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| 1 | Expression Patterns of ABA and GA Metabolism Genes and Hormone Levels during Rice Seed Development and Imbibition: A Comparison of Dormant and Non-Dormant Rice Cultivars显示文摘Seed dormancy is an important agronomic trait in cereals. Using deep dormant(N22), medium dormant(ZH11), and non-dormant(G46B)rice cultivars, we correlated seed dormancy phenotypes with abscisic acid(ABA) and gibberellin(GA) metabolism gene expression profiles and phytohormone levels during seed development and imbibition. A time course analysis of ABA and GA content during seed development showed that N22 had a high ABA level at early and middle seed developmental stages, while at late developmental stage it declined to the level of ZH11; however, its ABA/GA ratio maintained at a high level throughout seed development. By contrast, G46 B had the lowest ABA content during seed development though at early developmental stage its ABA level was close to that of ZH11, and its ABA/GA ratio peaked at late developmental stage that was at the same level of ZH11. Compared with N22 and G46 B, ZH11 had an even and medium ABA level during seed development and its ABA/GA ratio peaked at the middle developmental stage. Moreover, the seed development time-point having high ABA/GA ratio also had relatively high transcript levels for key genes in ABA and GA metabolism pathways across three cultivars. These indicated that the embryo-imposed dormancy has been induced before the late developmental stage and is determined by ABA/GA ratio. A similar analysis during seed imbibition showed that ABA was synthesized in different degrees for the three cultivars. In addition, water uptake assay for intact mature seeds suggested that water could permeate through husk barrier into seed embryo for all three cultivars; however, all three cultivars showed distinct colors by vanillin-staining indicative of the existence | Yang Liu Jun Fang Fan Xu Jinfang Chu Cunyu Yan Michael R.Schlappi Youping Wang Chengcai Chu | 2014 | Journal of Genetics and Genomics2014，41，6： | 7 |
| 2 | Innovation of Talent Cultivation Mode under the Background of Transnational Cooperation显示文摘 | Lihui Xie Junyue Cheng Youping Fan | 2014 | 教育研究前沿(中英文版)2014，4，2： | 0 |
| 3 | Targeting cancer cell plasticity by HDAC inhibition to reverse EBV-induced dedifferentiation in nasopharyngeal carcinoma显示文摘Application of differentiation therapy targeting cellular plasticity for the treatment of solid malignancies has been lagging.Nasopharyngeal carci noma(NPC)is a distinctive cancer with poor differe ntiatio n and high prevalenee of Epstein-Barr virus(EBV)infection.Here,we show that the expressi on of EBV latent protein LMP1 in duces dediffere ntiated and stem-like status with high plasticity through the transcriptional inhibition of CEBPA.Mechanistically,LMP1 upregulates STAT5A and recruits HDAC 1/2 to the CEBPA locus to reduce its histone acetylation.HDAC inhibition restored CEBPA expression,reversing cellular dedifferentiation and stem-like status in mouse xeno graft models.These fin dings provide a novel mecha nistic epigenetic-based in sight into virus-induced cellular plasticity and propose a promising concept of differentiation therapy in solid tumor by using HDAC inhibitors to target cellular plasticity. | Jiajun Xie Zifeng Wang Wenjun Fan Youping Liu Fang Liu Xiangbo Wan Meiling Liu Xuan Wang Deshun Zeng Van Wang Bin He Min Yan Zijian Zhang Mengjuan Zhang Zhijie Hou Chunli Wang Zhijie Kang Wenfeng Fang Li Zhang Eric W-F Lam Xiang Guo Jinsong Yan Yixin Zeng Mingyuan Chen Quentin Liu | 2021 | Signal Transduction and Targeted Therapy2021，6，10： | 0 |
| 4 | Deeper Attention-Based Network for Structured Data显示文摘Deep learning methods are applied into structured data and in typical methods,low-order features are discarded after combining with high-order featuresfor prediction tasks.However,in structured data,ignorance of low-order features may cause the low prediction rate.To address this issue,in this paper,deeper attention-based network(DAN)is proposed.With DAN method,to keep both low-and high-order features,attention average pooling layer was utilized to aggregate features of each order.Furthermore,by shortcut connections from each layer to attention average pooling layer,DAN can be built extremely deep to obtain enough capacity.Experimental results show DAN has good performance and works effectively. | Xiaohua Wu Youping Fan Wanwan Peng Hong Pang Yu Luo | 2020 | 国际计算机前沿大会会议论文集2020，，1： | 0 |
| 5 | Intelligent Breakage Assessment of Composite Insulators on Overhead Transmission Lines by Ellipse Detection Based on IRHT显示文摘With the development of unmanned aerial vehicle(UAV)technology,visible images are playing an important role in the maintenance of power systems.To achieve the shed breakage evaluation of composite insulators by UAV visible images,an intelligent fault assessment method is proposed.First,the composite insulators in visible light images are identified by Faster-RCNN.After image preprocessing,the image is enhanced and the noise is removed.Then,a canny operator is used to extract the edge of the sheds.An Improved Randomized Hough Transform(IRHT)is used to detect the ellipses in the edge image.The parameters of the detected ellipse,length of major axes and minor axes,center coordinates and deflection angle of major axes,are used to realize the segmentation of the composite insulator.Finally,the number of pixel points in the ellipse and the distance between the points and the ellipse boundary are used to judge whether there are breakage or cracks on the sheds.The area ratio of the breakage to the whole shed is calculated based on the number of pixel points inside the broken area.This method can be realized without a large amount of training dataset of the specific fault type and provides a technical basis for the online fault assessment of a composite insulator on overhead transmission lines. | Zhikang Yuan Linxuan He Shaohe Wang Youping Tu Zhaojing Li Cong Wang Fan Li | 2023 | CSEE Journal of Power and Energy Systems2023，9，5： | 0 |
| 6 | Multiclassification algorithm and its realization based on least square support vector machine algorithm显示文摘As a new type of learning machine developed on the basis of statistics learning theory, support vector machine (SVM) plays an important role in knowledge discovering and knowledge updating by constructing nonlinear optimal classifier. However, realizing SVM requires resolving quadratic programming under constraints of inequality, which results in calculation difficulty while learning samples gets larger. Besides, standard SVM is incapable of tackling multiclassification. To overcome the bottleneck of populating SVM, with training algorithm presented, the problem of quadratic programming is converted into that of resolving a linear system of equations composed of a group of equation constraints by adopting the least square SVM(LSSVM) and introducing a modifying variable which can change inequality constraints into equation constraints, which simplifies the calculation. With regard to multiclassification, an LSSVM applicable in multiclassification is deduced. Finally, efficiency of the algorithm is checked by using universal Circle in square and twospirals to measure the performance of the classifier. | Fan Youping Chen Yunping Sun Wansheng Li Yu | 2005 | Journal of Systems Engineering and Electronics2005，16，4： | 0 |
| 7 | Decay-like fracture diagnosis of composite insulator based on small sample virtual expansion and radar graph mapping显示文摘Due to the complexity of test procedures and the high cost of measurements,the mechanism of the decay-like fracture is unclear,which brings hard concepts and the small sample problem.Therefore,it is intractable to establish accurate data-driven models.To solve the above mentioned problems,this paper proposes a data-driven modeling method based on radar graph mapping models and virtual sample generation(Radar-VSG).The main idea of the proposed method is to construct and select the most appropriate input features by using radar graph mapping,and to generate virtual samples by using the local outlier factor based on the isometric feature mapping algorithm(Isomap-LOF).To verify the effectiveness of our approach,a set of 27 training samples and 127 testing samples from China Southern Power Grid was applied.Experimental results suggested the accuracy was up to 100%after adding more than 27 virtual samples,with a 4.75%improvement.And the model has the best generalisation ability for 270 virtual samples,with the root mean square error of 0.018.Compared with support vector machine and four advanced VSG methods,the proposed Radar-VSG can achieve better performance. | Ben Shang Youping Fan Yuqing Zhang Lei Yang Zijiang Wang Yating Zhang Zian Zeng Jianyi Guo | 2023 | High Voltage2023，8，2： | 0 |
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