16 research outputs found
Graph Signal Restoration Using Nested Deep Algorithm Unrolling
Graph signal processing is a ubiquitous task in many applications such as
sensor, social, transportation and brain networks, point cloud processing, and
graph neural networks. Graph signals are often corrupted through sensing
processes, and need to be restored for the above applications. In this paper,
we propose two graph signal restoration methods based on deep algorithm
unrolling (DAU). First, we present a graph signal denoiser by unrolling
iterations of the alternating direction method of multiplier (ADMM). We then
propose a general restoration method for linear degradation by unrolling
iterations of Plug-and-Play ADMM (PnP-ADMM). In the second method, the unrolled
ADMM-based denoiser is incorporated as a submodule. Therefore, our restoration
method has a nested DAU structure. Thanks to DAU, parameters in the proposed
denoising/restoration methods are trainable in an end-to-end manner. Since the
proposed restoration methods are based on iterations of a (convex) optimization
algorithm, the method is interpretable and keeps the number of parameters small
because we only need to tune graph-independent regularization parameters. We
solve two main problems in existing graph signal restoration methods: 1)
limited performance of convex optimization algorithms due to fixed parameters
which are often determined manually. 2) large number of parameters of graph
neural networks that result in difficulty of training. Several experiments for
graph signal denoising and interpolation are performed on synthetic and
real-world data. The proposed methods show performance improvements to several
existing methods in terms of root mean squared error in both tasks
Interaction of Relaxin-Like Gonad-Stimulating Substance with Ovarian Follicle Cells of the Starfish Asterina pectinifera
Distribution of Contrast Medium Epidurally Injected at Thoracic and Lumbar Vertebral Segments
Skp2-Mediated Degradation of p27 Regulates Progression into Mitosis
AbstractAlthough Skp2 has been thought to mediate the degradation of p27 at the G1-S transition, Skp2−/− cells exhibit accumulation of p27 in S-G2 phase with overreplication. We demonstrate that Skp2−/−p27−/− mice do not exhibit the overreplication phenotype, suggesting that p27 accumulation is required for its development. Hepatocytes of Skp2−/− mice entered the endoduplication cycle after mitogenic stimulation, whereas this phenotype was not apparent in Skp2−/−p27−/− mice. Cdc2-associated kinase activity was lower in Skp2−/− cells than in wild-type cells, and a reduction in Cdc2 activity was sufficient to induce overreplication. The lack of p27 degradation in G2 phase in Skp2−/− cells may thus result in suppression of Cdc2 activity and consequent inhibition of entry into M phase. These data suggest that p27 proteolysis is necessary for the activation of not only Cdk2 but also Cdc2, and that Skp2 contributes to regulation of G2-M progression by mediating the degradation of p27