Abstract Using the method of stepwise multivariate linear regression (SMLR), the quantitative structure activity relationships (QSAR) of two isomeric series of taxol and its derivatives have been studied. It was foun...Abstract Using the method of stepwise multivariate linear regression (SMLR), the quantitative structure activity relationships (QSAR) of two isomeric series of taxol and its derivatives have been studied. It was found that the molar refractivity of the C3′substituent of the C13 side chain has significant correlation with its activity. We deduce that structural changes in the C3′substituents may be critical to the anticancer function. It would be useful to the design and synthesis of taxol like compounds with improved activities.展开更多
Understanding the spatial-temporal dynamics of crop nitrogen(N)use efficiency(NUE)and the relationship with explanatory environmental variables can support land-use management and policymaking.Nevertheless,the applica...Understanding the spatial-temporal dynamics of crop nitrogen(N)use efficiency(NUE)and the relationship with explanatory environmental variables can support land-use management and policymaking.Nevertheless,the application of statistical models for evaluating the explanatory variables of space-time variation in crop NUE is still under-researched.In this study,stepwise multiple linear regression(SMLR)and Random Forest(RF)were used to evaluate the spatial and temporal variation of NUE indicators(i.e.,partial factor productivity of N(PFPN);partial nutrient balance of N(PNBN))at county scale in Northeast China(Heilongjiang,Liaoning and Jilin provinces)from 1990 to 2015.Explanatory variables included agricultural management practices,topography,climate,economy,soil and crop types.Results revealed that the PFPN was higher in the northern parts and lower in the center of the Northeast China and PNBN increased from southern to northern parts during the 1990–2015 period.The NUE indicators decreased with time in most counties during the study period.The model efficiency coefficients of the SMLR and RF models were 0.44 and 0.84 for PFPN,and 0.67 and 0.89 for PNBN,respectively.The RF model had higher relative importance of soil and climatic covariates and lower relative importance of crop covariates compared to the SMLR model.The planting area index of vegetables and beans,soil clay content,saturated water content,enhanced vegetation index in November&December,soil bulk density,and annual minimum temperature were the main explanatory variables for both NUE indicators.This is the first study to show the quantitative relative importance of explanatory variables for NUE at a county level in Northeast China using RF and SMLR.This novel study gives reference measurements to improve crop NUE which is one of the most effective means of managing N for sustainable development,ensuring food security,alleviating environmental degradation and increasing farmer’s profitability.展开更多
现有多跳频信号参数估计方法稀疏线性回归(Sparse Linear Regression,SLR)存在计算量大、内存消耗大的缺点。事实上,频率跳变只在少数几个数据点上发生,大部分数据不包含跳变信息。基于此,提出一种基于正交匹配追踪(Orthogonal Matching...现有多跳频信号参数估计方法稀疏线性回归(Sparse Linear Regression,SLR)存在计算量大、内存消耗大的缺点。事实上,频率跳变只在少数几个数据点上发生,大部分数据不包含跳变信息。基于此,提出一种基于正交匹配追踪(Orthogonal Matching Pursuit,OMP)和SLR相结合的跳频信号参数估计方法。该方法将接收到的样本数据均匀分段,对每段数据用OMP算法预处理,检测出发生频率跳变的数据段以及估计出没有发生跳变的数据段的频率;对这些发生跳变的数据段分别用SLR算法估计得到各段的跳时和频率;拼接可以得到整个样本的跳时、跳频图案等。仿真结果表明,该方法在在保持SLR精确估计性能的同时,能有效减少计算量。展开更多
文摘Abstract Using the method of stepwise multivariate linear regression (SMLR), the quantitative structure activity relationships (QSAR) of two isomeric series of taxol and its derivatives have been studied. It was found that the molar refractivity of the C3′substituent of the C13 side chain has significant correlation with its activity. We deduce that structural changes in the C3′substituents may be critical to the anticancer function. It would be useful to the design and synthesis of taxol like compounds with improved activities.
基金the China Scholarship Council(CSC)(201903250115)the National Natural Science Foundation of China(31972515)the China Agriculture Research System of MOF and MARA(CARS-09-P31).
文摘Understanding the spatial-temporal dynamics of crop nitrogen(N)use efficiency(NUE)and the relationship with explanatory environmental variables can support land-use management and policymaking.Nevertheless,the application of statistical models for evaluating the explanatory variables of space-time variation in crop NUE is still under-researched.In this study,stepwise multiple linear regression(SMLR)and Random Forest(RF)were used to evaluate the spatial and temporal variation of NUE indicators(i.e.,partial factor productivity of N(PFPN);partial nutrient balance of N(PNBN))at county scale in Northeast China(Heilongjiang,Liaoning and Jilin provinces)from 1990 to 2015.Explanatory variables included agricultural management practices,topography,climate,economy,soil and crop types.Results revealed that the PFPN was higher in the northern parts and lower in the center of the Northeast China and PNBN increased from southern to northern parts during the 1990–2015 period.The NUE indicators decreased with time in most counties during the study period.The model efficiency coefficients of the SMLR and RF models were 0.44 and 0.84 for PFPN,and 0.67 and 0.89 for PNBN,respectively.The RF model had higher relative importance of soil and climatic covariates and lower relative importance of crop covariates compared to the SMLR model.The planting area index of vegetables and beans,soil clay content,saturated water content,enhanced vegetation index in November&December,soil bulk density,and annual minimum temperature were the main explanatory variables for both NUE indicators.This is the first study to show the quantitative relative importance of explanatory variables for NUE at a county level in Northeast China using RF and SMLR.This novel study gives reference measurements to improve crop NUE which is one of the most effective means of managing N for sustainable development,ensuring food security,alleviating environmental degradation and increasing farmer’s profitability.
文摘现有多跳频信号参数估计方法稀疏线性回归(Sparse Linear Regression,SLR)存在计算量大、内存消耗大的缺点。事实上,频率跳变只在少数几个数据点上发生,大部分数据不包含跳变信息。基于此,提出一种基于正交匹配追踪(Orthogonal Matching Pursuit,OMP)和SLR相结合的跳频信号参数估计方法。该方法将接收到的样本数据均匀分段,对每段数据用OMP算法预处理,检测出发生频率跳变的数据段以及估计出没有发生跳变的数据段的频率;对这些发生跳变的数据段分别用SLR算法估计得到各段的跳时和频率;拼接可以得到整个样本的跳时、跳频图案等。仿真结果表明,该方法在在保持SLR精确估计性能的同时,能有效减少计算量。
