Plant Homeo Domain(PHD)proteins are involved in diverse biological processes during plant growth.However,the regulation of PHD genes on rice cold stress response remains largely unknown.Here,we reported that PHD17 neg...Plant Homeo Domain(PHD)proteins are involved in diverse biological processes during plant growth.However,the regulation of PHD genes on rice cold stress response remains largely unknown.Here,we reported that PHD17 negatively regulated cold tolerance in rice seedlings as a cleavage target of miR1320.PHD17 expression was greatly induced by cold stress,and was down-regulated by miR1320 overexpression and up-regulated by miR1320 knockdown.Through 5'RACE and dual luciferase assays,we found that miR1320 targeted and cleaved the 3'UTR region of PHD17.PHD17 was a nuclearlocalized protein and acted as a transcriptional activator in yeast.PHD17 overexpression reduced cold tolerance of rice seedlings,while knockout of PHD17 increased cold tolerance,partially via the CBF cold signaling.By combining transcriptomic and physiological analyses,we demonstrated that PHD17 modulated ROS homeostasis and flavonoid accumulation under cold stress.K-means clustering analysis revealed that differentially expressed genes in PHD17 transgenic lines were significantly enriched in the jasmonic acid(JA)biosynthesis pathway,and expression of JA biosynthesis and signaling genes was verified to be affected by PHD17.Cold stress tests applied with MeJA or IBU(JA synthesis inhibitor)further suggested the involvement of PHD17 in JA-mediated cold signaling.Taken together,our results suggest that PHD17 acts downstream of miR1320 and negatively regulates cold tolerance of rice seedlings through JA-mediated signaling pathway.展开更多
An algorithm to track multiple sharply maneuvering targets without prior knowledge about new target birth is proposed. These targets are capable of achieving sharp maneuvers within a short period of time, such as dron...An algorithm to track multiple sharply maneuvering targets without prior knowledge about new target birth is proposed. These targets are capable of achieving sharp maneuvers within a short period of time, such as drones and agile missiles.The probability hypothesis density (PHD) filter, which propagates only the first-order statistical moment of the full target posterior, has been shown to be a computationally efficient solution to multitarget tracking problems. However, the standard PHD filter operates on the single dynamic model and requires prior information about target birth distribution, which leads to many limitations in terms of practical applications. In this paper,we introduce a nonzero mean, white noise turn rate dynamic model and generalize jump Markov systems to multitarget case to accommodate sharply maneuvering dynamics. Moreover, to adaptively estimate newborn targets’information, a measurement-driven method based on the recursive random sampling consensus (RANSAC) algorithm is proposed. Simulation results demonstrate that the proposed method achieves significant improvement in tracking multiple sharply maneuvering targets with adaptive birth estimation.展开更多
考虑到存活目标与新生目标在动态演化特性上的差异性,提出了面向快速多目标跟踪的协同概率假设密度(collaborative probability hypothesis density,CoPHD)滤波框架。该框架利用存活目标的状态信息,将量测动态划分为存活目标量测集与新...考虑到存活目标与新生目标在动态演化特性上的差异性,提出了面向快速多目标跟踪的协同概率假设密度(collaborative probability hypothesis density,CoPHD)滤波框架。该框架利用存活目标的状态信息,将量测动态划分为存活目标量测集与新生目标量测集,在两个量测集分别运用PHD组处理更新基础上建立了处理模块的交互与协同机制,力图在保证跟踪精度的同时提高计算效率。该框架由于采用PHD组处理方式而具有状态自动提取功能。进一步给出了该框架的序贯蒙特卡罗算法实现。仿真结果表明,该算法在计算效率以及状态提取精度上具有明显优势。展开更多
基金supported by the National Natural Science Foundation of China (31971826,U20A2025)Natural Science Foundation of Heilongjiang province (JQ2021C002)the College Student Innovation and Entrepreneurship Program Training Program (202210223055)。
文摘Plant Homeo Domain(PHD)proteins are involved in diverse biological processes during plant growth.However,the regulation of PHD genes on rice cold stress response remains largely unknown.Here,we reported that PHD17 negatively regulated cold tolerance in rice seedlings as a cleavage target of miR1320.PHD17 expression was greatly induced by cold stress,and was down-regulated by miR1320 overexpression and up-regulated by miR1320 knockdown.Through 5'RACE and dual luciferase assays,we found that miR1320 targeted and cleaved the 3'UTR region of PHD17.PHD17 was a nuclearlocalized protein and acted as a transcriptional activator in yeast.PHD17 overexpression reduced cold tolerance of rice seedlings,while knockout of PHD17 increased cold tolerance,partially via the CBF cold signaling.By combining transcriptomic and physiological analyses,we demonstrated that PHD17 modulated ROS homeostasis and flavonoid accumulation under cold stress.K-means clustering analysis revealed that differentially expressed genes in PHD17 transgenic lines were significantly enriched in the jasmonic acid(JA)biosynthesis pathway,and expression of JA biosynthesis and signaling genes was verified to be affected by PHD17.Cold stress tests applied with MeJA or IBU(JA synthesis inhibitor)further suggested the involvement of PHD17 in JA-mediated cold signaling.Taken together,our results suggest that PHD17 acts downstream of miR1320 and negatively regulates cold tolerance of rice seedlings through JA-mediated signaling pathway.
基金supported by the National Natural Science Foundation of China (61773142)。
文摘An algorithm to track multiple sharply maneuvering targets without prior knowledge about new target birth is proposed. These targets are capable of achieving sharp maneuvers within a short period of time, such as drones and agile missiles.The probability hypothesis density (PHD) filter, which propagates only the first-order statistical moment of the full target posterior, has been shown to be a computationally efficient solution to multitarget tracking problems. However, the standard PHD filter operates on the single dynamic model and requires prior information about target birth distribution, which leads to many limitations in terms of practical applications. In this paper,we introduce a nonzero mean, white noise turn rate dynamic model and generalize jump Markov systems to multitarget case to accommodate sharply maneuvering dynamics. Moreover, to adaptively estimate newborn targets’information, a measurement-driven method based on the recursive random sampling consensus (RANSAC) algorithm is proposed. Simulation results demonstrate that the proposed method achieves significant improvement in tracking multiple sharply maneuvering targets with adaptive birth estimation.
文摘考虑到存活目标与新生目标在动态演化特性上的差异性,提出了面向快速多目标跟踪的协同概率假设密度(collaborative probability hypothesis density,CoPHD)滤波框架。该框架利用存活目标的状态信息,将量测动态划分为存活目标量测集与新生目标量测集,在两个量测集分别运用PHD组处理更新基础上建立了处理模块的交互与协同机制,力图在保证跟踪精度的同时提高计算效率。该框架由于采用PHD组处理方式而具有状态自动提取功能。进一步给出了该框架的序贯蒙特卡罗算法实现。仿真结果表明,该算法在计算效率以及状态提取精度上具有明显优势。
