• The Journal of Korean Medicine
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• v.33 no.4
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• pp.42-49
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• 2012

Objectives: The purpose of this study was to investigate effects of Red Ginseng-Ejung-tang Water Extract (ER) on cytokine production in RAW 264.7 mouse macrophages stimulated by lipopolysaccharide (LPS). Methods: Levels of various cytokines such as interleukin (IL)-6, IL-10, IL-2, IL-12p70, vascular endothelial growth factor (VEGF), monocyte chemoattractant protein (MCP)-1, macrophage inflammatory protein (MIP)-2, keratinocyte-derived chemokine (KC), tumor necrosis factor (TNF)-alpha, granulocyte macrophage colony-stimulating factor (GM-CSF) were measured by high-throughput multiplex bead array cytokine assay based on xMAP (multi-analyte profiling beads) technology. Results: ER significantly decreased levels of IL-6, IL-10, IL-2, IL-12p70, VEGF, and MCP-1 for 24 hrs incubation at the concentrations of 25, 50, and $100{\mu}g/mL$ in LPS-induced RAW 264.7 cells (P < 0.05). But ER did not exert significant effects on production of MIP-2, KC, TNF-${\alpha}$, and GM-CSF in LPS-induced RAW 264.7 cells. Conclusions: These results suggest that ER has an anti-inflammatory property related with its inhibition of cytokine production in LPS-induced macrophages.

• Proceedings of the KIPE Conference
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• 2019.11a
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• pp.70-72
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• 2019

For the safe and reliable operation of Lithium-ion batteries in Electric Vehicles (EVs) or Energy Storage Systems (ESSs), it is essential to have accurate information of the battery such as State of Charge (SOC). Many kinds of different techniques to estimate the SOC of the batteries have been developed so far such as the Kalman Filter. However, when it is applied to the multiple number of batteries it is difficult to maintain the accuracy of the estimation over all cells due to the difference in parameter value of each cell. Moreover the difference in the parameter of each cell may become larger as the operation time accumulates due to aging. In this paper a novel Deep Neural Network (DNN) based SOC estimation method for multi cell application is proposed. In the proposed method DNN is implemented to learn non-linear relationship of the voltage and current of the lithium-ion battery at different SOCs and different temperatures. In the training the voltage and current data of the Lithium battery at charge and discharge cycles obtained at different temperatures are used. After the comprehensive training with the data obtained with a cell resulting estimation algorithm is applied to the other cells. The experimental results show that the Mean Absolute Error (MAE) of the estimation is 0.56% at 25℃, and 3.16% at 60℃ with the proposed SOC estimation algorithm.

• Proceedings of the SCSK Conference
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• 2003.09b
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• pp.200-200
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• 2003

Intact mammalian hair and wool fibres are multi-compartmental composite materials consisting of a sulphur-rich outer protective cuticle layer surrounding elongated, highly keratinized, cortex cells. The cortex cells themselves are made up of crystalline, filamentous, low-sulphur a-helical keratin molecules embedded in a matrix of highly cross-linked, globular high-sulphur keratins. It is the structurally organised and highly disulphide cross-linked nature of these materials that provides them with their remarkable mechanical properties. However these mechanical properties are sensitive to environmental conditions such as water content, temperature and chemical treatment and the importance of their ultra-structural arrangements to overall mechanical properties in different environments is still not fully understood.(omitted)

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07a
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• pp.146-149
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• 2004

Porous silicon(PS) as an excellent light diffuser can be used as an antireflection layer without other antireflection coating(ARC) materials. PS layers were obtained by electrochemical etching(ECE) anodization of silicon wafers in hydrofluoric acid/ethanol/de-ionized(DI) water solution($HF/EtOH/H_2O$). This technique is based on the selective removal of Si atoms from the sample surface forming a layer of PS with adjustable optical, electrical, and mechanical properties. A PS layer with optimal ARC characteristics was obtained in charge density (Q) of 5.2 $C/cm^2$. The weighted reflectance is reduced from 33 % to 4 % in the wavelength between 400 and 1000 nm. The weighted reflectance with optimized PS layers is much less than that obtained with a commercial SiNx ARC on a potassium hydroxide(KOH) pre-textured multi-crystalline silicon(mc-Si) surface.

• 한국신재생에너지학회:학술대회논문집
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• 2006.06a
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• pp.145-148
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• 2006

The protocrystalline silicon (pc-Si:H) multilayer solar cell is very promising owing to its fast stabilization with low degradation against light irradiation. However, the pc-Si:H multi layers have not extensively been investigated in detail on its material characteristics yet. We present the material characteristics of pc-Si:H multilayer using a transmission electron microscopy(TEM), and Raman spectroscopy. In addition, we present the superior light-soaking behavior of the pc-Si:H mutt i layer solar cell. A TEM micrograph shows that a pc-Si:H multilayer has a repeatedly layered structure and crystalline-like objects in a-Si:H matrix. A Raman spectra introduces improved short-range-order and medium-range-order in pc-Si:H multilayer. As a result the excellent metastability of the pc-Si:H multilayer solar cell is primarily due to the repeatedly layered structure that improves a structural order in absorber layer.

• Imaging Science in Dentistry
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• v.49 no.3
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• pp.235-240
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• 2019

Osteosarcoma is the most common primary bone tumor after plasma cell neoplasms. Osteosarcoma has diverse histological features and is characterized by the presence of malignant spindle cells and pluripotent neoplastic mesenchymal cells that produce immature bone, cartilage, and fibrous tissue. Osteosarcoma most frequently develops in the extremities of long bones, but can occur in the jaw in rare cases. The clinical and biological behavior of osteosarcoma of the jaw slightly differs from that of long-bone osteosarcoma. The incidence of jaw osteosarcoma is greater in the third to fourth decades of life, whereas long-bone osteosarcoma mostly occurs in the second decade of life. Osteosarcoma of the jaw has a lower tendency to metastasize and a better prognosis than long-bone osteosarcoma. Radiographically, osteosarcoma can present as a poorly-defined lytic, sclerotic, or mixed-density lesion with periosteal bone reaction response. Multi-detector computed tomography is useful for identifying the extent of bone destruction, as well as soft tissue involvement of the lesion. The current case report presents a fibroblastic osteosarcoma involving the left hemimandible with very unusual radiographic features.

• Molecules and Cells
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• v.44 no.3
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• pp.127-135
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• 2021

Since the introduction of RNA sequencing (RNA-seq) as a high-throughput mRNA expression analysis tool, this procedure has been increasingly implemented to identify cell-level transcriptome changes in a myriad of model systems. However, early methods processed cell samples in bulk, and therefore the unique transcriptomic patterns of individual cells would be lost due to data averaging. Nonetheless, the recent and continuous development of new single-cell RNA sequencing (scRNA-seq) toolkits has enabled researchers to compare transcriptomes at a single-cell resolution, thus facilitating the analysis of individual cellular features and a deeper understanding of cellular functions. Nonetheless, the rapid evolution of high throughput single-cell "omics" tools has created the need for effective hypothesis verification strategies. Particularly, this issue could be addressed by coupling cell engineering techniques with single-cell sequencing. This approach has been successfully employed to gain further insights into disease pathogenesis and the dynamics of differentiation trajectories. Therefore, this review will discuss the current status of cell engineering toolkits and their contributions to single-cell and genome-wide data collection and analyses.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.1
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• pp.1-8
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• 2021

For the safe and reliable operation of lithium-ion batteries in electric vehicles or energy storage systems, having accurate information of the battery, such as the state of charge (SOC), is essential. Many different techniques of battery SOC estimation have been developed, such as the Kalman filter. However, when this filter is applied to multiple batteries, it has difficulty maintaining the accuracy of the estimation over all cells owing to the difference in parameter values of each cell. The difference in the parameter of each cell may increase as the operation time accumulates due to aging. In this paper, a novel deep neural network (DNN)-based SOC estimation method for multi-cell application is proposed. In the proposed method, DNN is implemented to determine the nonlinear relationships of the voltage and current at different SOCs and temperatures. In the training, the voltage and current data obtained at different temperatures during charge/discharge cycles are used. After the comprehensive training with the data obtained from the cycle test with a cell, the resulting algorithm is applied to estimate the SOC of other cells. Experimental results show that the mean absolute error of the estimation is 1.213% at 25℃ with the proposed DNN-based SOC estimation method.

• BMB Reports
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• v.54 no.6
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• pp.305-310
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• 2021

Cereblon (CRBN) is a multi-functional protein that acts as a substrate receptor of the E3 ligase complex and a molecular chaperone. While CRBN is proposed to function in mitochondria, its specific roles are yet to be established. Here, we showed that knockdown of CRBN triggers oxidative stress and calcium overload in mitochondria, leading to disruption of mitochondrial membrane potential. Notably, long-term CRBN depletion using PROteolysis TArgeting Chimera (PROTAC) induced irreversible mitochondrial dysfunction, resulting in cell death. Our collective findings indicate that CRBN is required for mitochondrial homeostasis in cells.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.159-166
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• 2021

In order to analyze cell images, accurate segmentation of each cell is indispensable. However, the reality is that accurate cell image segmentation is not easy due to various noises, dense cells, and inconsistent shape of cells. Therefore, in this paper, we propose an algorithm that combines marker-based watershed segmentation and ellipse fitting method for glioblastoma cell segmentation. In the proposed algorithm, in order to solve the over-segmentation problem of the existing watershed method, the marker-based watershed technique is primarily performed through "seeding using local minima". In addition, as a second process, the concave point search using ellipse fitting for final segmentation based on the connection line between the concave points has been performed. To evaluate the performance of the proposed algorithm, we compared three algorithms with other algorithms along with the calculation of segmentation accuracy, and we applied the algorithm to other cell image data to check the generalization and propose a solution.