• Journal of Radiation Protection and Research
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• v.48 no.1
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• pp.28-43
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• 2023

Background: High-fidelity meteorological data is a prerequisite for the realistic simulation of atmospheric dispersion of radioactive materials near nuclear power plants (NPPs). However, many meteorological models frequently overestimate near-surface wind speeds, failing to represent local meteorological conditions near NPPs. This study presents a new high-resolution (approximately 1 km) meteorological downscaling method for modeling short-range (< 100 km) atmospheric dispersion of accidental NPP plumes. Materials and Methods: Six considerations from literature reviews have been suggested for a new dynamic downscaling method. The dynamic downscaling method is developed based on the Weather Research and Forecasting (WRF) model version 3.6.1, applying high-resolution land-use and topography data. In addition, a new subgrid-scale topographic drag parameterization has been implemented for a realistic representation of the atmospheric surface-layer momentum transfer. Finally, a year-long simulation for the Kori and Wolsong NPPs, located in southeastern coastal areas, has been made for 2016 and evaluated against operational surface meteorological measurements and the NPPs' on-site weather stations. Results and Discussion: The new dynamic downscaling method can represent multiscale atmospheric motions from the synoptic to the boundary-layer scales and produce three-dimensional local meteorological fields near the NPPs with a 1.2 km grid resolution. Comparing the year-long simulation against the measurements showed a salient improvement in simulating near-surface wind fields by reducing the root mean square error of approximately 1 m/s. Furthermore, the improved wind field simulation led to a better agreement in the Eulerian estimate of the local atmospheric dispersion. The new subgrid-scale topographic drag parameterization was essential for improved performance, suggesting the importance of the subgrid-scale momentum interactions in the atmospheric surface layer. Conclusion: A new dynamic downscaling method has been developed to produce high-resolution local meteorological fields around the Kori and Wolsong NPPs, which can be used in short-range atmospheric dispersion modeling near the NPPs.

• Geomechanics and Engineering
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• v.32 no.3
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• pp.255-270
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• 2023

One of the main parameters that affect the design of suction caisson-supported offshore structures is uplift behavior. Pull-out of suction caissons is profoundly utilized as the offshore wind turbine foundations accompany by a tensile resistance that is a function of a complex interaction between the caisson dimensions, geometry, wall roughness, soil type, load history, pull-out rate, and many other parameters. In this paper, a parametric study using a 3-D finite element model (FEM) of a single offshore suction caisson (SOSC) surrounded by saturated soil is performed to examine the effect of some key factors on the tensile resistance of the suction bucket foundation. Among the aforementioned parameters, caisson geometry and uplift loading as well as the difference between the tensile resistance and suction pressure on the behavior of the soil-foundation system including tensile capacity are investigated. For this purpose, a full model including 3-D suction caisson, soil, and soil-structure interaction (SSI) is developed in Abaqus based on the u-p formulation accounting for soil displacement (u) and pore pressure, P.The dynamic responses of foundations are compared and validated with the known results from the literature. The paper has focused on the effect of geometry change of 3-D SOSC to present the soil-structure interaction and the tensile capacity. Different 3-D caisson models such as triangular, pentagonal, hexagonal, and octagonal are employed. It is observed that regardless of the caisson geometry, by increasing the uplift loading rate, the tensile resistance increases. More specifically, it is found that the resistance to pull-out of the cylinder is higher than the other geometries and this geometry is the optimum one for designing caissons.

• Journal of the Korean Geotechnical Society
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• v.22 no.2
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• pp.41-53
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• 2006

The brittle materials like rocks show complicated strain-softening behavior after the peak which is hard to model using the classical constitutive models based on the relation between strain and stress tensors. A kinematically constrained three-dimensional microplane constitutive model is developed for granite. The model is verified by fitting the experimented data of Westerly granite and Bonnet granite. The triaxial behavior of granite is well reproduced by the model as well as the uniaxial behavior. We studied the development of the fracture zone in granite during blasting impact using the model with the standard finite element method. All the results obtained from the microplane model developed are compared to those from the linear elasticity model which is commonly used in many researches and practices. It is found that the nonlinearity of rocks sigificantly affects the results of analysis.

• Journal of Periodontal and Implant Science
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• v.53 no.1
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• pp.20-37
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• 2023

Purpose: Our pilot study showed that a 3-dimensional dual drug delivery scaffold (DDDS) loaded with Chinese herbs significantly increased the regenerated bone volume fraction. This study aimed to confirm the synergistic anti-inflammatory and osteogenic preclinical effects of this system. Methods: The targets and pathways of parthenolide and naringin were predicted. Three cell models were used to assess the anti-inflammatory effects of parthenolide and the osteogenic effects of naringin. First, the distance between the cementoenamel junction and alveolar bone crest (CEJ-ABC) and the bone mineral density (BMD) of surgical defects were measured in a rat model of periodontitis with periodontal fenestration defects. Additionally, the mRNA expression levels of matrix metallopeptidase 9 (MMP9) and alkaline phosphatase (ALP) were measured. Furthermore, the number of inflammatory cells and osteoclasts, as well as the protein expression levels of tumor necrosis factor-alpha (TNF-α) and levels of ALP were determined. Results: Target prediction suggested prostaglandin peroxidase synthase (PTGS2) as a potential target of parthenolide, while cytochrome P450 family 19 subfamily A1 (CYP19A1) and taste 2 receptor member 31 (TAS2R31) were potential targets of naringin. Parthenolide mainly targeted inflammation-related pathways, while naringin participated in steroid hormone synthesis and taste transduction. In vitro experiments revealed significant antiinflammatory effects of parthenolide on RAW264.7 cells, and significant osteogenic effects of naringin on bone marrow mesenchymal stem cells and MC3T3-E1 cells. DDDS loaded with parthenolide and naringin decreased the CEJ-ABC distance and increased BMD and ALP levels in a time-dependent manner. Inflammation was significantly alleviated after 14 days of DDDS treatment. Additionally, after 56 days, the DDDS group exhibited the highest BMD and ALP levels. Conclusions: DDDS loaded with parthenolide and naringin in a rat model achieved significant synergistic anti-inflammatory and osteogenic effects, providing powerful preclinical evidence.

• Composites Research
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• v.36 no.2
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• pp.92-100
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• 2023

In this paper, a machine learning and deep learning model for the design of circuit analog (CA) radar absorbing structure with a cross-dipole pattern on a glass fiber fabric reinforced plastic is presented. The proposed model can directly calculate reflection loss in the Ku-band (12-18 GHz) without three-dimensional electromagnetic numerical analysis based on the geometry of the Cross-Dipole pattern. For this purpose, the optimal learning model was derived by applying various machine learning and deep learning techniques, and the results calculated by the learning model were compared with the electromagnetic wave absorption characteristics obtained by 3D electromagnetic wave numerical analysis to evaluate the comparative advantages of each model. Most of the implemented models showed similar calculated results to the numerical results, but it was found that the Fully-Connected model could provide the most similar calculated results.

• Journal of Technologic Dentistry
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• v.46 no.2
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• pp.21-27
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• 2024

Purpose: This study aimed to analyze the stress distribution and deformation in implant abutments made from titanium (Ti-6Al-4V), zirconia, and polyetheretherketone (PEEK), including their screws and fixtures, under various loading conditions using finite element analysis (FEA). Methods: Three-dimensional models of the mandible with implant abutments were created using Siemens NX software (NX10.0.0.24, Siemens). FEA was conducted using Abaqus to simulate occlusal loads and assess stress distribution and deformation. Material properties such as Young's modulus and Poisson's ratio were assigned to each component based on literature and experimental data. Results: The FEA results revealed distinct stress distribution patterns among the materials. Titanium alloy abutments exhibited the highest stress resistance and the most uniform stress distribution, making them highly suitable for long-term stability. Zirconia abutments showed strong mechanical properties with higher stress concentration, indicating potential vulnerability to fracture despite their aesthetic advantages. PEEK abutments demonstrated the least stress resistance and higher deformation compared to other abutment materials, but offered superior shock absorption, though they posed a higher risk of mechanical failure under high load conditions. Conclusion: The study emphasizes the importance of selecting appropriate materials for dental implants. Titanium offers durability and uniform stress distribution, making it highly suitable for long-term stability. Zirconia provides aesthetic benefits but has a higher risk of fracture compared to titanium. PEEK excels in shock absorption but has a higher risk of mechanical failure compared to both titanium and zirconia. These insights can guide improved implant designs and material choices for various clinical needs.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.55-66
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• 2024

Gender classification techniques have received a lot of attention from researchers because they can be used in various fields such as forensics, surveillance systems, and demographic studies. As previous studies have shown that there are distinctive features between male and female gait, various techniques have been proposed to classify gender from three dimensional(3-D) gait data. However, some of the gait features extracted from 3-D gait data using existing techniques are similar or redundant to each other or do not help in gender classification. In this study, we propose a method to select features that are useful for gender classification using a correlation-based feature selection technique. To demonstrate the effectiveness of the proposed feature selection technique, we compare the performance of gender classification models before and after applying the proposed feature selection technique using a 3-D gait dataset available on the Internet. Eight machine learning algorithms applicable to binary classification problems were utilized in the experiments. The experimental results show that the proposed feature selection technique can reduce the number of features by 22, from 82 to 60, while maintaining the gender classification performance.

• Tuberculosis and Respiratory Diseases
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• v.87 no.1
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• pp.52-64
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• 2024

Chronic respiratory diseases such as idiopathic pulmonary fibrosis, chronic obstructive pulmonary disease, and respiratory infections injure the alveoli; the damage evoked is mostly irreversible and occasionally leads to death. Achieving a detailed understanding of the pathogenesis of these fatal respiratory diseases has been hampered by limited access to human alveolar tissue and the differences between mice and humans. Thus, the development of human alveolar organoid (AO) models that mimic in vivo physiology and pathophysiology has gained tremendous attention over the last decade. In recent years, human pluripotent stem cells (hPSCs) have been successfully employed to generate several types of organoids representing different respiratory compartments, including alveolar regions. However, despite continued advances in three-dimensional culture techniques and single-cell genomics, there is still a profound need to improve the cellular heterogeneity and maturity of AOs to recapitulate the key histological and functional features of in vivo alveolar tissue. In particular, the incorporation of immune cells such as macrophages into hPSC-AO systems is crucial for disease modeling and subsequent drug screening. In this review, we summarize current methods for differentiating alveolar epithelial cells from hPSCs followed by AO generation and their applications in disease modeling, drug testing, and toxicity evaluation. In addition, we review how current hPSC-AOs closely resemble in vivo alveoli in terms of phenotype, cellular heterogeneity, and maturity.

• Geomechanics and Engineering
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• v.37 no.5
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• pp.453-465
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• 2024

This paper presents a logarithmic shear deformation theory to study the thermal buckling response of power-law FG one-dimensional structures in thermal conditions with different boundary conditions. It is assumed that the functionally graded material and thermal properties are supposed to vary smoothly according to a contentious function across the vertical direction of the beams. A P-FG type function is employed to describe the volume fraction of material and thermal properties of the graded (1D) beam. The Ritz model is employed to solve the thermal buckling problems in immovable boundary conditions. The outcomes of the stability analysis of FG beams with temperature-dependent and independent properties are presented. The effects of the thermal loading are considered with three forms of rising: nonlinear, linear and uniform. Numerical results are obtained employing the present logarithmic theory and are verified by comparisons with the other models to check the accuracy of the developed theory. A parametric study was conducted to investigate the effects of various parameters on the critical thermal stability of P-FG beams. These parameters included support type, temperature fields, material distributions, side-to-thickness ratios, and temperature dependency.

• Computers and Concrete
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• v.34 no.4
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• pp.409-425
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• 2024

This paper utilizes LS-DYNA software to numerically investigate impact response and damage evaluation of fiber-reinforced polymer (FRP) bars-reinforced ultra-high-performance concrete (UHPC) composite beams (FRP-UHPC beams). Three-dimensional finite element (FE) models are established and calibrated by using literature-based static and impact tests, demonstrating high accuracy in simulating FRP-UHPC beams under impact loading. Parametric analyses explore the effects of impact mass, impactor height, FRP bar type and diameter, and clear span length on dynamic response and damage modes. Two failure modes emerge: tensile failure with bottom longitudinal reinforcement fracture and compression failure with local concrete compression near the impact region. Impact mass or height variation under the same impact energy significantly affects the first peak impact force, but minimally influences peak midspan displacement with a difference of no more than 5% and damage patterns. Increasing static flexural load-carrying capacity enhances FRP-UHPC beam impact resistance, reducing displacement deformation by up to 30%. Despite similar static load-carrying capacities, different FRP bars result in varied impact resistance. The paper proposes a damage assessment index based on impact energy, static load-carrying capacity, and clear span length, correlating well with beam end rotation. Their linearly-fitting coefficient was 1.285, 1.512, and 1.709 for the cases with CFRP, GFRP, and BFRP bars, respectively. This index establishes a foundation for an impact-resistant design method, including a simplified formula for peak midspan displacement assessment.