• Korean Journal of Veterinary Research
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• 제51권3호
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• pp.217-225
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• 2011

Glatiramer acetate (GA; Copaxone) has been shown to be effective in preventing and suppressing experimental autoimmune encephalomyelitis (EAE), the animal model of multiple sclerosis (MS). It has been recently shown that GA-reactive T cells migrate through the blood-brain barrier, accumulate in the central nervous system (CNS), secrete antiinflammatory cytokines and suppress production of proinflammatory cytokines of EAE and MS. Development of EAE requires coordinated expression of a number of genes involved in the activation and effector functions of inflammatory cells. Activation of inflammatory cells is regulated at the transcriptional level by several families of transcription factors. One of these is the nuclear factor kappa B ($NF{\kappa}B$) family which is present in a variety of cell types and involved in the activation of immune-relative genes during inflammatory process. Since it is highly activated at site of inflammation, $NF{\kappa}B$ activation is also implicated in the pathogenesis of EAE. In this study, we examined whether the inhibition of $NF{\kappa}B$ activation induced by GA can have suppressive therapeutic effects in EAE mice. We observed the expression of $NF{\kappa}B$ and phospho-$I{\kappa}B$ proteins increased in GA-treated EAE mice compared to EAE control groups. The immunoreactivity in inflammatory cells and glial cells of $NF{\kappa}B$ and phospho-$I{\kappa}B$ significantly decreased at the GA-treated EAE mice. These results suggest that treatment of GA in EAE inhibits the activation of $NF{\kappa}B$ and phophorylation of $I{\kappa}B$ in the CNS. Subsequently, the inhibition of $NF{\kappa}B$ activation and $I{\kappa}B$ phosphorylation leads to the anti-inflammatory effects thereby to reduce the progression and severity of EAE.

• Fire Science and Engineering
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• 제28권6호
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• pp.62-68
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• 2014

The high predictive performance of fire detector models is essentially required for the reliable design of evacuation safety using the fire modeling. The main objective of the present study is to measure input information in order to predict the accurate activation time of photoelectric smoke detector adopted in fire dynamics simulator (FDS) recognized a representative fire model. To end this, the fire detector evaluator (FDE) which could be measured the device properties of detector was used, and the input information of Heskestad and Cleary's models was obtained for a spot-type photoelectric smoke detector. In addition, the activation times of smoke detector predicted using default values into FDS and measured values in the present study were quantitatively compared. As a result, the Heskestad model could result in an inaccurate the activation time of photoelectric smoke detector compared to the Cleary model. In addition, there was a distinct difference between the default values used into FDS and the measured values in terms of device properties of smoke detector, and thus the activation time also showed a significant difference.

• Clinical and Experimental Pediatrics
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• 제54권11호
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• pp.456-462
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• 2011

Purpose: Synthesis of regulated on activation, normal T-cells expressed and secreted (RANTES) in the airway has previously been shown to be elevated after respiratory syncytial virus (RSV) infection. However, since few studies have examined whether RSV-infected asthma patients express a higher level of RANTES than do normal individuals, we used a murine model of asthma to address this question. Methods: We prepared Dermatophagoides farinae-sensitized mice as an asthma model, and then infected them with RSV and analyzed the changes in airway responsiveness and the cell populations and cytokine levels of bronchoalveolar lavage fluid. Results: RANTES synthesis increased in response to RSV infection in both control mice and in asthma model (D. farinae) mice. However, there was no significant difference in the amount of RANTES produced following RSV infection between control and D. farinae mice. RSV infection affected neither interferon-${\gamma}$ synthesis nor airway responsiveness in either control or D. farinae mice. Conclusion: RSV infection did not induce more RANTES in a murine model of asthma than in control mice.

• Journal of the Korea Society of Computer and Information
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• 제26권7호
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• pp.29-36
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• 2021

In this paper, we classify ECG signal data for mobile devices using deep learning models. To classify abnormal heartbeats with high accuracy, three factors of the deep learning model are selected, and the classification accuracy is compared according to the changes in the conditions of the factors. We apply a CNN model that can self-extract features of ECG data and compare the performance of a total of 48 combinations by combining conditions of the depth of model, optimization method, and activation functions that compose the model. Deriving the combination of conditions with the highest accuracy, we obtained the highest classification accuracy of 97.88% when we applied 19 convolutional layers, an optimization method SGD, and an activation function Mish. In this experiment, we confirmed the suitability of feature extraction and abnormal beat detection of 1-channel ECG signals using CNN.

• Journal of the Korean Society of Radiology
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• 제18권1호
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• pp.21-26
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• 2024

The one of the famous deep learning models for object detection task is you only look once version 5 (YOLOv5) framework based on the one stage architecture. In addition, YOLOv5 model indicated high performance for accurate lesion detection using the bottleneck CSP layer and skip connection function. The purpose of this study was to evaluate the performance of YOLOv5 framework according to various hyperparameters in position emission tomogrpahy (PET) phantom images. The dataset was obtained from QIN PET segmentation challenge in 500 slices. We set the bounding box to generate ground truth dataset using labelImg software. The hyperparameters for network train were applied by changing optimization function (SDG, Adam, and AdamW), activation function (SiLU, LeakyRelu, Mish, and Hardwish), and YOLOv5 model size (nano, small, large, and xlarge). The intersection over union (IOU) method was used for performance evaluation. As a results, the condition of outstanding performance is to apply AdamW, Hardwish, and nano size for optimization function, activation function and model version, respectively. In conclusion, we confirmed the usefulness of YOLOv5 network for object detection performance in nuclear medicine images.

• Toxicological Research
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• 제34권4호
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• pp.333-341
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• 2018

Ferulate is a phenolic compound abundant in wheat germ and bran and has been investigated for its beneficial activities. The aim of the present study is to evaluate the efficacy of ferulate against the oxidative stress-induced imbalance of protein tyrosine kinases (PTKs), protein tyrosine phosphatases (PTPs), and serine/threonine protein phosphatase 2A (PP2A), in connection with our previous finding that oxidative stress-induced imbalance of PTKs and PTPs is linked with proinflammatory nuclear factor-kappa B $(NF-{\kappa}B)$ activation. To test the effects of ferulate on this process, we utilized two oxidative stress-induced inflammatory models. First, YPEN-1 cells were pretreated with ferulate for 1 hr prior to the administration of 2,2'-Azobis(2-methylpropionamidine) dihydrochloride (AAPH). Second, 20-month-old Sprague-Dawley rats were fed ferulate for 10 days. After ferulate treatment, the activities of PTKs, PTPs, and PP2A were measured because these proteins either directly or indirectly promote $NF-{\kappa}B$ activation. Our results revealed that in YPEN-1 cells, ferulate effectively suppressed AAPH-induced increases in reactive oxygen species (ROS) and $NF-{\kappa}B$ activity, as well as AAPH-induced PTK activation. Furthermore, ferulate also inhibited AAPH-induced PTP and PP2A inactivation. In the aged kidney model, ferulate suppressed aging-induced activation of PTKs and ameliorated aging-induced inactivation of PTPs and PP2A. Thus, herein we demonstrated that ferulate could modulate PTK/PTP balance against oxidative stress-induced inactivation of PTPs and PP2A, which is closely linked with $NF-{\kappa}B$ activation. Based on these results, the ability of ferulate to modulate oxidative stress-related inflammatory processes is established, which suggests that this compound could act as a novel therapeutic agent.

• Proceedings of KOSOMES biannual meeting
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• 해양환경안전학회 2018년도 공동국제학술발표회
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• pp.159-159
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• 2018

• Journal of the Korean Data and Information Science Society
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• 제14권1호
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• pp.119-129
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• 2003

We propose a new logistic regression model of normality curves for normal(diseased) and abnormal(nondiseased) classifications by neural networks in data mining. The fitted logistic regression lines are estimated, interpreted and plotted by the neural network technique. A few goodness-of-fit test statistics for normality are discussed and the performances by the fitted logistic regression lines are conducted.

• Journal of Industrial Technology
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• 제1권
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• pp.47-51
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• 1981

A Kinetic model of desorption of hydrogen in $Dy_2Co_7-H$ system has been suggested and rate equation of each step of the model has been compared with experimental results. The reat controlling step was hydrogen recombination in metal surface. The activation energy of over-all reaction was about 23kcal/mole.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 한국화재소방학회 1997년도 International Symposium on Fire Science and Technology
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• pp.625-632
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• 1997

A two-dimensional zone-like model is developed to predict the interaction between hot gas layer and water droplets after sprinkler activation. The model combines the motion equations for each droplet with heat and mass transfer between the gas and water. The results indicate that negative buoyancy in the hot layer can only be obtained if the initial temperature profile is uniform. If an experimental profile Is used instead, positive buoyancy results. This conclusion has been confirmed with experimental data.