We present in this paper several efficient numerical schemes for the magneto-hydrodynamic(MHD)equations. These semi-discretized(in time) schemes are based on the standard and rotational pressure-correction schemes for...We present in this paper several efficient numerical schemes for the magneto-hydrodynamic(MHD)equations. These semi-discretized(in time) schemes are based on the standard and rotational pressure-correction schemes for the Navier-Stokes equations and do not involve a projection step for the magnetic field. We show that these schemes are unconditionally energy stable, present an effective algorithm for their fully discrete versions and carry out demonstrative numerical experiments.展开更多
The evolutionary dynamics of behavioral traits reflect phenotypic and genetic changes. Methodological difficulties in analyzing the genetic dynamics of complex traits have left open questions on the mechanisms that ha...The evolutionary dynamics of behavioral traits reflect phenotypic and genetic changes. Methodological difficulties in analyzing the genetic dynamics of complex traits have left open questions on the mechanisms that have shaped complex beha- viors and cognitive abilities. A strategy to investigate the change of behavior across generations is to assume that genetic con- straints have a negligible role in evolution （the phenotypic gambit） and focus on the phenotype as a proxy for genetic evolution. Empirical evidence and technologic advances in genomics question the choice of neglecting the genetic underlying the dynamics of behavioral evolution. I first discuss the relevance of genetic factors - e.g. genetic variability, genetic linkage, gene interactions - in shaping evolution, showing the importance of taking genetic factors into account when dealing with evolutionary dynamics. I subsequently describe the recent advancements in genetics and genomics that make the investigation of the ongoing evolutionary process of behavioral traits finally attainable. In particular, by applying genomic resequencing to experimental evolution - a me- thod called Evolve ＆ Resequence - it is possible to monitor at the same time phenotypic and genomie changes in populations exposed to controlled selective pressures. Experimental evolution of associative learning, a well-known trait that promptly re- sponds to selection, is a convenient model to illustrate this approach applied to behavior and cognition. Taking into account the recent achievements of the field, I discuss how to design and conduct an effective Evolve ＆ Resequence study on associative learning in Drosophila. By integrating phenotypic and genomic data in the investigation of evolutionary dynamics, new insights can be gained on longstanding questions such as the modularity of mind and its evolution .展开更多
基金supported by National Science Foundation of USA (Grant No. DMS1419053)
文摘We present in this paper several efficient numerical schemes for the magneto-hydrodynamic(MHD)equations. These semi-discretized(in time) schemes are based on the standard and rotational pressure-correction schemes for the Navier-Stokes equations and do not involve a projection step for the magnetic field. We show that these schemes are unconditionally energy stable, present an effective algorithm for their fully discrete versions and carry out demonstrative numerical experiments.
文摘The evolutionary dynamics of behavioral traits reflect phenotypic and genetic changes. Methodological difficulties in analyzing the genetic dynamics of complex traits have left open questions on the mechanisms that have shaped complex beha- viors and cognitive abilities. A strategy to investigate the change of behavior across generations is to assume that genetic con- straints have a negligible role in evolution （the phenotypic gambit） and focus on the phenotype as a proxy for genetic evolution. Empirical evidence and technologic advances in genomics question the choice of neglecting the genetic underlying the dynamics of behavioral evolution. I first discuss the relevance of genetic factors - e.g. genetic variability, genetic linkage, gene interactions - in shaping evolution, showing the importance of taking genetic factors into account when dealing with evolutionary dynamics. I subsequently describe the recent advancements in genetics and genomics that make the investigation of the ongoing evolutionary process of behavioral traits finally attainable. In particular, by applying genomic resequencing to experimental evolution - a me- thod called Evolve ＆ Resequence - it is possible to monitor at the same time phenotypic and genomie changes in populations exposed to controlled selective pressures. Experimental evolution of associative learning, a well-known trait that promptly re- sponds to selection, is a convenient model to illustrate this approach applied to behavior and cognition. Taking into account the recent achievements of the field, I discuss how to design and conduct an effective Evolve ＆ Resequence study on associative learning in Drosophila. By integrating phenotypic and genomic data in the investigation of evolutionary dynamics, new insights can be gained on longstanding questions such as the modularity of mind and its evolution .
