• Title/Summary/Keyword: linear growth model

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Electromagnetic Electron-Cyclotron Wave for Ring Distribution with Alternating Current (AC) Electric Field in Saturn Magnetosphere

  • Haridas, Annex Edappattu;Kanwar, Shefali;Pandey, Rama Shankar
    • Journal of Astronomy and Space Sciences
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    • v.39 no.2
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    • pp.35-42
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    • 2022
  • During their respective missions, the spacecraft Voyager and Cassini measured several Saturn magnetosphere parameters at different radial distances. As a result of information gathered throughout the journey, Voyager 1 discovered hot and cold electron distribution components, number density, and energy in the 6-18 Rs range. Observations made by Voyager of intensity fluctuations in the 20-30 keV range show electrons are situated in the resonance spectrum's high energy tail. Plasma waves in the magnetosphere can be used to locate Saturn's inner magnetosphere's plasma clusters, which are controlled by Saturn's spin. Electromagnetic electron cyclotron (EMEC) wave ring distribution function has been investigated. Kinetic and linear approaches have been used to study electromagnetic cyclotron (EMEC) wave propagation. EMEC waves' stability can be assessed by analyzing the dispersion relation's effect on the ring distribution function. The primary goal of this study is to determine the impact of the magnetosphere parameters which is observed by Cassini. The magnetosphere of Saturn has also been observed. When the plasma parameters are increased as the distribution index, the growth/damping rate increases until the magnetic field model affects the magnetic field at equator, as can be seen in the graphs. We discuss the outputs of our model in the context of measurements made in situ by the Cassini spacecraft.

Association of growth hormone and insulin-like growth factor I genotype with body weight, dominance of body weight, and mRNA expression in Korat slow-growing chickens

  • Sinpru, Panpradub;Bunnom, Rujjira;Poompramun, Chotima;Kaewsatuan, Pramin;Sornsan, Sirangkun;Kubota, Satoshi;Molee, Wittawat;Molee, Amonrat
    • Animal Bioscience
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    • v.34 no.12
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    • pp.1886-1894
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    • 2021
  • Objective: Growth hormone (GH) and insulin-like growth factor I (IGF-I) play a critical role in animal growth rates. We aimed to investigate the effect of GH and IGF-I genotypes on body weight (BW), dominance, and gene expression in slow-growing chickens at different ages. Methods: A total of 613 Korat chickens (KRs) were bred and divided into three groups by genotype - A1A1, A1A3, and A3A3 for GH and AA, AC, and CC for IGF-I. Chickens were weighed every two weeks, and liver and breast muscle tissues were collected at 10 weeks of age. Genetic parameters of KRs were estimated using ASReml software. The GH and IGF-I mRNA levels were measured by quantitative polymerase chain reaction. Significant differences between traits were analyzed using the generalized linear model. Results: A significant effect of GH genotypes on BW was found at most ages, and the A1A1 genotype had the highest value of BW. Compared with the A3A3 genotype, the A1A1 and A1A3 genotypes showed a higher dominance effect at 0 and 2 weeks, and genotype A1A1 had the highest value of dominance at 8 weeks of age. A difference in GH mRNA levels between genotypes was detected in breast muscle at 6 weeks and in the liver tissue at 2 weeks. In the case of IGF-I gene, the AA genotype had the highest BW at the beginning of life. Significant differences in BW dominance were found at 2 weeks. However, IGF-I mRNA levels were not different among genotypes in both breast muscles and liver tissues. Conclusion: Our results revealed that GH and IGF-I influence growth, but may not be involved in heterosis. GH can be used as a marker gene in selection programs for growth because the homozygous genotype (A1A1) had the highest BW at all ages. The IGF-I is not a useful marker gene for selection programs.

Stochastic projection on international migration using Coherent functional data model (일관성 함수적 자료모형을 활용한 국제인구이동의 확률적 예측)

  • Kim, Soon-Young;Oh, Jinho
    • The Korean Journal of Applied Statistics
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    • v.32 no.4
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    • pp.517-541
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    • 2019
  • According to the OECD (2015) and UN (2017), Korea was classified as an immigration country. The designation as an immigration country means that net migration will remain positive and international migration is likely to affect population growth. KOSTAT (2011) used a model with more than 15 parameters to divide sexes, immigration and emigration based on the Wilson (2010) model, which takes into account population migration factors. Five years later, we assume the average of domestic net migration rate for the last five years and foreign government policy likely quota. However, both of these results were conservative estimates of international migration and provide different results than those used by the OECD and UN to classify an immigration country. In this paper, we proposed a stochastic projection on international migration using nonparametric model (FDM by Hyndman and Ullah (2007) and Coherent FDM by Hyndman et al. (2013)) that uses a functional data model for the international migration data of Korea from 2000-2017, noting the international migration such as immigration, emigration and net migration is non-linear and not linear. According to the result, immigration rate will be 1.098(male), 1.026(female) in 2018 and 1.228(male), 1.152(female) in 2025 per 1000 population, and the emigration rate will be 0.907(male), 0.879(female) in 2018 and 0.987(male), 0.959(female) in 2025 per 1000 population. Thus the net migration is expected to increase to 0.191(male), 0.148(female) in 2018 and 0.241(male), 0.192(female) in 2025 per 1000 population.

Ground-based model study for spaceflight experiments under microgravity environments on thermo-solutal convection during physical vapor transport of mercurous chloride

  • Choi, Jeong-Gil;Lee, Kyong-Hwan;Kim, Geug-Tae
    • Journal of the Korean Crystal Growth and Crystal Technology
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    • v.17 no.6
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    • pp.256-263
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    • 2007
  • For $P_B=50Torr,\;P_T=5401Torr,\;T_S=450^{\circ}C,\;{\Delta}T=20K$, Ar=5, Pr=3.34, Le=0.01, Pe=4.16, Cv=1.05, adiabatic and linear thermal profiles at walls, the intensity of solutal convection (solutal Grashof number $Grs=7.86{\times}10^6$) is greater than that of thermal convection (thermal Grashof number $Grt=4.83{\times}10^5$) by one order of magnitude, which is based on the solutally buoyancy-driven convection due to the disparity in the molecular weights of the component A ($Hg_2Cl_2$) and B (He). With increasing the partial pressure of component B from 20 up to 800 Torr, the rate is decreased exponentially. It is also interesting that as the partial pressure of component B is increased by a factor of 2, the rate is approximately reduced by a half. For systems under consideration, the rate increases linearly and directly with the dimensionless Peclet number which reflects the intensity of condensation and sublimation at the crystal and source region. The convective transport decreases with lower g level and is changed to the diffusive mode at $0.1g_0$. In other words, for regions in which the g level is $0.1g_0$ or less, the diffusion-driven convection results in a parabolic velocity profile and a recirculating cell is not likely to occur. Therefore a gravitational acceleration level of less than $0.1g_0$ can be adequate to ensure purely diffusive transport.

Use of Adaptive Meshes in Simulation of Combustion Phenomena

  • Yi, Sang-Chul;Koo, Sang-Man
    • Proceedings of the Korea Association of Crystal Growth Conference
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    • 1996.06b
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    • pp.285-309
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    • 1996
  • Non oxide ceramics such as nitrides of transition metals have shown significant potential for future economic impact, in diverse applications in ceramic, aerospace and electronic industries, as refractory products, abrasives and cutting tools, aircraft components, and semi-conductor substrates amid others. Combustion synthesis has become an attractive alternative to the conventional furnace technology to produce these materials cheaply, faster and at a higher level of purity. However he process os highly exothermic and manifests complex dynamics due to its strongly non-linear nature. In order to develop an understanding of this process and to study the effect of operational parameters on the final outcome, numerical modeling is necessary, which would generated essential knowledge to help scale-up the process. the model is based on a system of parabolic-hyperbolic partial differential equations representing the heat, mass and momentum conservation relations. The model also takes into account structural change due to sintering and volumetric expansion, and their effect on the transport properties of the system. The solutions of these equations exhibit steep moving spatial gradients in the form of reaction fronts, propagating in space with variable velocity, which gives rise to varying time scales. To cope with the possibility of extremely abrupt changes in the values of the solution over very short distances, adaptive mesh techniques can be applied to resolve the high activity regions by ordering grid points in appropriate places. To avoid a control volume formulation of the solution of partial differential equations, a simple orthogonal, adaptive-mesh technique is employed. This involves separate adaptation in the x and y directions. Through simple analysis and numerical examples, the adaptive mesh is shown to give significant increase in accuracy in the computations.

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Sintering process optimization of ZnO varistor materials by machine learning based metamodel (기계학습 기반의 메타모델을 활용한 ZnO 바리스터 소결 공정 최적화 연구)

  • Kim, Boyeol;Seo, Ga Won;Ha, Manjin;Hong, Youn-Woo;Chung, Chan-Yeup
    • Journal of the Korean Crystal Growth and Crystal Technology
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    • v.31 no.6
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    • pp.258-263
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    • 2021
  • ZnO varistor is a semiconductor device which can serve to protect the circuit from surge voltage because its non-linear I-V characteristics by controlling the microstructure of grain and grain boundaries. In order to obtain desired electrical properties, it is important to control microstructure evolution during the sintering process. In this research, we defined a dataset composed of process conditions of sintering and relative permittivity of sintered body, and collected experimental dataset with DOE. Meta-models can predict permittivity were developed by learning the collected experimental dataset on various machine learning algorithms. By utilizing the meta-model, we can derive optimized sintering conditions that could show the maximum permittivity from the numerical-based HMA (Hybrid Metaheuristic Algorithm) optimization algorithm. It is possible to search the optimal process conditions with minimum number of experiments if meta-model-based optimization is applied to ceramic processing.

Genome-wide association studies to identify quantitative trait loci and positional candidate genes affecting meat quality-related traits in pigs

  • Jae-Bong Lee;Ji-Hoon Lim;Hee-Bok Park
    • Journal of Animal Science and Technology
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    • v.65 no.6
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    • pp.1194-1204
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    • 2023
  • Meat quality comprises a set of key traits such as pH, meat color, water-holding capacity, tenderness and marbling. These traits are complex because they are affected by multiple genetic and environmental factors. The aim of this study was to investigate the molecular genetic basis underlying nine meat quality-related traits in a Yorkshire pig population using a genome-wide association study (GWAS) and subsequent biological pathway analysis. In total, 45,926 single nucleotide polymorphism (SNP) markers from 543 pigs were selected for the GWAS after quality control. Data were analyzed using a genome-wide efficient mixed model association (GEMMA) method. This linear mixed model-based approach identified two quantitative trait loci (QTLs) for meat color (b*) on chromosome 2 (SSC2) and one QTL for shear force on chromosome 8 (SSC8). These QTLs acted additively on the two phenotypes and explained 3.92%-4.57% of the phenotypic variance of the traits of interest. The genes encoding HAUS8 on SSC2 and an lncRNA on SSC8 were identified as positional candidate genes for these QTLs. The results of the biological pathway analysis revealed that positional candidate genes for meat color (b*) were enriched in pathways related to muscle development, muscle growth, intramuscular adipocyte differentiation, and lipid accumulation in muscle, whereas positional candidate genes for shear force were overrepresented in pathways related to cell growth, cell differentiation, and fatty acids synthesis. Further verification of these identified SNPs and genes in other independent populations could provide valuable information for understanding the variations in pork quality-related traits.

Genetic Parameters of Pre-adjusted Body Weight Growth and Ultrasound Measures of Body Tissue Development in Three Seedstock Pig Breed Populations in Korea

  • Choy, Yun Ho;Mahboob, Alam;Cho, Chung Il;Choi, Jae Gwan;Choi, Im Soo;Choi, Tae Jeong;Cho, Kwang Hyun;Park, Byoung Ho
    • Asian-Australasian Journal of Animal Sciences
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    • v.28 no.12
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    • pp.1696-1702
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    • 2015
  • The objective of this study was to compare the effects of body weight growth adjustment methods on genetic parameters of body growth and tissue among three pig breeds. Data collected on 101,820 Landrace, 281,411 Yorkshire, and 78,068 Duroc pigs, born in Korean swine breeder farms since 2000, were analyzed. Records included body weights on test day and amplitude (A)-mode ultrasound carcass measures of backfat thickness (BF), eye muscle area (EMA), and retail cut percentage (RCP). Days to 90 kg body weight (DAYS90), through an adjustment of the age based on the body weight at the test day, were obtained. Ultrasound measures were also pre-adjusted (ABF, EMA, AEMA, ARCP) based on their test day measures. The (co)variance components were obtained with 3 multi-trait animal models using the REMLF90 software package. Model I included DAYS90 and ultrasound traits, whereas model II and III accounted DAYS90 and pre-adjusted ultrasound traits. Fixed factors were sex (sex) and contemporary groups (herd-year-month of birth) for all traits among the models. Additionally, model I and II considered a linear covariate of final weight on the ultrasound measure traits. Heritability ($h^2$) estimates for DAYS90, BF, EMA, and RCP ranged from 0.36 to 0.42, 0.34 to 0.43, 0.20 to 0.22, and 0.39 to 0.45, respectively, among the models. The $h^2$ estimates of DAYS90 from model II and III were also somewhat similar. The $h^2$ for ABF, AEMA, and ARCP were 0.35 to 0.44, 0.20 to 0.25, and 0.41 to 0.46, respectively. Our heritability estimates varied mostly among the breeds. The genetic correlations ($r_G$) were moderately negative between DAYS90 and BF (-0.29 to -0.38), and between DAYS90 and EMA (-0.16 to -0.26). BF had strong $r_G$ with RCP (-0.87 to -0.93). Moderately positive $r_G$ existed between DAYS90 and RCP (0.20 to 0.28) and between EMA and RCP (0.35 to 0.44) among the breeds. For DAYS90, model II and III, its correlations with ABF, AEMA, and ARCP were mostly low or negligible except the $r_G$ between DAYS90 and AEMA from model III (0.27 to 0.30). The $r_G$ between AEMA and ABF and between AEMA and ARCP were moderate but with negative and positive signs, respectively; also reflected influence of pre-adjustments. However, the $r_G$ between BF and RCP remained non-influential to trait pre-adjustments or covariable fits. Therefore, we conclude that ultrasound measures taken at a body weight of about 90 kg as the test final should be adjusted for body weight growth. Our adjustment formulas, particularly those for BF and EMA, should be revised further to accommodate the added variation due to different performance testing endpoints with regard to differential growth in body composition.

Genetic Aspects of the Growth Curve Parameters in Hanwoo Cows (한우 암소의 성장곡선 모수에 대한 유전적 경향)

  • Lee, Chang-U;Choe, Jae-Gwan;Jeon, Gi-Jun;Kim, Hyeong-Cheol
    • Journal of Animal Science and Technology
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    • v.48 no.1
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    • pp.29-38
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    • 2006
  • The objective of this study was to estimate genetic variances of growth curve parameters in Hanwoo cows. The data used in this study were records from 1,083 Hanwoo cows raised at Hanwoo Experiment Station, National Livestock Research Institute(NLRI). First evaluation model(Model I) fit year-season of birth and age of dam as fixed effects and second model(Model II) added age at the final weight as a linear covariate to Model I. Heritability estimates of A, b and k from Gompertz model were 0.22, 0.11 and 0.07 using modelⅠ and 0.28, 0.11 and 0.12 using modelⅡ. Those from Von Bertalanffy model were 0.22, 0.11 and 0.07 using modelⅠ, 0.28, 0.11 and 0.12 using modelⅡ. Heritability estimates of A, b and k from Logistic model were 0.14, 0.07 and 0.05 using modelⅠ, 0.18, 0.07 and 0.12 using modelⅡ. Heritability estimates of A from Gompertz model were higher than those from Von Bertalanffy model or Logistic model in both model Ⅰand model Ⅱ. Heritability estimates of b from Logistic model were higher than those from Gompertz model or Von Bertalanffy model in both modelⅠand model Ⅱ. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight, 12 month weight, 18 month weight, 24 month weight, 36 month weight were after linear age adjustment 0.27, 0.11, 0.19, 0.14, 0.16, 0.23, 0.52 and 0.32, respectively. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight and 24 month weight fit by Gompertz model were larger than those estimated from linearly adjusted data. Heritability estimates of 12 month weight, 18 month weight and 36 month weight fit by Von Bertalanffy model were larger than those estimated from linearly adjusted data. In the multitrait analyses for parameters from Gompertz model, genetic and phenotypic correlations between A and k parameters were -0.47 and -0.67 using modelⅠand -0.56 and -0.63 using model Ⅱ. Those between the A and b parameters were 0.69 and 0.34 using modelⅠand 0.72 and 0.37 using model Ⅱ. Those between the b and k parameters were -0.26 and 0.01 using modelⅠand -0.30 and 0.01 using model Ⅱ. In the multitrait analyses for parameters from Von Bertalanffy model, genetic and phenotypic correlations between A and k parameters were -0.49 and -0.67 suing model Ⅰ and -0.57 and -0.70 using modelⅡ. Those between the A and b parameters were 0.61 and 0.33 using modelⅠ and 0.60 and 0.30 using model Ⅱ. Those between the b and k parameters were -0.20 and 0.02 using modelⅠ and 0.16 and 0.00 using modelⅡ. In the multitrait analyses for parameters from Logistic model, genetic and phenotypic correlations between A and k parameters were -0.43 and -0.67 using model Ⅰ and -0.50 and -0.63 using modelⅡ. Those between the A and b parameters were 0.47 and 0.22 using modelⅠ and 0.38 and 0.24 using modelⅡ. Those between the b and k parameters were -0.09 and 0.02 using model Ⅰ and -0.02 and 0.13 using model Ⅱ.

Factors Associated With Post-Traumatic Growth in Patients With Cancer (암환자의 외상 후 성장에 영향을 미치는 요인)

  • Nam Pyo Lee;Jong Woo Kim;Myungjae Baik;Mi Ae Oh;A Ra Lee;Won Sub Kang
    • Korean Journal of Psychosomatic Medicine
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    • v.31 no.2
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    • pp.79-88
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    • 2023
  • Objectives : Cancer diagnosis causes significant distress while it may also bring positive change: post-traumatic growth. This study was conducted to analyze factors that affect post-traumatic growth. Methods : Medical records of 52 cancer patients who received psychiatric treatment at a university hospital in Seoul were reviewed and the correlation between post-traumatic growth and following factors were analyzed: Resilience, Anxious thoughts and tendencies, Mindful attention awareness, Acceptance attitude Results : Using Multiple Generalized Linear model, a positive correlation was found between post-traumatic growth and resilience (B=1.45, p<0.0001), mindful attention awareness (B=0.58, p=0.0030) and acceptance attitude (B=1.29, p=0.0003), while anxious thoughts and tendencies (B=-0.84, p<0.0001) had negative association. Conclusions : Factors that have a positive impact on post-traumatic growth were resilience, mindful attention awareness, acceptance attitude and a factor with a negative impact was anxious thoughts and tendencies; Factors that impact post-traumatic growth need to be taken into account, when approaching the treatment of cancer patients.