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In this paper we report on our efforts to reproduce results presented in a paper titled "A Parallel Connectivity Algorithm for de Bruijn Graphs in Metagenomic Applications," which shows that the parallel graph-based algorithm developed scales to over a thousand cores, and runs faster than traditional Breadth First Search algorithms.
The large difference in the amplitude and washout of the two components again implicates parallel connectivity.
A more simple parallel connectivity model is therefore proposed here for the kidney.
Correlations between various binding parameters support the concept of the parallel connectivity compartmental model.
This observation further corroborates the robustness of the parallel connectivity model.
Due to lack of a transfer barrier in the kidneys, a parallel connectivity model was applied for curve fitting and parameter estimation.
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These two connectivity maps are generated by executing the IFT with anti-parallel connectivity functions: V_{o}^{notparallel}(a)=displaystylemax_{pi_{a}inPi(G,a)}{f_{min}^{notparallel:S_{o} }(pi_{a}) } (9).
Thus, we suggest that postponing distance-dependent elimination of SAC SAC connections until after eye-opening allows both the dense connectivity needed for wave propagation and the selective anti-parallel connectivity needed for direction selectivity.
It is, therefore, likely that this decrease in spine number results in altered synaptic plasticity, possibly leading to decreased parallel fiber connectivity.
This enables chemical similarity to be explored and extended in parallel with IK connectivity.
In the initial stage of the creative design of some specific mechanisms such as the parallel manipulator, the connectivity between the base and the end-effector must satisfy the requirement.
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