Topological Quantum Phase Transition in 5dd Transition Metal Oxide Na2_2IrO3_3

We predict a quantum phase transition from normal to topological insulators in the 5$d$ transition metal oxide Na$_2$IrO$_3$, where the transition can be driven by the change of the long-range hopping and trigonal crystal field terms. From the first-principles-derived tight-binding Hamiltonian we determine the phase boundary through the parity analysis. In addition, our first-principles calculations for Na$_2$IrO$_3$ model structures show that the interlayer distance can be an important parameter for the existence of a three-dimensional strong topological insulator phase. Na$_2$IrO$_3$ is suggested to be a candidate material which can have both a nontrivial topology of bands and strong electron correlations

YY1 is autoregulated through its own DNA-binding sites

<p>Abstract</p> <p>Background</p> <p>The transcription factor Yin Yang 1 (YY1) is a ubiquitously expressed, multifunctional protein that controls a large number of genes and biological processes in vertebrates. As a general transcription factor, the proper levels of YY1 protein need to be maintained for the normal function of cells and organisms. However, the mechanism for the YY1 homeostasis is currently unknown.</p> <p>Results</p> <p>The current study reports that the YY1 gene locus of all vertebrates contains a cluster of its own DNA-binding sites within the 1^stintron. The intact structure of these DNA-binding sites is absolutely necessary for transcriptional activity of the YY1 promoter. In an inducible cell line system that over-expresses an exogenous YY1 gene, the overall increased levels of YY1 protein caused a reduction in transcription levels of the endogenous YY1 gene. Reversion to the normal levels of YY1 protein restored the transcriptional levels of the endogenous YY1 to normal levels. This homeostatic response was also mediated through its cluster of YY1 binding sites.</p> <p>Conclusion</p> <p>Taken together, the transcriptional level of YY1 is self-regulated through its internal DNA-binding sites. This study identifies YY1 as the first known autoregulating transcription factor in mammalian genomes.</p

Color dipole cross section and inelastic structure function

Instead of starting from a theoretically motivated form of the color dipole cross section in the dipole picture of deep inelastic scattering, we start with a parametrization of the deep inelastic structure function for electromagnetic scattering with protons, and then extract the color dipole cross section. Using the parametrizations of $F_2(\xi=x \ {\rm or}\ W^2,Q^2)$ by Donnachie-Landshoff and Block et al., we find the dipole cross section from an approximate form of the presumed dipole cross section convoluted with the perturbative photon wave function for virtual photon splitting into a color dipole with massless quarks. The color dipole cross section determined this way reproduces the original structure function within about 10\% for $0.1$ GeV$^2\leq Q^2\leq 10$ GeV$^2$. We discuss the large and small form of the dipole cross section and compare with other parameterizations.Comment: 11 pages, 12 figure

Sodium Biphenyl as Anolyte for Sodium-Seawater Batteries

Sodium-based battery systems have recently attracted increasing research interest due to the abundant resources employed. Among various material candidates for the negative electrode, sodium metal provides the highest capacity of theoretically 1165 mAh g(-1) and a very low redox potential of -2.71 versus the standard hydrogen electrode. However, the high reactivity of sodium metal toward the commonly used electrolytes results in severe side reactions, including the evolution of gaseous decomposition products, and, in addition, the risk of dendritic sodium growth, potentially causing a disastrous short circuit of the cell. Herein, the use of sodium biphenyl (Na-BP) as anolyte for the Na-seawater batteries (Na-SWB) is investigated. The catholyte for the open-structured positive electrode is natural seawater with sodium cations dissolved therein. Remarkably, the significant electronic and ionic conductivities of the Na-BP anolyte enable a low overpotential for the sodium deposition upon charge, allowing for high capacity and excellent capacity retention for 80 cycles in full Na-SWB. Additionally, the Na-BP anolyte suppresses gas evolution and dendrite growth by forming a homogeneous surface layer on the metallic negative electrode

End-to-End Learnable Multi-Scale Feature Compression for VCM

The proliferation of deep learning-based machine vision applications has given rise to a new type of compression, so called video coding for machine (VCM). VCM differs from traditional video coding in that it is optimized for machine vision performance instead of human visual quality. In the feature compression track of MPEG-VCM, multi-scale features extracted from images are subject to compression. Recent feature compression works have demonstrated that the versatile video coding (VVC) standard-based approach can achieve a BD-rate reduction of up to 96% against MPEG-VCM feature anchor. However, it is still sub-optimal as VVC was not designed for extracted features but for natural images. Moreover, the high encoding complexity of VVC makes it difficult to design a lightweight encoder without sacrificing performance. To address these challenges, we propose a novel multi-scale feature compression method that enables both the end-to-end optimization on the extracted features and the design of lightweight encoders. The proposed model combines a learnable compressor with a multi-scale feature fusion network so that the redundancy in the multi-scale features is effectively removed. Instead of simply cascading the fusion network and the compression network, we integrate the fusion and encoding processes in an interleaved way. Our model first encodes a larger-scale feature to obtain a latent representation and then fuses the latent with a smaller-scale feature. This process is successively performed until the smallest-scale feature is fused and then the encoded latent at the final stage is entropy-coded for transmission. The results show that our model outperforms previous approaches by at least 52% BD-rate reduction and has $\times5$ to $\times27$ times less encoding time for object detection. It is noteworthy that our model can attain near-lossless task performance with only 0.002-0.003% of the uncompressed feature data size.Comment: Under peer review for IEEE TCSV

Two evolutionarily conserved sequence elements for Peg3/Usp29 transcription

<p>Abstract</p> <p>Background</p> <p>Two evolutionarily Conserved Sequence Elements, CSE1 and CSE2 (YY1 binding sites), are found within the 3.8-kb CpG island surrounding the bidirectional promoter of two imprinted genes, <it>Peg3 </it>(Paternally expressed gene 3) and <it>Usp29 </it>(Ubiquitin-specific protease 29). This CpG island is a likely ICR (Imprinting Control Region) that controls transcription of the 500-kb genomic region of the <it>Peg3 </it>imprinted domain.</p> <p>Results</p> <p>The current study investigated the functional roles of CSE1 and CSE2 in the transcriptional control of the two genes, <it>Peg3 </it>and <it>Usp29</it>, using cell line-based promoter assays. The mutation of 6 YY1 binding sites (CSE2) reduced the transcriptional activity of the bidirectional promoter in the <it>Peg3 </it>direction in an orientation-dependent manner, suggesting an activator role for CSE2 (YY1 binding sites). However, the activity in the <it>Usp29 </it>direction was not detectable regardless of the presence/absence of YY1 binding sites. In contrast, mutation of CSE1 increased the transcriptional activity of the promoter in both the <it>Peg3 </it>and <it>Usp29 </it>directions, suggesting a potential repressor role for CSE1. The observed repression by CSE1 was also orientation-dependent. Serial mutational analyses further narrowed down two separate 6-bp-long regions within the 42-bp-long CSE1 which are individually responsible for the repression of <it>Peg3 </it>and <it>Usp29</it>.</p> <p>Conclusion</p> <p>CSE2 (YY1 binding sites) functions as an activator for <it>Peg3 </it>transcription, while CSE1 acts as a repressor for the transcription of both <it>Peg3 </it>and <it>Usp29</it>.</p

Rediscovery of the Effectiveness of Standard Convolution for Lightweight Face Detection

This paper analyses the design choices of face detection architecture that improve efficiency between computation cost and accuracy. Specifically, we re-examine the effectiveness of the standard convolutional block as a lightweight backbone architecture on face detection. Unlike the current tendency of lightweight architecture design, which heavily utilizes depthwise separable convolution layers, we show that heavily channel-pruned standard convolution layer can achieve better accuracy and inference speed when using a similar parameter size. This observation is supported by the analyses concerning the characteristics of the target data domain, face. Based on our observation, we propose to employ ResNet with a highly reduced channel, which surprisingly allows high efficiency compared to other mobile-friendly networks (e.g., MobileNet-V1,-V2,-V3). From the extensive experiments, we show that the proposed backbone can replace that of the state-of-the-art face detector with a faster inference speed. Also, we further propose a new feature aggregation method maximizing the detection performance. Our proposed detector EResFD obtained 80.4% mAP on WIDER FACE Hard subset which only takes 37.7 ms for VGA image inference in on CPU. Code will be available at https://github.com/clovaai/EResFD