Transfer RNAs(tRNAs)adopt a stable L-shaped tertiary structure crucial for their involvement in protein translation.Among various divalent metal ions,magnesium ions play a pivotal role in preserving the tertiary struc...Transfer RNAs(tRNAs)adopt a stable L-shaped tertiary structure crucial for their involvement in protein translation.Among various divalent metal ions,magnesium ions play a pivotal role in preserving the tertiary structure of tRNA.However,the precise location of the Mg^(2+)binding pocket in human tRNA remains elusive.In this investigation,we identified the Mg^(2+)binding site within human tRNAGln using suppressor tRNA^(Gln).This variant of tRNA recognizes premature stop codons(specificlly UAG)and facilitates the expression of fll-length proteis.By mutating sites 8 and C72 in supprssr tRNAcl,we assessed the decoding efficiency of the resulting mutant suppressor tRNAs,which serves as a measure of tRNA's ability to decode genetic information.Our analysis revealed that the U8C mutant suppressor tRNA exhibited a significantly lower Mg^(2+)content compared to the C72U mutant.Furthermore,we observed a notable reduction in decoding efficiency in the U8-mutated suppressor tRNA,as evidenced by GFP fluorescence and Western blotting analysis.Conversely,mutations at the C72 site had a comparatively minor impact on decoding efficiency.These findings underscored the tight binding of Mg^(2+)to the U8 site of human tRNAGln,crucial for maintaining the stability of tRNA tertiary structure and translation efficacy.Additionally,our investigation delved into the influence of glutamine availability on tRNA decoding efficiency at the cellular level.The results indicated that both the concentration of amino acids and the codon context of TAG could modulate tRNA decoding efficiency.This study provided valuable insights into the structure and function of tRNA,laying the groundwork for further exploration in this field.展开更多
We propose a pipeline structure for Schnorr-Euchner sphere decoding algorithm in this article. It divides the search tree of the original algorithm into blocks and executes the search from block to block. When one blo...We propose a pipeline structure for Schnorr-Euchner sphere decoding algorithm in this article. It divides the search tree of the original algorithm into blocks and executes the search from block to block. When one block search of a signal is over, the part in the pipeline structure that processes this block search can load another signal and search. Several signals can be processed at the same time in one pipeline. Blocks are arranged to lower the whole complexity in the way that the previously search blocks are the blocks those have more probability to generate the final solution. Simulation experiment results show the average process delay can drop to the range from 48.77% to 60.18% in a 4-by-4 antenna system with 16QAM modulation, or from 30.31% to 61.59% in a 4-by-4 antenna system with 64QAM modulation.展开更多
In this paper,it has proposed a realtime implementation of low-density paritycheck(LDPC) decoder with less complexity used for satellite communication on FPGA platform.By adopting a(2048.4096)irregular quasi-cyclic(QC...In this paper,it has proposed a realtime implementation of low-density paritycheck(LDPC) decoder with less complexity used for satellite communication on FPGA platform.By adopting a(2048.4096)irregular quasi-cyclic(QC) LDPC code,the proposed partly parallel decoding structure balances the complexity between the check node unit(CNU) and the variable node unit(VNU) based on min-sum(MS) algorithm,thereby achieving less Slice resources and superior clock performance.Moreover,as a lookup table(LUT) is utilized in this paper to search the node message stored in timeshare memory unit,it is simple to reuse and save large amount of storage resources.The implementation results on Xilinx FPGA chip illustrate that,compared with conventional structure,the proposed scheme can achieve at last 28.6%and 8%cost reduction in RAM and Slice respectively.The clock frequency is also increased to 280 MHz without decoding performance deterioration and convergence speed reduction.展开更多
目的 化学结构识别是化学和计算机视觉领域的一个重要问题,传统光学化学结构识别技术在复杂化学结构识别任务中易发生信息丢失或误识别的现象,同时又因为化学物质的结构多样性常导致其无法解析,识别效果不佳。而基于深度学习的模型通常...目的 化学结构识别是化学和计算机视觉领域的一个重要问题,传统光学化学结构识别技术在复杂化学结构识别任务中易发生信息丢失或误识别的现象,同时又因为化学物质的结构多样性常导致其无法解析,识别效果不佳。而基于深度学习的模型通常具有网络结构复杂度高、上下文信息易丢失和识别率低的问题。为此,提出一种结合注意力机制和编码器—解码器架构的化学结构识别方法。方法 首先,使用改进的ResNet50(residual network)作为特征提取器抓取表征信息;其次,使用BLSTM(bi-directional long-short term memory)作为行编码器为ResNet50提取的表征信息加强空间信息;最后,使用去填充模块和基于覆盖注意力机制的LSTM(long short-term memory)网络作为模型解码器,对化学结构图像进行解码,将编码结果解码为SMILES(simplified molecular input line entry system)序列。结果 在Indigo、ChemDraw、CLEF(Conference and Labs of the Evaluation Forum)、JPO(Japanese Patent Office)、UOB(University of Birmingham)、USPTO(United States Patent and Trademark Office)、Staker、ACS(American Chemistry Society)、CASIA-CSDB(Institute of Automation of Chinese Academy of Sciences—Chemical Structure Database)和Mini CASIA-CSDB数据集上,所提方法识别准确率分别为71.1%、70.21%、45.8%、30.3%、53.02%、58.21%、43.39%、46.3%、84.42%和85.78%,高于SwimOCSR、Image2Mol和ChemPix模型得分。结论 与其他模型相比,本文方法通过少量训练集能够获得较高的识别准确率。展开更多
基金National Natural Science Foundation of China(Grant No.U23A20106)National Key Research and Development Program of China(Grant No.91510100MA6CG8UJ4K)。
文摘Transfer RNAs(tRNAs)adopt a stable L-shaped tertiary structure crucial for their involvement in protein translation.Among various divalent metal ions,magnesium ions play a pivotal role in preserving the tertiary structure of tRNA.However,the precise location of the Mg^(2+)binding pocket in human tRNA remains elusive.In this investigation,we identified the Mg^(2+)binding site within human tRNAGln using suppressor tRNA^(Gln).This variant of tRNA recognizes premature stop codons(specificlly UAG)and facilitates the expression of fll-length proteis.By mutating sites 8 and C72 in supprssr tRNAcl,we assessed the decoding efficiency of the resulting mutant suppressor tRNAs,which serves as a measure of tRNA's ability to decode genetic information.Our analysis revealed that the U8C mutant suppressor tRNA exhibited a significantly lower Mg^(2+)content compared to the C72U mutant.Furthermore,we observed a notable reduction in decoding efficiency in the U8-mutated suppressor tRNA,as evidenced by GFP fluorescence and Western blotting analysis.Conversely,mutations at the C72 site had a comparatively minor impact on decoding efficiency.These findings underscored the tight binding of Mg^(2+)to the U8 site of human tRNAGln,crucial for maintaining the stability of tRNA tertiary structure and translation efficacy.Additionally,our investigation delved into the influence of glutamine availability on tRNA decoding efficiency at the cellular level.The results indicated that both the concentration of amino acids and the codon context of TAG could modulate tRNA decoding efficiency.This study provided valuable insights into the structure and function of tRNA,laying the groundwork for further exploration in this field.
文摘We propose a pipeline structure for Schnorr-Euchner sphere decoding algorithm in this article. It divides the search tree of the original algorithm into blocks and executes the search from block to block. When one block search of a signal is over, the part in the pipeline structure that processes this block search can load another signal and search. Several signals can be processed at the same time in one pipeline. Blocks are arranged to lower the whole complexity in the way that the previously search blocks are the blocks those have more probability to generate the final solution. Simulation experiment results show the average process delay can drop to the range from 48.77% to 60.18% in a 4-by-4 antenna system with 16QAM modulation, or from 30.31% to 61.59% in a 4-by-4 antenna system with 64QAM modulation.
文摘In this paper,it has proposed a realtime implementation of low-density paritycheck(LDPC) decoder with less complexity used for satellite communication on FPGA platform.By adopting a(2048.4096)irregular quasi-cyclic(QC) LDPC code,the proposed partly parallel decoding structure balances the complexity between the check node unit(CNU) and the variable node unit(VNU) based on min-sum(MS) algorithm,thereby achieving less Slice resources and superior clock performance.Moreover,as a lookup table(LUT) is utilized in this paper to search the node message stored in timeshare memory unit,it is simple to reuse and save large amount of storage resources.The implementation results on Xilinx FPGA chip illustrate that,compared with conventional structure,the proposed scheme can achieve at last 28.6%and 8%cost reduction in RAM and Slice respectively.The clock frequency is also increased to 280 MHz without decoding performance deterioration and convergence speed reduction.
文摘目的 化学结构识别是化学和计算机视觉领域的一个重要问题,传统光学化学结构识别技术在复杂化学结构识别任务中易发生信息丢失或误识别的现象,同时又因为化学物质的结构多样性常导致其无法解析,识别效果不佳。而基于深度学习的模型通常具有网络结构复杂度高、上下文信息易丢失和识别率低的问题。为此,提出一种结合注意力机制和编码器—解码器架构的化学结构识别方法。方法 首先,使用改进的ResNet50(residual network)作为特征提取器抓取表征信息;其次,使用BLSTM(bi-directional long-short term memory)作为行编码器为ResNet50提取的表征信息加强空间信息;最后,使用去填充模块和基于覆盖注意力机制的LSTM(long short-term memory)网络作为模型解码器,对化学结构图像进行解码,将编码结果解码为SMILES(simplified molecular input line entry system)序列。结果 在Indigo、ChemDraw、CLEF(Conference and Labs of the Evaluation Forum)、JPO(Japanese Patent Office)、UOB(University of Birmingham)、USPTO(United States Patent and Trademark Office)、Staker、ACS(American Chemistry Society)、CASIA-CSDB(Institute of Automation of Chinese Academy of Sciences—Chemical Structure Database)和Mini CASIA-CSDB数据集上,所提方法识别准确率分别为71.1%、70.21%、45.8%、30.3%、53.02%、58.21%、43.39%、46.3%、84.42%和85.78%,高于SwimOCSR、Image2Mol和ChemPix模型得分。结论 与其他模型相比,本文方法通过少量训练集能够获得较高的识别准确率。
