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The plant N-degron pathways of ubiquitinmediated proteolysis 被引量:7
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作者 Michael John Holdsworth Jorge Vicente +2 位作者 Gunjan Sharma mohamad abbas Agata Zubrycka 《Journal of Integrative Plant Biology》 SCIE CAS CSCD 2020年第1期70-89,共20页
The amino-terminal residue of a protein(or amino-terminus of a peptide following protease cleavage)can be an important determinant of its stability,through the Ubiquitin Proteasome System associated N-degron pathways.... The amino-terminal residue of a protein(or amino-terminus of a peptide following protease cleavage)can be an important determinant of its stability,through the Ubiquitin Proteasome System associated N-degron pathways.Plants contain a unique combination of N-degron pathways(previously called the N-end rule pathways)E3 ligases,PROTEOLYSIS(PRT)6 and PRT1,recognizing non-overlapping sets of amino-terminal residues,and others remain to be identified.Although only very few substrates of PRT1 or PRT6 have been identified,substrates of the oxygen and nitric oxide sensing branch of the PRT6 N-degron pathway include key nuclear-located transcription factors(ETHYLENE RESPONSE FACTOR VIIs and LITTLE ZIPPER 2)and the histone-modifying Polycomb Repressive Complex 2 component VERNALIZATION 2.In response to reduced oxygen or nitric oxide levels(and other mechanisms that reduce pathway activity)these stabilized substrates regulate diverse aspects of growth and development,including response to flooding,salinity,vernalization(cold-induced flowering)and shoot apical meristem function.The N-degron pathways show great promise for use in the improvement of crop performance and for biotechnological applications.Upstream proteases,components of the different pathways and associated substrates still remain to be identified and characterized to fully appreciate how regulation of protein stability through the amino-terminal residue impacts plant biology. 展开更多
关键词 STABILITY RESIDUE CLEAVAGE
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Evaluation of computer vision techniques for automated hardhat detection in indoor construction safety applications 被引量:2
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作者 Bahaa Eddine MNEYMNEH mohamad abbas Hiam KHOURY 《Frontiers of Engineering Management》 2018年第2期227-239,共13页
Construction is considered among the most dangerous industries and is responsible for a large portion of total worker fatalities. A construction worker has a probability of 1-in-200 of dying on the job during a 45-yea... Construction is considered among the most dangerous industries and is responsible for a large portion of total worker fatalities. A construction worker has a probability of 1-in-200 of dying on the job during a 45-year career, mainly due to fires, falls, and being struck by or caught between objects. Hence, employers must ensure their workers wear personal protective equipment(PPE), in particular hardhats, if they are at risk of falling, being struck by falling objects, hitting their heads on static objects, or coming in proximity to electrical hazards.However, monitoring the presence and proper use of hardhats becomes inefficient when safety officers must survey large areas and a considerable number of workers.Using images captured from indoor jobsites, this paper evaluates existing computer vision techniques, namely object detection and color-based segmentation tools, used to rapidly detect if workers are wearing hardhats.Experiments are conducted and the results highlight the potential of cascade classifiers, in particular, to accurately,precisely, and rapidly detect hardhats under different scenarios and for repetitive runs, and the potential of color-based segmentation to eliminate false detections. 展开更多
关键词 CONSTRUCTION safety personal protectiveequipment hardhat computer vision
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