• Molecules and Cells
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• v.28 no.4
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• pp.375-382
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• 2009

The 26S proteasome is a 2-MDa complex with a central role in protein turn over. The 26S proteasome is comprised of one 20S core particle and two 19S regulatory particles (RPs). The RPN12a protein, a non-ATPase subunit of the 19S RP, was previously shown to be involved in cytokinin signaling in Arabidopsis. To further investigate cellular roles of RPN12a, RNAi transgenic plants of RPN12a were constructed. As expected, the 35S:RNAi-RPN12a plants showed cytokinin signaling defective phenotypes, including abnormal formation of leaves and inflorescences. Furthermore, RNAi knock-down transgenic plants exhibited additional unique phenotypes, including concave and heart-shape cotyledons, triple cotyledons, irregular and clustered guard cells, and defects in phyllotaxy, all of which are typical for defective cytokinin signaling. We next examined the mRNA level of cytokinin signaling components, including type-A ARRs, type-B ARRs, and CRFs. The expression of type-A ARRs, encoding negative regulators of cytokinin signaling, was markedly reduced in 35S:RNAi-RPN12a transgenic plants relative to that in wild type plants, while type-B ARRs and CRFs were unaffected. Our results also indicate that in vivo stability of the ARR5 protein, a negative regulator of cytokinin signaling, is mediated by the 26S proteasome complex. These results suggest that RPN12a participates in feedback inhibitory mechanism of cytokinin signaling through modulation of the abundance of ARR5 protein in Arabidopsis.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.921-926
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• 2009

The RPN provides information which includes the risk level and the priority order of maintenance tasks for components. However, if there is no sufficient historical failure data, the historical failure data from other sources can be applied to the target system. And if we use historical data from other sources without any process, there will be concomitant problems according to a discord of each system characteristic, a difference between the present and the date of failure data, etc. In this paper, a new methodology is proposed to model the failure rate as a fuzzy function to resolve these problems. Taking advantage of this result, the RPN can be calculated by using the fuzzy operation. The proposed method is applied to the substation system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5555-5567
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• 2018

State-of-art instance segmentation networks are successful at generating 2D segmentation mask for region proposals with highest classification score, yet 3D object segmentation task is limited to geocentric embedding or detector of Sliding Shapes. To this end, we propose an amodal 3D instance segmentation network called A3IS-CNN, which extends the detector of Deep Sliding Shapes to amodal 3D instance segmentation by adding a new branch of 3D ConvNet called A3IS-branch. The A3IS-branch which takes 3D amodal ROI as input and 3D semantic instances as output is a fully convolution network(FCN) sharing convolutional layers with existing 3d RPN which takes 3D scene as input and 3D amodal proposals as output. For two branches share computation with each other, our 3D instance segmentation network adds only a small overhead of 0.25 fps to Deep Sliding Shapes, trading off accurate detection and point-to-point segmentation of instances. Experiments show that our 3D instance segmentation network achieves at least 10% to 50% improvement over the state-of-art network in running time, and outperforms the state-of-art 3D detectors by at least 16.1 AP.

• Journal of the Korea Institute of Building Construction
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• v.16 no.6
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• pp.519-527
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• 2016

The demand of construction risk analysis is rapidly increased to improve the competitiveness of construction companies and the sound management of the construction project. However, estimating the amount and uncertainty of the risk is difficult due to the wide range of risks in the construction industry. Moreover, most of the research on risk management of construction risk is only focused on the causes of risk without separate the internal and external risk. This study statistically analysis the internal risk and external risk based on the accidents cases which are caused at construction sites to define the difference and importances of the risk. An accident cause analysis and T-test analysis are carried out to reach the goal of study. The results of the study are expected to be used as a guideline of construction project risk analysis.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.1823-1827
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• 2012

The gene encoding the Nin one binding (NOB1) protein which plays an essential role in protein degradation has been investigated for possible tumor promoting functions. The present study was focused on NOB1 as a possible therapeutic target for breast cancer treatment. Lentivirus mediated NOB1 siRNA transfection was used to silence the NOB1 gene in two established breast cancer cell lines, MCF-7 and MDA-MB-231, successful transfection being confirmed by fluorescence imaging. NOB1 deletion caused significant decline in cell proliferation was observed in both cell lines as investigated by MTT assay. Furthermore the number and size of the colonies formed were also significantly reduced in the absence of NOB1. Moreover NOB1 gene knockdown arrested the cell cycle and inhibited cell cycle related protein expression. Collectively these results indicate that NOB1 plays an essential role in breast cancer cell proliferation and its gene expression could be a therapeutic target.