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Whereas benign apoptotic cells (e.g. heart muscle cells of myocarditis patients) execute apoptosis, tumor cells apparently block the endonuclease driven execution of apoptosis by expression of proteins inhibiting endonucleases [ 4, 5] or other apoptosis executing proteins.
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We must now add to this list the pros and cons of a cloud-centric, model-driven execution environment.
Apps that run on model-driven execution platforms also participate in all the advantages of the cloud, including horizontal scalability and pay-as-you-go, pay-for-what-you-use pricing.
The aPaaS distinction is unclear as well, as some code generation vendors provide cloud-based development environments, while some of the cloud-centric model-driven execution platforms have on-premises options.
Depending on the specifics of the platform, code generation may also create higher performance applications than the model-driven execution platform alternative, as they may compile down into executable bytecode that runs more quickly than the alternative's interpreted approach.
In the other corner of this boxing match are vendors that take a model-driven execution platform approach.
Section 1 elaborates on the architecture of the PaaSHopper middleware with respect to portability, interoperability, and policy-driven execution and storage.
We evaluate recently introduced schedulers for event-driven execution and utilization-driven dynamic multi-grain parallelization on Cell.
We schedule tasks in data-driven execution according to coherent data, propose an adaptive ray compaction to eliminate inactive threads, maintain task efficiency of threads in a warp, and design two heuristics to decrease the compaction cost.
The difference is in the execution, as model-driven execution platforms actually run the models.
Model-driven execution platforms typically run in a public cloud, although a few vendors offer private cloud and on-premises versions of their platforms as well.
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