We use density functional theory and time-dependent together with a set of extensive mul- tidimensional visualization techniques to characterize the influence of keto effect on charge distribution at ground state and ...We use density functional theory and time-dependent together with a set of extensive mul- tidimensional visualization techniques to characterize the influence of keto effect on charge distribution at ground state and electronic transitions for neutral and charged hexaphyrin aromaticity with and without keto-defect. It is found that the aromaticity is the key fac- tor to influence the ground state Mulliken charges distribution properties, other than the meso-aryl-substituted effect. But with the enhancement of the keto-defect, the distribution changes of Mulliken charges on the hexaphyrin groups are larger than those on the pentaflu- orophenyl substituted groups, following with the aromaticity changes from nonaromatic to aromatic. Furthermore, through characterizing by transition density and charge difference density, direct visual evidence for neutral and charged aromaticity with and without keto- defect can be clearly derived, and the ability of charge transfer between units of monoradical （nonaromaticity） and singlet biradical （aromaticity） forms is much stronger than that of neutral forms.展开更多
This paper presents a method which uses multiple types of expert knowledge together in 3D medical image segmentation based on rough set theory. The focus of this paper is how to approximate a ROI(region of interest) w...This paper presents a method which uses multiple types of expert knowledge together in 3D medical image segmentation based on rough set theory. The focus of this paper is how to approximate a ROI(region of interest) when there are multiple types of expert knowledge. Based on rough set theory, the image can be split into three regions: positive regions; negative regions; boundary regions. With multiple knowledge we refine ROI as an intersection of all of the expected shapes with single knowledge. At last we show the results of implementing a rough 3D image segmentation and visualization system.展开更多
文摘We use density functional theory and time-dependent together with a set of extensive mul- tidimensional visualization techniques to characterize the influence of keto effect on charge distribution at ground state and electronic transitions for neutral and charged hexaphyrin aromaticity with and without keto-defect. It is found that the aromaticity is the key fac- tor to influence the ground state Mulliken charges distribution properties, other than the meso-aryl-substituted effect. But with the enhancement of the keto-defect, the distribution changes of Mulliken charges on the hexaphyrin groups are larger than those on the pentaflu- orophenyl substituted groups, following with the aromaticity changes from nonaromatic to aromatic. Furthermore, through characterizing by transition density and charge difference density, direct visual evidence for neutral and charged aromaticity with and without keto- defect can be clearly derived, and the ability of charge transfer between units of monoradical （nonaromaticity） and singlet biradical （aromaticity） forms is much stronger than that of neutral forms.
基金PHD Site from Chinese Educational Department,Grant number:20040699015
文摘This paper presents a method which uses multiple types of expert knowledge together in 3D medical image segmentation based on rough set theory. The focus of this paper is how to approximate a ROI(region of interest) when there are multiple types of expert knowledge. Based on rough set theory, the image can be split into three regions: positive regions; negative regions; boundary regions. With multiple knowledge we refine ROI as an intersection of all of the expected shapes with single knowledge. At last we show the results of implementing a rough 3D image segmentation and visualization system.
