Amorphous solid dispersion(ASD)is one of the most effective approaches for delivering poorly soluble drugs.In ASDs,polymeric materials serve as the carriers in which the drugs are dispersed at the molecular level.To p...Amorphous solid dispersion(ASD)is one of the most effective approaches for delivering poorly soluble drugs.In ASDs,polymeric materials serve as the carriers in which the drugs are dispersed at the molecular level.To prepare the solid dispersions,there are many polymers with various physicochemical and thermochemical characteristics available for use in ASD formulations.Polymer selection is of great importance because it influences the stability,solubility and dissolution rates,manufacturing process,and bioavailability of the ASD.This review article provides a comprehensive overview of ASDs from the perspectives of physicochemical characteristics of polymers,formulation designs and preparation methods.Furthermore,considerations of safety and regulatory requirements along with the studies recommended for characterizing and evaluating polymeric carriers are briefly discussed.展开更多
特征选择是面向对象信息提取的关键步骤之一。本文针对分离阈值(separability and threshold,SEaTH)这一特征选择方法在实际应用中存在的不足,例如未考虑特征值的离散程度,仅利用J-M距离评判单一特征,特征间可能存在较强相关性,以及无...特征选择是面向对象信息提取的关键步骤之一。本文针对分离阈值(separability and threshold,SEaTH)这一特征选择方法在实际应用中存在的不足,例如未考虑特征值的离散程度,仅利用J-M距离评判单一特征,特征间可能存在较强相关性,以及无法有效确定出分类顺序,提出了一种改进的SEaTH算法(optimized SEaTH,OPSEaTH)。OPSEaTH算法首先在J-M距离基础上构建了一类特征评价指标(E值),有效解决了特征值的离散度问题;然后,基于E值构建出特征组合评价指标(C_(e)值),可有效评估得到每种地物的最佳特征组合并自动确定出地物的分类顺序;最后基于eCognition等分类器可完成对地物对象的最终有效分类。利用高分二号遥感影像数据对本文方法进行了测试,并将结果分别与SEaTH算法、DPC、OIF和最近邻分类器的分类结果进行了对比,结果表明:OPSEaTH算法不仅能有效降低特征维数、优化特征空间,还能够对分类顺序进行自动化合理确定,总体精度和Kappa系数及其他精度指标,均显著优于基于SEaTH算法的特征选择结果。本文方法无论从特征降维效果、分类结果精度还是计算效率方面均优于DPC、OIF和最近邻分类器结果。OPSEaTH是一种更优的特征选择方法。展开更多
基金the National Natural Science Foundation of China(No.81872813,22108313,82273880)Natural Science Foundation of Jiangsu Province(No.BK 20200573,BK 20200576)+1 种基金Fundamental Research Funds for the Central Universities(No 2632022ZD16)the Scientific Research Fund of Hunan Provincial Education Department(No.22B0820).
文摘Amorphous solid dispersion(ASD)is one of the most effective approaches for delivering poorly soluble drugs.In ASDs,polymeric materials serve as the carriers in which the drugs are dispersed at the molecular level.To prepare the solid dispersions,there are many polymers with various physicochemical and thermochemical characteristics available for use in ASD formulations.Polymer selection is of great importance because it influences the stability,solubility and dissolution rates,manufacturing process,and bioavailability of the ASD.This review article provides a comprehensive overview of ASDs from the perspectives of physicochemical characteristics of polymers,formulation designs and preparation methods.Furthermore,considerations of safety and regulatory requirements along with the studies recommended for characterizing and evaluating polymeric carriers are briefly discussed.
文摘特征选择是面向对象信息提取的关键步骤之一。本文针对分离阈值(separability and threshold,SEaTH)这一特征选择方法在实际应用中存在的不足,例如未考虑特征值的离散程度,仅利用J-M距离评判单一特征,特征间可能存在较强相关性,以及无法有效确定出分类顺序,提出了一种改进的SEaTH算法(optimized SEaTH,OPSEaTH)。OPSEaTH算法首先在J-M距离基础上构建了一类特征评价指标(E值),有效解决了特征值的离散度问题;然后,基于E值构建出特征组合评价指标(C_(e)值),可有效评估得到每种地物的最佳特征组合并自动确定出地物的分类顺序;最后基于eCognition等分类器可完成对地物对象的最终有效分类。利用高分二号遥感影像数据对本文方法进行了测试,并将结果分别与SEaTH算法、DPC、OIF和最近邻分类器的分类结果进行了对比,结果表明:OPSEaTH算法不仅能有效降低特征维数、优化特征空间,还能够对分类顺序进行自动化合理确定,总体精度和Kappa系数及其他精度指标,均显著优于基于SEaTH算法的特征选择结果。本文方法无论从特征降维效果、分类结果精度还是计算效率方面均优于DPC、OIF和最近邻分类器结果。OPSEaTH是一种更优的特征选择方法。
