Introducing PCR products into plasmids vectors is key for molecular techniques. Ideally cloning vectors are easy to construct, modify and propagate, neither require advanced techniques nor special equipment or reagent...Introducing PCR products into plasmids vectors is key for molecular techniques. Ideally cloning vectors are easy to construct, modify and propagate, neither require advanced techniques nor special equipment or reagents and efficiently incorporate PCR products at close to zero empty vector background. We provide an easy to engineer self-made cloning vector, neither requiring sophisticated tools or techniques nor advanced cloning knowledge. Through recombination we obtained the pUC18ccdB vector, carrying the ccdB suicide gene within the pUC18 backbone. When SmaI cleaved (within the ccdB) vector was T4 ligated with small (0.2 kbp) and intermediate (1.3 to 2.2 kbp) blunt end PCR-products and transformed into E. coli, the amount of clones with incorporated PCR product was comparable to commercial PCR-cloning kits and at a close to zero PCR product negative background. In conclusion we present a simple, versatile and cheap approach to an efficient “home made” PCR-cloning vector that allows integration of crude blunt end PCR products at close to zero background.展开更多
This paper considered the optimal control problem for distributed parameter systems with mixed phase-control constraints and end-point constraints. Pontryagin's maximum principle for optimal control are derived vi...This paper considered the optimal control problem for distributed parameter systems with mixed phase-control constraints and end-point constraints. Pontryagin's maximum principle for optimal control are derived via Duboviskij-Milujin theorem.展开更多
This study develops new real-time freeway rear-end crash potential predictors using support vector machine(SVM) technique. The relationship between rear-end crash occurrences and traffic conditions were explored using...This study develops new real-time freeway rear-end crash potential predictors using support vector machine(SVM) technique. The relationship between rear-end crash occurrences and traffic conditions were explored using historical loop detector data from Interstate-894 in Milwaukee, Wisconsin, USA. The extracted loop detection data were aggregated over different stations and time intervals to produce explanatory features. A feature selection process, which addresses the interaction between SVM classifiers and explanatory features, was adopted to identify the features that significantly influence rear-end crashes. Afterwards, the identified significant explanatory features over three separate time levels were used to train three SVM models. In the end, the multi-layer perceptron(MLP) artificial neural network models were used as benchmarks to evaluate the performance of SVM models. The results show that the proposed feature selection procedure greatly enhances the accuracy and generalization capability of SVM models. Moreover, the optimal SVM classifier achieves 81.1% overall prediction precision rate. In comparison with MLP artificial neural networks, SVM models provide better results in terms of crash prediction accuracy and false positive rate, which confirms the superior performance of SVM technique in rear-end crash potential prediction analysis.展开更多
文摘Introducing PCR products into plasmids vectors is key for molecular techniques. Ideally cloning vectors are easy to construct, modify and propagate, neither require advanced techniques nor special equipment or reagents and efficiently incorporate PCR products at close to zero empty vector background. We provide an easy to engineer self-made cloning vector, neither requiring sophisticated tools or techniques nor advanced cloning knowledge. Through recombination we obtained the pUC18ccdB vector, carrying the ccdB suicide gene within the pUC18 backbone. When SmaI cleaved (within the ccdB) vector was T4 ligated with small (0.2 kbp) and intermediate (1.3 to 2.2 kbp) blunt end PCR-products and transformed into E. coli, the amount of clones with incorporated PCR product was comparable to commercial PCR-cloning kits and at a close to zero PCR product negative background. In conclusion we present a simple, versatile and cheap approach to an efficient “home made” PCR-cloning vector that allows integration of crude blunt end PCR products at close to zero background.
文摘This paper considered the optimal control problem for distributed parameter systems with mixed phase-control constraints and end-point constraints. Pontryagin's maximum principle for optimal control are derived via Duboviskij-Milujin theorem.
基金Project(BK20160685)supported by the Science Foundation of Jiangsu Province,ChinaProject(61620106002)supported by the National Natural Science Foundation of China
文摘This study develops new real-time freeway rear-end crash potential predictors using support vector machine(SVM) technique. The relationship between rear-end crash occurrences and traffic conditions were explored using historical loop detector data from Interstate-894 in Milwaukee, Wisconsin, USA. The extracted loop detection data were aggregated over different stations and time intervals to produce explanatory features. A feature selection process, which addresses the interaction between SVM classifiers and explanatory features, was adopted to identify the features that significantly influence rear-end crashes. Afterwards, the identified significant explanatory features over three separate time levels were used to train three SVM models. In the end, the multi-layer perceptron(MLP) artificial neural network models were used as benchmarks to evaluate the performance of SVM models. The results show that the proposed feature selection procedure greatly enhances the accuracy and generalization capability of SVM models. Moreover, the optimal SVM classifier achieves 81.1% overall prediction precision rate. In comparison with MLP artificial neural networks, SVM models provide better results in terms of crash prediction accuracy and false positive rate, which confirms the superior performance of SVM technique in rear-end crash potential prediction analysis.
