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The use of natural acellular matrices could solve the issues that have been encountered so far with animal studies for lung regeneration, since in an optimally decellularized lung the hierarchical pulmonary network and alveolus-capillary junctions would be preserved.
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Applying the standard low-rank model on the gene disease associations matrix P ≈ WH T, we could solve the following optimization problem: (1) min W ∈ ℝ N g × k, H ∈ ℝ N d × k ∑ (i, j ) ∈ Ω (P i j − W i T H j ) 2 + 1 2 λ (‖ W ‖ F 2 + ‖ H ‖ F 2 ), where λ is a regularization parameter, W i and H j denote the latent factor for the i-th gene and the j-th disease, respectively.
It should be noted that for singular or nearly singular problems, one could solve the LS problem by using singular-value filtering on the design matrix, which is the most robust technique.
"I could solve problems.
They could solve this in a second.
A VAT could solve that problem.
It could solve her paparazzi problem forever.
Who could solve this problem?
Technology could solve this hurdle, too.
He implied that he could solve it.
A biometric advance could solve that".
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com