• The Korean Journal of Physiology and Pharmacology
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• 제16권3호
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• pp.199-204
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• 2012

We evaluated the role of Tat-mediated p66shc transduction on the activation of endothelial nitric oxide synthase in cultured mouse endothelial cells. To construct the Tat-p66shc fusion protein, human full length p66shc cDNA was fused with the Tat-protein transduction domain. Transduction of TAT-p66shc showed a concentration- and time-dependent manner in endothelial cells. Tat-mediated p66shc transduction showed increased hydrogen peroxide and superoxide production, compared with Tat-p66shc (S/A), serine 36 residue mutant of p66shc. Tat-mediated p66shc transduction decreased endothelial nitric oxide synthase phosphorylation in endothelial cells. Furthermore, Tat-mediated p66shc transduction augmented TNF-${\alpha}$-induced p38 MAPK phosphorylation in endothelial cells. These results suggest that Tat-mediated p66shc transduction efficiently inhibited endothelial nitric oxide synthase phosphorylation in endothelial cells.

• Archives of Pharmacal Research
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• 제19권1호
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• pp.18-22
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• 1996

Acrylate-terminated poly (ethylene glycol) (PEG) macromer was prepared by the reaction of PEG with acryloyl chloride. Photopolymerization of PEG macromer resulted in the formation of cross-linked PEG network. Interpenetrating polymer networks (IPNs) based on PEG and poly(acrylic acid) (PAA) was obtained via template polymerization of AA to the PEG network by UV curing. The swelling degree of the IPNs hydrogel increased with an increase of pH value due to the association-dissociation between carboxylic acid of PAA and either of PEG through hydrogen bounding. The swelling-deswelling behavior proceeded reversibly for the IPNs upon changing pH. Release of indomethacin from the IPNs demonstrated "on-off" regulation with pH fluctuation.

• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.89-94
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• 2022

The Saudi Vision 2030 defined the directions of the national economy and market towards diversifying sources of income, and developing energy to become less dependent on oil. The study sought through a theoretical review to identify the reality of the energy sector and the areas of investment available in the field of renewable energy. Findings showed that investment in the renewable energy sector is a promising source according to solar, wind, hydrogen, geothermal energy and burning waste than landfill to extract biogas for less emission. The renewable energy sector faces challenges related to technology, production cost, price, quantity of production and consumption, and markets. The study revealed some recommendations providing and suggested electronic marketing system to provide investors and consumers with energy available from renewable sources.

• International Journal of Advanced Culture Technology
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• 제11권1호
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• pp.325-331
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• 2023

In this paper, we propose a mixed neural network structure of CNN and LSTM that can be used to detect or predict odor occurrence, which is most required in manufacturing industry or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data such as hydrogen sulfide, ammonia, benzene, and toluene in real time, and applies this data to an inference model to detect and predict odor conditions. The proposed model evaluated the prediction accuracy of the learning model through performance indicators according to accuracy, and the evaluation result showed an average performance of 94% or more.

• International Journal of Advanced Culture Technology
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• 제11권4호
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• pp.464-469
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• 2023

As modern society develops, the number of diseases caused by bad smells is increasing. As it can harm people's health, it is important to predict in advance the extent to which bad smells may occur, inform the public about this, and take preventive measures. In this paper, we propose a hybrid neural network structure of CNN and LSTM that can be used to detect or predict the occurrence of odors, which are most required in manufacturing or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data, including hydrogen sulfide, ammonia, benzene, and toluene, in real time, and applies this data to the inference model to detect and predict the odor state. The proposed model evaluated the prediction accuracy of the training model through performance indicators based on accuracy, and the evaluation results showed an average performance of more than 94%.

• 한국수소및신에너지학회논문집
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• 제23권6호
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• pp.678-687
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• 2012

Concentration fields of solid powder in a liquid fuel were quantitatively measured by a visualization technique. The measurement system consists of a camcoder and three LCD monitors. The solid powder (glass powder) were filled in a head tank which was installed over a main mixing tank ($D{\times}H$, $310{\times}370mm$). The main mixing tank was filled with JetA1 fuel oil. With a sudden opening of the upper tank by pressurized nitrogen gas with 1.9 bar, the solid powder were poured into the JetA1 oil. An impeller type agitator was being rotated in the mixing with 700 rpm for the enhancements of mixing. Uniform visualization for the mixing flow field was made by the light from the three LCD monitors, and the visualized images were captured by the camcoder. The color images captured by the camcoder The color information of the captured images was decoded into three principle colors R, G, and B to get quantitattive relations between the concentrations of the solid powder and the colors. To get better fitting for the strong non-linearity between the concentration and the color, a neural network which has strong fitting performances was used. Analyses on the transient mixing of the solid powders were quantitatively made.

• Composites Research
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• 제37권3호
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• pp.197-203
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• 2024

고분자 복합재료의 기계적 특성 향상에 유리한 탄소섬유(Carbon fiber, CF)와 전도 특성 향상에 유리한 다중벽 탄소나노튜브(Multi-walled carbon nanotube, MWCNT)의 동시 혼입을 통해 기계적, 전기적 및 열적 특성을 동시에 향상시킬 수 있다. 본 연구에서는 우수한 양산 가공성과 준수한 기계적 특성을 나타내는 탄소장섬유 열가소성플라스틱(Carbon long fiber thermoplastic, CLFT)에 MWCNT를 혼입하여 전기적 및 열적 특성 제어하였다. 제조된 복합재료의 기계적 및 전기적 특성은 필러의 혼입 양에 가장 크게 영향을 받았다. 반면, 열적 특성은 MWCNT의 혼입으로 연결된 필러 네트워크가 형성됨으로써 더 우수한 결과를 나타내었다. MWCNT 혼입 CLFT의 필러 혼입량, 필러 조성 및 필러 네트워크 구조를 조절함으로써 목적에 적합한 기계적, 전기적 및 열적 특성 제어할 수 있었다.

• 센서학회지
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• 제21권1호
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• pp.46-52
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• 2012

The rapid water pollution in stream, river, lake and sea in recent years raises an urgent need for continuous monitoring and policymaking to conserve the global clean environment. In particular, the increasing water pollution in coastal marine areas adds to the importance of the environmental monitoring systems. In this paper, the mobile server is designed to gathers information of the water quality at coastal areas. The obtained data by the server is transmitted from field servers to the base station via multi-hop communication in wireless sensor network. The information collected includes dissolved oxygen(DO), hydrogen ion exponent(pH), temperature, etc. By the information provided the real-time monitoring of water quality at the coastal marine area. In addition, wireless sensor network-based flooding routing protocol was designed and used to transfer the measured water quality information efficiently. Telosb sensor node is programmed using nesC language in TinyOS platform for small scale wireless sensor network monitoring from a remote server.

• Bulletin of the Korean Chemical Society
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• 제28권9호
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• pp.1472-1476
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• 2007

Artificial neural networks (ANNs) are successfully developed for the modeling and prediction of normalized polarity parameter (ETN) of 216 various solvents with diverse chemical structures using a quantitative-structure property relationship. ANN with architecture 5-9-1 is generated using five molecular descriptors appearing in the multi-parameter linear regression (MLR) model. The most positive charge of a hydrogen atom (q+), total charge in molecule (qt), molecular volume of solvent (Vm), dipole moment (μ) and polarizability term (πI) are input descriptors and its output is ETN. It is found that properly selected and trained neural network with 192 solvents could fairly represent the dependence of normalized polarity parameter on molecular descriptors. For evaluation of the predictive power of the generated ANN, an optimized network is applied for prediction of the ETN values of 24 solvents in the prediction set, which are not used in the optimization procedure. Correlation coefficient (R) and root mean square error (RMSE) of 0.903 and 0.0887 for prediction set by MLR model should be compared with the values of 0.985 and 0.0375 by ANN model. These improvements are due to the fact that the ETN of solvents shows non-linear correlations with the molecular descriptors.

• Molecules and Cells
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• 제25권3호
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• pp.352-357
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• 2008

Osteoprotegerin (OPG) is a soluble decoy receptor that inhibits osteoclastogenesis and is closely associated with bone resorption processes. We have designed and determined the solution structures of potent OPG analogue peptides, derived from sequences of the cysteine-rich domain of OPG. The inhibitory effects of the peptides on osteoclastogenesis are dose-dependent ($10^{-6}M-10^{-4}M$), and the activity of the linear peptide at $10^{-4}M$ is ten-fold higher than that of the cyclic OPG peptide. Both linear and cyclic peptides have a ${\beta}$-turn-like conformation and the cyclic peptide has a rigid conformation, suggesting that structural flexibility is an important factor for receptor binding. Based on structural and biochemical information about RANKL and the OPG peptides, we suggest that complex formation between the peptide and RANKL is mediated by both hydrophobic and hydrogen bonding interactions. These results provide structural insights that should aid in the design of peptidyl-mimetic inhibitors for treating metabolic bone diseases caused by abnormal osteoclast recruitment.