Low-Rank Tensor Completion Based on Bivariate Equivalent Minimax-Concave Penalty

Low-rank tensor completion (LRTC) is an important problem in computer vision and machine learning. The minimax-concave penalty (MCP) function as a non-convex relaxation has achieved good results in the LRTC problem. To makes all the constant parameters of the MCP function as variables so that futherly improving the adaptability to the change of singular values in the LRTC problem, we propose the bivariate equivalent minimax-concave penalty (BEMCP) theorem. Applying the BEMCP theorem to tensor singular values leads to the bivariate equivalent weighted tensor $\Gamma$-norm (BEWTGN) theorem, and we analyze and discuss its corresponding properties. Besides, to facilitate the solution of the LRTC problem, we give the proximal operators of the BEMCP theorem and BEWTGN. Meanwhile, we propose a BEMCP model for the LRTC problem, which is optimally solved based on alternating direction multiplier (ADMM). Finally, the proposed method is applied to the data restorations of multispectral image (MSI), magnetic resonance imaging (MRI) and color video (CV) in real-world, and the experimental results demonstrate that it outperforms the state-of-arts methods.Comment: arXiv admin note: text overlap with arXiv:2109.1225

Accessing the transport properties of graphene and its multi-layers at high carrier density

We present a comparative study of high carrier density transport in mono-, bi-, and trilayer graphene using electric-double-layer transistors to continuously tune the carrier density up to values exceeding 10^{14} cm^{-2}. Whereas in monolayer the conductivity saturates, in bi- and trilayer flling of the higher energy bands is observed to cause a non-monotonic behavior of the conductivity, and a large increase in the quantum capacitance. These systematic trends not only show how the intrinsic high-density transport properties of graphene can be accessed by field-effect, but also demonstrate the robustness of ion-gated graphene, which is crucial for possible future applications.Comment: 4 figures, 4 page

Convergence Analysis of Particle Swarm Optimizer and Its Improved Algorithm Based on Velocity Differential Evolution

This paper presents an analysis of the relationship of particle velocity and convergence of the particle swarm optimization. Its premature convergence is due to the decrease of particle velocity in search space that leads to a total implosion and ultimately fitness stagnation of the swarm. An improved algorithm which introduces a velocity differential evolution (DE) strategy for the hierarchical particle swarm optimization (H-PSO) is proposed to improve its performance. The DE is employed to regulate the particle velocity rather than the traditional particle position in case that the optimal result has not improved after several iterations. The benchmark functions will be illustrated to demonstrate the effectiveness of the proposed method

SAPA: Similarity-Aware Point Affiliation for Feature Upsampling

We introduce point affiliation into feature upsampling, a notion that describes the affiliation of each upsampled point to a semantic cluster formed by local decoder feature points with semantic similarity. By rethinking point affiliation, we present a generic formulation for generating upsampling kernels. The kernels encourage not only semantic smoothness but also boundary sharpness in the upsampled feature maps. Such properties are particularly useful for some dense prediction tasks such as semantic segmentation. The key idea of our formulation is to generate similarity-aware kernels by comparing the similarity between each encoder feature point and the spatially associated local region of decoder features. In this way, the encoder feature point can function as a cue to inform the semantic cluster of upsampled feature points. To embody the formulation, we further instantiate a lightweight upsampling operator, termed Similarity-Aware Point Affiliation (SAPA), and investigate its variants. SAPA invites consistent performance improvements on a number of dense prediction tasks, including semantic segmentation, object detection, depth estimation, and image matting. Code is available at: https://github.com/poppinace/sapaComment: Accepted to NeurIPS 2022. Code is available at https://github.com/poppinace/sap

Geometry Aligned Variational Transformer for Image-conditioned Layout Generation

Layout generation is a novel task in computer vision, which combines the challenges in both object localization and aesthetic appraisal, widely used in advertisements, posters, and slides design. An accurate and pleasant layout should consider both the intra-domain relationship within layout elements and the inter-domain relationship between layout elements and the image. However, most previous methods simply focus on image-content-agnostic layout generation, without leveraging the complex visual information from the image. To this end, we explore a novel paradigm entitled image-conditioned layout generation, which aims to add text overlays to an image in a semantically coherent manner. Specifically, we propose an Image-Conditioned Variational Transformer (ICVT) that autoregressively generates various layouts in an image. First, self-attention mechanism is adopted to model the contextual relationship within layout elements, while cross-attention mechanism is used to fuse the visual information of conditional images. Subsequently, we take them as building blocks of conditional variational autoencoder (CVAE), which demonstrates appealing diversity. Second, in order to alleviate the gap between layout elements domain and visual domain, we design a Geometry Alignment module, in which the geometric information of the image is aligned with the layout representation. In addition, we construct a large-scale advertisement poster layout designing dataset with delicate layout and saliency map annotations. Experimental results show that our model can adaptively generate layouts in the non-intrusive area of the image, resulting in a harmonious layout design.Comment: To be published in ACM MM 202

Expression of Fbxo7 in haematopoietic progenitor cells cooperates with p53 loss to promote lymphomagenesis.

Fbxo7 is an unusual F box protein that augments D-type cyclin complex formation with Cdk6, but not Cdk4 or Cdk2, and its over-expression has been demonstrated to transform immortalised fibroblasts in a Cdk6-dependent manner. Here we present new evidence in vitro and in vivo on the oncogenic potential of this regulatory protein in primary haematopoietic stem and progenitor cells (HSPCs). Increasing Fbxo7 expression in HSPCs suppressed their colony forming ability in vitro, specifically decreasing CD11b (Mac1) expression, and these effects were dependent on an intact p53 pathway. Furthermore, increased Fbxo7 levels enhanced the proliferative capacity of p53 null HSPCs when they were grown in reduced concentrations of stem cell factor. Finally, irradiated mice reconstituted with p53 null, but not wild-type, HSPCs expressing Fbxo7 showed a statistically significant increase in the incidence of T cell lymphoma in vivo. These data argue that Fbxo7 negatively regulates the proliferation and differentiation of HSPCs in a p53-dependent manner, and that in the absence of p53, Fbxo7 expression can promote T cell lymphomagenesis

The emergence of global phase coherence from local pairing in underdoped cuprates

In conventional metal superconductors such as aluminum, the large number of weakly bounded Cooper pairs become phase coherent as soon as they start to form. The cuprate high critical temperature ($T_c$) superconductors, in contrast, belong to a distinctively different category. To account for the high $T_c$, the attractive pairing interaction is expected to be strong and the coherence length is short. Being doped Mott insulators, the cuprates are known to have low superfluid density, thus are susceptible to phase fluctuations. It has been proposed that pairing and phase coherence may occur separately in cuprates, and $T_c$ corresponds to the phase coherence temperature controlled by the superfluid density. To elucidate the microscopic processes of pairing and phase ordering in cuprates, here we use scanning tunneling microscopy to image the evolution of electronic states in underdoped $\rm Bi_2La_xSr_{2-x}CuO_{6+{\delta}}$. Even in the insulating sample, we observe a smooth crossover from the Mott insulator to superconductor-type spectra on small islands with chequerboard order and emerging quasiparticle interference patterns following the octet model. Each chequerboard plaquette contains approximately two holes, and exhibits a stripy internal structure that has strong influence on the superconducting features. Across the insulator to superconductor boundary, the local spectra remain qualitatively the same while the quasiparticle interferences become long-ranged. These results suggest that the chequerboard plaquette with internal stripes plays a crucial role on local pairing in cuprates, and the global phase coherence is established once its spatial occupation exceeds a threshold

Auto-Ubiquitination-Induced Degradation of MALT1-API2 Prevents BCL10 Destabilization in t(11;18)(q21;q21)-Positive MALT Lymphoma

BACKGROUND: The translocation t(11;18)(q21;q21) is the most frequent chromosomal aberration associated with MALT lymphoma and results in constitutive NF-kappaB activity via the expression of an API2-MALT1 fusion protein. The properties of the reciprocal MALT1-API2 were never investigated as it was reported to be rarely transcribed. PRINCIPAL FINDINGS: Our data indicate the presence of MALT1-API2 transcripts in the majority of t(11;18)(q21;q21)-positive MALT lymphomas. Based on the breakpoints in the MALT1 and API2 gene, the MALT1-API2 protein contains the death domain and one or both immunoglobulin-like domains of MALT1 (approximately 90% of cases)--mediating the possible interaction with BCL10--fused to the RING domain of API2. Here we show that this RING domain enables MALT1-API2 to function as an E3 ubiquitin ligase for BCL10, inducing its ubiquitination and proteasomal degradation in vitro. Expression of MALT1-API2 transcripts in t(11;18)(q21;q21)-positive MALT lymphomas was however not associated with a reduction of BCL10 protein levels. CONCLUSION: As we observed MALT1-API2 to be an efficient target of its own E3 ubiquitin ligase activity, our data suggest that this inherent instability of MALT1-API2 prevents its accumulation and renders a potential effect on MALT lymphoma development via destabilization of BCL10 unlikely