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Your search keyword '"Tian, Yimin"' showing total 88 results
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88 results on '"Tian, Yimin"'

10. Recruitment of RNA Polymerase II to Metabolic Gene Promoters Is Inhibited in the Failing Heart Possibly Through PGC-1α (Peroxisome Proliferator-Activated Receptor-γ Coactivator-1α) Dysregulation

Author

Bhat, Santosh, Chin, Adave, Shirakabe, Akihiro, Ikeda, Yoshiyuki, Ikeda, Shohei, Zhai, Peiyong, Hsu, Chiao-po, Sayed, Danish, Abdellatif, Maha, Byun, Jaemin, Schesing, Kevin, Tang, Fan, Tian, Yimin, Babu, Gopal, Ralda, Guersom, Warren, Junco S., Cho, Jaeyeaon, Sadoshima, Junichi, and Oka, Shin-ichi

Published
2019
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15. An improved image segmentation algorithm based on the maximum class variance method

Author

Qi Qianhui, Tian Yimin, and Han Lili

Subjects
maximum large class variance method, cuckoo algorithm, image segmentation, the image processing, Engineering (General). Civil engineering (General), TA1-2040
Abstract

Image segmentation is an important part of image processing. The result of image segmentation directly affects the effect of subsequent image processing. However the efficiency of the traditional maximum class variance method is low. This paper uses the cuckoo algorithm to optimize the traditional maximum class variance method to achieve a better segmentation effect. This image segmentation method combined with optimization theory can achieve the purpose of finding the optimal segmentation.

Published
2020
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16. Research on edge detection algorithm based on improved sobel operator

Author

Han Lili, Tian Yimin, and Qi Qianhui

Subjects
edge detection, sobel operator, morphology, thinning edge, location accuracy, Engineering (General). Civil engineering (General), TA1-2040
Abstract

In order to solve the shortcomings of traditional Sobel edge detection operator, such as low accuracy of image edge location and rough edge extracted, an improved edge detection algorithm based on Sobel operator is proposed. Firstly, in the aspect of the accuracy of edge detection, the direction template is increased from two directions of horizontal and vertical to eight directions; secondly, in terms of the rough edge extracted and the noise sensitivity, combined with the operation of mathematical morphology, the edge can be refined, and at the same time, some part of the noise can be suppressed. The experiment results show that the improved edge detection algorithm has a better accuracy in image positioning, and a certain ability to suppress noise. Finally, the detected image edge of the image is more delicate and clear than the traditional Sobel operator.

Published
2020
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33. Analysis of Characteristics of Ore about Iron Deposit of Da Hong Mountain in Yun Nan Province

Author

Zhang Yuefeng, Li Jun, Tian Yimin, Yao Yanling, Zhang Yaguang, and Ma Mengling

Subjects
Engineering (General). Civil engineering (General), TA1-2040
Abstract

This thesis aims to analyse the deposit characteristics about Da Hong Mountains Iron ore in Yunnan province. The texture and structure, especially the chemical composition, is different in every section of deposit after comparing. Moreover, the content of SiO2 is much higher than general iron ore. However, the content of other noble metals cannot reach the lowest industrial grade. Da Hong Mountains Iron ore has unique features because of metallogenic periods.

Published
2016
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34. An improved image segmentation algorithm based on the maximum class variance method

Author

Tian Yimin, Han Lili, and Qi Qianhui

Subjects
Variance method, Computer science, business.industry, maximum large class variance method, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Pattern recognition, cuckoo algorithm, Engineering (General). Civil engineering (General), Class (biology), Image segmentation algorithm, Artificial intelligence, the image processing, TA1-2040, business, image segmentation
Abstract

Image segmentation is an important part of image processing. The result of image segmentation directly affects the effect of subsequent image processing. However the efficiency of the traditional maximum class variance method is low. This paper uses the cuckoo algorithm to optimize the traditional maximum class variance method to achieve a better segmentation effect. This image segmentation method combined with optimization theory can achieve the purpose of finding the optimal segmentation.

Published
2020

38. Recruitment of RNA Polymerase II to Metabolic Gene Promoters is Inhibited in the Failing Heart Possibly Through PGC-1α Dysregulation

Author

Bhat, Santosh, Chin, Adave, Shirakabe, Akihiro, Ikeda, Yoshiyuki, Ikeda, Shohei, Zhai, Peiyong, Hsu, Chiao-po, Sayed, Danish, Abdellatif, Maha, Byun, Jaemin, Schesing, Kevin, Tang, Fan, Tian, Yimin, Babu, Gopal, Ralda, Guersom, Warren, Junco S., Cho, Jaeyeaon, Sadoshima, Junichi, and Oka, Shin-ichi

Subjects
Heart Failure, Mice, Knockout, Disease Models, Animal, Mice, urogenital system, Animals, Down-Regulation, RNA Polymerase II, Promoter Regions, Genetic, Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha, Article
Abstract

Proper dynamics of RNA polymerase II, such as promoter recruitment and elongation, are essential for transcription. PGC-1α (peroxisome proliferator-activated receptor [PPAR]-γ coactivator-1α), also termed PPARGC1a, is a transcriptional coactivator that stimulates energy metabolism, and PGC-1α target genes are downregulated in the failing heart. However, whether the dysregulation of polymerase II dynamics occurs in PGC-1α target genes in heart failure has not been defined.Chromatin immunoprecipitation-sequencing revealed that reduced promoter occupancy was a major form of polymerase II dysregulation on PGC-1α target metabolic gene promoters in the pressure-overload-induced heart failure model. PGC-1α-cKO (cardiac-specific PGC-1α knockout) mice showed phenotypic similarity to the pressure-overload-induced heart failure model in wild-type mice, such as contractile dysfunction and downregulation of PGC-1α target genes, even under basal conditions. However, the protein levels of PGC-1α were neither changed in the pressure-overload model nor in human failing hearts. Chromatin immunoprecipitation assays revealed that the promoter occupancy of polymerase II and PGC-1α was consistently reduced both in the pressure-overload model and PGC-1α-cKO mice. In vitro DNA binding assays using an endogenous PGC-1α target gene promoter sequence confirmed that PGC-1α recruits polymerase II to the promoter.These results suggest that PGC-1α promotes the recruitment of polymerase II to the PGC-1α target gene promoters. Downregulation of PGC-1α target genes in the failing heart is attributed, in part, to a reduction of the PGC-1α occupancy and the polymerase II recruitment to the promoters, which might be a novel mechanism of metabolic perturbations in the failing heart.

Published
2019

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