It has been challenging to correctly separate the mixed signals into source components when the source number is not known a priori.To reveal the complexity of the measured vibration signals,and provide the priori inf...It has been challenging to correctly separate the mixed signals into source components when the source number is not known a priori.To reveal the complexity of the measured vibration signals,and provide the priori information for the blind source separation,in this paper,we propose a novel source number estimation based on independent component analysis(ICA)and clustering evaluation analysis,and then carry out experiment studies with typical mechanical vibration signals from a shell structure.The results demonstrate that the proposed ICA based source number estimation performs stably and robustly for the shell structure.展开更多
Deuteron separation energy is not only the basis for validating the nuclear mass models and nucleon-nucleon interaction potential,but also can determine the stability of a nuclide to certain extent.Bayesian neural net...Deuteron separation energy is not only the basis for validating the nuclear mass models and nucleon-nucleon interaction potential,but also can determine the stability of a nuclide to certain extent.Bayesian neural network(BNN)approach,which has strong predictive power and can naturally give theoretical errors of predicted values,had been successfully applied to study the different kinds of separations except the deuteron separation.In this paper,several typical nuclear mass models,such as macroscopic model BW2,macroscopic-microscopic model WS4,and microscopic model HFB-31,are chosen to study the deuteron separation energy combining BNN approach.The root-mean-square deviations of these models are partly reduced.In addition,the inclusion of physical parameters related to the pair and shell effects in the input layer can further improve the theoretical accuracy for the deuteron separation energy.The results show that the theoretical predictions are more reliable as more physical features of BNN approach are included.展开更多
该文通过在金属-有机骨架材料(MOF)NH_(2)-MIL-125表面原位生长共价有机骨架材料(COF)TPA-COF,制备了核壳复合材料(MOF@COF)NH_(2)-MIL-125@TPA-COF,采用X-射线粉末衍射(PXRD)、红外光谱(FTIR)和扫描电镜(SEM)等手段对该复合材料进行表...该文通过在金属-有机骨架材料(MOF)NH_(2)-MIL-125表面原位生长共价有机骨架材料(COF)TPA-COF,制备了核壳复合材料(MOF@COF)NH_(2)-MIL-125@TPA-COF,采用X-射线粉末衍射(PXRD)、红外光谱(FTIR)和扫描电镜(SEM)等手段对该复合材料进行表征,并将其作为固定相成功制备了NH_(2)-MIL-125@TPA-COF色谱填充柱(25 cm long×2.1 mm i.d.)。在正相(正己烷-异丙醇(9∶1))、反相(甲醇-水(9∶1))高效液相色谱(HPLC)条件下,考察了该柱对一系列位置异构体的分离性能。结果表明,该柱在较低的背景压力(60~100 k Pa)下对9种位置异构体(溴硝基苯、硝基苯胺、氯苯酚、二硝基苯、碘苯胺、溴苯胺、苯二胺、甲苯胺和氯苯胺)表现出较好的分离能力,其中溴硝基苯、硝基苯胺和二硝基苯能达到基线分离,且最大分离度(Rs)为9.71。在反相HPLC条件下,邻-溴硝基苯、间-硝基苯胺和邻-氯苯酚的柱效分别为18424、19053、12954 plates·m^(2)。以溴硝基苯为分析物,在正相HPLC条件下,考察了该柱的重现性和稳定性。该柱通过5次重复进样(第50次、第100次、第150次、第200次、第250次),溴硝基苯保留时间和峰面积的相对标准偏差(RSD)分别为0.29%和0.89%,表明所制备的色谱柱具有较好的重现性和稳定性。核壳复合材料NH_(2)-MIL-125@TPA-COF作为一种新型的HPLC固定相用于位置异构体分离具有良好的应用前景。展开更多
复杂网络中,评估节点的重要性对于研究网络结构和传播过程有着重要意义.通过节点的位置,K-shell分解算法能够很好地识别关键节点,但是这种算法导致很多节点具有相同的K-shell(Ks)值.同时,现有的算法大都只考虑局部指标或者全局指标,导...复杂网络中,评估节点的重要性对于研究网络结构和传播过程有着重要意义.通过节点的位置,K-shell分解算法能够很好地识别关键节点,但是这种算法导致很多节点具有相同的K-shell(Ks)值.同时,现有的算法大都只考虑局部指标或者全局指标,导致评判节点重要性的因素单一.为了更好地识别关键节点,提出了EKSDN(Extended K-shell and Degree of Neighbors)算法,该算法综合考虑了节点的全局指标加权核值以及节点的局部指标度数.与SIR(Susceptible-Infectious-Recovered)模型在真实复杂网络中模拟结果相比,EKSDN算法能够更好地识别关键节点.展开更多
基金supported by China Postdoctoral Science Foundation (No. 2013M532032)National Nature Science Foundation of China (No. 51305329, 51035007)+1 种基金the Doctoral Foundation of Education Ministry of China (No. 20130201120040)the Shaanxi Postdoctoral Scientific research project
文摘It has been challenging to correctly separate the mixed signals into source components when the source number is not known a priori.To reveal the complexity of the measured vibration signals,and provide the priori information for the blind source separation,in this paper,we propose a novel source number estimation based on independent component analysis(ICA)and clustering evaluation analysis,and then carry out experiment studies with typical mechanical vibration signals from a shell structure.The results demonstrate that the proposed ICA based source number estimation performs stably and robustly for the shell structure.
基金Supported by National Natural Science Foundation of China (12065003)Central Government Guidance Funds for Local Scientific and Technological Development of China (Guike ZY22096024)+1 种基金Natural Science Foundation of Guangxi (2019GXNSFDA185011)Scientific Research and Technology Development Project of Guilin (20210104-2)。
文摘Deuteron separation energy is not only the basis for validating the nuclear mass models and nucleon-nucleon interaction potential,but also can determine the stability of a nuclide to certain extent.Bayesian neural network(BNN)approach,which has strong predictive power and can naturally give theoretical errors of predicted values,had been successfully applied to study the different kinds of separations except the deuteron separation.In this paper,several typical nuclear mass models,such as macroscopic model BW2,macroscopic-microscopic model WS4,and microscopic model HFB-31,are chosen to study the deuteron separation energy combining BNN approach.The root-mean-square deviations of these models are partly reduced.In addition,the inclusion of physical parameters related to the pair and shell effects in the input layer can further improve the theoretical accuracy for the deuteron separation energy.The results show that the theoretical predictions are more reliable as more physical features of BNN approach are included.
文摘该文通过在金属-有机骨架材料(MOF)NH_(2)-MIL-125表面原位生长共价有机骨架材料(COF)TPA-COF,制备了核壳复合材料(MOF@COF)NH_(2)-MIL-125@TPA-COF,采用X-射线粉末衍射(PXRD)、红外光谱(FTIR)和扫描电镜(SEM)等手段对该复合材料进行表征,并将其作为固定相成功制备了NH_(2)-MIL-125@TPA-COF色谱填充柱(25 cm long×2.1 mm i.d.)。在正相(正己烷-异丙醇(9∶1))、反相(甲醇-水(9∶1))高效液相色谱(HPLC)条件下,考察了该柱对一系列位置异构体的分离性能。结果表明,该柱在较低的背景压力(60~100 k Pa)下对9种位置异构体(溴硝基苯、硝基苯胺、氯苯酚、二硝基苯、碘苯胺、溴苯胺、苯二胺、甲苯胺和氯苯胺)表现出较好的分离能力,其中溴硝基苯、硝基苯胺和二硝基苯能达到基线分离,且最大分离度(Rs)为9.71。在反相HPLC条件下,邻-溴硝基苯、间-硝基苯胺和邻-氯苯酚的柱效分别为18424、19053、12954 plates·m^(2)。以溴硝基苯为分析物,在正相HPLC条件下,考察了该柱的重现性和稳定性。该柱通过5次重复进样(第50次、第100次、第150次、第200次、第250次),溴硝基苯保留时间和峰面积的相对标准偏差(RSD)分别为0.29%和0.89%,表明所制备的色谱柱具有较好的重现性和稳定性。核壳复合材料NH_(2)-MIL-125@TPA-COF作为一种新型的HPLC固定相用于位置异构体分离具有良好的应用前景。
文摘复杂网络中,评估节点的重要性对于研究网络结构和传播过程有着重要意义.通过节点的位置,K-shell分解算法能够很好地识别关键节点,但是这种算法导致很多节点具有相同的K-shell(Ks)值.同时,现有的算法大都只考虑局部指标或者全局指标,导致评判节点重要性的因素单一.为了更好地识别关键节点,提出了EKSDN(Extended K-shell and Degree of Neighbors)算法,该算法综合考虑了节点的全局指标加权核值以及节点的局部指标度数.与SIR(Susceptible-Infectious-Recovered)模型在真实复杂网络中模拟结果相比,EKSDN算法能够更好地识别关键节点.
