• Structural Engineering and Mechanics
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• v.48 no.1
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• pp.41-56
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• 2013

Initiation and growth of delamination is a great concern of designers of composite structures. Interface elements with de-cohesive constitutive law in the content of continuum damage mechanics can be used to predict initiation and growth of delamination in single and mixed mode conditions. In this paper, an interface element based on the cohesive zone method has been developed to simulate delaminatoin growth of post-buckled laminate under fatigue loading. The model was programmed as the user element and user material by the "User Programmable Features" in ANSYS finite element software. The interface element is a three-dimensional 20 node brick with small thickness. Because of mixed-mode condition of stress field at the delamination-front of post-buckled laminates, a mixed-mode bilinear constitutive law has been used as user material in this model. The constitutive law of interface element has been verified by modelling of a single element. A composite laminate with initial delamination under quasi-static compressive Loading available from literature has been remodeled with the present approach. Moreover, it will be shown that, the closer the delamination to the free surface of laminate, the slower the delamination growth under compressive fatigue loading. The effects of laminate configuration on delamination growth are also investigated.

• Genomics & Informatics
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• v.20 no.1
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• pp.8.1-8.14
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• 2022

Despite the success of recent genome-wide association studies investigating longitudinal traits, a large fraction of overall heritability remains unexplained. This suggests that some of the missing heritability may be accounted for by gene-gene and gene-time/environment interactions. In this paper, we develop a Bayesian variable selection method for longitudinal genetic data based on mixed models. The method jointly models the main effects and interactions of all candidate genetic variants and non-genetic factors and has higher statistical power than previous approaches. To account for the within-subject dependence structure, we propose a grid-based approach that models only one fixed-dimensional covariance matrix, which is thus applicable to data where subjects have different numbers of time points. We provide the theoretical basis of our Bayesian method and then illustrate its performance using data from the 1000 Genome Project with various simulation settings. Several simulation studies show that our multivariate method increases the statistical power compared to the corresponding univariate method and can detect gene-time/ environment interactions well. We further evaluate our method with different numbers of individuals, variants, and causal variants, as well as different trait-heritability, and conclude that our method performs reasonably well with various simulation settings.

• Genomics & Informatics
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• v.20 no.2
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• pp.16.1-16.12
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• 2022

Various methodologies for the genetic analysis of longitudinal data have been proposed and applied to data from large-scale genome-wide association studies (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with traits of interest and to detect SNP-time interactions. We recently proposed a grid-based Bayesian mixed model for longitudinal genetic data and showed that our Bayesian method increased the statistical power compared to the corresponding univariate method and well detected SNP-time interactions. In this paper, we further analyze longitudinal obesity-related traits such as body mass index, hip circumference, waist circumference, and waist-hip ratio from Korea Association Resource data to evaluate the proposed Bayesian method. We first conducted GWAS analyses of cross-sectional traits and combined the results of GWAS analyses through a meta-analysis based on a trajectory model and a random-effects model. We then applied our Bayesian method to a subset of SNPs selected by meta-analysis to further discover SNPs associated with traits of interest and SNP-time interactions. The proposed Bayesian method identified several novel SNPs associated with longitudinal obesity-related traits, and almost 25% of the identified SNPs had significant p-values for SNP-time interactions.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.231-239
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• 2015

A Poisson model is the first choice for counts data. Quasi Poisson or negative binomial models are usually used in cases of over (or under) dispersed data. However, these models might be unsuitable if the data consist of excessive number of zeros (zero inflated data). For zero inflated counts data, Zero Inflated Poisson (ZIP) or Zero Inflated Negative Binomial (ZINB) models are recommended to address the issue. In this paper, we further considered a situation where zero inflated data are spatially correlated. A mixed effect model with random effects that account for spatial autocorrelation is used to fit the data.

• Animal Bioscience
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• v.35 no.5
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• pp.648-658
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• 2022

Objective: The identification of nonlinear mixed models that describe the growth trajectory of New Zealand rabbits was performed based on weight records and carcass measures obtained using ultrasonography. Methods: Phenotypic records of body weight (BW) and loin eye area (LEA) were collected from 66 animals raised in a didactic-productive module of cuniculture located in the southern Piaui state, Brazil. The following nonlinear models were tested considering fixed parameters: Brody, Gompertz, Logistic, Richards, Meloun 1, modified Michaelis-Menten, Santana, and von Bertalanffy. The coefficient of determination (R²), mean squared error, percentage of convergence of each model (%C), mean absolute deviation of residuals, Akaike information criterion (AIC), and Bayesian information criterion (BIC) were used to determine the best model. The model that best described the growth trajectory for each trait was also used under the context of mixed models, considering two parameters that admit biological interpretation (A and k) with random effects. Results: The von Bertalanffy model was the best fitting model for BW according to the highest value of R² (0.98) and lowest values of AIC (6,675.30) and BIC (6,691.90). For LEA, the Logistic model was the most appropriate due to the results of R² (0.52), AIC (783.90), and BIC (798.40) obtained using this model. The absolute growth rates estimated using the von Bertalanffy and Logistic models for BW and LEA were 21.51g/d and 3.16 cm², respectively. The relative growth rates at the inflection point were 0.028 for BW (von Bertalanffy) and 0.014 for LEA (Logistic). Conclusion: The von Bertalanffy and Logistic models with random effect at the asymptotic weight are recommended for analysis of ponderal and carcass growth trajectories in New Zealand rabbits. The inclusion of random effects in the asymptotic weight and maturity rate improves the quality of fit in comparison to fixed models.

• Journal of Radiation Protection and Research
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• v.46 no.3
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• pp.83-97
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• 2021

Background: The lifetime risk of lung cancer incidence due to radiation for nonsmokers is overestimated because of the use of the average cancer baseline risk among a mixed population, including smokers. In recent years, the generalized multiplicative (GM)-excess relative risk (ERR) model has been developed in the life span study of atomic bomb survivors to consider the joint effect of radiation and smoking. Based on this background, this paper discusses the issues of radiation risk assessment considering smoking in two parts. Materials and Methods: In Part 1, we proposed a simple method of estimating the baseline risk for nonsmokers using current smoking data. We performed sensitivity analysis on baseline risk estimation to discuss the birth cohort effects. In Part 2, we applied the GM-ERR model for Japanese smokers to calculate lifetime attributable risk (LAR). We also performed a sensitivity analysis using other ERR models (e.g., simple additive (SA)-ERR model). Results and Discussion: In Part 1, the lifetime baseline risk from mixed population including smokers to nonsmokers decreased by 54% (44%-60%) for males and 24% (18%-29%) for females. In Part 2, comparison of LAR between SA- and GM-ERR models showed that if the radiation dose was ≤200 mGy or less, the difference between these ERR models was within the standard deviation of LAR due to the uncertainty of smoking information. Conclusion: The use of mixed population for baseline risk assessment overestimates the risk for lung cancer due to low-dose radiation exposure in Japanese males.

• Journal of Microbiology and Biotechnology
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• v.15 no.2
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• pp.337-345
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• 2005

The degradation of phenanthrene, a model PAH compound, by microorganisms either in the mixed culture or individual strain, isolated from oil-contaminated soil in oil refmery vicinity sites, was examined. The effects of pH, temperature, initial concentration of phenanthrene, and the addition of carbon sources on biodegradation potential were also investigated. Results showed that soil samples collected from four oil refinery sites in Korea had different degrees of PAH contamination and different indigenous phenanthrene-degrading microorganisms. The optimal conditions for phenanthrene biodegradation were determined to be 30$^{circ}C$ and pH 7.0. A significantly positive relationship was observed between the microbial growth and the rate of phenanthrene degradation. However, the phenanthrene biodegradation capability of the mixed culture was not related to the degree of PAH contamination in soil. In low phenanthrene concentration, the growth and biodegradation rates of the mixed cultures did not increase over those of the individual strain, especially IC10. High concentration of phenanthrene inhibited the growth of microbial strains and biodegradation of phenanthrene, but was less inhibitory on the mixed culture. Finally, when non-ionic surfactants such as Brij 30 and Brij 35 were present at the level above critical micelle concentrations (CMCs), phenanthrene degradation was completely inhibited and delayed by the addition of Triton X100 and Triton N101.

• 유체기계공업학회:학술대회논문집
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• 1998.12a
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• pp.33-41
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• 1998

In this study, the performance prediction programs for centrifugal pumps are developed. To estimate the losses in the centrifugal pump impellers, two-zone model and TEIS(two elements in series) model are applied to the program. The basic concept of two zone model considers the primary zone that is an isentropic core flow and the secondary zone that is non-isentropic region at the impeller exit. The flows through two different zones mixed out at the impeller exit and the mixing process occurs with an increase in entropy, a decrease in total pressure. The level of the core flow diffusion in a impeller was calculated using TEIS(two elements in series) model. The effects of various parameters which are used in this program on the prediction of head and efficiency are discussed. The correlation curves to select the effectiveness of the primitive TEIS model were suggested according to the specific speed of the centrifugal pumps.

• The KSFM Journal of Fluid Machinery
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• v.2 no.1 s.2
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• pp.56-63
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• 1999

In this study, the performance prediction programs for centrifugal pumps are developed. To estimate the losses in the centrifugal pump impellers, a two-zone model and TEIS(two elements in series) model are applied to the program. The basic concept of a two zone model considers the primary zone that is an isentropic core flow and the secondary zone that has a non-isentropic region at the impeller exit. The flow goes through two different zones and is mixed out at the impeller exit and the mixing process occurs with an increase in entropy, a decrease in total pressure. The level of the core flow diffusion in an impeller was calculated using TEIS(two elements in series) model. The effects of various parameters which are used in this program on the prediction of head and efficiency are discussed. The correlation curves used to select the effectiveness of the primitive TEIS model were suggested according to the specific speed of the centrifugal pumps.

• Food Science and Biotechnology
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• v.16 no.5
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• pp.753-758
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• 2007

This study was conducted to investigate the antioxidant activity of paprika in the lard-pork model system adding ground fresh paprika (3%) and paprika powders (5%). Paprika powders were obtained through 4 drying methods (freeze, vacuum, far infrared-ray, and hot-air). In the lard and meat-fat mixture (containing lard 30%) containing paprika powders, the rate of increase in the peroxide value (POV) and thiobarbituric acid (TBA) value decreased notably during the refrigerated storage ($4^{\circ}C$) compared to the control without paprika. Therefore, paprika powders showed potent antioxidant activity and especially the freeze dried paprika powder revealed the most effective activity among them. However, its antioxidant activity was still lower than that of the fresh paprika because the addition of fresh paprika in the lard and meat-fat mixture merely increased the POV and TBA value. In linoleic acid oxidation, the addition of capsanthin 500 ppm to mixed linoleic acid and 10 ppm of $FeCl_3$ (LF) inhibited the formation of peroxides by 15.2% compared to LF, showing its iron scavenging ability. When mixed antioxidants (${\beta}$-carotene 200 ppm + ascorbic acid 100 ppm, capsanthin 200 ppm + ascorbic acid 100 ppm) were added in LF, synergistic effects were obtained with 57.7 and 60.4% of inhibition of peroxide formation, respectively.