Larix olgensis A.Henry is a fast-growing tree used for aff orestation in northeastern China and has great ecological and economic value.For studying developmental genes in the xylem of this species,we investigated the...Larix olgensis A.Henry is a fast-growing tree used for aff orestation in northeastern China and has great ecological and economic value.For studying developmental genes in the xylem of this species,we investigated the Myb transcription factor family,one of the largest families of transcription factors in plants,which plays an important role in the regulation of lignifi cation in plant secondary walls.By sequencing a L.olgensis cDNA library using the Illumina HiSeq2500 high-throughput sequencing platform,we obtained 58,683 unigene sequences,of which 16,554 unigenes were longer than 1000 bp,accounting for 28.2%of the total database.The alignment of these genes with the GO,COG,KEGG,Swiss-Prot and NR databases resulted in annotated 29,350 unigenes.We obtained a total of 1460 differentially expressed genes,of which 453 were upregulated and 1007 were downregulated at the two developmental stages analyzed.The gene annotations showed a wide range of biological functions and metabolic pathways.The 10 Myb transcription factors that were obtained from the diff erentially expressed genes were analyzed by real-time quantitative PCR(qRT-PCR).The results showed that four Myb transcription factors may be associated with xylem development in L.olgensis.Due to the large genome size of conifers,genomics research on these species has lagged behind that for other plant groups.Our data provide the basis for further studies on xylem development in L.olgensis.展开更多
We propose and numerically demonstrate a photonic computing primitive designed for integrated spiking neural networks (SNNs) based on add-drop ring microresonators (ADRMRs) and electrically reconfigurable phasechange ...We propose and numerically demonstrate a photonic computing primitive designed for integrated spiking neural networks (SNNs) based on add-drop ring microresonators (ADRMRs) and electrically reconfigurable phasechange material (PCM) photonic switches. In this neuromorphic system, the passive silicon-based ADRMR,equipped with a power-tunable auxiliary light, effectively demonstrates nonlinearity-induced dual neural dynamics encompassing spiking response and synaptic plasticity that can generate single-wavelength optical neural spikes with synaptic weight. By cascading these ADRMRs with different resonant wavelengths, weighted multiple-wavelength spikes can be feasibly output from the ADRMR-based hardware arrays when external wavelengthaddressable optical pulses are injected;subsequently, the cumulative power of these weighted output spikes is utilized to ascertain the activation status of the reconfigurable PCM photonic switches. Moreover, the reconfigurable mechanism driving the interconversion of the PCMs between the resonant-bonded crystalline states and the covalent-bonded amorphous states is achieved through precise thermal modulation. Drawing from the thermal properties, an innovative thermodynamic leaky integrate-and-firing (TLIF) neuron system is proposed. With the TLIF neuron system as the fundamental unit, a fully connected SNN is constructed to complete a classic deep learning task:the recognition of handwritten digit patterns. The simulation results reveal that the exemplary SNN can effectively recognize 10 numbers directly in the optical domain by employing the surrogate gradient algorithm. The theoretical verification of our architecture paves a whole new path for integrated photonic SNNs, with the potential to advance the field of neuromorphic photonic systems and enable more efficient spiking information processing.展开更多
文摘Larix olgensis A.Henry is a fast-growing tree used for aff orestation in northeastern China and has great ecological and economic value.For studying developmental genes in the xylem of this species,we investigated the Myb transcription factor family,one of the largest families of transcription factors in plants,which plays an important role in the regulation of lignifi cation in plant secondary walls.By sequencing a L.olgensis cDNA library using the Illumina HiSeq2500 high-throughput sequencing platform,we obtained 58,683 unigene sequences,of which 16,554 unigenes were longer than 1000 bp,accounting for 28.2%of the total database.The alignment of these genes with the GO,COG,KEGG,Swiss-Prot and NR databases resulted in annotated 29,350 unigenes.We obtained a total of 1460 differentially expressed genes,of which 453 were upregulated and 1007 were downregulated at the two developmental stages analyzed.The gene annotations showed a wide range of biological functions and metabolic pathways.The 10 Myb transcription factors that were obtained from the diff erentially expressed genes were analyzed by real-time quantitative PCR(qRT-PCR).The results showed that four Myb transcription factors may be associated with xylem development in L.olgensis.Due to the large genome size of conifers,genomics research on these species has lagged behind that for other plant groups.Our data provide the basis for further studies on xylem development in L.olgensis.
基金National Natural Science Foundation of China(62171087)Sichuan Science and Technology Program(2021JDJQ0023)Fundamental Research Funds for the Central Universities (ZYGX2019J003)。
文摘We propose and numerically demonstrate a photonic computing primitive designed for integrated spiking neural networks (SNNs) based on add-drop ring microresonators (ADRMRs) and electrically reconfigurable phasechange material (PCM) photonic switches. In this neuromorphic system, the passive silicon-based ADRMR,equipped with a power-tunable auxiliary light, effectively demonstrates nonlinearity-induced dual neural dynamics encompassing spiking response and synaptic plasticity that can generate single-wavelength optical neural spikes with synaptic weight. By cascading these ADRMRs with different resonant wavelengths, weighted multiple-wavelength spikes can be feasibly output from the ADRMR-based hardware arrays when external wavelengthaddressable optical pulses are injected;subsequently, the cumulative power of these weighted output spikes is utilized to ascertain the activation status of the reconfigurable PCM photonic switches. Moreover, the reconfigurable mechanism driving the interconversion of the PCMs between the resonant-bonded crystalline states and the covalent-bonded amorphous states is achieved through precise thermal modulation. Drawing from the thermal properties, an innovative thermodynamic leaky integrate-and-firing (TLIF) neuron system is proposed. With the TLIF neuron system as the fundamental unit, a fully connected SNN is constructed to complete a classic deep learning task:the recognition of handwritten digit patterns. The simulation results reveal that the exemplary SNN can effectively recognize 10 numbers directly in the optical domain by employing the surrogate gradient algorithm. The theoretical verification of our architecture paves a whole new path for integrated photonic SNNs, with the potential to advance the field of neuromorphic photonic systems and enable more efficient spiking information processing.
