Tolerance After Liver Transplantation: Where Are We?

info:eu-repo/semantics/publishedVersio

Charge breaking bounds in the Zee model

We study the possibility that charge breaking minima occur in the Zee model. We reach very different conclusions from those attained in simpler, two Higgs doublet models, and the reason for this is traced back to the existence of cubic terms in the potential. A scan of the Zee model's parameter space shows that CB is restricted to a narrow region of values of the parameters

Neutral minima in two-Higgs doublet models

We study the neutral minima of two-Higgs doublet models, showing that these potentials can have at least two such minima with different depths. We analyse the phenomenology of these minima for the several types of two-Higgs doublet potentials, where CP is explicitly broken, spontaneously broken or preserved. We discover that it is possible to have a neutral minimum in these potentials where the masses of the known particles have their standard values, with another deeper minimum where those same particles acquire different masses.Comment: 20 pages, 3 figure

Energy-aware dynamic pricing model for cloud environments

Energy consumption is a critical operational cost for Cloud providers. However, as commercial providers typically use fixed pricing schemes that are oblivious about the energy costs of running virtual machines, clients are not charged according to their actual energy impact. Some works have proposed energy-aware cost models that are able to capture each client’s real energy usage. However, those models cannot be naturally used for pricing Cloud services, as the energy cost is calculated after the termination of the service, and it depends on decisions taken by the provider, such as the actual placement of the client’s virtual machines. For those reasons, a client cannot estimate in advance how much it will pay. This paper presents a pricing model for virtualized Cloud providers that dynamically derives the energy costs per allocation unit and per work unit for each time period. They account for the energy costs of the provider’s static and dynamic energy consumption by sharing out them according to the virtual resource allocation and the real resource usage of running virtual machines for the corresponding time period. Newly arrived clients during that period can use these costs as a baseline to calculate their expenses in advance as a function of the number of requested allocation and work units. Our results show that providers can get comparable revenue to traditional pricing schemes, while offering to the clients more proportional prices than fixed-price models.Peer ReviewedPostprint (author's final draft