针对火电机组SO_(2)排放质量浓度的影响因素众多,难以准确预测的问题,提出一种改进向量加权平均(weighted mean of vectors,INFO)算法与双向长短期记忆(bi-directional long short term memory,Bi-LSTM)神经网络相结合的预测模型(改进IN...针对火电机组SO_(2)排放质量浓度的影响因素众多,难以准确预测的问题,提出一种改进向量加权平均(weighted mean of vectors,INFO)算法与双向长短期记忆(bi-directional long short term memory,Bi-LSTM)神经网络相结合的预测模型(改进INFO-Bi-LSTM模型)。采用Circle混沌映射和反向学习产生高质量初始化种群,引入自适应t分布提升INFO算法跳出局部最优解和全局搜索的能力。选取改进INFO-Bi-LSTM模型和多种预测模型对炉内外联合脱硫过程中4种典型工况下的SO_(2)排放质量浓度进行预测,将预测结果进行验证对比。结果表明:改进INFO算法的寻优能力得到提升,并且改进INFO-Bi-LSTM模型精度更高,更加适用于SO_(2)排放质量浓度的预测,可为变工况下的脱硫控制提供控制理论支撑。展开更多
Objective The detection of RNA single nucleotide polymorphism(SNP)is of great importance due to their association with protein expression related to various diseases and drug responses.At present,splintR ligase-assist...Objective The detection of RNA single nucleotide polymorphism(SNP)is of great importance due to their association with protein expression related to various diseases and drug responses.At present,splintR ligase-assisted methods are important approaches for RNA direct detection,but its specificity will be limited when the fidelity of ligases is not ideal.The aim of this study was to create a method to improve the specificity of splintR ligase for RNA detection.Methods In this study,a dualcompetitive-padlock-probe(DCPLP)assay without the need for additional enzymes or reactions is proposed to improve specificity of splintR ligase ligation.To verify the method,we employed dual competitive padlock probe-mediated rolling circle amplification(DCPLP-RCA)to genotype the CYP2C9 gene.Results The specificity was well improved through the competition and strand displacement of dual padlock probe,with an 83.26%reduction in nonspecific signal.By detecting synthetic RNA samples,the method demonstrated a dynamic detection range of 10 pmol/L-1 nmol/L.Furthermore,clinical samples were applied to the method to evaluate its performance,and the genotyping results were consistent with those obtained using the qPCR method.Conclusion This study has successfully established a highly specific direct RNA SNP detection method,and provided a novel avenue for accurate identification of various types of RNAs.展开更多
文摘针对火电机组SO_(2)排放质量浓度的影响因素众多,难以准确预测的问题,提出一种改进向量加权平均(weighted mean of vectors,INFO)算法与双向长短期记忆(bi-directional long short term memory,Bi-LSTM)神经网络相结合的预测模型(改进INFO-Bi-LSTM模型)。采用Circle混沌映射和反向学习产生高质量初始化种群,引入自适应t分布提升INFO算法跳出局部最优解和全局搜索的能力。选取改进INFO-Bi-LSTM模型和多种预测模型对炉内外联合脱硫过程中4种典型工况下的SO_(2)排放质量浓度进行预测,将预测结果进行验证对比。结果表明:改进INFO算法的寻优能力得到提升,并且改进INFO-Bi-LSTM模型精度更高,更加适用于SO_(2)排放质量浓度的预测,可为变工况下的脱硫控制提供控制理论支撑。
文摘Objective The detection of RNA single nucleotide polymorphism(SNP)is of great importance due to their association with protein expression related to various diseases and drug responses.At present,splintR ligase-assisted methods are important approaches for RNA direct detection,but its specificity will be limited when the fidelity of ligases is not ideal.The aim of this study was to create a method to improve the specificity of splintR ligase for RNA detection.Methods In this study,a dualcompetitive-padlock-probe(DCPLP)assay without the need for additional enzymes or reactions is proposed to improve specificity of splintR ligase ligation.To verify the method,we employed dual competitive padlock probe-mediated rolling circle amplification(DCPLP-RCA)to genotype the CYP2C9 gene.Results The specificity was well improved through the competition and strand displacement of dual padlock probe,with an 83.26%reduction in nonspecific signal.By detecting synthetic RNA samples,the method demonstrated a dynamic detection range of 10 pmol/L-1 nmol/L.Furthermore,clinical samples were applied to the method to evaluate its performance,and the genotyping results were consistent with those obtained using the qPCR method.Conclusion This study has successfully established a highly specific direct RNA SNP detection method,and provided a novel avenue for accurate identification of various types of RNAs.
