目的:通过整合分析甘草抗炎活性与性状特征数据,研究感官评价的科学性。方法:基于核苷酸结合寡聚化结构域样受体蛋白3(NLRP3)炎症小体细胞模型,建立甘草的抗炎生物效价测定方法,根据测定生物效价将采集的甘草样品分级。通过电子鼻、色...目的:通过整合分析甘草抗炎活性与性状特征数据,研究感官评价的科学性。方法:基于核苷酸结合寡聚化结构域样受体蛋白3(NLRP3)炎症小体细胞模型,建立甘草的抗炎生物效价测定方法,根据测定生物效价将采集的甘草样品分级。通过电子鼻、色彩色差仪等采集不同等级甘草样品的性状信息,通过主成分分析(PCA)、正交偏最小二乘法-判别分析(OPLS-DA)分析不同等级甘草的差异性,并进一步考察性状特征与甘草抗炎活性的关联性。结果:实验结果显示,甘草提取物对尼日利亚菌素诱导的小鼠原代骨髓巨噬细胞NLRP3炎症小体的激活具有明显抑制作用,根据甘草的抗炎生物效价,可将10批次甘草分为两个等级,一等甘草的生物效价为5.949~11.418 U·mg^(–1),二等甘草的生物效价为1.575~1.887 U·mg^(–1);PCA结果显示,两等级甘草可以聚成两类;OPLS-DA结果显示,R^(2)X=0.534,R^(2)Y=0.863,Q^(2)=0.75,模型的拟合能力较好,预测能力较强,并且发现色度值b^(*)和断面直径(2R)的变量重要性投影(variable important inprojection,VIP)分别为1.54294、1.26011,均大于1,两者可能是导致两等级甘草药效差异的关键参数,经过实测值比较,两等级甘草在b^(*)上的差异有统计学意义(P<0.01)。结论:研究表明,甘草的b^(*)与甘草抗炎活性具有显著的相关性,是其质量评价的一个重要指标,也佐证了甘草传统评价具有一定的科学性。展开更多
湿地自然教育有助于湿地保护。利用CiteSpace软件分析了2002—2021年CNKI以及WOS两大数据库检索的自然教育相关的文章。结果表明:(1)湿地自然教育年度发文量逐年递增;《湿地科学与管理》期刊对该领域关注度最高,《Journal of cleaner pr...湿地自然教育有助于湿地保护。利用CiteSpace软件分析了2002—2021年CNKI以及WOS两大数据库检索的自然教育相关的文章。结果表明:(1)湿地自然教育年度发文量逐年递增;《湿地科学与管理》期刊对该领域关注度最高,《Journal of cleaner production》期刊在该领域具有较强的影响力。(2)湿地自然教育的研究主体是各类高校,美国发文数量最多并与其他国家有较好的合作关系。(3)湿地自然教育研究领域涉及到湿地、保护、环境教育、生态知识和湿地文化;国外湿地自然教育研究重点在自然能力、水、教育和课程;国内湿地自然教育研究重点在生态旅游、湿地公园和自然学校。展开更多
In order to make full use of the driver’s long-term driving experience in the process of perception, interaction and vehicle control of road traffic information, a driving behavior rule extraction algorithm based on ...In order to make full use of the driver’s long-term driving experience in the process of perception, interaction and vehicle control of road traffic information, a driving behavior rule extraction algorithm based on artificial neural network interface(ANNI) and its integration is proposed. Firstly, based on the cognitive learning theory, the cognitive driving behavior model is established, and then the cognitive driving behavior is described and analyzed. Next, based on ANNI, the model and the rule extraction algorithm(ANNI-REA) are designed to explain not only the driving behavior but also the non-sequence. Rules have high fidelity and safety during driving without discretizing continuous input variables. The experimental results on the UCI standard data set and on the self-built driving behavior data set, show that the method is about 0.4% more accurate and about 10% less complex than the common C4.5-REA, Neuro-Rule and REFNE. Further, simulation experiments verify the correctness of the extracted driving rules and the effectiveness of the extraction based on cognitive driving behavior rules. In general, the several driving rules extracted fully reflect the execution mechanism of sequential activity of driving comprehensive cognition, which is of great significance for the traffic of mixed traffic flow under the network of vehicles and future research on unmanned driving.展开更多
文摘目的:通过整合分析甘草抗炎活性与性状特征数据,研究感官评价的科学性。方法:基于核苷酸结合寡聚化结构域样受体蛋白3(NLRP3)炎症小体细胞模型,建立甘草的抗炎生物效价测定方法,根据测定生物效价将采集的甘草样品分级。通过电子鼻、色彩色差仪等采集不同等级甘草样品的性状信息,通过主成分分析(PCA)、正交偏最小二乘法-判别分析(OPLS-DA)分析不同等级甘草的差异性,并进一步考察性状特征与甘草抗炎活性的关联性。结果:实验结果显示,甘草提取物对尼日利亚菌素诱导的小鼠原代骨髓巨噬细胞NLRP3炎症小体的激活具有明显抑制作用,根据甘草的抗炎生物效价,可将10批次甘草分为两个等级,一等甘草的生物效价为5.949~11.418 U·mg^(–1),二等甘草的生物效价为1.575~1.887 U·mg^(–1);PCA结果显示,两等级甘草可以聚成两类;OPLS-DA结果显示,R^(2)X=0.534,R^(2)Y=0.863,Q^(2)=0.75,模型的拟合能力较好,预测能力较强,并且发现色度值b^(*)和断面直径(2R)的变量重要性投影(variable important inprojection,VIP)分别为1.54294、1.26011,均大于1,两者可能是导致两等级甘草药效差异的关键参数,经过实测值比较,两等级甘草在b^(*)上的差异有统计学意义(P<0.01)。结论:研究表明,甘草的b^(*)与甘草抗炎活性具有显著的相关性,是其质量评价的一个重要指标,也佐证了甘草传统评价具有一定的科学性。
文摘湿地自然教育有助于湿地保护。利用CiteSpace软件分析了2002—2021年CNKI以及WOS两大数据库检索的自然教育相关的文章。结果表明:(1)湿地自然教育年度发文量逐年递增;《湿地科学与管理》期刊对该领域关注度最高,《Journal of cleaner production》期刊在该领域具有较强的影响力。(2)湿地自然教育的研究主体是各类高校,美国发文数量最多并与其他国家有较好的合作关系。(3)湿地自然教育研究领域涉及到湿地、保护、环境教育、生态知识和湿地文化;国外湿地自然教育研究重点在自然能力、水、教育和课程;国内湿地自然教育研究重点在生态旅游、湿地公园和自然学校。
基金Project(2017YFB0102503)supported by the National Key Research and Development Program of ChinaProjects(U1664258,51875255,61601203)supported by the National Natural Science Foundation of China+1 种基金Projects(DZXX-048,2018-TD-GDZB-022)supported by the Jiangsu Province’s Six Talent Peak,ChinaProject(18KJA580002)supported by Major Natural Science Research Project of Higher Learning in Jiangsu Province,China
文摘In order to make full use of the driver’s long-term driving experience in the process of perception, interaction and vehicle control of road traffic information, a driving behavior rule extraction algorithm based on artificial neural network interface(ANNI) and its integration is proposed. Firstly, based on the cognitive learning theory, the cognitive driving behavior model is established, and then the cognitive driving behavior is described and analyzed. Next, based on ANNI, the model and the rule extraction algorithm(ANNI-REA) are designed to explain not only the driving behavior but also the non-sequence. Rules have high fidelity and safety during driving without discretizing continuous input variables. The experimental results on the UCI standard data set and on the self-built driving behavior data set, show that the method is about 0.4% more accurate and about 10% less complex than the common C4.5-REA, Neuro-Rule and REFNE. Further, simulation experiments verify the correctness of the extracted driving rules and the effectiveness of the extraction based on cognitive driving behavior rules. In general, the several driving rules extracted fully reflect the execution mechanism of sequential activity of driving comprehensive cognition, which is of great significance for the traffic of mixed traffic flow under the network of vehicles and future research on unmanned driving.
