• Journal of Ginseng Research
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• v.46 no.4
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• pp.550-560
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• 2022

Background: The effect of ginsenoside Rh2 (G-Rh2) on mast cell-mediated anaphylaxis remains unclear. Herein, we investigated the effects of G-Rh2 on OVA-induced asthmatic mice and on mast cell-mediated anaphylaxis. Methods: Asthma model was established for evaluating airway changes and ear allergy. RPMCs and RBL-2H3 were used for in vitro experiments. Calcium uptake, histamine release and degranulation were detected. ELISA and Western blot measured cytokine and protein levels, respectively. Results: G-Rh2 inhibited OVA-induced airway remodeling, the production of TNF-α, IL-4, IL-8, IL-1β and the degranulation of mast cells of asthmatic mice. G-Rh2 inhibited the activation of Syk and Lyn in lung tissue of OVA-induced asthmatic mice. G-Rh2 inhibited serum IgE production in OVA induced asthmatic mice. Furthermore, G-Rh2 reduced the ear allergy in IgE-sensitized mice. G-Rh2 decreased the ear thickness. In vitro experiments G-Rh2 significantly reduced calcium uptake and inhibited histamine release and degranulation in RPMCs. In addition, G-Rh2 reduced the production of IL-1β, TNF-α, IL-8, and IL-4 in IgE-sensitized RBL-2H3 cells. Interestingly, G-Rh2 was involved in the FcεRI pathway activation of mast cells and the transduction of the Lyn/Syk signaling pathway. G-Rh2 inhibited PI3K activity in a dose-dependent manner. By blocking the antigen-induced phosphorylation of Lyn, Syk, LAT, PLCγ2, PI3K ERK1/2 and Raf-1 expression, G-Rh2 inhibited the NF-κB, AKT-Nrf2, and p38MAPK-Nrf2 pathways. However, G-Rh2 up-regulated Keap-1 expression. Meanwhile, G-Rh2 reduced the levels of p-AKT, p38MAPK and Nrf2 in RBL-2H3 sensitized IgE cells and inhibited NF-κB signaling pathway activation by activating the AKT-Nrf2 and p38MAPK-Nrf2 pathways. Conclusion: G-Rh2 inhibits mast cell-induced allergic inflammation, which might be mediated by the AKT-Nrf2/NF-kB and p38MAPK-Nrf2/NF-κB signaling pathways.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4327-4330
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• 2012

The mouse double minute 2 (MDM2) gene plays a key role in the p53 pathway, and the SNP 309T/G single-nucleotide polymorphism in the promoter region of MDM2 has been shown to be associated with increased risk of cancer. However, no consistent results were found concerning the relationships between the polymorphism and prostate cancer risk. This meta-analysis, covering 4 independent case-control studies, was conducted to better understand the association between MDM2-SNP T309G and prostate cancer risk focusing on overall and subgroup aspects. The analysis revealed, no matter what kind of genetic model was used, no significant association between MDM2-SNP T309G and prostate cancer risk in overall analysis (GT/TT: OR = 0.84, 95%CI = 0.60-1.19; GG/TT: OR = 0.69, 95%CI = 0.43-1.11; dominant model: OR = 0.81, 95%CI= 0.58-1.13; recessive model: OR = 1.23, 95%CI = 0.95-1.59). In subgroup analysis, the polymorphism seemed more likely to be a protective factor in Europeans (GG/TT: OR = 0.52, 95%CI = 0.31-0.87; recessive model: OR = 0.58, 95%CI = 0.36-0.95) than in Asian populations, and a protective effect of the polymorphism was also seen in hospital-based studies in all models (GT/TT: OR = 0.74, 95%CI = 0.57-0.97; GG/TT: OR = 0.55, 95%CI = 0.38-0.79; dominant model: OR = 0.69, 95%CI = 0.54-0.89; recessive model: OR = 0.70, 95%CI = 0.51-0.97). However, more primary studies with a larger number of samples are required to confirm our findings.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.33-38
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• 2019

In this paper, we propose a new blockchain technology that could comply with GDPR. The proposed model can prevent illegal access by controlling access to the personal information according to a access policy. For example, it can control access to the information on a role-basis and information validation period. The core mechanism of the proposed model is to encrypt the personal information with public key which is associated with users attributes policy, and then decrypt it with a private key and users attributes based on a Attribute-based Encryption scheme. It can reduce a trusted third-part risk by replacing it with a number of nodes selected from the blockchain. And also the private key is generated in the form of one-time token to improve key management efficiency. We proved the feasibility by simulating the proposed model using the chaincode of the Hyperledger Fabric and evaluate the security.

• Steel and Composite Structures
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• v.38 no.6
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• pp.637-656
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• 2021

The component-based method is widely used to analyze the initial stiffness of joint in steel structures. In this study, an analytical component model for determining the column face stiffness of square or rectangular hollow section (SHS/RHS) subjected to tension was established, focusing on endplate connections. Equations for calculating the stiffness of the SHS/RHS column face in bending were derived through regression analysis using numerical results obtained from a finite element model database. Because the presence of bolt holes decreased the bending stiffness of the column face, this effect was calculated using a novel plate-spring-based model through numerical analysis. The developed component model was first applied to predict the bending stiffness of the SHS column face determined through tests. Furthermore, this model was incorporated into the component-based method with other effective components, e.g., bolts under tension, to determine the tensile stiffness of the T-stub connections, which connects the SHS column, and the initial rotational stiffness of the joints. A comparison between the model predictions, test data, and numerical results confirms that the proposed model shows satisfactory accuracy in evaluating the bending stiffness of SHS column faces.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.2
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• pp.75-93
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• 2013

In applying Markowitz's portfolio selection model to the stock market, we developed a comprehensive investment decision-making framework including key inputs for portfolio theory (i.e., individual stocks' expected rate of return and covariance) and minimum required expected return. For estimating the key inputs of our decision-making framework, we utilized an exponentially weighted moving average (EWMA) which places more emphasis on recent data than the conventional simple moving average (SMA). We empirically analyzed the investment results of the decision-making framework with the same 15 stocks in Samsung Group Funds found in the Korean stock market between 2007 and 2011. This five-year investment horizon is marked by global financial crises including the U.S. subprime mortgage crisis, the collapse of Lehman Brothers, and the European sovereign-debt crisis. We measure portfolio performance in terms of rate of return, standard deviation of returns, and Sharpe ratio. Results are compared with the following benchmarks : 1) KOSPI, 2) Samsung Group Funds, 3) Talmudic portfolio based on the na$\ddot{i}$ve 1/N rule, and 4) Markowitz's model with SMA. We performed sensitivity analyses on all the input parameters that are necessary for designing an investment decision-making framework : smoothing constant for EWMA, minimum required expected return for the portfolio, and portfolio rebalancing period. In conclusion, appropriate use of the comprehensive investment decision-making framework based on the Markowitz's model integrated with EWMA proves to achieve outstanding performance compared to the benchmarks.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3359-3366
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• 2023

In this study, a spiking cortical model (SCM) based n-g discrimination method is proposed. The SCM-based algorithm is compared with three other methods, namely: (i) the pulse-coupled neural network (PCNN), (ii) the charge comparison, and (iii) the zero-crossing. The objective evaluation criteria used for the comparison are the FoM-value and the time consumption of discrimination. Experimental results demonstrated that our proposed method outperforms the other methods significantly with the highest FoM-value. Specifically, the proposed method exhibits a 34.81% improvement compared with the PCNN, a 50.29% improvement compared with the charge comparison, and a 110.02% improvement compared with the zero-crossing. Additionally, the proposed method features the second-fastest discrimination time, where it is 75.67% faster than the PCNN, 70.65% faster than the charge comparison and 38.4% slower than the zero-crossing. Our study also discusses the role and change pattern of each parameter of the SCM to guide the selection process. It concludes that the SCM's outstanding ability to recognize the dynamic information in the pulse signal, improved accuracy when compared to the PCNN, and better computational complexity enables the SCM to exhibit excellent n-γ discrimination performance while consuming less time.

• Wind and Structures
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• v.38 no.4
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• pp.309-323
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• 2024

The gust factor and turbulence intensity are two crucial parameters that characterize the properties of turbulence. In tropical cyclones (TCs), these parameters exhibit significant variability, yet there is a lack of established formulas to account for their probabilistic characteristics with consideration of their inherent connection. On this condition, a probabilistic analysis of gust factors and turbulence intensities of TCs is conducted based on fourteen sets of wind data collected at the Sutong Cable-stayed Bridge site. Initially, the turbulence intensities and gust factors of recorded data are computed, followed by an analysis of their probability densities across different ranges categorized by mean wind speed. The Gaussian, lognormal, and generalized extreme value (GEV) distributions are employed to fit the measured probability densities, with subsequent evaluation of their effectiveness. The Gumbel distribution, which is a specific instance of the GEV distribution, has been identified as an optimal choice for probabilistic characterizations of turbulence intensity and gust factor in TCs. The corresponding empirical models are then established through curve fitting. By utilizing the Gumbel distribution as a template, the nexus between the probability density functions of turbulence intensity and gust factor is built, leading to the development of a generalized probabilistic model that statistically describe turbulence intensity and gust factor in TCs. Finally, these empirical models are validated using measured data and compared with suggestions recommended by specifications.

• ETRI Journal
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• v.38 no.1
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• pp.70-80
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• 2016

This paper addresses the problem of robust waveform design for distributed multiple-radar systems (DMRSs) based on low probability of intercept (LPI), where signal-to-interference-plus-noise ratio (SINR) and mutual information (MI) are utilized as the metrics for target detection and information extraction, respectively. Recognizing that a precise characterization of a target spectrum is impossible to capture in practice, we consider that a target spectrum lies in an uncertainty class bounded by known upper and lower bounds. Based on this model, robust waveform design approaches for the DMRS are developed based on LPI-SINR and LPI-MI criteria, where the total transmitting energy is minimized for a given system performance. Numerical results show the effectiveness of the proposed approaches.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.4
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• pp.38-44
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• 2003

In this paper configuration design is viewed as an engineering discipline that plays a key role in the design integration process at early-stage development of a complex and large-scale product. Taking as an instance an aircraft development program that Korean engineers had experienced in Lockheed-Martin company, the process of early-stage configuration design is recapitulated and then a role model of effective design integration activities is presented.

• BMB Reports
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• v.46 no.5
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• pp.252-257
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• 2013

Fibroblast activation protein (FAP) is a specific serine protease expressed in tumor stroma proven to be a stimulatory factor in the progression of some cancers. The purpose of this study was to investigate the effects of FAP knockdown on tumor growth and the tumor microenvironment. Mice bearing 4T1 subcutaneous tumors were treated with liposome-shRNA complexes targeting FAP. Tumor volumes and weights were monitored, and FAP, collagen, microvessel density (MVD), and apoptosis were measured. Our studies showed that shRNA targeting of FAP in murine breast cancer reduces FAP expression, inhibits tumor growth, promotes collagen accumulation (38%), and suppresses angiogenesis (71.7%), as well as promoting apoptosis (by threefold). We suggest that FAP plays a role in tumor growth and in altering the tumor microenvironment. Targeting FAP may therefore represent a supplementary therapy for breast cancer.