Interaction-driven topological phase diagram of twisted bilayer MoTe2_2

Twisted bilayer MoTe$_2$ is a promising platform to investigate the interplay between topology and many-body interaction. We present a theoretical study of its interaction-driven quantum phase diagrams based on a three-orbital model, which can be viewed as a generalization of the Kane-Mele-Hubbard model with an additional orbital and realistic Coulomb repulsion. We predict a cascade of phase transitions tuned by the twist angle $\theta$. At the hole filling factor $\nu=1$ (one hole per moir\'e unit cell), the ground state can be in the multiferroic phase with coexisting spontaneous layer polarization and magnetism, the quantum anomalous Hall phase, and finally the topologically trivial magnetic phases, as $\theta$ increases from $1.5^{\circ}$ to $5^{\circ}$. At $\nu=2$, the ground state can have a second-order phase transition between an antiferromagnetic phase and the quantum spin Hall phase as $\theta$ passes through a critical value. The dependence of the phase boundaries on model parameters such as the gate-to-sample distance, the dielectric constant, and the moir\'e potential amplitude is examined. The predicted phase diagrams can guide the search for topological phases in twisted transition metal dichalcogenide homobilayers.Comment: 12 pages, 7 figures. Comments and Collaborations are Welcome

Identification and profiling of microRNA between back and belly Skin in Rex rabbits (Oryctolagus cuniculus)

[EN] Skin is an important trait for Rex rabbits and skin development is influenced by many processes, including hair follicle cycling, keratinocyte differentiation and formation of coat colour and skin morphogenesis. We identified differentially expressed microRNAs (miRNAs) between the back and belly skin in Rex rabbits. In total, 211 miRNAs (90 upregulated miRNAs and 121 downregulated miRNAs) were identified with a |log2 (fold change)|>1 and P-value<0.05. Using target gene prediction for the miRNAs, differentially expressed predicted target genes were identified and the functional enrichment and signalling pathways of these target genes were processed to reveal their biological functions. A number of differentially expressed miRNAs were found to be involved in regulation of the cell cycle, skin epithelium differentiation, keratinocyte proliferation, hair follicle development and melanogenesis. In addition, target genes regulated by miRNAs play key roles in the activities of the Hedgehog signalling pathway, Wnt signalling pathway, Osteoclast differentiation and MAPK pathway, revealing mechanisms of skin development. Nine candidate miRNAs and 5 predicted target genes were selected for verification of their expression by quantitative reverse transcription polymerase chain reaction. A regulation network of miRNA and their target genes was constructed by analysing the GO enrichment and signalling pathways. Further studies should be carried out to validate the regulatory relationships between candidate miRNAs and their target genes.This study was supported by the Modern Agricultural Industrial System Special Funding (CARS-44-A-1), the Priority Academic Programme Development of Jiangsu Higher Education Institutions (2014-134) and the General Programme of Natural Science Foundation of the Higher Education Institutions of Jiangsu Province (16KJB230001).Zhao, B.; Chen, Y.; Mu, L.; Hu, S.; Wu, X. (2018). Identification and profiling of microRNA between back and belly Skin in Rex rabbits (Oryctolagus cuniculus). World Rabbit Science. 26(2):179-190. https://doi.org/10.4995/wrs.2018.7058SWORD179190262Adamidi C. 2008. Discovering microRNAs from deep sequencing data using miRDeep. Nature Biotechnol., 26: 407-415. https://doi.org/10.1038/nbt1394Adijanto J., Castorino J.J., Wang Z.X., Maminishkis A., Grunwald G.B., Philp N.J. 2012. 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Characterisation and functional analysis of the WIF1 gene and its role in hair follicle growth and development of the Angora rabbit

[EN] Growth and development of hair follicles (HF) is a complex and dynamic process in most mammals. As HF growth and development regulate rabbit wool yield, exploring the role of genes involved in HF growth and development may be relevant. In this study, the coding sequence of the Angora rabbit (Oryctolagus cuniculus) WIF1 gene was cloned. The length of the coding region sequence was found to be 1140 bp, which encodes 379 amino acids. Bioinformatics analysis indicated that the WIF1 protein was unstable, hydrophilic and located in the extracellular region, contained a putative signal peptide and exhibited a high homology in different mammals. Moreover, WIF1 was significantly downregulated in the high wool production in the Angora rabbit group. Overexpression and knockdown studies revealed that WIF1 regulates HF growth and development-related genes and proteins, such as LEF1 and CCND1. WIF1 activated β-catenin/TCF transcriptional activity, promoted cell apoptosis and inhibited cellular proliferation. These results indicate that WIF1 might be important for HF development. This study, therefore, provides a theoretical foundation for investigating WIF1 in HF growth and development.This research was funded by This research was funded by National Natural Science Foundation of China (Grant No. 32102529), China Agriculture Research System of MOF and MARA (CARS-43-A-1).Zhao, B.; Li, J.; Zhang, X.; Bao, Z.; Chen, Y.; Wu, X. (2022). Characterisation and functional analysis of the WIF1 gene and its role in hair follicle growth and development of the Angora rabbit. World Rabbit Science. 30(3):209-218. https://doi.org/10.4995/wrs.2022.1735320921830

Hierarchical Dense Correlation Distillation for Few-Shot Segmentation-Extended Abstract

Few-shot semantic segmentation (FSS) aims to form class-agnostic models segmenting unseen classes with only a handful of annotations. Previous methods limited to the semantic feature and prototype representation suffer from coarse segmentation granularity and train-set overfitting. In this work, we design Hierarchically Decoupled Matching Network (HDMNet) mining pixel-level support correlation based on the transformer architecture. The self-attention modules are used to assist in establishing hierarchical dense features, as a means to accomplish the cascade matching between query and support features. Moreover, we propose a matching module to reduce train-set overfitting and introduce correlation distillation leveraging semantic correspondence from coarse resolution to boost fine-grained segmentation. Our method performs decently in experiments. We achieve 50.0% mIoU on COCO dataset one-shot setting and 56.0% on five-shot segmentation, respectively. The code will be available on the project website. We hope our work can benefit broader industrial applications where novel classes with limited annotations are required to be decently identified.Comment: Accepted to CVPR 2023 VISION Workshop, Oral. The extended abstract of Hierarchical Dense Correlation Distillation for Few-Shot Segmentation. arXiv admin note: substantial text overlap with arXiv:2303.1465

GroupContrast: Semantic-aware Self-supervised Representation Learning for 3D Understanding

Self-supervised 3D representation learning aims to learn effective representations from large-scale unlabeled point clouds. Most existing approaches adopt point discrimination as the pretext task, which assigns matched points in two distinct views as positive pairs and unmatched points as negative pairs. However, this approach often results in semantically identical points having dissimilar representations, leading to a high number of false negatives and introducing a "semantic conflict" problem. To address this issue, we propose GroupContrast, a novel approach that combines segment grouping and semantic-aware contrastive learning. Segment grouping partitions points into semantically meaningful regions, which enhances semantic coherence and provides semantic guidance for the subsequent contrastive representation learning. Semantic-aware contrastive learning augments the semantic information extracted from segment grouping and helps to alleviate the issue of "semantic conflict". We conducted extensive experiments on multiple 3D scene understanding tasks. The results demonstrate that GroupContrast learns semantically meaningful representations and achieves promising transfer learning performance.Comment: CVPR 202

Fabrication of equiatomic FeCo alloy parts with high magnetic properties by fields activated sintering

Electrical field activated sintering technology combined with micro-forming (Micro-FAST), as a new rapid powder sintering/forming method, is used to fabricate FeCo alloy parts. The successfully prepared FeCo parts have a high saturation of 214.11 emu/g and a low coercivity of 16 Oe, and these values are 20% and 10% higher than that of commercially available FeCoV alloy parts on the saturation and coercivity respectively. During the sintering process, the high current application shortened the densification time and enhanced the uniformity of the microstructure significantly. The grain sizes of FeCo alloys were in a range of 5–6 mm, and good isotropy was also shown. The low angle grain boundary (LAGB) accounted for more than 30% and the low angle misorientation accounted for more than 30% of the sample parts. Furthermore, the formation of the nano B2 phase was promoted during the Micro-FAST, and the size of the B2 phase was about 5 nm. The coherent interface between a and B2 was conducive for reducing the coercivity. As a consequence, the outstanding microstructure formed by Micro-FAST makes the FeCo alloys have high saturation and low coercivity

Pulmonary neuroendocrine cells: Crucial players in respiratory function and airway-nerve communication

Pulmonary neuroendocrine cells (PNECs) are unique airway epithelial cells that blend neuronal and endocrine functions, acting as key sensors in the lung. They respond to environmental stimuli like allergens by releasing neuropeptides and neurotransmitters. PNECs stand out as the only lung epithelial cells innervated by neurons, suggesting a significant role in airway-nerve communication via direct neural pathways and hormone release. Pathological conditions such as asthma are linked to increased PNECs counts and elevated calcitonin gene-related peptide (CGRP) production, which may affect neuroprotection and brain function. CGRP is also associated with neurodegenerative diseases, including Parkinson’s and Alzheimer’s, potentially due to its influence on inflammation and cholinergic activity. Despite their low numbers, PNECs are crucial for a wide range of functions, highlighting the importance of further research. Advances in technology for producing and culturing human PNECs enable the exploration of new mechanisms and cell-specific responses to targeted therapies for PNEC-focused treatments

Chromosome-level genome assembly of a high-altitude-adapted frog (Rana kukunoris) from the Tibetan plateau provides insight into amphibian genome evolution and adaptation

Background The high-altitude-adapted frog Rana kukunoris, occurring on the Tibetan plateau, is an excellent model to study life history evolution and adaptation to harsh high-altitude environments. However, genomic resources for this species are still underdeveloped constraining attempts to investigate the underpinnings of adaptation. Results The R. kukunoris genome was assembled to a size of 4.83 Gb and the contig N50 was 1.80 Mb. The 6555 contigs were clustered and ordered into 12 pseudo-chromosomes covering similar to 93.07% of the assembled genome. In total, 32,304 genes were functionally annotated. Synteny analysis between the genomes of R. kukunoris and a low latitude species Rana temporaria showed a high degree of chromosome level synteny with one fusion event between chr11 and chr13 forming pseudo-chromosome 11 in R. kukunoris. Characterization of features of the R. kukunoris genome identified that 61.5% consisted of transposable elements and expansions of gene families related to cell nucleus structure and taste sense were identified. Ninety-five single-copy orthologous genes were identified as being under positive selection and had functions associated with the positive regulation of proteins in the catabolic process and negative regulation of developmental growth. These gene family expansions and positively selected genes indicate regions for further interrogation to understand adaptation to high altitude. Conclusions Here, we reported a high-quality chromosome-level genome assembly of a high-altitude amphibian species using a combination of Illumina, PacBio and Hi-C sequencing technologies. This genome assembly provides a valuable resource for subsequent research on R. kukunoris genomics and amphibian genome evolution in general.Peer reviewe

SciMMIR:Benchmarking Scientific Multi-modal Information Retrieval

Multi-modal information retrieval (MMIR) is a rapidly evolving field, where significant progress, particularly in image-text pairing, has been made through advanced representation learning and cross-modality alignment research. However, current benchmarks for evaluating MMIR performance in image-text pairing within the scientific domain show a notable gap, where chart and table images described in scholarly language usually do not play a significant role. To bridge this gap, we develop a specialised scientific MMIR (SciMMIR) benchmark by leveraging open-access paper collections to extract data relevant to the scientific domain. This benchmark comprises 530K meticulously curated image-text pairs, extracted from figures and tables with detailed captions in scientific documents. We further annotate the image-text pairs with two-level subset-subcategory hierarchy annotations to facilitate a more comprehensive evaluation of the baselines. We conducted zero-shot and fine-tuning evaluations on prominent multi-modal image-captioning and visual language models, such as CLIP and BLIP. Our analysis offers critical insights for MMIR in the scientific domain, including the impact of pre-training and fine-tuning settings and the influence of the visual and textual encoders. All our data and checkpoints are publicly available at https://github.com/Wusiwei0410/SciMMIR