Krox-20, a C2H2-type zinc-finger transcription factor, plays an important role in rhombomere development. This study reveals that the Krox-20 null mutation impacts the development of mesencephalic trigeminal (Me5) neurons, a cell group traditionally thought to emerge from the mesencephalon. Based on cell counting studies, we show that Krox-20 null mutants have twice as many Me5 neurons relative to wildtypes at E15, but by birth have half the number of Me5 cells as wildtypes. TUNEL studies reveal a period of increased apoptosis from E17-P0 in mutants. The mutation does not result in differences in Me5 cell size, morphology, gene expression or peripheral projection patterns between genotypes, as demonstrated by retrograde tracing and Brn3a immunohistochemistry. The data suggest that Krox-20 regulates the period and extent of Me5 apoptosis, impacting the final number of Me5 neurons. The loss of Me5 in Krox-20–/– mice may highlight species-specific differences in the origin of these cells.
International audienceThe Virtual Machine Mapping Problem (VMMP) arise by the development of cloud computing. Focusing on a novel approach for cloud broker model in multi-clouds environment, we present a new model to deal with VMMP that takes into account the uncertainty of the VM execution time, hence allowing to obtain robust assignment solutions. The uncertainty of the VM execution time is modeled by (i) relying on a truncated normal distribution for constructing mapping instances, and (ii) by using the expected value of the generating truncated normal distribution. The proposed methods, for the optimization for the VMMP, are conducted on the Grid5000 in order to bring a detailed results comparison between the obtained results from the experimental study with different benchmarks
In this paper, we present a new energy efficiency model and architecture for cloud management based on a prediction model with Gaussian Mixture Models. The methodology relies on a distributed agent model and the validation will be performed on OpenStack. This paper intends to be a position paper, the implementation and experimental run will be conducted in future work. The design concept leverages the prediction model by providing a full architecture binding the resource demands, the predictions and the actual cloud environment (Openstack). The prediction analysis feeds the power-aware agents that run on the compute nodes in order to turn the nodes into sleep mode when the load state is low to reduce the energy consumption of the data center.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.