Chandra Observation of a Weak Shock in the Galaxy Cluster A2556

Based on a 21.5 ks \chandra\ observation of A2556, we identify an edge on the surface brightness profile (SBP) at about 160$h_{71}^{-1}$ kpc northeast of the cluster center, and it corresponds to a shock front whose Mach number $\mathcal{M}$ is calculated to be $1.25_{-0.03}^{+0.02}$. No prominent substructure, such as sub-cluster, is found in either optical or X-ray band that can be associated with the edge, suggesting that the conventional super-sonic motion mechanism may not work in this case. As an alternative solution, we propose that the nonlinear steepening of acoustic wave, which is induced by the turbulence of the ICM at the core of the cluster, can be used to explain the origin of the shock front. Although nonlinear steepening weak shock is expected to occur frequently in clusters, why it is rarely observed still remains a question that requires further investigation, including both deeper X-ray observation and extensive theoretical studies.Comment: 15 pages, 4 figures, accepted by Ap

Predicting Aesthetic Score Distribution through Cumulative Jensen-Shannon Divergence

Aesthetic quality prediction is a challenging task in the computer vision community because of the complex interplay with semantic contents and photographic technologies. Recent studies on the powerful deep learning based aesthetic quality assessment usually use a binary high-low label or a numerical score to represent the aesthetic quality. However the scalar representation cannot describe well the underlying varieties of the human perception of aesthetics. In this work, we propose to predict the aesthetic score distribution (i.e., a score distribution vector of the ordinal basic human ratings) using Deep Convolutional Neural Network (DCNN). Conventional DCNNs which aim to minimize the difference between the predicted scalar numbers or vectors and the ground truth cannot be directly used for the ordinal basic rating distribution. Thus, a novel CNN based on the Cumulative distribution with Jensen-Shannon divergence (CJS-CNN) is presented to predict the aesthetic score distribution of human ratings, with a new reliability-sensitive learning method based on the kurtosis of the score distribution, which eliminates the requirement of the original full data of human ratings (without normalization). Experimental results on large scale aesthetic dataset demonstrate the effectiveness of our introduced CJS-CNN in this task.Comment: AAAI Conference on Artificial Intelligence (AAAI), New Orleans, Louisiana, USA. 2-7 Feb. 201

Superabsorbent Polymers:From long-established, microplastics generating systems, to sustainable, biodegradable and future proof alternatives

Superabsorbent polymers (SAPs) play important roles in our daily life, as they are applied in products for hygiene, agriculture, construction, etc. The most successful commercially used types of SAPs are acrylate-based, which include poly(acrylic acid)s, poly(acrylamide)s, poly(acrylonitrile)s and their salts. The acrylate-based SAPs have superior water-absorbent properties, but they have high molecular weight and in addition an entirely carbon atom-based and cross-linked backbone. These factors endow them with poor (bio)degradability, which has a devastating impact on the environment where such SAP-containing materials may end up at the end of their lifetime. Furthermore, the raw materials for production of acrylate-based SAPs are mostly petroleum-based. From the viewpoint of sustainability, a bio-based resource would be the ideal candidate to replace the fossil-based ones. To overcome the shortcomings of the existing SAPs, bio-based and degradable SAPs are required. This review will then cover the following topics: (1) the technology development history and state-of-the-art of current SAPs; (2) the product designing principles of SAPs; (3) an in-depth introduction and discussion of the structural characteristics and properties of different kinds of SAPs derived from both fossil or renewable resources and (4) novel polycondensate-based, potentially biodegradable SAPs with promising industrial applicability

Exploring the Cosmic Reionization Epoch in Frequency Space: An Improved Approach to Remove the Foreground in 21 cm Tomography

Aiming to correctly restore the redshifted 21 cm signals emitted by the neutral hydrogen during the cosmic reionization processes, we re-examine the separation approaches based on the quadratic polynomial fitting technique in frequency space to investigate whether they works satisfactorily with complex foreground, by quantitatively evaluate the quality of restored 21 cm signals in terms of sample statistics. We construct the foreground model to characterize both spatial and spectral substructures of the real sky, and use it to simulate the observed radio spectra. By comparing between different separation approaches through statistical analysis of restored 21 cm spectra and corresponding power spectra, as well as their constraints on the mean halo bias $b$ and average ionization fraction $x_e$ of the reionization processes, at $z=8$ and the noise level of 60 mK we find that, although the complex foreground can be well approximated with quadratic polynomial expansion, a significant part of Mpc-scale components of the 21 cm signals (75% for $\gtrsim 6h^{-1}$ Mpc scales and 34% for $\gtrsim 1h^{-1}$ Mpc scales) is lost because it tends to be mis-identified as part of the foreground when single-narrow-segment separation approach is applied. The best restoration of the 21 cm signals and the tightest determination of $b$ and $x_e$ can be obtained with the three-narrow-segment fitting technique as proposed in this paper. Similar results can be obtained at other redshifts.Comment: 33 pages, 14 figures. Accepted for publication in Ap

Low-crystallinity to highly amorphous copolyesters with high glass transition temperatures based on rigid carbohydrate-derived building blocks

The current trend of developing novel biobased polymeric materials is focused more on utilizing the unique structural/physical properties of renewable building blocks towards niche market applications. In this work, with the aim of developing low-crystallinity to amorphous polyesters with enhanced thermal properties, a series of copolyesters based on rigid and structurally asymmetric carbohydrate-derived building blocks, namely furan-2,5-dicarboxylic acid and isosorbide, and 1,4-butanediol were successfully synthesized using melt polycondensation. The copolyesters were obtained with varied chemical compositions and rather high molecular weights (Mn = 24 000–31 000 g mol−1) and intrinsic viscosities ([η] = 0.56–0.72 dL g−1). Incorporation of both building blocks significantly enhances the glass transition temperatures (Tg = 38–107 °C) of polyesters, and also efficiently inhibits the crystallization of the copolyesters. A low content of isosorbide (ca 10 mol%) leads to complete transition of the homopolyester to nearly fully amorphous materials. Detailed characterizations of the chemical structures and thermal properties of the synthesized copolyesters were conducted using various analytical techniques. In addition, hydrolytic and enzymatic degradations of the copolymers in the presence of porcine pancreatic lipase and cutinase were also investigated

Selenium‐doping induced two antiferromagnetic transitions in thiospinel compounds CuCo₂S_(4‐x)Se_x (0 ≤ x ≤ 0.8)

A series of copper thiospinels compounds, CuCo₂S_(4‐x)Se_x (x = 0, 0.2, 0.4, 0.6, 0.8), have been successfully synthesized by solid state reaction and their structure and magnetic properties have been studied. The Rietveld refinements of X‐Ray diffractions indicate that both the lattice constants and the nearest neighbor Cu‐Cu distances increase with increasing selenium doping. A weakly antiferromagnetic transition occurring at about 4 K is observed in CuCo₂S₄. Two antiferromagnetic transitions at about 3.5 K and 6 K are observed in selenium‐doped samples, which suggest that the exchange couplings associated with Cu‐S(Se)‐Cu and Cu‐Se(S)‐Cu, respectively, are responsible for the two antiferromagnetic transitions. Detailed analysis of the experimental results further indicate that the nearest‐neighbor molecular field coefficient is comparable to the next‐neighbor molecular field coefficient. We propose a reasonable model to explain this phenomenon

Research advances in huntingtin-associated protein 1 and its application prospects in diseases

Huntingtin-associated protein 1 (HAP1) was the first protein discovered to interact with huntingtin. Besides brain, HAP1 is also expressed in the spinal cord, dorsal root ganglion, endocrine, and digestive systems. HAP1 has diverse functions involving in vesicular transport, receptor recycling, gene transcription, and signal transduction. HAP1 is strongly linked to several neurological diseases, including Huntington’s disease, Alzheimer’s disease, epilepsy, ischemic stroke, and depression. In addition, HAP1 has been proved to participate in cancers and diabetes mellitus. This article provides an overview of HAP1 regarding the tissue distribution, cell localization, functions, and offers fresh perspectives to investigate its role in diseases