Optical properties and responsive mechanisms of three newly synthesized fluorescent probes for hypochlorous acid (HOC1) are investigated by employing time-dependent density functional theory. The computational resul...
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Optical properties and responsive mechanisms of three newly synthesized fluorescent probes for hypochlorous acid (HOC1) are investigated by employing time-dependent density functional theory. The computational results show that the absorption and emission properties of these probes change obviously when they react with hypochlorous acid. It is found that the probe FHZ has the best performance according to the probing behavior. Moreover, the responsive mechanisms of the probes are studied by analyzing the distributions of molecular orbitals and charge transfer, which are shown as the photon- induced electron transfer (PET) for FHZ and the intramolecular charge transfer OCT) for the other two probes. Specially, solvent effect on optical properties of the probe FHZ before and after reaction is studied within the polarizable continuum model (PCM). It is shown that performance of the probe depends crucially on the solvent polarity. Our computational results agree well with the experimental measurement, and provide information for design of efficient two-photon fluorescent probes.
In this paper, we propose a novel improved binarized normed gradients (BING) objectness method based on the multi-feature boosting learning. A series of difference of gaussians (DoG) of the images with given parameter...
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It is known that detecting small moving objects in as- tronomical image sequences is a significant research problem in space surveillance. The new theory, compressive sensing, pro- vides a very easy and computationall...
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It is known that detecting small moving objects in as- tronomical image sequences is a significant research problem in space surveillance. The new theory, compressive sensing, pro- vides a very easy and computationally cheap coding scheme for onboard astronomical remote sensing. An algorithm for small moving space object detection and localization is proposed. The algorithm determines the measurements of objects by comparing the difference between the measurements of the current image and the measurements of the background scene. In contrast to reconstruct the whole image, only a foreground image is recon- structed, which will lead to an effective computational performance, and a high level of localization accuracy is achieved. Experiments and analysis are provided to show the performance of the pro- posed approach on detection and localization.
Single image super resolution (SR) aims to estimate high resolution (HR) image from the low resolution (LR) one, and estimating accuracy of HR image gradient is very important for edge directed image SR methods. In th...
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This study proposes a motion cue based pedestrian detection method with two-trame-filtering (Tff) for video surveillance. The novel motion cue is exploited by the gray value variation between two frames. Then Tff pr...
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This study proposes a motion cue based pedestrian detection method with two-trame-filtering (Tff) for video surveillance. The novel motion cue is exploited by the gray value variation between two frames. Then Tff processing filters the gradient magnitude image by the variation map. Summa- tions of the Tff gradient magnitudes in cells are applied to train a pre-deteetor to exclude most of the background regions. Histogram of Tff oriented gradient (HTffOG) feature is proposed for pedestrian detection. Experimental results show that this method is effective and suitable for real-time surveil- lance applications.
Videos captured in low light environment tend to be poor visual effect. To get better visual experience, a video enhancement algorithm based on improved center-surrounded Retinex and optical flow is proposed in this p...
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Face image super resolution, also referred to as face hallucination, is aiming to estimate the high-resolution (HR) face image from its low-resolution (LR) version. In this paper, a novel two-layer face hallucination ...
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A new general network model for two complex networks with time-varying delay coupling is *** we investigate its synchronization *** two complex networks of the model differ in dynamic nodes,the number of nodes and the...
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A new general network model for two complex networks with time-varying delay coupling is *** we investigate its synchronization *** two complex networks of the model differ in dynamic nodes,the number of nodes and the coupling *** using adaptive controllers,a synchronization criterion is *** examples are given to demonstrate the effectiveness of the obtained synchronization *** study may widen the application range of synchronization,such as in chaotic secure communication.
Camera calibration is the essential step of obtaining 3D information from 2D views in the field of computer vision, which is widely used in the area of 3D reconstruction, navigation, visual supervision, etc. A camera ...
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The organization of human brain function is diverse on different spatial scales. Various cognitive states are always represented as distinct activity patterns across the specific brain region on fine scales. Conventio...
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The organization of human brain function is diverse on different spatial scales. Various cognitive states are always represented as distinct activity patterns across the specific brain region on fine scales. Conventional univariate analysis of functional MRI data seeks to determine how a particular cognitive state is encoded in brain activity by analyzing each voxel separately without considering the fine-scale patterns information contained in the local brain regions. In this paper, a local multivariate distance mapping (LMDM) technique is proposed to detect the brain activation and to map the fine-scale brain activity patterns. LMDM directly represents the local brain activity with the patterns across multiple voxels rather than individual voxels, and it employs the multivariate distance between different patterns to discriminate the brain state on fine scales. Experiments with simulated and real fMRI data demonstrate that LMDM technique can dramatically increase the sensitivity of the detection for the fine-scale brain activity patterns which contain the subtle information of the experimental conditions.
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