Thousands of long-distance mobile mRNAs were identified from different grafting systems,based on high-throughput sequencing technology.Moreover,the long-distance delivery of RNAs was proved to involve multiple mechani...Thousands of long-distance mobile mRNAs were identified from different grafting systems,based on high-throughput sequencing technology.Moreover,the long-distance delivery of RNAs was proved to involve multiple mechanisms.Here,we analyzed the homology,motif,and tRNA-like structure(TLS)of long-distance mobile mRNAs identified by RNA-seq as well as the RNA-binding protein(RBP)in nine grafting combinations including Arabidopsis thaliana,Vitis vinifera,Cucumis sativus,Citrullus lanatus,Nicotiana benthamiana,Malus domestica,Pyrus spp.,Glycine max and Phaseolus vulgaris.Although several mRNAs were found to be shared in herbaceous,woody,and related species,the vast majority of long-distance mobile mRNAs were species-specific.Four non-specific movement-related motifs were identified,while the TLS was not necessary for mRNA long distance mobility.In addition,we found that RBPs were conserved among herbaceous and woody plants as well as related species.This paper reports a further in-depth analysis of the endogenous mechanisms by which the species-specific transportable m RNAs were selected by bioinformatics,in order to provide insights for future research on long-distance mobile mRNAs.展开更多
Gas flexible pipes are critical multi-layered equipment for offshore oil and gas development.Under high pressure conditions,small molecular components of natural gas dissolve into the polymer inner liner of the flexib...Gas flexible pipes are critical multi-layered equipment for offshore oil and gas development.Under high pressure conditions,small molecular components of natural gas dissolve into the polymer inner liner of the flexible pipes and further diffuse into the annular space,incurring annular pressure build-up and/or production of acidic environment,which poses serious challenges to the structure and integrity of the flexible pipes.Gas permeation in pipes is a complex phenomenon governed by various factors such as internal pressure and temperature,annular structure,external temperature.In a long-distance gas flexible pipe,moreover,gas permeation exhibits non-uniform features,and the gas permeated into the annular space flows along the metal gap.To assess the complex gas transport behavior in long-distance gas flexible pipes,a mathematical model is established in this paper considering the multiphase flow phenomena inside the flexible pipes,the diffusion of gas in the inner liner,and the gas seepage in the annular space under varying permeable properties of the annulus.In addition,the effect of a variable temperature is accounted.A numerical calculation method is accordingly constructed to solve the coupling mathematical equations.The annular permeability was shown to significantly influence the distribution of annular pressure.As permeability increases,the annular pressure tends to become more uniform,and the annular pressure at the wellhead rises more rapidly.After annular pressure relief followed by shut-in,the pressure increase follows a convex function.By simulating the pressure recovery pattern after pressure relief and comparing it with test results,we deduce that the annular permeability lies between 123 and 512 m D.The results help shed light upon assessing the annular pressure in long distance gas flexible pipes and thus ensure the security of gas transport in the emerging development of offshore resources.展开更多
为实现高超声速飞行器姿态自抗扰控制的参数整定,提出一种模糊Q学习算法。首先,采用强化学习中的Q学习算法来实现姿态自抗扰控制参数的离线闭环快速自适应整定;然后,根据模糊控制的思路,将控制参数划分为不同区域,通过设定奖励,不断更新...为实现高超声速飞行器姿态自抗扰控制的参数整定,提出一种模糊Q学习算法。首先,采用强化学习中的Q学习算法来实现姿态自抗扰控制参数的离线闭环快速自适应整定;然后,根据模糊控制的思路,将控制参数划分为不同区域,通过设定奖励,不断更新Q表;最后,将训练好的Q表用于飞行器的控制。仿真结果表明,相对于传统的线性自抗扰控制(linear active disturbance rejection control,LADRC)和滑模控制,基于Q学习的LADRC省去了人工调试参数的繁琐过程,且仍具有良好的跟踪效果。蒙特卡罗仿真测试结果验证了基于Q学习的LADRC的鲁棒性。展开更多
传统的拓扑优化算法均基于灵敏度分析的方式求解,如渐进结构优化法(Evolutionary Structural Optimization, ESO)和变密度法(Solid Isotropic Material with Penalization, SIMP)等,灵敏度分析依赖于严谨的数学模型,结果可信度高,但面...传统的拓扑优化算法均基于灵敏度分析的方式求解,如渐进结构优化法(Evolutionary Structural Optimization, ESO)和变密度法(Solid Isotropic Material with Penalization, SIMP)等,灵敏度分析依赖于严谨的数学模型,结果可信度高,但面对不同的结构和约束条件都需要反复重新推导单元灵敏度,对使用人员的数学能力有较高要求,而且也导致了收敛速度慢、迭代步数多的问题。针对现有优化方法中存在的缺陷,结合强化学习Q学习理论和元胞自动机原理,提出一种新的拓扑优化方法:Q学习-元胞法(Q-learning-Cellular Automaton, QCA),尝试为工程构件的优化设计提供一种新思路。这种方法以有限元单元作为元胞,将所有元胞的智能行为集成为一个Q-learning智能体。训练过程中,各个元胞首先完成对自身环境的感知,然后调用智能体进行决策并通过环境交互得到反馈,智能体也借此得到大量数据来学习更新,整个过程不涉及数学模型推导,通过智能体和元胞的不断探索即可完成优化。在此基础上,探讨元胞的选择及其邻域和状态的描述方式,针对元胞的动作空间及收益函数进行比选,进而编制相关拓扑优化软件。优化算例表明,QCA方法优化后的拓扑构型与传统优化方法的构型基本一致,迭代步数较SIMP法降低了64%,且柔顺度更低。Q学习-元胞法在结构拓扑优化中具备良好的可行性,计算效率高且具有迁移优化能力,在结构拓扑优化领域极具潜力。展开更多
基金supported by the 111 Project(Grant No.B17043)the 2115 Talent Development Program of China Agricultural University。
文摘Thousands of long-distance mobile mRNAs were identified from different grafting systems,based on high-throughput sequencing technology.Moreover,the long-distance delivery of RNAs was proved to involve multiple mechanisms.Here,we analyzed the homology,motif,and tRNA-like structure(TLS)of long-distance mobile mRNAs identified by RNA-seq as well as the RNA-binding protein(RBP)in nine grafting combinations including Arabidopsis thaliana,Vitis vinifera,Cucumis sativus,Citrullus lanatus,Nicotiana benthamiana,Malus domestica,Pyrus spp.,Glycine max and Phaseolus vulgaris.Although several mRNAs were found to be shared in herbaceous,woody,and related species,the vast majority of long-distance mobile mRNAs were species-specific.Four non-specific movement-related motifs were identified,while the TLS was not necessary for mRNA long distance mobility.In addition,we found that RBPs were conserved among herbaceous and woody plants as well as related species.This paper reports a further in-depth analysis of the endogenous mechanisms by which the species-specific transportable m RNAs were selected by bioinformatics,in order to provide insights for future research on long-distance mobile mRNAs.
基金supported by the Natural Science Research Project of Guangling College of Yangzhou University,China (ZKZD18004)General Program of Natural Science Research in Higher Education Institutions of Jiangsu Province,China (20KJD430006)。
文摘Gas flexible pipes are critical multi-layered equipment for offshore oil and gas development.Under high pressure conditions,small molecular components of natural gas dissolve into the polymer inner liner of the flexible pipes and further diffuse into the annular space,incurring annular pressure build-up and/or production of acidic environment,which poses serious challenges to the structure and integrity of the flexible pipes.Gas permeation in pipes is a complex phenomenon governed by various factors such as internal pressure and temperature,annular structure,external temperature.In a long-distance gas flexible pipe,moreover,gas permeation exhibits non-uniform features,and the gas permeated into the annular space flows along the metal gap.To assess the complex gas transport behavior in long-distance gas flexible pipes,a mathematical model is established in this paper considering the multiphase flow phenomena inside the flexible pipes,the diffusion of gas in the inner liner,and the gas seepage in the annular space under varying permeable properties of the annulus.In addition,the effect of a variable temperature is accounted.A numerical calculation method is accordingly constructed to solve the coupling mathematical equations.The annular permeability was shown to significantly influence the distribution of annular pressure.As permeability increases,the annular pressure tends to become more uniform,and the annular pressure at the wellhead rises more rapidly.After annular pressure relief followed by shut-in,the pressure increase follows a convex function.By simulating the pressure recovery pattern after pressure relief and comparing it with test results,we deduce that the annular permeability lies between 123 and 512 m D.The results help shed light upon assessing the annular pressure in long distance gas flexible pipes and thus ensure the security of gas transport in the emerging development of offshore resources.
文摘为实现高超声速飞行器姿态自抗扰控制的参数整定,提出一种模糊Q学习算法。首先,采用强化学习中的Q学习算法来实现姿态自抗扰控制参数的离线闭环快速自适应整定;然后,根据模糊控制的思路,将控制参数划分为不同区域,通过设定奖励,不断更新Q表;最后,将训练好的Q表用于飞行器的控制。仿真结果表明,相对于传统的线性自抗扰控制(linear active disturbance rejection control,LADRC)和滑模控制,基于Q学习的LADRC省去了人工调试参数的繁琐过程,且仍具有良好的跟踪效果。蒙特卡罗仿真测试结果验证了基于Q学习的LADRC的鲁棒性。
