Laser-induced breakdown spectroscopy(LIBS) is a sensitive optical technique that is capable of rapid multi-elemental analysis. The development of this technique for elemental analysis of pharmaceutical products may ev...Laser-induced breakdown spectroscopy(LIBS) is a sensitive optical technique that is capable of rapid multi-elemental analysis. The development of this technique for elemental analysis of pharmaceutical products may eventually revolutionize the field of human health. Under normal circumstances, the elemental analysis of pharmaceutical products based on chemical methods is time-consuming and complicated. In this investigation, the principal aim is to develop an LIBS-based methodology for elemental analysis of pharmaceutical products. This LIBS technique was utilized for qualitative as well as quantitative analysis of the elements present in Ca-based tablets. All the elements present in the tablets were detected and their percentage compositions were verified in a single shot, using the proposed instrument. These elements(e.g., Ca, Mg, Fe, Zn, and others) were identified by the wavelengths of their spectral lines, which were verified using the NIST database. The approximate amount of each element was determined based on their observed peaks and the result was in exact agreement with the content specification. The determination of the composition of prescription drug for patients is highly important in numerous circumstances. For example, the exploitation of LIBS may facilitate elemental decomposition of medicines to determine the accuracy of the stated composition information. Moreover, the approach can provide element-specific, meaningful, and accurate information related to pharmaceutical products.展开更多
Monitoring indoor harmful gas can obtain the infrared spectra of mixed harmful gases.Since the absorption bands of mixed gases overlap and their qualitative and quantitative analyses are not easy,feature extraction me...Monitoring indoor harmful gas can obtain the infrared spectra of mixed harmful gases.Since the absorption bands of mixed gases overlap and their qualitative and quantitative analyses are not easy,feature extraction method based on joint approximative diagonalization of eigenmatrix（JADE）is proposed.By fully mining the hidden information of original data and analyzing higher-order statistics information of the data,each substance spectrum in the mixed gas can be accurately distinguished.In addition,a multi-dimensional data quantitative analysis model of the extracted independent source is established by using support vector machine（SVM）based on regular theory.The experimental results show that the correlation coefficients of the components of mixed gases is above 0.999 1by quantitative analysis,which verifies the accuracy of this feature extraction method.展开更多
A new method for submarine pipeline routing risk quantitative analysis was provided, and the study was developed from qualitative analysis to quantitative analysis.The characteristics of the potential risk of the subm...A new method for submarine pipeline routing risk quantitative analysis was provided, and the study was developed from qualitative analysis to quantitative analysis.The characteristics of the potential risk of the submarine pipeline system were considered, and grey-mode identification theory was used. The study process was composed of three parts: establishing the indexes system of routing risk quantitative analysis, establishing the model of grey-mode identification for routing risk quantitative analysis, and establishing the standard of mode identification result. It is shown that this model can directly and concisely reflect the hazard degree of the routing through computing example, and prepares the routing selection for the future.展开更多
It is necessary to quantitatively identify different diseases and nitrogen-water stress for the guidance in spraying specific fungicides and fertilizer applications.The winter wheat diseases,in combination with nitrog...It is necessary to quantitatively identify different diseases and nitrogen-water stress for the guidance in spraying specific fungicides and fertilizer applications.The winter wheat diseases,in combination with nitrogen-water stress,are therefore common causes of yield loss in winter wheat in China.Powdery mildew(Blumeria graminis)and stripe rust(Puccinia striiformis f.sp.Tritici)are two of the most prevalent winter wheat diseases in China.This study investigated the potential of continuous wavelet analysis to identify the powdery mildew,stripe rust and nitrogen-water stress using canopy hyperspectral data.The spectral normalization process was applied prior to the analysis.Independent t-tests were used to determine the sensitivity of the spectral bands and vegetation index.In order to reduce the number of wavelet regions,correlation analysis and the independent t-test were used in conjunction to select the features of greatest importance.Based on the selected spectral bands,vegetation indices and wavelet features,the discriminate models were established using Fisher’s linear discrimination analysis(FLDA)and support vector machine(SVM).The results indicated that wavelet features were superior to spectral bands and vegetation indices in classifying different stresses,with overall accuracies of 0.91,0.72,and 0.72 respectively for powdery mildew,stripe rust and nitrogen-water by using FLDA,and 0.79,0.67 and 0.65 respectively by using SVM.FLDA was more suitable for differentiating stresses in winter wheat,with respective accuracies of 78.1%,95.6%and 95.7%for powdery mildew,stripe rust,and nitrogen-water stress.Further analysis was performed whereby the wavelet features were then split into high-scale and low-scale feature subsets for identification.The accuracies of high-scale and low-scale features with an overall accuracy(OA)of 0.61 and 0.73 respectively were lower than those of all wavelet features with an OA of 0.88.The detection of the severity of stripe rust using this method showed an enhanced reliability(R^(2)=0.828).展开更多
The cross-sectional area (CSA) of small pulmonary vessels can be quantified by CT, which is a reliable method of evaluating vascular alterations in such vessels. However, the optimal number of slices required for accu...The cross-sectional area (CSA) of small pulmonary vessels can be quantified by CT, which is a reliable method of evaluating vascular alterations in such vessels. However, the optimal number of slices required for accurate quantitation remains unknown. We evaluated relationships among all slices at 10-mm interval and all slices at 3-cm interval, 6-cm interval, and 3-slices and found the closest correlation (0.939) between all slices at 10-mm intervals and 3-cm intervals. Thus, all slices at 3-cm intervals are suitable for accurately measuring CSA.展开更多
目的建立龙胆泻肝片中黄芩的薄层色谱(thin-layer chromatography,TLC)鉴别方法、一测多评法(quantitative analysis of multi-components by single marker,QAMS)和显微鉴别方法,评价龙胆泻肝片中黄芩的质量。方法采用QAMS测定龙胆泻...目的建立龙胆泻肝片中黄芩的薄层色谱(thin-layer chromatography,TLC)鉴别方法、一测多评法(quantitative analysis of multi-components by single marker,QAMS)和显微鉴别方法,评价龙胆泻肝片中黄芩的质量。方法采用QAMS测定龙胆泻肝片中黄芩的黄芩苷、汉黄芩苷、黄芩素、汉黄芩素4种黄酮类成分的含量;采用TLC鉴别龙胆泻肝片中黄芩、黄芩苷、黄芩素、汉黄芩素。参照《中华人民共和国药典》(2020年版)显微鉴别法对龙胆泻肝片粉末进行鉴别。结果以黄芩苷为内参物,汉黄芩苷、黄芩素、汉黄芩素的相对校正因子分别为0.792、0.598、0.518,22批次龙胆泻肝片样品QAMS与外标法的含量测定结果无显著性差异;建立的龙胆泻肝片中黄芩、黄芩苷、黄芩素、汉黄芩素的TLC鉴别方法专属性强;龙胆泻肝片粉末中可观测到黄芩的显微特征韧皮纤维。结论建立的TLC鉴别方法、QAMS和显微鉴别方法可为龙胆泻肝片中黄芩的质量控制和评价提供参考。展开更多
Let X∈Alex^(n)(−1)be an n-dimensional Alexandrov space with curvature≥−1.Let the r-scale(k,ε)-singular set S_(ε,r)^(k)(X)be the collection of x∈X so that B_(r)(x)is notr-close to a ball in any splitting spaceℝ^(k...Let X∈Alex^(n)(−1)be an n-dimensional Alexandrov space with curvature≥−1.Let the r-scale(k,ε)-singular set S_(ε,r)^(k)(X)be the collection of x∈X so that B_(r)(x)is notr-close to a ball in any splitting spaceℝ^(k+1)×Z.We show that there exists C(n,ε)>0 and𝛽(n,ε)>0,independent of the volume,so that for any disjoint collection{B_(ri)(xi)∶x_(i)∈S_(ε,βri)^(k)(X)∩B_(1),r_(i)≤1,the packing estimateΣr_(i)^(k)≤C holds.Consequently,we obtain the Hausdorff measure estimates H^(k)(S_(ε)^(k)(X))∩B_(1))≤C and H^(n)(B_(r)(S_(ε,βri)^(k))∩B_(1))≤C rn−k.This answers an open question in Kapovitch et al.(Metric-measure boundary and geodesic flow on Alexandrov spaces.arXiv:1705.04767(2017)).We also show that the k-singular set S^(k)(X)=⋃ε>0⋂r>0 S_(ε,r)^(k)𝜖,ris k-rectifiable and construct examples to show that such a structure is sharp.For instance,in the k=1 case we can build for any closed set T⊆S^(1)andε>0 a space Y∈Alex^(3)(0)with S_(ε)^(1)(Y)=Ф(T),whereФ∶S^(1)→Y is a bi-Lipschitz embedding.Taking T to be a Cantor set it gives rise to an example where the singular set is a 1-rectifiable,1-Cantor set with positive 1-Hausdorff measure.展开更多
文摘Laser-induced breakdown spectroscopy(LIBS) is a sensitive optical technique that is capable of rapid multi-elemental analysis. The development of this technique for elemental analysis of pharmaceutical products may eventually revolutionize the field of human health. Under normal circumstances, the elemental analysis of pharmaceutical products based on chemical methods is time-consuming and complicated. In this investigation, the principal aim is to develop an LIBS-based methodology for elemental analysis of pharmaceutical products. This LIBS technique was utilized for qualitative as well as quantitative analysis of the elements present in Ca-based tablets. All the elements present in the tablets were detected and their percentage compositions were verified in a single shot, using the proposed instrument. These elements(e.g., Ca, Mg, Fe, Zn, and others) were identified by the wavelengths of their spectral lines, which were verified using the NIST database. The approximate amount of each element was determined based on their observed peaks and the result was in exact agreement with the content specification. The determination of the composition of prescription drug for patients is highly important in numerous circumstances. For example, the exploitation of LIBS may facilitate elemental decomposition of medicines to determine the accuracy of the stated composition information. Moreover, the approach can provide element-specific, meaningful, and accurate information related to pharmaceutical products.
基金National Natural Science Foundation of China(No.61127015)
文摘Monitoring indoor harmful gas can obtain the infrared spectra of mixed harmful gases.Since the absorption bands of mixed gases overlap and their qualitative and quantitative analyses are not easy,feature extraction method based on joint approximative diagonalization of eigenmatrix（JADE）is proposed.By fully mining the hidden information of original data and analyzing higher-order statistics information of the data,each substance spectrum in the mixed gas can be accurately distinguished.In addition,a multi-dimensional data quantitative analysis model of the extracted independent source is established by using support vector machine（SVM）based on regular theory.The experimental results show that the correlation coefficients of the components of mixed gases is above 0.999 1by quantitative analysis,which verifies the accuracy of this feature extraction method.
文摘A new method for submarine pipeline routing risk quantitative analysis was provided, and the study was developed from qualitative analysis to quantitative analysis.The characteristics of the potential risk of the submarine pipeline system were considered, and grey-mode identification theory was used. The study process was composed of three parts: establishing the indexes system of routing risk quantitative analysis, establishing the model of grey-mode identification for routing risk quantitative analysis, and establishing the standard of mode identification result. It is shown that this model can directly and concisely reflect the hazard degree of the routing through computing example, and prepares the routing selection for the future.
基金supported by Free Exploration Project of the State Key Laboratory of Remote Sensing Science at Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences(17ZY-01)the National Natural Science Foundation of China(61661136004)Hainan Provincial Department of Science and Technology under Grant(ZDKJ2016021).
文摘It is necessary to quantitatively identify different diseases and nitrogen-water stress for the guidance in spraying specific fungicides and fertilizer applications.The winter wheat diseases,in combination with nitrogen-water stress,are therefore common causes of yield loss in winter wheat in China.Powdery mildew(Blumeria graminis)and stripe rust(Puccinia striiformis f.sp.Tritici)are two of the most prevalent winter wheat diseases in China.This study investigated the potential of continuous wavelet analysis to identify the powdery mildew,stripe rust and nitrogen-water stress using canopy hyperspectral data.The spectral normalization process was applied prior to the analysis.Independent t-tests were used to determine the sensitivity of the spectral bands and vegetation index.In order to reduce the number of wavelet regions,correlation analysis and the independent t-test were used in conjunction to select the features of greatest importance.Based on the selected spectral bands,vegetation indices and wavelet features,the discriminate models were established using Fisher’s linear discrimination analysis(FLDA)and support vector machine(SVM).The results indicated that wavelet features were superior to spectral bands and vegetation indices in classifying different stresses,with overall accuracies of 0.91,0.72,and 0.72 respectively for powdery mildew,stripe rust and nitrogen-water by using FLDA,and 0.79,0.67 and 0.65 respectively by using SVM.FLDA was more suitable for differentiating stresses in winter wheat,with respective accuracies of 78.1%,95.6%and 95.7%for powdery mildew,stripe rust,and nitrogen-water stress.Further analysis was performed whereby the wavelet features were then split into high-scale and low-scale feature subsets for identification.The accuracies of high-scale and low-scale features with an overall accuracy(OA)of 0.61 and 0.73 respectively were lower than those of all wavelet features with an OA of 0.88.The detection of the severity of stripe rust using this method showed an enhanced reliability(R^(2)=0.828).
文摘The cross-sectional area (CSA) of small pulmonary vessels can be quantified by CT, which is a reliable method of evaluating vascular alterations in such vessels. However, the optimal number of slices required for accurate quantitation remains unknown. We evaluated relationships among all slices at 10-mm interval and all slices at 3-cm interval, 6-cm interval, and 3-slices and found the closest correlation (0.939) between all slices at 10-mm intervals and 3-cm intervals. Thus, all slices at 3-cm intervals are suitable for accurately measuring CSA.
文摘目的建立龙胆泻肝片中黄芩的薄层色谱(thin-layer chromatography,TLC)鉴别方法、一测多评法(quantitative analysis of multi-components by single marker,QAMS)和显微鉴别方法,评价龙胆泻肝片中黄芩的质量。方法采用QAMS测定龙胆泻肝片中黄芩的黄芩苷、汉黄芩苷、黄芩素、汉黄芩素4种黄酮类成分的含量;采用TLC鉴别龙胆泻肝片中黄芩、黄芩苷、黄芩素、汉黄芩素。参照《中华人民共和国药典》(2020年版)显微鉴别法对龙胆泻肝片粉末进行鉴别。结果以黄芩苷为内参物,汉黄芩苷、黄芩素、汉黄芩素的相对校正因子分别为0.792、0.598、0.518,22批次龙胆泻肝片样品QAMS与外标法的含量测定结果无显著性差异;建立的龙胆泻肝片中黄芩、黄芩苷、黄芩素、汉黄芩素的TLC鉴别方法专属性强;龙胆泻肝片粉末中可观测到黄芩的显微特征韧皮纤维。结论建立的TLC鉴别方法、QAMS和显微鉴别方法可为龙胆泻肝片中黄芩的质量控制和评价提供参考。
文摘Let X∈Alex^(n)(−1)be an n-dimensional Alexandrov space with curvature≥−1.Let the r-scale(k,ε)-singular set S_(ε,r)^(k)(X)be the collection of x∈X so that B_(r)(x)is notr-close to a ball in any splitting spaceℝ^(k+1)×Z.We show that there exists C(n,ε)>0 and𝛽(n,ε)>0,independent of the volume,so that for any disjoint collection{B_(ri)(xi)∶x_(i)∈S_(ε,βri)^(k)(X)∩B_(1),r_(i)≤1,the packing estimateΣr_(i)^(k)≤C holds.Consequently,we obtain the Hausdorff measure estimates H^(k)(S_(ε)^(k)(X))∩B_(1))≤C and H^(n)(B_(r)(S_(ε,βri)^(k))∩B_(1))≤C rn−k.This answers an open question in Kapovitch et al.(Metric-measure boundary and geodesic flow on Alexandrov spaces.arXiv:1705.04767(2017)).We also show that the k-singular set S^(k)(X)=⋃ε>0⋂r>0 S_(ε,r)^(k)𝜖,ris k-rectifiable and construct examples to show that such a structure is sharp.For instance,in the k=1 case we can build for any closed set T⊆S^(1)andε>0 a space Y∈Alex^(3)(0)with S_(ε)^(1)(Y)=Ф(T),whereФ∶S^(1)→Y is a bi-Lipschitz embedding.Taking T to be a Cantor set it gives rise to an example where the singular set is a 1-rectifiable,1-Cantor set with positive 1-Hausdorff measure.
