FeAs-based superconductivity: a case study of the effects of transition metal doping on BaFe2As2

The recently discovered FeAs-based superconductors are a new, promising set of materials for both technological as well as basic research. They offer transition temperatures as high as 55 K as well as essentially isotropic and extremely large upper, superconducting critical fields in excess of 40 T at 20 K. In addition they may well provide insight into exotic superconductivity that extends beyond just FeAs-based superconductivity, perhaps even shedding light on the still perplexing CuO-based high-Tc materials. Whereas superconductivity can be induced in the RFeAsO (R = rare earth) and AEFe2As2 (AE = Ba, Sr, Ca)) families by a number of means, transition metal doping of BaFe2As2, e.g. Ba(Fe1-xTMx)2As2, offers the easiest experimental access to a wide set of materials. In this review we present an overview and summary of the effect of TM doping (TM = Co, Ni, Cu, Pd, and Rh) on BaFe2As2. The resulting phase diagrams reveal the nature of the interaction between the structural, magnetic and superconducting phase transitions in these compounds and delineate a region of phase space that allows for the stabilization of superconductivity.Comment: edited and shortened version is accepted to AR:Condensed Matter Physic

Chosen-plaintext attack of an image encryption scheme based on modified permutation-diffusion structure

Since the first appearance in Fridrich's design, the usage of permutation-diffusion structure for designing digital image cryptosystem has been receiving increasing research attention in the field of chaos-based cryptography. Recently, a novel chaotic Image Cipher using one round Modified Permutation-Diffusion pattern (ICMPD) was proposed. Unlike traditional permutation-diffusion structure, the permutation is operated on bit level instead of pixel level and the diffusion is operated on masked pixels, which are obtained by carrying out the classical affine cipher, instead of plain pixels in ICMPD. Following a \textit{divide-and-conquer strategy}, this paper reports that ICMPD can be compromised by a chosen-plaintext attack efficiently and the involved data complexity is linear to the size of the plain-image. Moreover, the relationship between the cryptographic kernel at the diffusion stage of ICMPD and modulo addition then XORing is explored thoroughly

Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems

The proximal gradient algorithm has been popularly used for convex optimization. Recently, it has also been extended for nonconvex problems, and the current state-of-the-art is the nonmonotone accelerated proximal gradient algorithm. However, it typically requires two exact proximal steps in each iteration, and can be inefficient when the proximal step is expensive. In this paper, we propose an efficient proximal gradient algorithm that requires only one inexact (and thus less expensive) proximal step in each iteration. Convergence to a critical point %of the nonconvex problem is still guaranteed and has a $O(1/k)$ convergence rate, which is the best rate for nonconvex problems with first-order methods. Experiments on a number of problems demonstrate that the proposed algorithm has comparable performance as the state-of-the-art, but is much faster

Downlink and Uplink Intelligent Reflecting Surface Aided Networks: NOMA and OMA

Intelligent reflecting surfaces (IRSs) are envisioned to provide reconfigurable wireless environments for future communication networks. In this paper, both downlink and uplink IRS-aided non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) networks are studied, in which an IRS is deployed to enhance the coverage by assisting a cell-edge user device (UD) to communicate with the base station (BS). To characterize system performance, new channel statistics of the BS-IRS-UD link with Nakagami-$m$ fading are investigated. For each scenario, the closed-form expressions for the outage probability and ergodic rate are derived. To gain further insight, the diversity order and high signal-to-noise ratio (SNR) slope for each scenario are obtained according to asymptotic approximations in the high-SNR regime. It is demonstrated that the diversity order is affected by the number of IRS reflecting elements and Nakagami fading parameters, but the high-SNR slope is not related to these parameters. Simulation results validate our analysis and reveal the superiority of the IRS over the full-duplex decode-and-forward relay.Comment: Accepted for publication in the IEEE Transactions on Wireless Communication

An efficient ant colony system based on receding horizon control for the aircraft arrival sequencing and scheduling problem

The aircraft arrival sequencing and scheduling (ASS) problem is a salient problem in air traffic control (ATC), which proves to be nondeterministic polynomial (NP) hard. This paper formulates the ASS problem in the form of a permutation problem and proposes a new solution framework that makes the first attempt at using an ant colony system (ACS) algorithm based on the receding horizon control (RHC) to solve it. The resultant RHC-improved ACS algorithm for the ASS problem (termed the RHC-ACS-ASS algorithm) is robust, effective, and efficient, not only due to that the ACS algorithm has a strong global search ability and has been proven to be suitable for these kinds of NP-hard problems but also due to that the RHC technique can divide the problem with receding time windows to reduce the computational burden and enhance the solution's quality. The RHC-ACS-ASS algorithm is extensively tested on the cases from the literatures and the cases randomly generated. Comprehensive investigations are also made for the evaluation of the influences of ACS and RHC parameters on the performance of the algorithm. Moreover, the proposed algorithm is further enhanced by using a two-opt exchange heuristic local search. Experimental results verify that the proposed RHC-ACS-ASS algorithm generally outperforms ordinary ACS without using the RHC technique and genetic algorithms (GAs) in solving the ASS problems and offers high robustness, effectiveness, and efficienc

A novel surface segmentation approach for robotic manipulator-based maintenance operation planning

This paper presents a novel approach to segmenting a three-dimensional surface map by considering the task requirements and the movements of an industrial robot manipulator. Maintenance operations, such as abrasive blasting, that are performed by a field robot manipulator can be made more efficient by exploiting surface segmentation. The approach in this paper utilises an aggregate of multiple connectivity graphs, with graph edges defined by task constraints, and graph vertices that correspond to small, maintenance-specific target surfaces, known as Scale-Like Discs (SLDs). The task constraints for maintenance operations are based on the characteristics of neighbouring SLDs. The combined connectivity graphs are analysed to find clusters of vertices, thus segmenting the surface map into groups of related SLDs. Experiments conducted in three typical bridge maintenance environments have shown that the approach can reduce garnet usage by 10%-40% and reduce the manipulator joint movements by up to 35%. © 2012 Elsevier B.V. All rights reserved