To analyze the dynamic response and reliability of a continuous beam bridge under the action of an extra heavy vehicle, a vehicle–bridge coupled vibration model was established based on the virtual work principle and...To analyze the dynamic response and reliability of a continuous beam bridge under the action of an extra heavy vehicle, a vehicle–bridge coupled vibration model was established based on the virtual work principle and vehicle–bridge displacement compatibility equation, which can accurately simulate the dynamic characteristics of the vehicle and bridge. Results show that deck roughness has an important function in the effect of the vehicle on the bridge. When an extra heavy vehicle passes through the continuous beam bridge at a low speed of 5 km/h, the impact coefficient reaches a high value, which should not be disregarded in bridge safety assessments. Considering that no specific law exists between the impact coefficient and vehicle speed, vehicle speed should not be unduly limited and deck roughness repairing should be paid considerable attention. Deck roughness has a significant influence on the reliability index, which decreases as deck roughness increases. For the continuous beam bridge in this work, the reliability index of each control section is greater than the minimum reliability index. No reinforcement measures are required for over-sized transport.展开更多
Essential proteins play a vital role in biological processes,and the combination of gene expression profiles with Protein-Protein Interaction(PPI)networks can improve the identification of essential proteins.However,g...Essential proteins play a vital role in biological processes,and the combination of gene expression profiles with Protein-Protein Interaction(PPI)networks can improve the identification of essential proteins.However,gene expression data are prone to significant fluctuations due to noise interference in topological networks.In this work,we discretized gene expression data and used the discrete similarities of the gene expression spectrum to eliminate noise fluctuation.We then proposed the Pearson Jaccard coefficient(PJC)that consisted of continuous and discrete similarities in the gene expression data.Using the graph theory as the basis,we fused the newly proposed similarity coefficient with the existing network topology prediction algorithm at each protein node to recognize essential proteins.This strategy exhibited a high recognition rate and good specificity.We validated the new similarity coefficient PJC on PPI datasets of Krogan,Gavin,and DIP of yeast species and evaluated the results by receiver operating characteristic analysis,jackknife analysis,top analysis,and accuracy analysis.Compared with that of node-based network topology centrality and fusion biological information centrality methods,the new similarity coefficient PJC showed a significantly improved prediction performance for essential proteins in DC,IC,Eigenvector centrality,subgraph centrality,betweenness centrality,closeness centrality,NC,PeC,and WDC.We also compared the PJC coefficient with other methods using the NF-PIN algorithm,which predicts proteins by constructing active PPI networks through dynamic gene expression.The experimental results proved that our newly proposed similarity coefficient PJC has superior advantages in predicting essential proteins.展开更多
Conventional Al-Si materials always have a coarse and discontinuous Si structure,which limits their application as thermal management materials.Fortunately,nature has evolved efficient strategies to form complex micro...Conventional Al-Si materials always have a coarse and discontinuous Si structure,which limits their application as thermal management materials.Fortunately,nature has evolved efficient strategies to form complex microstructures that exhibit excellent wear resistance and thermal properties;one such example is found in the red deer antler.Here,inspired by the antler structure,AleSi composites with a novel fenestrated network-particle structure(F-N)and with a common isolated island structure(I-I)are designed and prepared.Subsequently,the dynamic formation of F-N is tracked and studied using computational fluid dynamics(CFD)simulation.To investigate the reinforcement mechanisms of F-N,the wear resistances and thermal properties of F-N and I-I are compared and analyzed.Simulation and experimental results show that the reconstruction of a semi-continuous structure promotes the formation of a striated structure,whereas flowing Si particles provide some sites for the formation of the fenestrated structure.The dynamic formation of F-N is strongly influenced by the convectionediffusion process and the flow path.Moreover,this biomimetic F-N structure exhibits better wear resistance and thermal properties than I-I,owing to its strong structural support and high expansion resistance.This work is expected to provide new perspectives on the microstructural design of thermal management materials with good wear resistance.展开更多
基金Project(50779032)supported by the National Natural Science Foundation of ChinaProject(20090451330)supported by the Postdoctoral Foundation of ChinaProject(BS2013SF007)supported by Shandong Scientific Research Award Foundation for Outstanding Young Scientists,China
文摘To analyze the dynamic response and reliability of a continuous beam bridge under the action of an extra heavy vehicle, a vehicle–bridge coupled vibration model was established based on the virtual work principle and vehicle–bridge displacement compatibility equation, which can accurately simulate the dynamic characteristics of the vehicle and bridge. Results show that deck roughness has an important function in the effect of the vehicle on the bridge. When an extra heavy vehicle passes through the continuous beam bridge at a low speed of 5 km/h, the impact coefficient reaches a high value, which should not be disregarded in bridge safety assessments. Considering that no specific law exists between the impact coefficient and vehicle speed, vehicle speed should not be unduly limited and deck roughness repairing should be paid considerable attention. Deck roughness has a significant influence on the reliability index, which decreases as deck roughness increases. For the continuous beam bridge in this work, the reliability index of each control section is greater than the minimum reliability index. No reinforcement measures are required for over-sized transport.
基金supported by the Shenzhen KQTD Project(No.KQTD20200820113106007)China Scholarship Council(No.201906725017)+2 种基金the Collaborative Education Project of Industry-University cooperation of the Chinese Ministry of Education(No.201902098015)the Teaching Reform Project of Hunan Normal University(No.82)the National Undergraduate Training Program for Innovation(No.202110542004).
文摘Essential proteins play a vital role in biological processes,and the combination of gene expression profiles with Protein-Protein Interaction(PPI)networks can improve the identification of essential proteins.However,gene expression data are prone to significant fluctuations due to noise interference in topological networks.In this work,we discretized gene expression data and used the discrete similarities of the gene expression spectrum to eliminate noise fluctuation.We then proposed the Pearson Jaccard coefficient(PJC)that consisted of continuous and discrete similarities in the gene expression data.Using the graph theory as the basis,we fused the newly proposed similarity coefficient with the existing network topology prediction algorithm at each protein node to recognize essential proteins.This strategy exhibited a high recognition rate and good specificity.We validated the new similarity coefficient PJC on PPI datasets of Krogan,Gavin,and DIP of yeast species and evaluated the results by receiver operating characteristic analysis,jackknife analysis,top analysis,and accuracy analysis.Compared with that of node-based network topology centrality and fusion biological information centrality methods,the new similarity coefficient PJC showed a significantly improved prediction performance for essential proteins in DC,IC,Eigenvector centrality,subgraph centrality,betweenness centrality,closeness centrality,NC,PeC,and WDC.We also compared the PJC coefficient with other methods using the NF-PIN algorithm,which predicts proteins by constructing active PPI networks through dynamic gene expression.The experimental results proved that our newly proposed similarity coefficient PJC has superior advantages in predicting essential proteins.
基金supported by the financial support of the National Science Foundation of China(No.51607132 and No.51906189)the National Science Foundation of Shaanxi(No:2019JQ-842).
文摘Conventional Al-Si materials always have a coarse and discontinuous Si structure,which limits their application as thermal management materials.Fortunately,nature has evolved efficient strategies to form complex microstructures that exhibit excellent wear resistance and thermal properties;one such example is found in the red deer antler.Here,inspired by the antler structure,AleSi composites with a novel fenestrated network-particle structure(F-N)and with a common isolated island structure(I-I)are designed and prepared.Subsequently,the dynamic formation of F-N is tracked and studied using computational fluid dynamics(CFD)simulation.To investigate the reinforcement mechanisms of F-N,the wear resistances and thermal properties of F-N and I-I are compared and analyzed.Simulation and experimental results show that the reconstruction of a semi-continuous structure promotes the formation of a striated structure,whereas flowing Si particles provide some sites for the formation of the fenestrated structure.The dynamic formation of F-N is strongly influenced by the convectionediffusion process and the flow path.Moreover,this biomimetic F-N structure exhibits better wear resistance and thermal properties than I-I,owing to its strong structural support and high expansion resistance.This work is expected to provide new perspectives on the microstructural design of thermal management materials with good wear resistance.