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Weiti Cui Zihan Zhuang Peihao Jiang Jincheng Pan Gan Zhao Sheng Xu Wenbiao Shen 《International journal of molecular sciences》2022,23(14)
Cinnamoyl-CoA reductase (CCR) is a pivotal enzyme in plant lignin synthesis, which has a role in plant secondary cell wall development and environmental stress defense. Alfalfa is a predominant legume forage with excellent quality, but the lignin content negatively affects fodder digestibility. Currently, there is limited information on CCR characteristics, gene expression, and its role in lignin metabolism in alfalfa. In this study, we identified 30 members in the CCR gene family of Medicago sativa. In addition, gene structure, conserved motif, and evolution analysis suggested MsCCR1–7 presumably functioned as CCR, while the 23 MsCCR-likes fell into three categories. The expression patterns of MsCCRs/MsCCR-likes suggested their role in plant development, response to environmental stresses, and phytohormone treatment. These results were consistent with the cis-elements in their promoters. Histochemical staining showed that lignin accumulation gradually deepened with the development, which was consistent with gene expression results. Furthermore, recombinant MsCCR1 and MsCCR-like1 were purified and the kinetic parameters were tested under four substrates. In addition, three-dimensional structure models of MsCCR1 and MsCCR-like1 proteins showed the difference in the substrate-binding motif H212(X)2K215R263. These results will be useful for further application for legume forage quality modification and biofuels industry engineering in the future. 相似文献
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电网工程架空线路塔杆放样多在复杂山区进行,传统基于经纬仪、全站仪和手持差分卫星定位等设备的放样方式劳动强度大、耗时长且数据易出错。提出了一种无人机载智能塔基定位的放样方法,该方法以无人机、激光投点器为硬件基础,研究开发智能放样软件。将电网工程架空线路上各塔杆中心桩坐标输入智能放样软件平台,可实时计算各塔杆20个放样点的平面坐标,并根据DEM模型、地表树木、交通线路及其他障碍物分布状况自动规划无人机放样航线、调整航高,在各放样点上方悬停后进行激光投点,高效引导地表人员快速确定放样点位。经过多轮测试,结果表明:采用无人机载智能塔基定位放样系统可快速、高精度完成输电线路塔杆放样,大幅降低了传统放样方式中放样点布设的次数与时长,为电网施工放样提供了有效支撑。 相似文献
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For large-scale radio frequency identification ( RFID) indoor positioning system, the positioning scale isrelatively large, with less labeled data and more unlabeled data, and it is easily affected by multipath and whitenoise. An RFID positioning algorithm based on semi-supervised actor-critic co-training (SACC) was proposed tosolve this problem. In this research, the positioning is regarded as Markov decision-making process. Firstly, theactor-critic was combined with random actions and selects the unlabeled best received signal arrival intensity(RSSI) data by co-training of the semi-supervised. Secondly, the actor and the critic were updated by employingKronecker-factored approximation calculate (K-FAC) natural gradient. Finally, the target position was obtained byco-locating with labeled RSSI data and the selected unlabeled RSSI data. The proposed method reduced the cost ofindoor positioning significantly by decreasing the number of labeled data. Meanwhile, with the increase of thepositioning targets, the actor could quickly select unlabeled RSSI data and updates the location model. Experimentshows that, compared with other RFID indoor positioning algorithms, such as twin delayed deep deterministic policygradient (TD3), deep deterministic policy gradient (DDPG), and actor-critic using Kronecker-factored trustregion ( ACKTR), the proposed method decreased the average positioning error respectively by 50.226%,41.916%, and 25.004%. Meanwhile, the positioning stability was improved by 23.430%, 28.518%, and38.631%. 相似文献
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Zihan Ma Xiaofei Lu Sunghyun Park Tatsuya Shinagawa Masashi Okubo Kazuhiro Takanabe Atsuo Yamada 《Advanced functional materials》2023,33(25):2214466
Hydrogen is a promising alternative to fossil fuels that can reduce greenhouse gas emissions. Decoupled water electrolysis system using a reversible proton storage redox mediator, where the oxygen evolution reaction and hydrogen evolution reaction are separated in time and space, is an effective approach to producing hydrogen gas with high purity, high flexibility, and low cost. To realize fast hydrogen production in such a system, a redox mediator capable of releasing protons rapidly is required. Herein, α-MoO3, with an ultrafast proton transfer property that can be explained by a dense hydrogen bond network in the lattice oxygen arrays of HxMoO3, is examined as a high-rate redox mediator for fast hydrogen production in acidic electrolytes. The α-MoO3 redox mediator shows both a large capacity of 204 mAh g−1 and fast hydrogen production at a current rate of 10 A cm−2(≈153 A g−1), outperforming most of the previously reported solid-state redox mediators. 相似文献
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针对移动卫星通信系统在高动态和强机动等复杂地理环境下,测控系统不能保证天线姿态稳定和指向实时对准的问题,提出了一种量测误差实时渐变的强跟踪姿态估计算法。通过量测误差实时渐变来改善强跟踪滤波中渐消因子突增造成的过调节问题;通过引入多重渐消因子对保证滤波预测方差阵的对称性不被破坏;通过强跟踪滤波提高天线姿态在强机动下的稳定性,增强对突变的跟踪能力。实验仿真表明,该算法在强机动和高动态条件下有较强模型参数失配的鲁棒性和突变情况下的跟踪能力,能有效提高天线姿态在高动态下的估计精度。 相似文献