The time-dependent Jones Wilkins-Lee equation products for aluminized explosives. To obtain the of state （JWL-EOS） is applied to describe detonation state time-dependent JWL-EOS parameters, cylinder tests and underw...The time-dependent Jones Wilkins-Lee equation products for aluminized explosives. To obtain the of state （JWL-EOS） is applied to describe detonation state time-dependent JWL-EOS parameters, cylinder tests and underwater explosion experiments are performed. According to the result of the wall radial velocity in cylinder tests and the shock wave pressures in underwater explosion experiments, the time-dependent JWL-EOS parameters are determined by iterating these variables in AUTODYN hydroeode simulations until the experimental values are reproduced. In addition, to verify the reliability of the derived JWL-EOS parameters, the aluminized explosive experiment is conducted in concrete. The shock wave pressures in the affected concrete bodies are measured by using manganin pressure sensors, and the rod velocity is obtained by using a high-speed camera. Simultaneously, the shock wave pressure and the rod velocity are calculated by using the derived time-dependent JWL equation of state. The calculated results are in good agreement with the experimental data.展开更多
Taking a coupled system of wave equations with Dirichlet boundary controls as an example,by splitting and merging some synchronization groups of the state variables cor-responding to a given generalized synchronizatio...Taking a coupled system of wave equations with Dirichlet boundary controls as an example,by splitting and merging some synchronization groups of the state variables cor-responding to a given generalized synchronization matrix,this paper introduces two kinds of induced generalized exact boundary synchronizations to better determine its generalized exactly synchronizable states.展开更多
A decade ago mainstream molecular biologists regarded it impossible or biologically ill-motivated to understand the dynamics of complex biological phenomena, such as cancer genesis and progression, from a network pers...A decade ago mainstream molecular biologists regarded it impossible or biologically ill-motivated to understand the dynamics of complex biological phenomena, such as cancer genesis and progression, from a network perspective. Indeed, there are numerical difficulties even for those who were determined to explore along this direction. Undeterred, seven years ago a group of Chinese scientists started a program aiming to obtain quantitative connections between tumors and network dynamics. Many interesting results have been obtained. In this paper we wish to test such idea from a different angle: the connection between a normal biological process and the network dynamics. We have taken early myelopoiesis as our biological model. A standard roadmap for the cell-fate diversification during hematopoiesis has already been well established experimentally, yet little was known for its underpinning dynamical mechanisms. Compounding this difficulty there were additional experimental challenges, such as the seemingly conflicting hematopoietic roadmaps and the cell-fate inter-conversion events. With early myeloid cell-fate determination in mind, we constructed a core molecular endogenous network from well-documented gene regulation and signal transduction knowledge. Turning the network into a set of dynamical equations, we found computationally several structurally robust states. Those states nicely correspond to known cell phenotypes. We also found the states connecting those stable states.They reveal the developmental routes—how one stable state would most likely turn into another stable state. Such interconnected network among stable states enabled a natural organization of cell-fates into a multi-stable state landscape. Accordingly, both the myeloid cell phenotypes and the standard roadmap were explained mechanistically in a straightforward manner. Furthermore,recent challenging observations were also explained naturally. Moreover, the landscape visually enables a prediction of a pool of additional cell states and developmental routes, including the non-sequential and cross-branch transitions, which are testable by future experiments. In summary, the endogenous network dynamics provide an integrated quantitative framework to understand the heterogeneity and lineage commitment in myeloid progenitors.展开更多
基金Supported by the National Natural Science Foundation of China under Grant No 11172042
文摘The time-dependent Jones Wilkins-Lee equation products for aluminized explosives. To obtain the of state （JWL-EOS） is applied to describe detonation state time-dependent JWL-EOS parameters, cylinder tests and underwater explosion experiments are performed. According to the result of the wall radial velocity in cylinder tests and the shock wave pressures in underwater explosion experiments, the time-dependent JWL-EOS parameters are determined by iterating these variables in AUTODYN hydroeode simulations until the experimental values are reproduced. In addition, to verify the reliability of the derived JWL-EOS parameters, the aluminized explosive experiment is conducted in concrete. The shock wave pressures in the affected concrete bodies are measured by using manganin pressure sensors, and the rod velocity is obtained by using a high-speed camera. Simultaneously, the shock wave pressure and the rod velocity are calculated by using the derived time-dependent JWL equation of state. The calculated results are in good agreement with the experimental data.
文摘Taking a coupled system of wave equations with Dirichlet boundary controls as an example,by splitting and merging some synchronization groups of the state variables cor-responding to a given generalized synchronization matrix,this paper introduces two kinds of induced generalized exact boundary synchronizations to better determine its generalized exactly synchronizable states.
基金supported by the National Basic Research Program of China(2010CB529200)National Natural Science Foundation of China(91029738)
文摘A decade ago mainstream molecular biologists regarded it impossible or biologically ill-motivated to understand the dynamics of complex biological phenomena, such as cancer genesis and progression, from a network perspective. Indeed, there are numerical difficulties even for those who were determined to explore along this direction. Undeterred, seven years ago a group of Chinese scientists started a program aiming to obtain quantitative connections between tumors and network dynamics. Many interesting results have been obtained. In this paper we wish to test such idea from a different angle: the connection between a normal biological process and the network dynamics. We have taken early myelopoiesis as our biological model. A standard roadmap for the cell-fate diversification during hematopoiesis has already been well established experimentally, yet little was known for its underpinning dynamical mechanisms. Compounding this difficulty there were additional experimental challenges, such as the seemingly conflicting hematopoietic roadmaps and the cell-fate inter-conversion events. With early myeloid cell-fate determination in mind, we constructed a core molecular endogenous network from well-documented gene regulation and signal transduction knowledge. Turning the network into a set of dynamical equations, we found computationally several structurally robust states. Those states nicely correspond to known cell phenotypes. We also found the states connecting those stable states.They reveal the developmental routes—how one stable state would most likely turn into another stable state. Such interconnected network among stable states enabled a natural organization of cell-fates into a multi-stable state landscape. Accordingly, both the myeloid cell phenotypes and the standard roadmap were explained mechanistically in a straightforward manner. Furthermore,recent challenging observations were also explained naturally. Moreover, the landscape visually enables a prediction of a pool of additional cell states and developmental routes, including the non-sequential and cross-branch transitions, which are testable by future experiments. In summary, the endogenous network dynamics provide an integrated quantitative framework to understand the heterogeneity and lineage commitment in myeloid progenitors.
