• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.515-522
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• 2023

The aim of this study was to quantitatively evaluate a new stem volume table for estimating the growth, carbon storage, and greenhouse gas (GHG) absorption in Cryptomeria japonica and Chamaecyparis obtusa stands and to provide suggestions for improving the domestic GHG inventory. Carbon storage and GHG absorption were estimated using growing stock data obtained from invariable sub-sample plots between the 6^th and 7^th national forest inventories. We assessed changes in growing stock using the parameters employed by Kozak (1988) and Versions 1 and 2 of the stem volume table. Version 2 has new stem tables for 16 species, including Cryptomeria japonica, which were unavailable in Version 1. Version 2 also includes new data for trees with diameters at breast height equal to or greater than 30 cm. We found greater growing stock values using Version 2 than Version 1 for both stands, and the differences were statistically significant (p<0.001). Applying the new stem volume table increased GHG absorption by 22% for the Cryptomeria japonica stand and 13% for the Chamaecyparis obtusa stand. The growing stock estimation method used in this study should therefore be applied to re-estimate GHG absorptions in the forestry sector to produce accurate statistics for the IPCC guidelines.

• Animal Bioscience
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• v.36 no.12
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• pp.1806-1820
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• 2023

Objective: The present study was aimed primarily for estimating various genetic parameters (heritability, genetic correlations) of reproduction (age at first calving [AFC], first service period [FSP]); production (first lactation milk, solid-not fat, and fat yield) and lifetime traits (lifetime milk yield, productive life [PL], herd life [HL]) in Tharparkar cattle to check the association of reproduction traits with lifetime traits through two different methods (Frequentist and Bayesian) for comparative purpose. Methods: Animal breeding data of Tharparkar cattle (n = 964) collected from Livestock farm unit of ICAR-NDRI Karnal for the period 1990 through 2019 were analyzed using a Frequentist least squares maximum likelihood method (LSML; Harvey, 1990) and a multi-trait Bayesian-Gibbs sampler approach (MTGSAM) for genetic correlations estimation of all the traits. Estimated breeding values of sires was obtained by BLUP and Bayesian analysis for the production traits. Results: Heritability estimates of most of the traits were medium to high with the LSML (0.20±0.44 to 0.49±0.71) and Bayesian approach (0.24±0.009 to 0.61±0.017), respectively. However, more reliable estimates were obtained using the Bayesian technique. A higher heritability estimate was obtained for AFC (0.61±0.017) followed by first lactation fat yield, first lactation solid-not fat yield, FSP, first lactation milk yield (FLMY), PL (0.60±0.013, 0.60±0.006, 0.57±0.024, 0.57±0.020, 0.42±0.025); while a lower estimate for HL (0.38±0.034) by MTGSAM approach. Genetic and phenotypic correlations were negative for AFC-PL, AFC-HL, FSP-PL, and FSP-HL (-0.59±0.19, -0.59±0.24, -0.38±0.101 and -0.34±0.076) by the multi-trait Bayesian analysis. Conclusion: Breed and traits of economic importance are important for selection decisions to ensure genetic gain in cattle breeding programs. Favourable genetic and phenotypic correlations of AFC with production and lifetime traits compared to that of FSP indicated better scope of AFC for indirect selection of life-time traits at an early age. This also indicated that the present Tharparkar cattle herd had sufficient genetic diversity through the selection of AFC for the improvement of first lactation production and lifetime traits.

• Journal of the Korean Institute of Gas
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• v.27 no.3
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• pp.123-133
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• 2023

Commercial hydrogen fuel cell vehicles are charged by compressing gaseous hydrogen to high pressure and storing it in a storage tank in the vehicle. This process causes the temperature of the gas to rise, to ensure the safety to storage tanks, the temperature is limited. Therefore, a heat transfer model is needed to explain this temperature rise. The heat transfer model includes the convective heat transfer phenomenon, and accurate estimation is required. In this study, the convective heat transfer coefficient in the hydrogen fueling process was calculated and compared using various correlation equations considering physical phenomena. The hydrogen fueling process was classified into the fueling line from the dispenser to the tank inlet and the storage tank in the vehicle, and the convective heat transfer coefficients were estimated according to process parameters such as mass flow rate, diameter, temperature and pressure. As a result, in the case of the inside of the filling line, the convective heat transfer coefficient was about 1000 times larger than that of the inside of the storage tank, and in the case of the outside of the filling line, the convective heat transfer coefficient was about 3 times larger than that of the outside of the storage tank. Finally, as a result of a comprehensive analysis of convective heat transfer coefficients in each process, it was found that outside the storage tank was lowest in the entire hydrogen fueling process, thus dominated the heat transfer phenomenon.

• Advances in nano research
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• v.16 no.4
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• pp.375-394
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• 2024

The extensive utilization of concrete has given rise to environmental concerns, specifically concerning the depletion of river sand. To address this issue, waste deposits can provide manufactured-sand (MS) as a substitute for river sand. The objective of this study is to explore the application of machine learning techniques to facilitate the production of manufactured-sand concrete (MSC) containing stone nano-powder through estimating the splitting tensile strength (STS) containing compressive strength of cement (CSC), tensile strength of cement (TSC), curing age (CA), maximum size of the crushed stone (Dmax), stone nano-powder content (SNC), fineness modulus of sand (FMS), water to cement ratio (W/C), sand ratio (SR), and slump (S). To achieve this goal, a total of 310 data points, encompassing nine influential factors affecting the mechanical properties of MSC, are collected through laboratory tests. Subsequently, the gathered dataset is divided into two subsets, one for training and the other for testing; comprising 90% (280 samples) and 10% (30 samples) of the total data, respectively. By employing the generated dataset, novel models were developed for evaluating the STS of MSC in relation to the nine input features. The analysis results revealed significant correlations between the CSC and the curing age CA with STS. Moreover, when delving into sensitivity analysis using an empirical model, it becomes apparent that parameters such as the FMS and the W/C exert minimal influence on the STS. We employed various loss functions to gauge the effectiveness and precision of our methodologies. Impressively, the outcomes of our devised models exhibited commendable accuracy and reliability, with all models displaying an R-squared value surpassing 0.75 and loss function values approaching insignificance. To further refine the estimation of STS for engineering endeavors, we also developed a user-friendly graphical interface for our machine learning models. These proposed models present a practical alternative to laborious, expensive, and complex laboratory techniques, thereby simplifying the production of mortar specimens.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.1
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• pp.1-13
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• 2024

The southwestern part of the East Sea is known to have a high primary productivity compared to those in the northern and eastern parts, which is attributed to nutrients supplies either by Tsushima Warm Current or by coastal upwelling. However, research on the biological pump in this area is limited. We developed machine learning models to estimate net community production (NCP), a measure of biological pump, with high spatial and time scales of 4 km and 8 days, respectively. The models were fed with the input parameters of sea surface temperature, chlorophyll-a, mixed layer depths, and photosynthetically active radiation and trained with observed NCP derived from high resolution measurements of surface O₂/Ar. The root mean square error between the predicted values by the best performing machine model and the observed NCP was 6 mmol O₂ m^-2 d^-1, corresponding to 15% of the average of observed NCP. The NCP in the central part of the Ulleung Basin was highest in March at 49 mmol O₂ m^-2 d^-1 and lowest in June and July at 18 mmol O₂ m^-2 d^-1. These seasonal variations were similar to the vertical nitrate flux based on the ³He gas exchange rate and to the particulate organic carbon flux estimated by the ²³⁴Th disequilibrium method. To expand this method, which produces NCP estimate for spring and summer, to autumn and winter, it is necessary to devise a way to correct bias in NCP by the entrainment of subsurface waters during the seasons.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.155-163
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• 2009

In text-to-speech systems, the conversion of text into prosodic parameters is necessarily composed of three steps. These are the placement of prosodic boundaries. the determination of segmental durations, and the specification of fundamental frequency contours. Prosodic boundaries. as the most important and basic parameter. affect the estimation of durations and fundamental frequency. Break prediction is an important step in text-to-speech systems as break indices (BIs) have a great influence on how to correctly represent prosodic phrase boundaries, However. an accurate prediction is difficult since BIs are often chosen according to the meaning of a sentence or the reading style of the speaker. In Japanese, the prediction of an accentual phrase boundary (APB) and major phrase boundary (MPB) is particularly difficult. Thus, this paper presents a method to complement the prediction errors of an APB and MPB. First, we define a subtle BI in which it is difficult to decide between an APB and MPB clearly as a variable break (VB), and an explicit BI as a fixed break (FB). The VB is chosen using the classification and regression tree, and multiple prosodic targets in relation to the pith and duration are then generated. Finally. unit-selection is conducted using multiple prosodic targets. In the MOS test result. the original speech scored a 4,99. while proposed method scored a 4.25 and conventional method scored a 4.01. The experimental results show that the proposed method improves the naturalness of synthesized speech.

• Animal Bioscience
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• v.37 no.7
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• pp.1168-1176
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• 2024

Objective: As a charismatic species, cashmere goats have rich genetic resources. In the Inner Mongolia Autonomous Region, there are three cashmere goat varieties named and approved by the state. These goats are renowned for their high cashmere production and superior cashmere quality. Therefore, it is vitally important to protect their genetic resources as they will serve as breeding material for developing new varieties in the future. Methods: Three breeds including Inner Mongolia cashmere goats (IMCG), Hanshan White cashmere goats (HS), and Ujimqin white cashmere goats (WZMQ) were studied. IMCG were of three types: Aerbas (AEBS), Erlangshan (ELS), and Alashan (ALS). Nine DNA samples were collected for each population, and they were genomically re-sequenced to obtain high-depth data. The genetic diversity parameters of each population were estimated to determine selection intensity. Principal component analysis, phylogenetic tree construction and genetic differentiation parameter estimation were performed to determine genetic relationships among populations. Results: Samples from the 45 individuals from the five goat populations were sequenced, and 30,601,671 raw single nucleotide polymorphisms (SNPs) obtained. Then, variant calling was conducted using the reference genome, and 17,214,526 SNPs were retained after quality control. Individual sequencing depth of individuals ranged from 21.13× to 46.18×, with an average of 28.5×. In the AEBS, locus polymorphism (79.28) and expected heterozygosity (0.2554) proportions were the lowest, and the homologous consistency ratio (0.1021) and average inbreeding coefficient (0.1348) were the highest, indicating that this population had strong selection intensity. Conversely, ALS and WZMQ selection intensity was relatively low. Genetic distance between HS and the other four populations was relatively high, and genetic exchange existed among the other four populations. Conclusion: The Inner Mongolia cashmere goat (AEBS type) population has a relatively high selection intensity and a low genetic diversity. The IMCG (ALS type) and WZMQ populations had relatively low selection intensity and high genetic diversity. The genetic distance between HS and the other four populations was relatively high, with a moderate degree of differentiation. Overall, these genetic variations provide a solid foundation for resource identification of Inner Mongolia Autonomous Region cashmere goats in the future.

• Structural Engineering and Mechanics
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• v.90 no.6
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• pp.611-633
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• 2024

This study intends to investigate the response of multi-cell (MC) beams to flexural loads in which the primary reinforcement is composed of both metallic and non-metallic materials. "Multi-cell" describes beam sections with multiple longitudinal voids separated by thin webs. Seven reinforced concrete MC beams measuring 300×200×1800 mm were tested under flexural loadings until failure. Two series of beams are formed, depending on the type of main reinforcement that is being used. A control RC beam with no openings and six MC beams are found in these two series. Series one and two are reinforced with metallic and non-metallic main reinforcement, respectively, in order to maintain a constant reinforcement ratio. The first crack, ultimate load, deflection, ductility index, energy absorption, strain characteristics, crack pattern, and failure mode were among the structural parameters of the beams under investigation that were documented. The primary variables that vary are the kind of reinforcing materials that are utilized, as well as the kind and quantity of mesh layers. The outcomes of this study that looked at the experimental and numerical performance of ferrocement reinforced concrete MC beams are presented in this article. Nonlinear finite element analysis (NLFEA) was performed with ANSYS-16.0 software to demonstrate the behavior of composite MC beams with holes. A parametric study is also carried out to investigate the factors, such as opening size, that can most strongly affect the mechanical behavior of the suggested model. The experimental and numerical results obtained demonstrate that the FE simulations generated an acceptable degree of experimental value estimation. It's also important to demonstrate that, when compared to the control beam, the MC beam reinforced with geogrid mesh (MCGB) decreases its strength capacity by a maximum of 73.33%. In contrast, the minimum strength reduction value of 16.71% is observed in the MC beams reinforced with carbon reinforcing bars (MCCR). The findings of the experiments on MC beams with openings demonstrate that the presence of openings has a significant impact on the behavior of the beams, as there is a decrease in both the ultimate load and maximum deflection.

• Journal of Animal Science and Technology
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• v.66 no.4
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• pp.682-701
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• 2024

This study estimated the heritabilities (h²) and genetic and phenotypic correlations between reproductive traits, including calving interval (CI), age at first calving (AFC), gestation length (GL), number of artificial inseminations per conception (NAIPC), and carcass traits, including carcass weight (CWT), eye muscle area (EMA), backfat thickness (BF), and marbling score (MS) in Korean Hanwoo cows. In addition, the accuracy of genomic predictions of breeding values was evaluated by applying the genomic best linear unbiased prediction (GBLUP) and the weighted GBLUP (WGBLUP) method. The phenotypic data for reproductive and carcass traits were collected from 1,544 Hanwoo cows, and all animals were genotyped using Illumina Bovine 50K single nucleotide polymorphism (SNP) chip. The genetic parameters were estimated using a multi-trait animal model using the MTG2 program. The estimated h² for CI, AFC, GL, NAIPC, CWT, EMA, BF, and MS were 0.10, 0.13, 0.17, 0.11, 0.37, 0.35, 0.27, and 0.45, respectively, according to the GBLUP model. The GBLUP accuracy estimates ranged from 0.51 to 0.74, while the WGBLUP accuracy estimates for the traits under study ranged from 0.51 to 0.79. Strong and favorable genetic correlations were observed between GL and NAIPC (0.61), CWT and EMA (0.60), NAIPC and CWT (0.49), AFC and CWT (0.48), CI and GL (0.36), BF and MS (0.35), NAIPC and EMA (0.35), CI and BF (0.30), EMA and MS (0.28), CI and AFC (0.26), AFC and EMA (0.24), and AFC and BF (0.21). The present study identified low to moderate positive genetic correlations between reproductive and CWT traits, suggesting that a heavier body weight may lead to a longer CI, AFC, GL, and NAIPC. The moderately positive genetic correlation between CWT and AFC, and NAIPC, with a phenotypic correlation of nearly zero, suggesting that the genotype-environment interactions are more likely to be responsible for the phenotypic manifestation of these traits. As a result, the inclusion of these traits by breeders as selection criteria may present a good opportunity for developing a selection index to increase the response to the selection and identification of candidate animals, which can result in significantly increased profitability of production systems.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1822-1829
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• 2024

The search for materials that serve as good shields for radiation has become very important in light of the increasing exposure to ionizing radiation in various vital sectors. The aim is to search for novel materials with better radiation shielding properties that are stable, nontoxic, and abundant and environment friendly. The solidstate reaction approach has been used to synthesize a few ceramics, including BaZr_XTi_1-XO₃, Ba_1-XLa_XTiO₃ and Ba_1-XLa_XZr_XTi_1-XO₃ (with x = 0.10) i.eBaZr_0.10Ti_0.90O₃ (BZT), Ba_0.90La_0.10TiO₃ (BLT), and Ba_0.90La_0.10Zr_0.10Ti_0.90O₃ (BLZT). The density of the prepared samples varies from 6.3471 to 11.6003 g/cm³. The X-ray diffraction technique, shows strong peaks to confirm the crystalline structure of prepared ceramic samples. Using the G-P fitting approach, the advanced radiation shielding parameters (build-up factor) have been evaluated in the photon energy region of 1.5 keV-15 MeV. It is observed from the results that exposure buildup factor (EBF) and energy absorption buildup factor (EABF) are maximum for BLZT and has the minimum value for BZT in the entire photon energy regime. The results of this work should be useful in radiation shielding applications such as in industry, medicine, and nuclear engineering.