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RISS 인기검색어
- 검색키워드
- 저자 : Saeid Sadri (검색결과 3 건)
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Saeid Amini-Nik,Ali-Reza Sadri,Li Diao,Cassandra Belo,Marc G. Jeschke 생화학분자생물학회 2018 Experimental and molecular medicine Vol.50 No.-
Liver fibrosis is problematic after persistent injury. However, little is known about its response to an acute insult. Accumulation of myeloid lineage cells contributes into the promotion and resolution of inflammation and fibrosis. Using Cre-transgenic mice that specifically mark myeloid lineage cells with EYFP and burn as a model of acute systemic injury, we investigated the role of myeloid lineage cells in the liver after acute injury. Our data show that thermal injury in mice (30% total body surface area) induces fibrosis predominantly around portal venules whereas myeloid cells are enriched throughout the liver. The fibrosis peaks around 1–2 weeks post injury and resolves by week 3. Ablating myeloid cells led to lower fibrosis. Through FACS sorting, we isolated myeloid lineage cells (EYFP +ve cells) from injured animals and from the control uninjured animals and subjected the extracted RNA from these cells to microarray analysis. Microarray analysis revealed an inflammatory signature for EYFP +ve cells isolated from injured animals in comparison with control cells. Moreover, it showed modulation of components of the serotonin (5-HT) pathway in myeloid cells. Antagonizing the 5HT2A/2C receptor decreased fibrosis in thermally injured mice by skewing macrophages away from their pro-fibrotic phenotype. Macrophages conditioned with Ketanserin showed a lower profibrotic phenotype in a co-culture system with mesenchymal cells. There is a spatiotemporal pattern in liver fibrosis post-thermal injury, which is associated with the influx of myeloid cells. Treating mice with a 5HT2A/2C receptor antagonist promotes an anti-fibrotic effect, through modulating the phenotype of macrophages.
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Intelligent Diagnosis of Broken Bars in Induction Motors Based on New Features in Vibration Spectrum
Sadoughi, Alireza,Ebrahimi, Mohammad,Moallem, Mehdi,Sadri, Saeid The Korean Institute of Power Electronics 2008 JOURNAL OF POWER ELECTRONICS Vol.8 No.3
Many induction motor broken bar diagnosis methods are based on evaluating special components in machine signals spectrums. Current, power, flux, etc are among these signals. Frequencies related to a broken rotor fault are slip dependent, therefore, correct diagnosis of fault - especially when obtrusive frequency components are present - depends on accurate determination of motor velocity and slip. The traditional methods typically require several sensors that should be pre-installed in some cases. This paper presents a diagnosis method based on only a vibration sensor. Motor velocity oscillation due to a broken rotor causes frequency components at twice slip frequency difference around speed frequency in vibration spectrum. Speed frequency and its harmonics as well as twice supply frequency, can easily and accurately be found in a vibration spectrum, therefore th motor slip can be computed. Now components related to rotor fault can be found. It is shown that a trained neural network - as a substitute for an expert person - can easily categorize the existence and the severity of a fault according to the features extracted from the presented method. This method requires no information about th motor internal and has been able to diagnose correctly in all the laboratory tests.
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Intelligent Diagnosis of Broken Bars in Induction Motors Based on New Features in Vibration Spectrum
Alireza Sadoughi,Mohammad Ebrahimi,Mehdi Moallem,Saeid Sadri 전력전자학회 2008 JOURNAL OF POWER ELECTRONICS Vol.8 No.3
Many induction motor broken bar diagnosis methods are based on evaluating special components in machine signals spectrums. Current, power, flux, etc are among these signals. Frequencies related to a broken rotor fault are slip dependent, therefore, correct diagnosis of fault - especially when obtrusive frequency components are present - depends on accurate determination of motor velocity and slip. The traditional methods typically require several sensors that should be pre-installed in some cases. This paper presents a diagnosis method based on only a vibration sensor. Motor velocity oscillation due to a broken rotor causes frequency components at twice slip frequency difference around speed frequency in vibration spectrum. Speed frequency and its harmonics as well as twice supply frequency, can easily and accurately be found in a vibration spectrum, therefore the motor slip can be computed. Now components related to rotor fault can be found. It is shown that a trained neural network - as a substitute for an expert person - can easily categorize the existence and the severity of a fault according to the features extracted from the presented method. This method requires no information about the motor internal structure and has been able to diagnose correctly in all the laboratory tests.
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