A mathematical model was developed for layout optimization of truss structures with discrete variables subjected to dynamic stress, dynamic displacement and dynamic stability constraints. By using the quasi-static met...A mathematical model was developed for layout optimization of truss structures with discrete variables subjected to dynamic stress, dynamic displacement and dynamic stability constraints. By using the quasi-static method, the mathematical model of structure optimization under dynamic stress, dynamic displacement and dynamic stability constraints were transformed into one subjected to static stress, displacement and stability constraints. The optimization procedures include two levels, i.e., the topology optimization and the shape optimization. In each level, the comprehensive algorithm was used and the relative difference quotients of two kinds of variables were used to search the optimum solution. A comparison between the optimum results of model with stability constraints and the optimum results of model without stability constraint was given. And that shows the stability constraints have a great effect on the optimum solutions.展开更多
Integrin activation,the transition from a low to a high affinity state,regulates the numerous cellular responses consequent to integrin engagement by extracellular matrix proteins.Kindlin proteins,play crucial roles i...Integrin activation,the transition from a low to a high affinity state,regulates the numerous cellular responses consequent to integrin engagement by extracellular matrix proteins.Kindlin proteins,play crucial roles in the integrin-signaling pathway by directly interacting with and activating integrins,which mediate the cell-extracellular matrix adhesion and signaling.As a widely distributed PTB domain protein and a major member of the kindlin family,kindlin2 interacts withβ3-tail,bridges talin-activated integrins to promote integrin aggregation,and enhances talin-induced integrin activation.Thus,kindlin2 is identified as a coactivator of integrins.Unlike talins,kindlin2 cannot directly alter the conformation of the integrin transmembrane helix and fail to activate integrin alone.Nevertheless,although it is widely accepted that kindlins and talins synergistically promote integrin activation,the underlying mechanism is unclear.Thus,the study of the force dissociation of the kindlin2/β3-tail complex and the conformation stabilization under different mechanical micro-environments should be of great significance for the further understanding of the structural basis of its synergistically activation of integrin.To reveal the molecular dynamics mechanism of interaction between kindlin2 andβ3-tail,we perform molecular dynamics(MD)simulations for this complex with different computing strategies interaction.In MD simulations,the available crystal structures of Kindlin-2/β3-tail complex(Protein Data Bank code 5XQ1)was downloaded from the PDB database.Two software packages,VMD for visualization and modeling and NAMD 2.13 for energy minimizations and MD simulations,were used here.The steadystate conformation of the complex was obtained from the equilibrium simulation.The dissociation event was observed by the constant velocity simulation,and the mechanical stability of the complex was observed by the constant force simulation.Our results showed that,during the equilibrium of the kindlin2-F3/β34ail complex,the residue MET612,LYS613 and TRP615 on the F3 domain of kindlin2 contributed to hydrogen-bonding with the corresponding residues onβ3 integrin.These bonds exhibit moderate or strong stability through steered molecular dynamics(SMD)simulation.During the constant velocity simulation,the complex exhibits a variety of unfolding pathways against tension applications,which are mainly distinguished by the disruption of hydrogen-bonds between the F3 domain a1/a2 helixes andβ1/β2 sheets.During the constant force simulation,the different phases of the composite force dissociation have different dissociation probabilities,which shows the biphasic force-dependent characteristics.And,the key residues in the pulling were recognized according not only to the number of interacting residue pairs,but also to their bond strength.Using molecular dynamics simulation,we showed the steady state of the kindlin2-F3/β3-tail complex under different tensile forces,and observe the dynamic process of molecular interaction.A possible underlying biophysical mechanism is that,the dissociation of Kindlin2-F3/β3-tail complex is biphasic force-dependent,and the conformations under different stretching states have different binding affinities.This study not only provides insights into the structural basis and mechanical regulation mechanisms of the kindlin/integrin interaction,in understanding in kindlin/integrin-related signaling in different cellular biological processes,but also provides new ideas for novel drug design and the treatment of related diseases.展开更多
Deep neural network-based relational extraction research has made significant progress in recent years,andit provides data support for many natural language processing downstream tasks such as building knowledgegraph,...Deep neural network-based relational extraction research has made significant progress in recent years,andit provides data support for many natural language processing downstream tasks such as building knowledgegraph,sentiment analysis and question-answering systems.However,previous studies ignored much unusedstructural information in sentences that could enhance the performance of the relation extraction task.Moreover,most existing dependency-based models utilize self-attention to distinguish the importance of context,whichhardly deals withmultiple-structure information.To efficiently leverage multiple structure information,this paperproposes a dynamic structure attention mechanism model based on textual structure information,which deeplyintegrates word embedding,named entity recognition labels,part of speech,dependency tree and dependency typeinto a graph convolutional network.Specifically,our model extracts text features of different structures from theinput sentence.Textual Structure information Graph Convolutional Networks employs the dynamic structureattention mechanism to learn multi-structure attention,effectively distinguishing important contextual features invarious structural information.In addition,multi-structure weights are carefully designed as amergingmechanismin the different structure attention to dynamically adjust the final attention.This paper combines these featuresand trains a graph convolutional network for relation extraction.We experiment on supervised relation extractiondatasets including SemEval 2010 Task 8,TACRED,TACREV,and Re-TACED,the result significantly outperformsthe previous.展开更多
Nano-precision positioning stages are characterized by rigid-flexible coupling systems. The complex dynamic characteristics of mechanical structure of a stage, which are determined by structural and dynamic parameters...Nano-precision positioning stages are characterized by rigid-flexible coupling systems. The complex dynamic characteristics of mechanical structure of a stage, which are determined by structural and dynamic parameters, exert a serious influence on the accuracy of its motion and measurement. Systematic evaluation of such influence is essential for the design and improvement of stages. A systematic approach to modeling the dynamic accuracy of a nano-precision positioning stage is developed in this work by integrating a multi-rigid-body dynamic model of the mechanical system and measurement system models. The influence of structural and dynamic parameters, including aerostatic bearing configurations, motion plane errors, foundation vibrations, and positions of the acting points of driving forces, on dynamic accuracy is investigated by adopting the H-type configured stage as an example. The approach is programmed and integrated into a software framework that supports the dynamic design of nano-precision positioning stages. The software framework is then applied to the design of a nano-precision positioning stage used in a packaging lithography machine.展开更多
基金Project supported by the National Natural Science Foundation of China (Nos. 10002005 and 10421002)the Natural Science Foundation of Tianjin (No.02360081)the Education Committee Foundation of Tianjin (No.20022104)the Program for Changjiang Scholars and Innovative Research Team in University of China and the 211 Foundation of Dalian University of Technology
文摘A mathematical model was developed for layout optimization of truss structures with discrete variables subjected to dynamic stress, dynamic displacement and dynamic stability constraints. By using the quasi-static method, the mathematical model of structure optimization under dynamic stress, dynamic displacement and dynamic stability constraints were transformed into one subjected to static stress, displacement and stability constraints. The optimization procedures include two levels, i.e., the topology optimization and the shape optimization. In each level, the comprehensive algorithm was used and the relative difference quotients of two kinds of variables were used to search the optimum solution. A comparison between the optimum results of model with stability constraints and the optimum results of model without stability constraint was given. And that shows the stability constraints have a great effect on the optimum solutions.
基金supported by the National Natural Science Foundation of China ( 116272109, 11432006)
文摘Integrin activation,the transition from a low to a high affinity state,regulates the numerous cellular responses consequent to integrin engagement by extracellular matrix proteins.Kindlin proteins,play crucial roles in the integrin-signaling pathway by directly interacting with and activating integrins,which mediate the cell-extracellular matrix adhesion and signaling.As a widely distributed PTB domain protein and a major member of the kindlin family,kindlin2 interacts withβ3-tail,bridges talin-activated integrins to promote integrin aggregation,and enhances talin-induced integrin activation.Thus,kindlin2 is identified as a coactivator of integrins.Unlike talins,kindlin2 cannot directly alter the conformation of the integrin transmembrane helix and fail to activate integrin alone.Nevertheless,although it is widely accepted that kindlins and talins synergistically promote integrin activation,the underlying mechanism is unclear.Thus,the study of the force dissociation of the kindlin2/β3-tail complex and the conformation stabilization under different mechanical micro-environments should be of great significance for the further understanding of the structural basis of its synergistically activation of integrin.To reveal the molecular dynamics mechanism of interaction between kindlin2 andβ3-tail,we perform molecular dynamics(MD)simulations for this complex with different computing strategies interaction.In MD simulations,the available crystal structures of Kindlin-2/β3-tail complex(Protein Data Bank code 5XQ1)was downloaded from the PDB database.Two software packages,VMD for visualization and modeling and NAMD 2.13 for energy minimizations and MD simulations,were used here.The steadystate conformation of the complex was obtained from the equilibrium simulation.The dissociation event was observed by the constant velocity simulation,and the mechanical stability of the complex was observed by the constant force simulation.Our results showed that,during the equilibrium of the kindlin2-F3/β34ail complex,the residue MET612,LYS613 and TRP615 on the F3 domain of kindlin2 contributed to hydrogen-bonding with the corresponding residues onβ3 integrin.These bonds exhibit moderate or strong stability through steered molecular dynamics(SMD)simulation.During the constant velocity simulation,the complex exhibits a variety of unfolding pathways against tension applications,which are mainly distinguished by the disruption of hydrogen-bonds between the F3 domain a1/a2 helixes andβ1/β2 sheets.During the constant force simulation,the different phases of the composite force dissociation have different dissociation probabilities,which shows the biphasic force-dependent characteristics.And,the key residues in the pulling were recognized according not only to the number of interacting residue pairs,but also to their bond strength.Using molecular dynamics simulation,we showed the steady state of the kindlin2-F3/β3-tail complex under different tensile forces,and observe the dynamic process of molecular interaction.A possible underlying biophysical mechanism is that,the dissociation of Kindlin2-F3/β3-tail complex is biphasic force-dependent,and the conformations under different stretching states have different binding affinities.This study not only provides insights into the structural basis and mechanical regulation mechanisms of the kindlin/integrin interaction,in understanding in kindlin/integrin-related signaling in different cellular biological processes,but also provides new ideas for novel drug design and the treatment of related diseases.
文摘Deep neural network-based relational extraction research has made significant progress in recent years,andit provides data support for many natural language processing downstream tasks such as building knowledgegraph,sentiment analysis and question-answering systems.However,previous studies ignored much unusedstructural information in sentences that could enhance the performance of the relation extraction task.Moreover,most existing dependency-based models utilize self-attention to distinguish the importance of context,whichhardly deals withmultiple-structure information.To efficiently leverage multiple structure information,this paperproposes a dynamic structure attention mechanism model based on textual structure information,which deeplyintegrates word embedding,named entity recognition labels,part of speech,dependency tree and dependency typeinto a graph convolutional network.Specifically,our model extracts text features of different structures from theinput sentence.Textual Structure information Graph Convolutional Networks employs the dynamic structureattention mechanism to learn multi-structure attention,effectively distinguishing important contextual features invarious structural information.In addition,multi-structure weights are carefully designed as amergingmechanismin the different structure attention to dynamically adjust the final attention.This paper combines these featuresand trains a graph convolutional network for relation extraction.We experiment on supervised relation extractiondatasets including SemEval 2010 Task 8,TACRED,TACREV,and Re-TACED,the result significantly outperformsthe previous.
基金National Science and Technology Major Project of China (Grant Nos. 2009ZX02204- 006 and 2017ZX02101007-002)the National Natural Science Foundation of China (Grant Nos. 51435006 and 51675195).
文摘Nano-precision positioning stages are characterized by rigid-flexible coupling systems. The complex dynamic characteristics of mechanical structure of a stage, which are determined by structural and dynamic parameters, exert a serious influence on the accuracy of its motion and measurement. Systematic evaluation of such influence is essential for the design and improvement of stages. A systematic approach to modeling the dynamic accuracy of a nano-precision positioning stage is developed in this work by integrating a multi-rigid-body dynamic model of the mechanical system and measurement system models. The influence of structural and dynamic parameters, including aerostatic bearing configurations, motion plane errors, foundation vibrations, and positions of the acting points of driving forces, on dynamic accuracy is investigated by adopting the H-type configured stage as an example. The approach is programmed and integrated into a software framework that supports the dynamic design of nano-precision positioning stages. The software framework is then applied to the design of a nano-precision positioning stage used in a packaging lithography machine.
