https://www.selleckchem.com/pr....oducts/cx-4945-silmi
Here, we propose a novel neural network architecture that simultaneously learns and uses the population-level statistics of the spatial transformations to regularize the neural networks for unsupervised image registration. This regularization is in the form of a bottleneck autoencoder, which learns and adapts to the population of transformations required to align input images by encoding the transformations to a low dimensional manifold. The proposed architecture produces deformation fields that describe the population-lev

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Ni-rich layered cathodes suffer detrimental structural changes due to irreversible phase transformation (IPT). Precisely surface structural reconstruction through foreign element doping is a potential method to alleviate IPT propagation. The structure of surface reconstructed layer is greatly determined by the foreign element content and species. Herein, small doses of Ti and Al were co-substituted in LiNi0.92Co0.08O2 to synergistically regulate the surface reductive Ni distribution, consequently constructing thin rock salt phase at the