• Biomedical Science Letters
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• v.12 no.4
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• pp.337-341
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• 2006

Platelets clearly play an important role in inflammatory responses. In this study, we aimed to evaluate the relationship between aging and platelet activation. A total number of 799 persons (383 males and 416 females), who were apparently healthy and aged more than 20 years were recruited by a health promotion center in a community-based hospital in Seoul, Korea. We collected material data about their medical history and health behavior. Platelet parameters including mean platelet component (MPC), mean platelet volume (MPV), and platelet component distribution width (PCDW) were determined within 1 hour after blood collection using the ADVIA 120 automated hematology analyzer. The MPC of the women ($27.2{\pm}1.2$) was significantly love. than that of the men ($27.5{\pm}1.3$). The MPC of all participants was found to decrease with increasing age (P<0.01). Study participants in their twenties had the highest MPC ($27.7{\pm}1.1$), followed by those in their thirties ($27.6{\pm}1.1$), forties ($27.4{\pm}1.3$), fifties ($27.2{\pm}1.3$), sixties ($27.2{\pm}1.2$) and seventies ($27.1{\pm}1.2$). Multiple regression analysis showed that aging and gender were related with MPC after adjusting for confounding factors, including age, gender, smoking habit, hypertension, diabetes, body mass index and total cholesterol level. The this study shows that aging is related to platelet activation. Future research will need to determine the implications of increased platelet activation with aging, especially regarding the increased incidence of cardiovascular diseases and related mortalities that occur in older age groups.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1993.11a
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• pp.31-36
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• 1993

Three different methods were employed to measure the degree of aerial oxidation in coal and the resulting oxidation/weathering indices were applied to obtain kinetic parameters of aerial oxidation processes, The index (i.e., slurry pH, Free Swelling Index, weight gain) values were subjected to kinetic analysis based on power-law Arrhenius type reaction model. The results show that activation energy of the aerial oxidation in 20-29$0^{\circ}C$ is in the range of 12-16 ㎉/㏖ and the agreement among three techniques is remarkable. The first order kinetic model is suitable in describing low temperature aerial oxidation process, except in the FSI case where the zero order expression is the best one.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.1070-1079
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• 2016

In this paper, the design of recursive radial basis function neural networks based on incremental fuzzy c-means is introduced for processing the big data. Radial basis function neural networks consist of condition, conclusion and inference phase. Gaussian function is generally used as the activation function of the condition phase, but in this study, incremental fuzzy clustering is considered for the activation function of radial basis function neural networks, which could effectively do big data processing. In the conclusion phase, the connection weights of networks are given as the linear function. And then the connection weights are calculated by recursive least square estimation. In the inference phase, a final output is obtained by fuzzy inference method. Machine Learning datasets are employed to demonstrate the superiority of the proposed classifier, and their results are described from the viewpoint of the algorithm complexity and performance index.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.1-9
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• 2019

In this paper, we propose a Small Active Command scheme which reduces the power consumption of the command bus to DRAM. To do this, we target the ACTIVE command, which consists of multiple packets, containing the row address that occupies the largest size among the addresses delivered to the DRAM. The proposed scheme identifies frequently referenced row addresses as Hot pages first, and delivers index numbers of small caches (tables) located in the memory controller and DRAM. I-ACTIVE and I-PRECHARGE commands using unused bits of existing DRAM commands are added for index number transfer and cache synchronization management. Experimental results show that the proposed method reduces the command bus power consumption by 20% and 8.1% on average in the close-page and open-page policies, respectively.

• Biomolecules & Therapeutics
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• v.24 no.6
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• pp.638-649
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• 2016

In the previous study, the rhizome mixture of Anemarrhena asphodeloides and Coptis chinensis (DW2007), improved TNBS-, oxazolone-, or DSS-induced colitis in mice by regulating macrophage activation. Therefore, to understand the effect of DW2007 on the T cell differentiation involved in the adaptive immunity, we measured its effect on both Th17 and Treg cell differentiation in splenocytes, in the lamina propria of mice with DSS-induced colitis (DIC), and in the spleens of mice with collagen-induced arthritis (CIA). Results showed that DW2007 potently inhibited the differentiation of splenocytes into Th17 cells, but increased Treg cell differentiation in vitro. In the colon of wild type and $TLR4^{-/-}$ mice with DIC, DW2007 potently suppressed DSS-induced colon shortening and myeloperoxidase activity. DW2007 also suppressed collagen-induced paw thickening, clinical index, and myeloperoxidase activity in CIA mice. Overall, DW2007 potently suppressed Th17 cell differentiation in mice with CIA and DIC, but increased Treg cell differentiation. Moreover, DW2007 strongly inhibited the expression of TNF-${\alpha}$ and IL-$1{\beta}$, as well as the activation of NF-${\kappa}B$. Based on these findings, DW2007 may ameliorate inflammatory diseases by regulating the innate immunity via the inhibition of macrophage activation and the adaptive immunity via the correction of disturbed Th17/Treg cells.

• Fire Science and Engineering
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• v.34 no.4
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• pp.45-51
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• 2020

The aim of this study is to investigate the gas temperature and velocity during sprinkler activation considering the fire growth scenario based on the thermal response model of the sprinkler. The fire source is assumed to have time square fire growth scenarios with a maximum heat release rate of 3 MW. Eight types of standard and fast-response sprinkler heads with an operating temperature range of 65-105 ℃ and a response time index range of 25-171 m^1/2s^1/2 were adopted. The temperature difference between the gas stream and the sensing element of the sprinkler head decreased as the fire growth slowed down, and the RTI value decreased. The overall gas temperature and velocity conditions predicted using the FDS model at sprinkler activation were in reasonable agreement with those of standard test conditions of the sprinkler head response. However, the sprinkler head could be activated at lower limits of gas temperature and velocity under the current test conditions for a slowly growing fire scenario.

• Fire Science and Engineering
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• v.28 no.1
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• pp.37-43
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• 2014

The high predictive performance of fire detector models is essentially needed to assure the reliability of fire and evacuation modeling in the process of Performance-Based fire safety Design (PBD). The main objective of the present study is to measure input information in order to predictive the accurate activation time of fixed temperature heat detectors adopted in Fire Dynamics Simulator (FDS) as a representative fire model. To end this, Fire Detector Evaluator (FDE) which could be measured the device properties of detector was used, and the spot-type fixed temperature heat detectors of two thermistor types and one bimetal type were considered as research objectors. Activation temperature and Response Time Index (RTI) of detectors required for the fire modeling were measured, and then the RTI was measured for ceiling jet flow and vertical jet flow in consideration of the install location of detectors. The results of fire modeling using measured device properties were compared and validated with the experimental results of full-scale compartment fires. It was confirmed that, in result, the numerically predicted activation time of detector showed reasonable agreement with the measured activation time.

• Food Science of Animal Resources
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• v.33 no.4
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• pp.439-447
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• 2013

Time-temperature integrators (TTIs) are simple and cost-efficient tools which may be used to predict food quality. Enzymatic TTIs are devised to indicate food quality in the form of color alterations from green to red, based on the cumulative impacts of temperature and time period on the enzymatic reactions. In this study, the quality of ground beef patties was investigated for the parameters of pH levels, color, VBN, water holding capacity, and total microbial counts, depending on various storage temperatures (5, 15, and $25^{\circ}C$). TTIs were attached to the surface of the ground beef patties in order to evaluate the degree of correlating colorimetric changes with the determined quality parameters. Through the Arrhenius equation, activation energy and constant reaction rates of TTI, VBN, and total microbial counts were calculated as to observe the relationship between enzymatic reactions of the TTI and food spoilage reactions of the ground beef patties. VBN and total microbial counts were already increased to reach decomposition index (VBN: 20, total microbial count: 7-8 Log CFU/g) of meat at middle stage of storage period for each storage temperature. Although activation energy of TTI enzymatic reactions and food spoilage reactions of the ground beef patties were similar, the change of TTI color was not a coincidence for food spoilage at $5^{\circ}C$ and $15^{\circ}C$ of storage temperature. It was suggested that TTI should be designed individually for storage temperature, time, type of meat, or decomposition index of meat.

• The Journal of Pediatrics of Korean Medicine
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• v.35 no.1
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• pp.76-103
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• 2021

Objectives This study was designed to examine the effect of Gleditsiae Fructus n-hexane (GSF_Hx) on two different groups (on the LPS-induced activation of Raw264.7 cells in vitro, and on the DNCB-induced activation of atopic dermatitis NC/Nga Tnd mice in vivo) to find index components and active components of Gleditsiae Fructus. Methods GSF_Hx was analyzed by HPLC profiling and confirmed echinocystic acid (EA), oleanolic acid (OA) as index components of Gleditsiae Fructus. Using GSF_Hx, EA, OA, we investigated IL-6, TNF-α, NO production by ELISA analysis and evaluated manifestations of MAPKs transcription factors and NF-κB p65 translocation by western blotting. During In vivo study, atopic dermatitis was induced on NC/Nga Tnd mice by DNCB and administered GSF_Hx, EA, OA orally, and checked skin lesions and measured skin clinical score. Serum IgE level, Th1 and Th2 cytokines secretion and modulating molecular mediators and immune cells in the spleenocyte culture supernatant, PBMCs, ALN and dorsal skin were also measured by real-time PCR. Then, skin rash was evaluated and mast cell distribution was verified by H&E and toluidine blue staining on dorsal skin. Results It is possible that GSF_Hx, EA and OA reduce inflammation and allergic response of atopic dermatitis by suppressing Th1 and Th2 cytokines secretion and modulating molecular mediators and immune cells. They also had moisturizing effect by raising vitality of ceramide in dorsal skin of atopic dermatitis NC/Nga Tnd mice. However, EA particularly had better overall activity data than OA, that EA could be a more effective active component of Gleditsiae Fructus than OA. Conclusions Based on the inflammatory reduction property with moisturizing effect, GSF_Hx may play a role in effective treatment for atopic dermatitis.

• Journal of radiological science and technology
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• v.45 no.1
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• pp.41-47
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• 2022

The purpose of this study is to apply a deep learning model that can distinguish lung perfusion and lung ventilation images in nuclear medicine, and to evaluate the image classification ability. Image data pre-processing was performed in the following order: image matrix size adjustment, min-max normalization, image center position adjustment, train/validation/test data set classification, and data augmentation. The convolutional neural network(CNN) structures of VGG-16, ResNet-18, Inception-ResNet-v2, and SE-ResNeXt-101 were used. For classification model evaluation, performance evaluation index of classification model, class activation map(CAM), and statistical image evaluation method were applied. As for the performance evaluation index of the classification model, SE-ResNeXt-101 and Inception-ResNet-v2 showed the highest performance with the same results. As a result of CAM, cardiac and right lung regions were highly activated in lung perfusion, and upper lung and neck regions were highly activated in lung ventilation. Statistical image evaluation showed a meaningful difference between SE-ResNeXt-101 and Inception-ResNet-v2. As a result of the study, the applicability of the CNN model for lung scintigraphy classification was confirmed. In the future, it is expected that it will be used as basic data for research on new artificial intelligence models and will help stable image management in clinical practice.