Crystal structure of 3-methyl-2-oxo-2H-chromen-7-yl propionate, C13H12O4

Abstract C13H12O4, triclinic, P1̄ (no. 2), a = 6.141(5) Å, b = 8.108(6) Å, c = 12.234(9) Å, α = 79.257(12)°, β = 76.820(12)°, γ = 74.687(11)°, V = 566.8(7) Å3, Z = 2, R gt(F) = 0.0515, wR ref(F 2) = 0.1575, T = 296(2) K

An accretion disc with magnetic outflows triggered by a sudden mass accretion event in changing-look active galactic nucleus 1ES 1927+654

1ES 1927+654 was known as a type 2 Seyfert galaxy, which exhibited drastic variability recently in ultraviolet (UV)/optical and X-ray bands. An UV/optical outburst was observed in the end of 2017, and it reached the peak luminosity $\sim 50$ days later. The high-cadence observations showed a rapid X-ray flux decline with complete disappearance of the power-law hard X-ray component when the soft X-ray thermal emission reached its lowest level about $150$ days after the UV/optical peak. The power law X-ray component reappeared with thermal X-ray emission brightening from its lowest flux within next $\sim$ 100~days. We assume an episodic accretion event taking place in the outer region of the disc surrounding a central black hole (BH), which is probably due to a red giant star tidally disrupted by the BH. The inner thin disc with corona is completely swept by the accretion event when the gas reaches the innermost circular stable orbit. The field threading the disrupted star is dragged inwards by the disc formed after the tidal disruption event, which accelerates outflows from the disc. The disc dimmed since a large fraction of the energy released in the disc is tapped into the outflows. The accretion rate of the episodic accretion event declines, and ultimately it turns out to be a thin disc, which is inefficient for field advection, and the outflows are switched off. A thin disc with corona reappears later after the outburst.Comment: 11 pages, accepted by MNRA

A Unified Approximation Framework for Compressing and Accelerating Deep Neural Networks

Deep neural networks (DNNs) have achieved significant success in a variety of real world applications, i.e., image classification. However, tons of parameters in the networks restrict the efficiency of neural networks due to the large model size and the intensive computation. To address this issue, various approximation techniques have been investigated, which seek for a light weighted network with little performance degradation in exchange of smaller model size or faster inference. Both low-rankness and sparsity are appealing properties for the network approximation. In this paper we propose a unified framework to compress the convolutional neural networks (CNNs) by combining these two properties, while taking the nonlinear activation into consideration. Each layer in the network is approximated by the sum of a structured sparse component and a low-rank component, which is formulated as an optimization problem. Then, an extended version of alternating direction method of multipliers (ADMM) with guaranteed convergence is presented to solve the relaxed optimization problem. Experiments are carried out on VGG-16, AlexNet and GoogLeNet with large image classification datasets. The results outperform previous work in terms of accuracy degradation, compression rate and speedup ratio. The proposed method is able to remarkably compress the model (with up to 4.9x reduction of parameters) at a cost of little loss or without loss on accuracy.Comment: 8 pages, 5 figures, 6 table

Temperature-insensitive detection of low-concentration nanoparticles using a functionalized high-Q microcavity

The ability to detect nanoparticles in extremely dilute solutions in the presence of environmental noise is crucial for biosensing applications. In this paper we propose a scheme for detecting target nanoparticles through their scattering effects in a high-Q whispering gallery microcavity. The detection signal, defined as the total linewidth broadening of the two new split modes that appear upon nanoparticle adsorption, is highly sensitive and proportional to the nanoparticle concentration. Furthermore, this new method of detection eliminates the requirement for strict temperature control and is capable of distinguishing the signal from the biorecognitions (e.g., antibodies) initially attached to the resonator and that from the target nanoparticles (e.g., antigens)

Decoding the contribution of transcription factors to cell fate determination

It is well accepted that transcription factors (TFs) play a crucial role in determining cell identity. Although RNA expression or protein abundance data show that a large fraction of the total TFs are expressed in a given cell, however, only a small set of them is essential for specifying cell identity. This was elegantly demonstrated through reprogramming of somatic cells to induced pluripotent stem cells (iPSCs) by means of ectopic expression of only four key TFs, Oct-3/4 (Pou5f1), Sox2, Klf4 and c- Myc. In order to decipher the most predominant TFs in specific cell types, we developed a novel massively parallel protein activity assay, Active TF Identification (ATI) that measured DNA-binding activity of TFs in the cell nucleus. This method indicated that around 15 TFs have the highest DNA-binding activities, among which there are “common” TFs universally active in most cell types, “shared” TFs which are active in several cell types and “specific” TFs which are active in only one or two cell types. It has been well established that the gene transcription is highly correlated with disruption of nucleosomes at the gene regulatory elements. In order to test if TFs are the major determinant of chromatin accessibility, we compared the ATI data with the DNase I hypersensitive sites (DHSs) from the same cell or tissue type, and found out that the enriched subsequences in the ATI results are also enriched within the DHSs compared with the non-DHS regions. This suggested that the DNA-binding activity of TFs, especially the most active ones, played major roles in determining the chromatin accessibility. In addition, we also performed the ATI assay using nucleosomal DNA to determine the “pioneer” TFs in cells that are capable of binding condensed chromatin. This study has generated a deeper understanding of the gene regulatory logic and helped us to decipher important TFs in specific cell types