Bayesian Robust Tensor Ring Model for Incomplete Multiway Data

Robust tensor completion (RTC) aims to recover a low-rank tensor from its incomplete observation with outlier corruption. The recently proposed tensor ring (TR) model has demonstrated superiority in solving the RTC problem. However, the existing methods either require a pre-assigned TR rank or aggressively pursue the minimum TR rank, thereby often leading to biased solutions in the presence of noise. In this paper, a Bayesian robust tensor ring decomposition (BRTR) method is proposed to give more accurate solutions to the RTC problem, which can avoid exquisite selection of the TR rank and penalty parameters. A variational Bayesian (VB) algorithm is developed to infer the probability distribution of posteriors. During the learning process, BRTR can prune off slices of core tensor with marginal components, resulting in automatic TR rank detection. Extensive experiments show that BRTR can achieve significantly improved performance than other state-of-the-art methods

QARV: Quantization-Aware ResNet VAE for Lossy Image Compression

This paper addresses the problem of lossy image compression, a fundamental problem in image processing and information theory that is involved in many real-world applications. We start by reviewing the framework of variational autoencoders (VAEs), a powerful class of generative probabilistic models that has a deep connection to lossy compression. Based on VAEs, we develop a novel scheme for lossy image compression, which we name quantization-aware ResNet VAE (QARV). Our method incorporates a hierarchical VAE architecture integrated with test-time quantization and quantization-aware training, without which efficient entropy coding would not be possible. In addition, we design the neural network architecture of QARV specifically for fast decoding and propose an adaptive normalization operation for variable-rate compression. Extensive experiments are conducted, and results show that QARV achieves variable-rate compression, high-speed decoding, and a better rate-distortion performance than existing baseline methods. The code of our method is publicly accessible at https://github.com/duanzhiihao/lossy-vaeComment: Technical repor

Genome-wide identification of the TGA genes in common bean (Phaseolus vulgaris) and revealing their functions in response to Fusarium oxysporum f. sp. phaseoli infection

Fusarium wilt, which affects common bean all across the world, is caused by Fusarium oxysporum f. sp. Phaseoli (Fop). It is necessary to have functional genes in response to Fop infection because they might be used to manage disease. As a crucial regulator, TGA-binding transcription factor (TGA) is engaged in the defense mechanism of plants against pathogens. The role of TGA regulators in common bean in response to Fop infection, however, has not been documented. Hence, we performed genome-wide identified and characterized eight TGA genes in common bean. In this study, eight PvTGA genes were distributed on six chromosomes and classified into four subgroups. The PvTGA genes have the same conserved bZIP and DOG1 domains, but there are specific sequence structures in different PvTGAs. Phylogenetic and synteny analysis explained that PvTGA gene has a close genetic relationship with legume TGAs and that PvTGA03 and PvTGA05 may play an important role in evolution. Transcriptome data explained that expression levels of PvTGA genes showed diversity in different tissues. After Fop inoculation, the expression levels of PvTGA03 and PvTGA07 were significantly different between resistant and susceptible genotypes. Under SA treatment, the expression levels of PvTGA03, PvTGA04, PvTGA06, PvTGA07 and PvTGA08 were significantly different. These results imply that PvTGA03 and PvTGA07 play key roles in SA-mediated resistance to Fusarium wilt. Together, these findings advance knowledge of the PvTGA gene family in common bean and will help future studies aimed at reducing Fusarium wilt

ELUCID. VII. Using constrained hydro simulations to explore the gas component of the cosmic web

Using reconstructed initial conditions in the Sloan Digital Sky Survey (SDSS) survey volume, we carry out constrained hydrodynamic simulations in three regions representing different types of the cosmic web: the Coma cluster of galaxies; the SDSS Great Wall; and a large low-density region at z ∼ 0.05. These simulations, which include star formation and stellar feedback but no active galactic nucleus formation and feedback, are used to investigate the properties and evolution of intergalactic and intracluster media. About half of the warm-hot intergalactic gas is associated with filaments in the local cosmic web. Gas in the outskirts of massive filaments and halos can be heated significantly by accretion shocks generated by mergers of filaments and halos, respectively, and there is a tight correlation between the gas temperature and the strength of the local tidal field. The simulations also predict some discontinuities associated with shock fronts and contact edges, which can be tested using observations of the thermal Sunyaev-Zel’dovich effect and X-rays. A large fraction of the sky is covered by Lyα and O vi absorption systems, and most of the O vi systems and low-column-density H i systems are associated with filaments in the cosmic web. The constrained simulations, which follow the formation and heating history of the observed cosmic web, provide an important avenue to interpret observational data. With full information about the origin and location of the cosmic gas to be observed, such simulations can also be used to develop observational strategie

Genome-wide analysis reveals regulatory mechanisms and expression patterns of TGA genes in peanut under abiotic stress and hormone treatments

IntroductionThe TGA transcription factors, plays a crucial role in regulating gene expression. In cultivated peanut (Arachis hypogaea), which faces abiotic stress challenges, understanding the role of TGAs is important.MethodsIn this study, we conducted a comprehensive in analysis of the TGA gene family in peanut to elucidate their regulatory mechanisms and expression patterns under abiotic stress and hormone treatments. Furthermore, functional studies on the representative AhTGA gene in peanut cultivars were conducted using transgenic Arabidopsis and soybean hair roots.ResultsThe genome-wide analysis revealed that a total of 20 AhTGA genes were identified and classified into five subfamilies. Collinearity analysis revealed that AhTGA genes lack tandem duplication, and their amplification in the cultivated peanut genome primarily relies on the whole-genome duplication of the diploid wild peanut to form tetraploid cultivated peanut, as well as segment duplication between the A and B subgenomes. Promoter and Protein-protein interaction analysis identified a wide range of cis-acting elements and potential interacting proteins associated with growth and development, hormones, and stress responses. Expression patterns of AhTGA genes in different tissues, under abiotic stress conditions for low temperature and drought, and in response to hormonal stimuli revealed that seven AhTGA genes from groups I (AhTGA04, AhTGA14 and AhTGA20) and II (AhTGA07, AhTGA11, AhTGA16 and AhTGA18) are involved in the response to abiotic stress and hormonal stimuli. The hormone treatment results indicate that these AhTGA genes primarily respond to the regulation of jasmonic acid and salicylic acid. Overexpressing AhTGA11 in Arabidopsis enhances resistance to cold and drought stress by increasing antioxidant activities and altering endogenous hormone levels, particularly ABA, SA and JA.DiscussionThe AhTGA genes plays a crucial role in hormone regulation and stress response during peanut growth and development. The findings provide insights into peanut's abiotic stress tolerance mechanisms and pave the way for future functional studies

The Tsai-Wu failure criterion rationalised in the context of UD composites

This paper is to rationalise the empirical aspect of the Tsai-Wu failure criterion in the context of UD composites associated with the determination of the interactive strength property F12 based on the analytic geometry. It reveals that the condition of closed failure envelope cannot be satisfied by all UD composites and hence the restriction should be abandoned. Depending on the way the failure envelope opens, UD composites can be classified into two categories. (a) F12 can be determined uniquely using the conventional strength properties with an additional assumption that the material exhibits very high or infinite strength under triaxial compression at a specific stress ratio; or (b) The Tsai-Wu criterion leads to one of the two scenarios: either allowing infinite strength for an in-plane stress state or allowing infinite strength under triaxial stresses involving tension along fibres