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RISS 인기검색어
- 검색키워드
- 저자 : Yu-Ta Shen (검색결과 5 건)
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robust sliding mode controller design for a ball screw table driven by an air motor
Yu-Ta Shen,Yean-Ren Hwang,Chia-Sheng Cheng 대한기계학회 2009 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.23 No.11
Air motors are often applied in the automation industry in areas with special requirements, such as in sparkprohibited environments, the mining industry, chemical manufacturing plants, and similar locations. The purpose of this study is to analyze the behaviors of a ball screw table powered by a vane-type air motor and to design a robust sliding mode controller for the inlet pressure. The rotational speed of the air motor is closely related to the pressure and flow rate of the compressed air. Furthermore, the compressibility of the air and the friction in the mechanism mean that the overall system is nonlinear, with fluctuating input. A robust sliding mode control is developed to overcome the effects of variations in the inlet pressure and air leakage problems. The experimental results validate the robustness of the proposed position control strategy.
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The EGF/hnRNP Q1 axis is involved in tumorigenesis via the regulation of cell cycle-related genes
Yu-Chu Wang,Kung-Chao Chang,Bo-Wen Lin,Jenq-Chang Lee,Chien-Hsien Lai,Li-Jyuan Lin,Yun Yen,Chang-Shen Lin,Shiang-Jie Yang,Peng-Chan Lin,Chung-Ta Lee,Liang-Yi Hung 생화학분자생물학회 2018 Experimental and molecular medicine Vol.50 No.-
Heterogeneous nuclear ribonucleoprotein (hnRNP) Q1, an RNA-binding protein, has been implicated in many posttranscriptional processes, including RNA metabolism and mRNA splicing and translation. However, the role of hnRNP Q1 in tumorigenesis remains unclear. We previously performed RNA immunoprecipitation (RIP)-seq analysis to identify hnRNP Q1-interacting mRNAs and found that hnRNP Q1 targets a group of genes that are involved in mitotic regulation, including Aurora-A. Here, we demonstrate that altering the hnRNP Q1 level influences the expression of the Aurora-A protein, but not its mRNA. Stimulation with epidermal growth factor (EGF) enhances both binding between hnRNP Q1 and Aurora-A mRNA as well as the efficacy of the hnRNP Q1-induced translation of Aurora-A mRNA. The EGF/hnRNP Q1-induced translation of Aurora-A mRNA is mediated by the mTOR and ERK pathways. In addition, we show that hnRNP Q1 up-regulates the translation of a group of spindle assembly checkpoint (SAC) genes. hnRNP Q1 overexpression is positively correlated with the levels of Aurora-A and the SAC genes in human colorectal cancer tissues. In summary, our data suggest that hnRNP Q1 plays an important role in regulating the expression of a group of cell cycle-related genes. Therefore, it may contribute to tumorigenesis by up-regulating the translation of these genes in colorectal cancer.
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Dynamic analysis and fuzzy logic control for the vane-type air motor
Yean-Ren Hwang,Yu-Ta Shen,Min-Shin Chen 대한기계학회 2009 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.23 No.12
Air motors are widely used in the automation industry with special requirements, such as park-prohibited environments, mining, chemical manufacturing, and so on. However, during the past only few literatures discussed the dynamics of air motors or their control strategies. The purpose of this paper is to analyze the dynamics of a vane-type air motor, and design a fuzzy logic controller. It is found that the rotational speed of the air motor is strongly affected by the pressure and flow rate of the compressed air. Further, due to the mechanical friction, the overall system is actually nonlinear with dead-zone and has hysteretic behavior. The performance of conventional PI controllers implemented on the air motor usually results in large overshoot, slow response and significant fluctuation errors. To cope with the nonlinear effects of dead-zone and hysteretic behavior, we developed a fuzzy logic controller to improve the performance. The experimental results show that the proposed controller can effectively control the system with a settling time within 0.2 second, the error fluctuation less than 0.5% for high speed operation and 1.5% for low speed operation, and without any overshoot.
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Benzodiazepine-Associated Carcinogenesis
Shih-Chieh Ku,Pei-Shen Ho,Yu-Ting Tseng,Ta-Chuan Yeh,Shu-Li Cheng,Chih-Sung Liang 대한신경정신의학회 2018 PSYCHIATRY INVESTIGATION Vol.15 No.9
Objective Cellular, animal, and human epidemiological studies suggested that benzodiazepines increase the risk of cancer and cancer mortality. Obesity is also clearly linked to carcinogenesis. However, no human studies have examined benzodiazepine-associated carcinogenesis as assessed by changes in cancer biomarkers. Methods A total of 19 patients were recruited, and received a 6-week treatment of 0.5 mg lorazepam. The measured cancer biomarkers were angiopoietin-2 (ANG-2), soluble CD40 ligand, epidermal growth factor, endoglin, soluble Fas ligand (sFASL), heparin-binding EGF-like growth factor (HB-EGF), insulin-like growth factor binding protein, interleukin (IL)-6, IL-8, IL-18, plasminogen activator inhibitor (PLGF), placental growth factor, transforming growth factor (TGF)-α, tumor necrosis factor (TNF)-α, urokinase-type plasminogen (uPA), vascular endothelial growth factor (VEGF)-A, VEGF-C, and VEGF-D. Results Six cancer biomarkers were significantly increased in all patients as a whole. The subgroup analysis revealed a distinct pattern of change. Overweight patients showed a significant increase in 11 cancer biomarkers, including ANG-2, sFASL, HB-EGF, IL-8, PLGF, TGF-α, TNF-α, uPA, VEGF-A, VEGF-C, and VEGF-D. However, normal-weight patients did not show any changes in cancer biomarkers. Conclusion Adiposity may have primed the carcinogenic potential, leading to lorazepam-associated carcinogenesis in overweight patients. Epidemiological studies addressing this issue should consider the potential modulator contributing to benzodiazepine-associated carcinogenesis.
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Application of cepstrum and neural network to bearing fault detection
Yean-Ren Hwang,Kuo-Kuang Jen,Yu-Ta Shen 대한기계학회 2009 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.23 No.10
This paper proposes an integrated system for motor bearing diagnosis that combines the cepstrum coefficient method for feature extraction from motor vibration signals and artificial neural network (ANN) models. We divide the motor vibration signal, obtain the corresponding cepstrum coefficients, and classify the motor systems through ANN models. Utilizing the proposed method, one can identify the characteristics hiding inside a vibration signal and classify the signal, as well as diagnose the abnormalities. To evaluate this method, several tests for the normal and abnormal conditions were performed in the laboratory. The results show the effectiveness of cepstrum and ANN in detecting the bearing condition. The proposed method successfully extracted the corresponding feature vectors, distinguished the difference, and classified bearing faults correctly.
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