Cp_(2)TiCl_(2) as a Lewis acid precursor and nicotinic acid as a ligand have been used synergistically for the one-pot synthesis of 2-(N-substituted amino)-1,4-naphthoquinones.This method establishes a general strateg...Cp_(2)TiCl_(2) as a Lewis acid precursor and nicotinic acid as a ligand have been used synergistically for the one-pot synthesis of 2-(N-substituted amino)-1,4-naphthoquinones.This method establishes a general strategy for the functionalization and conversion of C-H bonds of 1,4-naphthoquinones into C-N bonds,providing an effective route to synthesize 2-(N-substituted amino)-1,4-naphthoquinone with high yield under mild conditions.Additionally,the synergistic catalytic mechanism was investigated by 1H NMR titration experiments and LC-MS analysis,with experimental results sufficiently and consistently supporting the proposed mechanism of the catalytic cycle.展开更多
Kernel-based methods work by embedding the data into a feature space and then searching linear hypothesis among the embedding data points. The performance is mostly affected by which kernel is used. A promising way is...Kernel-based methods work by embedding the data into a feature space and then searching linear hypothesis among the embedding data points. The performance is mostly affected by which kernel is used. A promising way is to learn the kernel from the data automatically. A general regularized risk functional （RRF） criterion for kernel matrix learning is proposed. Compared with the RRF criterion, general RRF criterion takes into account the geometric distributions of the embedding data points. It is proven that the distance between different geometric distdbutions can be estimated by their centroid distance in the reproducing kernel Hilbert space. Using this criterion for kernel matrix learning leads to a convex quadratically constrained quadratic programming （QCQP） problem. For several commonly used loss functions, their mathematical formulations are given. Experiment results on a collection of benchmark data sets demonstrate the effectiveness of the proposed method.展开更多
The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial charact...The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial characteristics is presented to estimate road traffic states. Firstly, the representative road traffic state data were extracted to establish the reference sequences of road traffic running characteristics(RSRTRC). Secondly, the spatial road traffic state data sequence was selected and the kernel function was constructed, with which the spatial road traffic data sequence could be mapped into a high dimensional feature space. Thirdly, the referenced and current spatial road traffic data sequences were extracted and the Euclidean distances in the feature space between them were obtained. Finally, the road traffic states were estimated from weighted averages of the selected k road traffic states, which corresponded to the nearest Euclidean distances. Several typical links in Beijing were adopted for case studies. The final results of the experiments show that the accuracy of this algorithm for estimating speed and volume is 95.27% and 91.32% respectively, which prove that this road traffic states estimation approach based on kernel-KNN matching of road traffic spatial characteristics is feasible and can achieve a high accuracy.展开更多
A fast algorithm based on the grayscale distribution of infrared target and the weighted kernel function was proposed for the moving target detection(MTD) in dynamic scene of image series. This algorithm is used to de...A fast algorithm based on the grayscale distribution of infrared target and the weighted kernel function was proposed for the moving target detection(MTD) in dynamic scene of image series. This algorithm is used to deal with issues like the large computational complexity, the fluctuation of grayscale, and the noise in infrared images. Four characteristic points were selected by analyzing the grayscale distribution in infrared image, of which the series was quickly matched with an affine transformation model. The image was then divided into 32×32 squares and the gray-weighted kernel(GWK) for each square was calculated. At last, the MTD was carried out according to the variation of the four GWKs. The results indicate that the MTD can be achieved in real time using the algorithm with the fluctuations of grayscale and noise can be effectively suppressed. The detection probability is greater than 90% with the false alarm rate lower than 5% when the calculation time is less than 40 ms.展开更多
OBJECTIVE Lychee seed,a famous traditional Chinese medicine,recently were reported to improve the learning and memory abilities in mice.However,it is still unclear whether lychee seed saponins(LSS)can improve the cogn...OBJECTIVE Lychee seed,a famous traditional Chinese medicine,recently were reported to improve the learning and memory abilities in mice.However,it is still unclear whether lychee seed saponins(LSS)can improve the cognitive function and associated mechanisms.METHODS In present studies,we established the Alzheimer disease(AD)model by injecting Aβ25-35 into the lateral ventricle of rats.Then the spatial learning and memory abilities of LSS-treated rats were evaluated with the Morris water maze,meanwhile the protein expressions of AKT,GSK3β and Tau in the hippocampal neuron were analyzed by immunohistochemistry and Western blotting.RESULTS The results showed LSS can improve the cognitive functions of AD rats through shortening the escape latency,increasing the number across the platform,platform quadrant dwell time and the percentage of the total distance run platform quadrant.The protein expression of AKT was significantly up-regulated and that of GSK3β and Tau were decreased remarkably in the hippocampal CA1 area.CONCLUSION Our study is the first to show that LSS significantly improve the cognitive function and prevent hippocampal neuronal injury of the rats with AD by activation of the PI3K/AKT/GSK3βsignaling pathway,suggesting LSS may be developed into the nutrient supplement for the treatment of AD.展开更多
基金2024 Special Talent Introduction Projects of Key R&D Program of Ningxia Hui Autonomous Region(2024BEH04049)the 2024 Guyuan City Innovation-Driven Achievement Transformation Project(2024BGTYF01-47)2025 Ningxia Natural Science Foundation Program(2025AAC030624).
文摘Cp_(2)TiCl_(2) as a Lewis acid precursor and nicotinic acid as a ligand have been used synergistically for the one-pot synthesis of 2-(N-substituted amino)-1,4-naphthoquinones.This method establishes a general strategy for the functionalization and conversion of C-H bonds of 1,4-naphthoquinones into C-N bonds,providing an effective route to synthesize 2-(N-substituted amino)-1,4-naphthoquinone with high yield under mild conditions.Additionally,the synergistic catalytic mechanism was investigated by 1H NMR titration experiments and LC-MS analysis,with experimental results sufficiently and consistently supporting the proposed mechanism of the catalytic cycle.
文摘为有效预测船舶油耗,提出一种基于混合核函数的船舶油耗预测模型。分别构建径向基函数(radial basis function,RBF)和多项式单核函数的支持向量回归(support vector regression,SVR)模型,并利用自适应随机搜索(adaptive random search,ARS)算法对两者进行优化。在此基础上,建立基于混合核函数ARS-SVR的船舶油耗预测模型。以一艘风帆助航的大型原油运输船(very large crude carrier,VLCC)为研究对象,基于实船监测数据开展船舶油耗预测。结果表明,与单一的RBF和多项式单核ARS-SVR相比,采用混合核函数ARS-SVR的模型的预测结果的均方根误差分别降低了19.8%和30.2%。所提出的船舶油耗预测模型可以提升风帆助航船油耗计算的准确率,有助于优化船舶能效和提升管理技术。
基金supported by the National Natural Science Fundation of China (60736021)the Joint Funds of NSFC-Guangdong Province(U0735003)
文摘Kernel-based methods work by embedding the data into a feature space and then searching linear hypothesis among the embedding data points. The performance is mostly affected by which kernel is used. A promising way is to learn the kernel from the data automatically. A general regularized risk functional （RRF） criterion for kernel matrix learning is proposed. Compared with the RRF criterion, general RRF criterion takes into account the geometric distributions of the embedding data points. It is proven that the distance between different geometric distdbutions can be estimated by their centroid distance in the reproducing kernel Hilbert space. Using this criterion for kernel matrix learning leads to a convex quadratically constrained quadratic programming （QCQP） problem. For several commonly used loss functions, their mathematical formulations are given. Experiment results on a collection of benchmark data sets demonstrate the effectiveness of the proposed method.
基金Projects(LQ16E080012,LY14F030012)supported by the Zhejiang Provincial Natural Science Foundation,ChinaProject(61573317)supported by the National Natural Science Foundation of ChinaProject(2015001)supported by the Open Fund for a Key-Key Discipline of Zhejiang University of Technology,China
文摘The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial characteristics is presented to estimate road traffic states. Firstly, the representative road traffic state data were extracted to establish the reference sequences of road traffic running characteristics(RSRTRC). Secondly, the spatial road traffic state data sequence was selected and the kernel function was constructed, with which the spatial road traffic data sequence could be mapped into a high dimensional feature space. Thirdly, the referenced and current spatial road traffic data sequences were extracted and the Euclidean distances in the feature space between them were obtained. Finally, the road traffic states were estimated from weighted averages of the selected k road traffic states, which corresponded to the nearest Euclidean distances. Several typical links in Beijing were adopted for case studies. The final results of the experiments show that the accuracy of this algorithm for estimating speed and volume is 95.27% and 91.32% respectively, which prove that this road traffic states estimation approach based on kernel-KNN matching of road traffic spatial characteristics is feasible and can achieve a high accuracy.
基金Project(61101185)supported by the National Natural Science Foundation of China
文摘A fast algorithm based on the grayscale distribution of infrared target and the weighted kernel function was proposed for the moving target detection(MTD) in dynamic scene of image series. This algorithm is used to deal with issues like the large computational complexity, the fluctuation of grayscale, and the noise in infrared images. Four characteristic points were selected by analyzing the grayscale distribution in infrared image, of which the series was quickly matched with an affine transformation model. The image was then divided into 32×32 squares and the gray-weighted kernel(GWK) for each square was calculated. At last, the MTD was carried out according to the variation of the four GWKs. The results indicate that the MTD can be achieved in real time using the algorithm with the fluctuations of grayscale and noise can be effectively suppressed. The detection probability is greater than 90% with the false alarm rate lower than 5% when the calculation time is less than 40 ms.
基金supported by Science and Technology Planning Project of Sichuan Province(2008SZ0050,14JC0798)Educational Commission of Sichuan Province(10ZA035,15ZA0155)+1 种基金Science and Technology Program of Luzhou(2015-S-43,2016LZXNYD-T03)Key Development Program of Southwest Medical University(2010ZD-010)
文摘OBJECTIVE Lychee seed,a famous traditional Chinese medicine,recently were reported to improve the learning and memory abilities in mice.However,it is still unclear whether lychee seed saponins(LSS)can improve the cognitive function and associated mechanisms.METHODS In present studies,we established the Alzheimer disease(AD)model by injecting Aβ25-35 into the lateral ventricle of rats.Then the spatial learning and memory abilities of LSS-treated rats were evaluated with the Morris water maze,meanwhile the protein expressions of AKT,GSK3β and Tau in the hippocampal neuron were analyzed by immunohistochemistry and Western blotting.RESULTS The results showed LSS can improve the cognitive functions of AD rats through shortening the escape latency,increasing the number across the platform,platform quadrant dwell time and the percentage of the total distance run platform quadrant.The protein expression of AKT was significantly up-regulated and that of GSK3β and Tau were decreased remarkably in the hippocampal CA1 area.CONCLUSION Our study is the first to show that LSS significantly improve the cognitive function and prevent hippocampal neuronal injury of the rats with AD by activation of the PI3K/AKT/GSK3βsignaling pathway,suggesting LSS may be developed into the nutrient supplement for the treatment of AD.
