• The Korean Journal of Food And Nutrition
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• v.35 no.5
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• pp.378-388
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• 2022

This study was conducted to determine the proximate compositions, nutritional components, and antioxidant effects of white and brown enoki mushrooms (Flammulina velutipes). The crude protein and carbohydrate contents were higher in the brown than white mushrooms, whereas the moisture, crude ash, crude lipid, and dietary fiber levels were lower. The mineral contents of the white mushroom was higher than levels obtained in the brown mushroom for the detected components (Ca, Cu, K, Mn, Na, and P). The amount of vitamin B₃ in the brown mushroom was 1.51 mg/100 g, which was 4.5 times higher than that in the white mushroom. The major fatty acids detected were palmitic acid, linoleic acid, and α-linolenic acid. The total polyphenol and flavonoid contents were highest in 70% ethanol extracts of the white and brown mushrooms, respectively. For the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity, a 70% methanol extract of the white enoki mushrooms showed an activity of 76.4% (p<0.05). For the ferric-reducing antioxidant power (FRAP) activity, a 70% methanol extract of the brown enoki mushrooms showed the highest value. Further, the total flavonoid contents were significantly correlated with the DPPH and FRAP activities.

• Animal Bioscience
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• v.34 no.10
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• pp.1623-1631
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• 2021

Objective: This study aimed to validate and evaluate the dry matter (DM) intake prediction model of the Korean feeding standards for dairy cattle (KFSD). Methods: The KFSD DM intake (DMI) model was developed using a database containing the data from the Journal of Dairy Science from 2006 to 2011 (1,065 observations 287 studies). The development (458 observations from 103 studies) and evaluation databases (168 observations from 74 studies) were constructed from the database. The body weight (kg; BW), metabolic BW (BW^0.75, MBW), 4% fat-corrected milk (FCM), forage as a percentage of dietary DM, and the dietary content of nutrients (% DM) were chosen as possible explanatory variables. A random coefficient model with the study as a random variable and a linear model without the random effect was used to select model variables and estimate parameters, respectively, during the model development. The best-fit equation was compared to published equations, and sensitivity analysis of the prediction equation was conducted. The KFSD model was also evaluated using in vivo feeding trial data. Results: The KFSD DMI equation is 4.103 (±2.994)+0.112 (±0.022)×MBW+0.284 (±0.020)×FCM-0.119 (±0.028)×neutral detergent fiber (NDF), explaining 47% of the variation in the evaluation dataset with no mean nor slope bias (p>0.05). The root mean square prediction error was 2.70 kg/d, best among the tested equations. The sensitivity analysis showed that the model is the most sensitive to FCM, followed by MBW and NDF. With the in vivo data, the KFSD equation showed slightly higher precision (R² = 0.39) than the NRC equation (R² = 0.37), with a mean bias of 1.19 kg and no slope bias (p>0.05). Conclusion: The KFSD DMI model is suitable for predicting the DMI of lactating dairy cows in practical situations in Korea.

• Composites Research
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• v.34 no.6
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• pp.426-433
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• 2021

The carbon fiber reinforced plastic manufacturing process has a problem in that a dimensional error occurs due to thermal deformation such as residual stress, spring-in, and warpage. The main causes of thermal deformation are various, including the shape of the product, the chemical shrinkage, thermal expansion of the resin, and the mold effect according to the material and surface condition of the mold. In this study, a viscoelastic model was applied to the plate model to predict the thermal deformation. The effects of chemical shrinkage and thermal expansion of the resin, which are the main causes of thermal deformation, were analyzed, and the analysis technique of the 3-D viscoelastic model with and without mold was also studied. Then, the L-shaped mold effect was analyzed using the verified 3D viscoelastic model analysis technique. The results show that different residual deformation occurs depending on the surface condition even when the same mold is used.

• Structural Engineering and Mechanics
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• v.82 no.1
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• pp.121-131
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• 2022

The main goal of this study is to prepare a program for analyzing High Strength Steel Fibrous Reinforced Concrete (HSSFRC) slabs and predict the response and strength of the slab instead of preparing a prototype and testing it in the laboratory. For this purpose, new equations are proposed to represent the material properties of High Strength Steel Fibrous Reinforced Concrete. The proposed equations obtained from performing regression analysis on many experimental results using statistical programs. The finite element method is adopted for non-linear analysis of the slabs. The eight-node "Serendipity element" (3 DoF) is chosen to represent the concrete. The layered approach is adopted for concrete elements and the steel reinforcement is represented by a smeared layer. The compression properties of the concrete are modeled by a work hardening plasticity approach and the yield condition is determined depending on the first two stress invariants. A tensile strength criterion is adopted in order to estimate the cracks propagation. many experimental results for testing slabs are compared with the numerical results of the present study and a good agreement is achieved regarding load-deflection curves and crack pattern. The response of the load deflection curve is slightly stiff at the beginning because the creep effect is not considered in this study and for assuming perfect bond between the steel reinforcement and the concrete, however, a great agreement is achieved between the ultimate load from the present study and experimental results. For the models of the tension stiffening and cracked shear modulus, the value of Bg and Bt (Where Bg and Bt are the curvature factor for the cracked shear modulus and tension stiffening models respectively) equal to 0.005 give good results compared with experimental result.

• Structural Engineering and Mechanics
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• v.84 no.2
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• pp.143-154
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• 2022

Corrosion of steel reinforcement is considered as the main cause of concrete structures deterioration, especially those under humid environmental conditions. Hence, fiber reinforced polymer (FRP) bars are being increasingly used as a replacement for conventional steel owing to their non-corrodible characteristics. However, predicting the shear strength of beams reinforced with FRP bars still challenging due to the lack of robust shear theory. Thus, this paper aims to develop an explicit data driven based model to predict the shear strength of FRP reinforced beams using multi-objective evolutionary polynomial regression analysis (MOGA-EPR) as data driven models learn the behavior from the input data without the need to employee a theory that aid the derivation, and thus they have an enhanced accuracy. This study also evaluates the accuracy of predictive models of shear strength of FRP reinforced concrete beams employed by different design codes by calculating and comparing the values of the mean absolute error (MAE), root mean square error (RMSE), mean (𝜇), standard deviation of the mean (𝜎), coefficient of determination (R²), and percentage of prediction within error range of ±20% (a20-index). Experimental database has been developed and employed in the model learning, validation, and accuracy examination. The statistical analysis illustrated the robustness of the developed model with MAE, RMSE, 𝜇, 𝜎, R², and a20-index of 14.6, 20.8, 1.05, 0.27, 0.85, and 0.61, respectively for training data and 10.4, 14.1, 0.98, 0.25, 0.94, and 0.60, respectively for validation data. Furthermore, the developed model achieved much better predictions than the standard predictive models as it scored lower MAE, RMSE, and 𝜎, and higher R² and a20-index. The new model can be used in future with confidence in optimized designs as its accuracy is higher than standard predictive models.

• Journal of The Korean Astronomical Society
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• v.56 no.1
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• pp.59-73
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• 2023

The second generation of stars in the globular clusters (GCs) of the Milky Way (MW) exhibit unusually high N, Na, or Al, compared to typical Galactic halo stars at similar metallicities. The halo field stars enhanced with such elements are believed to have originated in disrupted GCs or escaped from existing GCs. We identify such stars in the metallicity range -3.0 < [Fe/H] < 0.0 from a sample of ~36,800 giant stars observed in the Sloan Digital Sky Survey and Large Sky Area Multi-Object Fiber Spectroscopic Telescope survey, and present their dynamical properties. The N-rich population (NRP) and N-normal population (NNP) among our giant sample do not exhibit similarities in either in their metallicity distribution function (MDF) or dynamical properties. We find that, even though the MDF of the NRP looks similar to that of the MW's GCs in the range of [Fe/H] < -1.0, our analysis of the dynamical properties does not indicate similarities between them in the same metallicity range, implying that the escaped members from existing GCs may account for a small fraction of our N-rich stars, or the orbits of the present GCs have been altered by the dynamical friction of the MW. We also find a significant increase in the fraction of N-rich stars in the halo field in the very metal-poor (VMP; [Fe/H] < -2.0) regime, comprising up to ~20% of the fraction of the N-rich stars below [Fe/H] = -2.5, hinting that partially or fully destroyed VMP GCs may have in some degree contributed to the Galactic halo. A more detailed dynamical analysis of the NRP reveals that our sample of N-rich stars do not share a single common origin. Although a substantial fraction of the N-rich stars seem to originate from the GCs formed in situ, more than 60% of them are not associated with those of typical Galactic populations, but probably have extragalactic origins associated with Gaia Sausage/Enceladus, Sequoia, and Sagittarius dwarf galaxies, as well as with presently unrecognized progenitors.

• Korean Journal of Heritage: History & Science
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• v.55 no.4
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• pp.166-177
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• 2022

The Shiveet Khairkhan is located on Tsengel Som in the middle of Bayan-ulgi Aimag in the Altai region. Various remains have been identified, and it has been found to be an important area of the Eurasian steppe. In this study, the characteristics of textile fibers and dyes excavated from the tombs of the 1st~3rd century Xianbei period in the sites of Shiveet Khairkhan, Mongolia were investigated. As a result of analysis using optical microscopic observation and attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) for fiber identification, green and yellow fabrics were identified as silk fabrics. To investigate the properties of the dye, the surface reflectance of the dyed fabric was measured using an fiber optic reflectance spectrophotometer for non-destructive analysis. The green fabric appeared similar to the reflection spectrum of indigo dye. In addition, as a result of component analysis using gas chromatography-mass spectrometry, isatin and indigotine were detected. Isatin and indigotine are characteristic components of indigo dye, and it was found that the green fabric of the tombs of the Xianbei period was dyed using indigo dye. It was difficult to identify the type of dye in the yellow fabric as a result of reflectance spectrum and gas chromatography analysis. Indigo plants are a dye used for blue dyeing from thousands of years ago, and many species are distributed around the world. It was confirmed that the fabric was relatively well preserved and indigo dye was used for the green Jikryeongui (garment with a straight collar) in the ancient tomb of the Xianbei period about 1,800 years ago, even though it was buried for a long time. Scientific investigation of textile cultural heritage is an essential process for conservation treatment, restoration, exhibition, and the creation of a conservation environment. It is expected that related research will be activated in the future and will be helpful in interpreting the living culture at the time, preserving textiles, and a conservation environment.

• Journal of Korean Home Economics Education Association
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• v.31 no.3
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• pp.179-192
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• 2019

This study was performed to analyze the contents of food intake in middle school Home Economics textbook and the trends of food intake of middle school students in Korea to figure out the education direction of food intake. The contents of food intake were analyzed in major three kinds of middle school Home Economics textbook according to 2015 curriculum and the trends of food and nutrient intake were analyzed in 2,543 subjects aged 13 to 15 years using 2007~2015 Korea National Health and Nutrition Examination survey by logistic regression analysis or Pearson correlation coefficient. As a result, contents of food intake of textbook included food source of nutrient, food group name, necessity of eating diverse foods, recommended daily eating frequency of food group and menu planning according to meal composition guideline, however food intake trends were not included. Consumption of grains and grain products was increased until 2007 to 2010 year and was decreased after 2011 year(p=0.0012). Sugars and sweets, beverages and alcohols, and fish and shellfish consumption were increased during 2007~2015 year(p<0.0001). Carbohydrate, fat, vitamin A, thiamin and iron intakes were increased(p=0.0052), and energy ratio by carbohydrate was decreased(p=0.0009) and energy ratio by fat was increased(p<0.0001) during 2007~2015 year. Mean ratios of nutrient intake compared to the dietary reference intakes for Koreans were very low in dietary fiber(19-27%) and calcium(46-56%), but was higher in sodium(221-289%)(p<0.0001) regardless of year. There was a significant positive correlation between most food group intakes except sugars and sweets, bean and bean products, nuts and seeds, seaweeds, and beverages and alcohols and energy, protein, dietary fiber, vitamin A, riboflavin, calcium and iron intakes(p=0.0375). In the above, during the period from 2007 to 2015 year, intakes of sugars and sweets, beverages and alcohols, and fish and shellfish were increased, and intakes of dietary fiber and calcium were low and energy ratio by fat was increased, thus these trends are concerned to threaten nutritional balance and health of subjects. Therefore, Home Economics textbook of middle school needs to include food intake trends of adolescents with basic concepts to help them maintain balanced diet in the rapid change of food intake patterns for maintaining optimal nutrition and health.

• Journal of the Korea Concrete Institute
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• v.22 no.3
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• pp.381-388
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• 2010

In this study, characteristics of the seismic response of the non-earthquake resistant reinforced concrete (RC) frame were identified. The test building is designed to withstand only gravity loads and not in compliance with modern seismic codes. Smooth bars were utilized for the reinforcement. Members are provided with minimal amount of stirrups to withstand low levels of shear forces and the core concrete is virtually not confined. Columns are slender and more flexible than beams, and beam-column connections were built without stirrups. Through the modeling of an example RC frame, the feasibility of the fiber elementbased 3D nonlinear analysis method was investigated. Since the torsion is governed by the fundamental mode shape of the structure under dynamic loading, pushover analysis cannot predict torsional response accurately. Hence, dynamic response history analysis is a more appropriate analysis method to estimate the response of an asymmetric building. The latter method was shown to be accurate in representing global responses by the comparison of the analytical and experimental results. Analytical models without rigid links provided a good estimation of reduced stiffness and strength of the test structure due to bond-slip, by forming plastic hinges closer to the column ends. However, the absence of a proper model to represent the bond-slip poased the limitations on the current inelastic analysis schemes for the seismic analysis of buildings especially for those with round steel reinforcements. Thus, development of the appropriate bond-slip model is in need to achieve more accurate analysis.

• Fibers and Polymers
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• v.7 no.4
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• pp.344-351
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• 2006

This paper is intended to determine the optimal processing parameters applied to the dyeing procedure so that the desired color strength of a raw fabric can be achieved. Moreover, the processing parameters are also used for constructing a system to predict the fabric quality. The fabric selected is the nylon and Lycra blend. The dyestuff used for dyeing is acid dyestuff and the dyeing method is one-bath-two-section. The Taguchi quality method is applied for parameter design. The analysis of variance (ANOVA) is applied to arrange the optimal condition, significant factors and the percentage contributions. In the experiment, according to the target value, a confirmation experiment is conducted to evaluate the reliability. Furthermore, the genetic algorithm (GA) is combined with the back propagation neural network (BPNN) in order to establish the forecasting system for searching the best connecting weights of BPNN. It can be shown that this combination not only enhances the efficiency of the learning algorithm, but also decreases the dependency of the initial condition during the network training. Most of all, the robustness of the learning algorithm will be increased and the quality characteristic of fabric will be precisely predicted.