| 1 | The Patatin-Containing Phospholipase A pPLAIIα Modulates Oxylipin Formation and Water Loss in Arabidopsis thaliana显示文摘patatin 相关的 phospholipase A (pPLA ) 水解膜 glycerolipids 将生产 monoacyl 混合物和免费的丰满的酸。Phospholipids 被 pPLAII 在 sn-1 和 sn-2 劈开包括那些包含的 oxophytodienoic 酸,位置,和 galactolipids 能也用作底层。pPLAII 的脱离减少了 lysophosphatidylcholine 和 lysophosphatidylethanolamine 层次,而是增加的免费的亚麻酸的酸。pPLAII 缺乏的植物显示了 jasmonic 酸和甲基的高水平 jasmonate,以及 oxylipin-biosynthetic 中介 13-hydroperoxylinolenic 酸和比酸的 12-oxophytodienoic 野类型(WT ) 植物。涉及 oxylipin 生产的基因的表示比在 WT 植物在 pPLAII 缺乏的异种也是更高的。变异的植物比 WT 植物更快速失去了水。WT 和变异的植物的 stomata 对 abscisic 酸同样作出回应。响应干燥,异种和 WT 叶子以一样的率生产了 abscisic 酸,,但是,在干燥的 4h 以后, jasmonic 酸水平比 WT 离开的在异种是高得多的。这些结果显示 pPLAII 否定地调整 oxylipin 生产并且从膜在氧化地修改的丰满的酸的移动建议一个角色。 | Wen-Yu Yang Yong Zheng Sung Chul Bahn Xiang-Qing Pan Mao-Yin Li Hieu Sy Vu Mary R.Roth Brad Scheu Ruth Welt Yue-Yun Hong Xue-Min Wang | 2012 | Molecular Plant2012，5，2： | 5 |
| 2 | Intelligent Islanding Detection of Multi-distributed Generation Using Artificial Neural Network Based on Intrinsic Mode Function Feature显示文摘The integration of distributed energy resources(DERs) into distribution networks is becoming increasingly important, as it supports the continued adoption of renewable power generation, combined heat and power plants, and storage systems. Nevertheless, inadvertent islanding operation is one of the major protection issues in distribution networks connected to DERs. This study proposes an intelligent islanding detection method(IIDM) using an intrinsic mode function(IMF)feature-based grey wolf optimized artificial neural network(GWO-ANN). In the proposed IIDM, the modal voltage signal is pre-processed by variational mode decomposition followed by Hilbert transform on each IMF to derive highly involved features. Then, the energy and standard deviation of IMFs are employed to train/test the GWO-ANN model for identifying the islanding operations from other non-islanding events. To evaluate the performance of the proposed IIDM, various islanding and non-islanding conditions such as faults, voltage sag, linear and nonlinear load and switching, are considered as the training and testing datasets. Moreover, the proposed IIDM is evaluated under noise conditions for the measured voltage signal. The simulation results demonstrate that the proposed IIDM is capable of differentiating between islanding and non-islanding events without any sensitivity under noise conditions in the test signal. | Samuel Admasie Syed Basit Ali Bukhari Teke Gush Raza Haider Chul Hwan Kim | 2020 | Journal of Modern Power Systems and Clean Energy2020，8，3： | 2 |
您所在的机构暂未开通此部分的功能，请联系管理员