The concise and informative representation of hyperspectral imagery is achieved via the introduced diffusion geometric coordinates derived from nonlinear dimension reduction maps - diffusion maps. The huge-volume high...The concise and informative representation of hyperspectral imagery is achieved via the introduced diffusion geometric coordinates derived from nonlinear dimension reduction maps - diffusion maps. The huge-volume high- dimensional spectral measurements are organized by the affinity graph where each node in this graph only connects to its local neighbors and each edge in this graph represents local similarity information. By normalizing the affinity graph appropriately, the diffusion operator of the underlying hyperspectral imagery is well-defined, which means that the Markov random walk can be simulated on the hyperspectral imagery. Therefore, the diffusion geometric coordinates, derived from the eigenfunctions and the associated eigenvalues of the diffusion operator, can capture the intrinsic geometric information of the hyperspectral imagery well, which gives more enhanced representation results than traditional linear methods, such as principal component analysis based methods. For large-scale full scene hyperspectral imagery, by exploiting the backbone approach, the computation complexity and the memory requirements are acceptable. Experiments also show that selecting suitable symmetrization normalization techniques while forming the diffusion operator is important to hyperspectral imagery representation.展开更多
The aim of this study was to prepare arsenic trioxide (ATO)-loaded stealth PEGylated PLGA nanoparticles (PEG-PLGA-NPs) and to assess the merits of PEG-PLGA-NPs as drug carriers for ATO delivery. PEG-PLGA copolymer...The aim of this study was to prepare arsenic trioxide (ATO)-loaded stealth PEGylated PLGA nanoparticles (PEG-PLGA-NPs) and to assess the merits of PEG-PLGA-NPs as drug carriers for ATO delivery. PEG-PLGA copolymer was synthesized with methoxypolyethyleneglycol (Mw=5000), D, L-lactide, and glycolide by the ring-opening polymerization method. Amorphous ATO was transformed into cubic crystal form to increase its solu-bility in the organic solvent. ATO-loaded PEG-PLGA-NPs were prepared by the modified spontaneous emulsification solvent diffusion (SESD) method, and the main experimental factors influencing the characteristics of nanopar- ticles were investigated, to optimize the preparation. To confirm the escape of PEG-PLGA-NPs from phagocytosis by phagocytes, PEG-PLGA-NPs labeled rhodamine B uptake by murine peritoneal macrophages (MPM) were analyzed by flow cytometry. The results showed that the physicochemical characteristics of PEG-PLGA-NPs were affected by the type and concentration of the emulsifiers, polymer concentration, and drug concentration. ATO-loaded PEG-PLGA-NPs, with particle size of 120.8nm, zeta potential of-10.73mV, encapsulation efficiency of 73.6%, and drug loading of 1.36%, were prepared under optimal conditions. The images of transmission electron micros-copy (TEM) indicated that the optimized nanoparticles were near spherical and without aggregation or adhesion. The release experiments in vitro showed the ATO release from PEG-PLGA-NPs exhibited consequently sustained release for more than 26d, which was in accordance with Higuchi equation. The uptake of PEG-PLGA-NPs by MPM was found to decrease markedly compared to PLGA-NPs. The experimental results showed that PEG-PLGA-NPs were potential nano drug delivery carriers for ATO.展开更多
This paper deals with the special nonlinear reaction-diffusion equation. The finite difference scheme with incremental unknowns approximating to the differential equation (2.1) is set up by means of introducing incr...This paper deals with the special nonlinear reaction-diffusion equation. The finite difference scheme with incremental unknowns approximating to the differential equation (2.1) is set up by means of introducing incremental unknowns methods. Through the stability analyzing for the scheme, it was shown that the stability conditions of the finite difference schemes with the incremental unknowns are greatly improved when compared with the stability conditions of the corresponding classic difference scheme.展开更多
基金The National Key Technologies R & D Program during the 11th Five-Year Plan Period (No.2006BAB15B01)
文摘The concise and informative representation of hyperspectral imagery is achieved via the introduced diffusion geometric coordinates derived from nonlinear dimension reduction maps - diffusion maps. The huge-volume high- dimensional spectral measurements are organized by the affinity graph where each node in this graph only connects to its local neighbors and each edge in this graph represents local similarity information. By normalizing the affinity graph appropriately, the diffusion operator of the underlying hyperspectral imagery is well-defined, which means that the Markov random walk can be simulated on the hyperspectral imagery. Therefore, the diffusion geometric coordinates, derived from the eigenfunctions and the associated eigenvalues of the diffusion operator, can capture the intrinsic geometric information of the hyperspectral imagery well, which gives more enhanced representation results than traditional linear methods, such as principal component analysis based methods. For large-scale full scene hyperspectral imagery, by exploiting the backbone approach, the computation complexity and the memory requirements are acceptable. Experiments also show that selecting suitable symmetrization normalization techniques while forming the diffusion operator is important to hyperspectral imagery representation.
基金Supported by the Special Funds for Major State Basic Research Program of China (973 Program, No.2007CB935800)theNational High Technology Research and Development Program of China (863 Program, No.2004AA215162).
文摘The aim of this study was to prepare arsenic trioxide (ATO)-loaded stealth PEGylated PLGA nanoparticles (PEG-PLGA-NPs) and to assess the merits of PEG-PLGA-NPs as drug carriers for ATO delivery. PEG-PLGA copolymer was synthesized with methoxypolyethyleneglycol (Mw=5000), D, L-lactide, and glycolide by the ring-opening polymerization method. Amorphous ATO was transformed into cubic crystal form to increase its solu-bility in the organic solvent. ATO-loaded PEG-PLGA-NPs were prepared by the modified spontaneous emulsification solvent diffusion (SESD) method, and the main experimental factors influencing the characteristics of nanopar- ticles were investigated, to optimize the preparation. To confirm the escape of PEG-PLGA-NPs from phagocytosis by phagocytes, PEG-PLGA-NPs labeled rhodamine B uptake by murine peritoneal macrophages (MPM) were analyzed by flow cytometry. The results showed that the physicochemical characteristics of PEG-PLGA-NPs were affected by the type and concentration of the emulsifiers, polymer concentration, and drug concentration. ATO-loaded PEG-PLGA-NPs, with particle size of 120.8nm, zeta potential of-10.73mV, encapsulation efficiency of 73.6%, and drug loading of 1.36%, were prepared under optimal conditions. The images of transmission electron micros-copy (TEM) indicated that the optimized nanoparticles were near spherical and without aggregation or adhesion. The release experiments in vitro showed the ATO release from PEG-PLGA-NPs exhibited consequently sustained release for more than 26d, which was in accordance with Higuchi equation. The uptake of PEG-PLGA-NPs by MPM was found to decrease markedly compared to PLGA-NPs. The experimental results showed that PEG-PLGA-NPs were potential nano drug delivery carriers for ATO.
文摘This paper deals with the special nonlinear reaction-diffusion equation. The finite difference scheme with incremental unknowns approximating to the differential equation (2.1) is set up by means of introducing incremental unknowns methods. Through the stability analyzing for the scheme, it was shown that the stability conditions of the finite difference schemes with the incremental unknowns are greatly improved when compared with the stability conditions of the corresponding classic difference scheme.