Microstructural characterisation and thermal stability of an Mg-Al-Sr alloy prepared by rheo-diecasting

A commercial Mg-6Al-2Sr (AJ62) alloy has been prepared by a semisolid rheo-diecasting (RDC) process. The microstructure of the RDC alloy exhibits typical semisolid solidification features, i.e., 8.4 vol% primary α-Mg globules (23 μm in diameter), formed in the slurry maker at the primary solidification stage, uniformly distributed in the matrix of fine α-Mg grain size (8.2 μm) and intergranular eutectic Al4Sr lamellae, which resulted from secondary solidification inside the die. A ternary Mg-Al-Sr phase was also observed. Heat treatment revealed the extreme thermal stability of the RDC AJ62 alloy. The hardness showed little change up to 12 hours at 450°C, whilst the Al4Sr eutectic lamellae were broken up, spheroidised and coarsened during the annealing. The RDC alloy offers superior mechanical properties, especially ductility, over the same alloy produced by high pressure die-casting

Direction-of-Arrival Estimation Based on Sparse Recovery with Second-Order Statistics

Traditional direction-of-arrival (DOA) estimation techniques perform Nyquist-rate sampling of the received signals and as a result they require high storage. To reduce sampling ratio, we introduce level-crossing (LC) sampling which captures samples whenever the signal crosses predetermined reference levels, and the LC-based analog-to-digital converter (LC ADC) has been shown to efficiently sample certain classes of signals. In this paper, we focus on the DOA estimation problem by using second-order statistics based on the LC samplings recording on one sensor, along with the synchronous samplings of the another sensors, a sparse angle space scenario can be found by solving an $ell_1$ minimization problem, giving the number of sources and their DOA's. The experimental results show that our proposed method, when compared with some existing norm-based constrained optimization compressive sensing (CS) algorithms, as well as subspace method, improves the DOA estimation performance, while using less samples when compared with Nyquist-rate sampling and reducing sensor activity especially for long time silence signal

On computing explanations in argumentation

Copyright © 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.Argumentation can be viewed as a process of generating explanations. However, existing argumentation semantics are developed for identifying acceptable arguments within a set, rather than giving concrete justifications for them. In this work, we propose a new argumentation semantics, related admissibility, designed for giving explanations to arguments in both Abstract Argumentation and Assumption-based Argumentation. We identify different types of explanations defined in terms of the new semantics. We also give a correct computational counterpart for explanations using dispute forests

The SCUBA-2 850 μm\mu m follow-up of WISE-selected, luminous dust-obscured quasars

Hot dust-obscured galaxies (Hot DOGs) are a new population recently discovered in the \wise All-Sky survey. Multiwavelength follow-up observations suggest that they are luminous, dust-obscured quasars at high redshift. Here we present the JCMT SCUBA-2 850 $\mu m$ follow-up observations of 10 Hot DOGs. Four out of ten Hot DOGs have been detected at $>3\sigma$ level. Based on the IR SED decomposition approach, we derive the IR luminosities of AGN torus and cold dust components. Hot DOGs in our sample are extremely luminous with most of them having $L_{\rm IR}^{\rm tot}>10^{14} L_\odot$. The torus emissions dominate the total IR energy output. However, the cold dust contribution is still non-negligible, with the fraction of the cold dust contribution to the total IR luminosity $(\sim 8-24\%)$ being dependent on the choice of torus model. The derived cold dust temperatures in Hot DOGs are comparable to those in UV bright quasars with similar IR luminosity, but much higher than those in SMGs. Higher dust temperatures in Hot DOGs may be due to the more intense radiation field caused by intense starburst and obscured AGN activities. Fourteen and five submillimeter serendipitous sources in the 10 SCUBA-2 fields around Hot DOGs have been detected at $>3\sigma$ and $>3.5\sigma$ levels, respectively. By estimating their cumulative number counts, we confirm the previous argument that Hot DOGs lie in dense environments. Our results support the scenario in which Hot DOGs are luminous, dust-obscured quasars lying in dense environments, and being in the transition phase between extreme starburst and UV-bright quasars.Comment: 26 pages, 7 figures, PASP accepte