extraction conditions for bioactive components from peanut shells, which is a byproduct of peanut processing, were optimized to enhance the total phenolic content (TPC, Y1), total flavonoid content (TFC, Y2), and 2,2-diphenyl-1-picrylhydrazyl radical scavenging activity (RSA, Y3). In addition, this study evaluated the anti-obesity effect of peanut shell extract. Methods: Optimization of ultrasonic-assisted extraction (UAE) was performed using a response surface methodology. The independent variables applied for extraction were time (X1: 5.0-55.0), temperature (X2: 26.0-94.0), and ethanol concentration (X3: 0.0%-99.5%). Quadratic regression models were derived based on the results of 17 experimental sets, and an analysis of the variance was performed to verify its accuracy and precision of the regression equations. Results: When evaluating the effects of independent variables on responses using statistically-based optimization, the independent variable with the most significant effect on the TPC, TFC, and RSA was the ethanol concentration (p = 0.0008). The optimal extraction conditions to satisfy all three responses were 35.8 minutes, 82.7℃, and 96.0% ethanol. Under these conditions, the inhibitory activities of α-glucosidase and pancreatic lipase by the extract were 86.4% and 78.5%, respectively. Conclusion: In this study, UAE showed superior extraction efficiency compared to conventional hot-water extraction in the extraction of polyphenols and bioactive materials. In addition, α-glucosidase and pancreatic lipase inhibitory effects were identified, suggesting that peanut shells can be used as effective antioxidants and anti-obesity agents in functional foods and medicines.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.55-65
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• 2020

The purpose of this study is to empirically analyze the factors that affect start-up activities at the national level. Unlike most existing research about entrepreneurship at the individual level, this empirical analysis makes use of the total early-stage entrepreneurial activity(TEA) index at national level. This was developed by the Global Entrepreneur Monitor (GEM) as the measure for the degree of entrepreneurship of the countries. Based on the previous studies, not only national income level and unemployment rate, but also other factors including the cultural characteristics of the countries were included in our regression model. Using GEM's panel data, we found that the effectiveness of the factors depends on the stage of economic development. In particular, we found 'U-shape' relationship between the level of per capita income and entrepreneurship activity by the panel regression analysis using quadratic function. This analysis result can explicitly confirm what the existing literature have explained descriptively. Furthermore, the governmental support programs are shown to have significantly positive effects on the entrepreneurship or start-up activities in the factor-driven and efficiency-driven economies. On the contrary, those programs were not very helpful in the innovative economies. Lastly, this research suggests that the 'education and training' and the 'entrepreneurial culture' be the supportive norm for new business regardless of the economic development level.

• Journal of Korean Society of Forest Science
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• v.77 no.3
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• pp.331-337
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• 1988

To investigate the effects of forest stand and stony characteristics on interception loss from canopy trees, throughfall and stemflow under the canopy of a pine stand and a hardwood stand were measured during 4-month periods July to October, 1986 at the Kwanak Arboretum near Anyang, and the data were analysed by correlation and regression methods. The man results obtained from this study are summerized as follows : 1. The overall throughfall collected during measurement period were 593.5mm(76.7%) in the pine stand and 663.1mm(81.8%) in the hardwood stand oui of total percipitation of 773.8mm. Combined regression analysis describes the relation between total precipitation(P) and throughfall(T) in the pine stand as T=-1.8675+0.8320 P. in the hardwood stand as T=-8179+0.8805P. 2. And the sum of stemflow from measurement of total precipitation in the pine stand and the hardwood stand were 37.4mm(4.8%) and 15.5mm(2%), respectively. In total precipitation less than 2.5mm, stemflow were not measured in both the pine stand and the hardwood stand. Regression equations for the pine stand and the hardwood stand are S=-0.6155+0.0698P, S=-0.0497+0.0183P. The mean slope and intercept of the individual regression of stemflow on rainfall for each fewest stand indicate the proportion of the rain diverted to the trunks and trunk water capacity, respectively. 3. Interception loss accounted for 142.9mm(18.5%) in the pine stand and 125.2mm(16.2%), in the hardwood stand. 4. By quadratic predictive model of relation between interception loss and total incident rainfall, the extent of variance in interception loss explained was about 72% and 61% in the pine stand and the hardwood stand respectively.