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Establishment of a field visualization detection method for multiplex recombinase polymerase amplification combined with CRISPR/Cas12a in genetically modified crops 被引量:1
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作者 YAN Jingying NI Liang +2 位作者 SHEN Xingyu LÜ Bingtao LI Yu 《浙江大学学报(农业与生命科学版)》 北大核心 2025年第3期391-401,共11页
With the approval of more and more genetically modified(GM)crops in our country,GM safety management has become more important.Transgenic detection is a major approach for transgenic safety management.Nevertheless,a c... With the approval of more and more genetically modified(GM)crops in our country,GM safety management has become more important.Transgenic detection is a major approach for transgenic safety management.Nevertheless,a convenient and visual technique with low equipment requirements and high sensitivity for the field detection of GM plants is still lacking.On the basis of the existing recombinase polymerase amplification(RPA)technique,we developed a multiplex RPA(multi-RPA)method that can simultaneously detect three transgenic elements,including the cauliflower mosaic virus 35S gene(CaMV35S)promoter,neomycin phosphotransferaseⅡgene(NptⅡ)and hygromycin B phosphotransferase gene(Hyg),thus improving the detection rate.Moreover,we coupled this multi-RPA technique with the CRISPR/Cas12a reporter system,which enabled the detection results to be clearly observed by naked eyes under ultraviolet(UV)light(254 nm;which could be achieved by a portable UV flashlight),therefore establishing a multi-RPA visual detection technique.Compared with the traditional test strip detection method,this multi-RPA-CRISPR/Cas12a technique has the higher specificity,higher sensitivity,wider application range and lower cost.Compared with other polymerase chain reaction(PCR)techniques,it also has the advantages of low equipment requirements and visualization,making it a potentially feasible method for the field detection of GM plants. 展开更多
关键词 genetically modified crop recombinase polymerase amplification CRISPR/Cas12a field detection
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Research Progress of Agricultural Genetically Modified Crop Safety Evaluation
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作者 Li Ran Liang Liang +4 位作者 Zhao Haibo Zhao Yujia Fan Peilei Liu Ran Zhao Yue 《Journal of Northeast Agricultural University(English Edition)》 CAS 2024年第3期74-84,共11页
The commercial cultivation of genetically modified(GM)crops has eased the global food crisis and brought considerable economic and social benefits to countries.Because of the potential safety problems,it is necessary ... The commercial cultivation of genetically modified(GM)crops has eased the global food crisis and brought considerable economic and social benefits to countries.Because of the potential safety problems,it is necessary to make clear the molecular genetic characteristics,edible safety,planting,processing,and other aspects of the safety evaluation of GM crops.The safety problems existing in the cultivation of GM crops,safety evaluation and detection of GM crops were introduced in this paper,which provided the basis for safety evaluation and effective supervision of GM crops and their products.Commercial cultivation and reasonable supervision based on safety evaluation have far-reaching significance for ensuring consumer safety,enhancing the credibility of the national political system and enhancing citizens'confidence in the safety of GM crop products for consumption. 展开更多
关键词 genetically modified(GM)crop safety evaluation BIOSAFETY environmental safety detection method
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A Novel Evolutionary-Fuzzy Control Algorithm for Complex Systems 被引量:1
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作者 王攀 徐承志 +1 位作者 冯珊 徐爱华 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2002年第3期52-60,共9页
This paper presents an adaptive fuzzy control scheme based on modified genetic algorithm. In the control scheme, genetic algorithm is used to optimze the nonlinear quantization functions of the controller and some key... This paper presents an adaptive fuzzy control scheme based on modified genetic algorithm. In the control scheme, genetic algorithm is used to optimze the nonlinear quantization functions of the controller and some key parameters of the adaptive control algorithm. Simulation results show that this control scheme has satisfactory performance in MIMO systems, chaotic systems and delay systems. 展开更多
关键词 Modified genetic algorithm Nonlinear quantization factor Adaptive fuzzy controller ITAE index Complex systems.
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Best compromising crashworthiness design of automotive S-rail using TOPSIS and modified NSGAⅡ 被引量:6
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作者 Abolfazl Khalkhali 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第1期121-133,共13页
In order to reduce both the weight of vehicles and the damage of occupants in a crash event simultaneously, it is necessary to perform a multi-objective optimal design of the automotive energy absorbing components. Mo... In order to reduce both the weight of vehicles and the damage of occupants in a crash event simultaneously, it is necessary to perform a multi-objective optimal design of the automotive energy absorbing components. Modified non-dominated sorting genetic algorithm II(NSGA II) was used for multi-objective optimization of automotive S-rail considering absorbed energy(E), peak crushing force(Fmax) and mass of the structure(W) as three conflicting objective functions. In the multi-objective optimization problem(MOP), E and Fmax are defined by polynomial models extracted using the software GEvo M based on train and test data obtained from numerical simulation of quasi-static crushing of the S-rail using ABAQUS. Finally, the nearest to ideal point(NIP)method and technique for ordering preferences by similarity to ideal solution(TOPSIS) method are used to find the some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. Results represent that the optimum design point obtained from TOPSIS method exhibits better trade-off in comparison with that of optimum design point obtained from NIP method. 展开更多
关键词 automotive S-rail crashworthiness technique for ordering preferences by similarity to ideal solution(TOPSIS) method group method of data handling(GMDH) algorithm multi-objective optimization modified non-dominated sorting genetic algorithm(NSGA II) Pareto front
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