Waveguiding through a two-dimensional metallic photonic crystal

We present a two‐dimensional (2D) finite‐difference time domain simulation of the propagation of light through linear and bent channels in metallic photonic crystals. We took as a starting point the Bozhevolnyi experiment, consisting of the scattering of surface plasmons by a 2D structure of finitely sized periodic gold dots arranged in a triangular lattice of 400‐nm period. We model injection and propagation of light through linear channels of different widths. We also study the behaviour of light in the presence of a 90° bent line defect made in the structure. We show that the confinement depends on the orientation of the input and output line defects. The two cases of ΓM and ΓK orientations are considered and a spectral study for five different wavelengths is carried out.     

Evolutionary multi-objective portfolio optimization in practical context

This paper addresses evolutionary multi-objective portfolio optimization in the practical context by incorporating realistic constraints into the problem model and preference criterion into the optimization search process. The former is essential to enhance the realism of the classical mean-variance model proposed by Harry Markowitz, since portfolio managers often face a number of realistic constraints arising from business and industry regulations, while the latter reflects the fact that portfolio managers are ultimately interested in specific regions or points along the efficient frontier during the actual execution of their investment orders. For the former, this paper proposes an order-based representation that can be easily extended to handle various realistic constraints like floor and ceiling constraints and cardinality constraint. An experimental study, based on benchmark problems obtained from the OR-library, demonstrates its capability to attain a better approximation of the efficient frontier in terms of proximity and diversity with respect to other conventional representations. The experimental results also illustrated its viability and practicality in handling the various realistic constraints. A simple strategy to incorporate preferences into the multi-objective optimization process is highlighted and the experimental study demonstrates its capability in driving the evolutionary search towards specific regions of the efficient frontier.     

Automatic symbolic derivation of order conditions for two-stage complex Rosenbrock schemes

Rosenbrock methods are known to be good in numerical modeling of stiff problems. In this work, a new symbolic algorithm is proposed for automating the derivation of order conditions for two-stage Rosenbrock schemes with complex coefficients. Software implementation of the proposed algorithm is discussed in detail.     

Automatic verification of reduction techniques in Higher Order Logic

In this paper we propose an automatic methodology to verify the soundness of model checking reduction techniques. The idea is to use the consistency of the specifications to verify if the reduced model is faithful to the original one. The user provides the reduction technique, the specification and the system under verification. Then, using Higher Order Logic he verifies automatically if the reduction technique is soundly applied. The method is completely defined in an MDG–HOL special integration platform that combines an automatic high level model checking tool Multiway Decision Graphs (MDGs) within the HOL theorem prover. We provide two case studies, the first one is the reduction using SAT–MDG of an Island Tunnel Controller and the second one is the MDG–HOL assume-guarantee reduction of the Look-Aside Interface. The obtained results of our approach offer a considerable gain in terms of the correctness of heuristics and reduction techniques as applied to commercial model checking, however a small penalty is paid in terms of CPU time and memory usage.     

A low‐power,area‐efficient multichannel receiver for micro MRI

A new integrated, low‐noise, low‐power, and area‐efficient multichannel receiver for magnetic resonance imaging (MRI) is described. The proposed receiver presents an alternative technique to overcome the use of multiple receiver front‐ends in parallel MRI. The receiver consists of three main stages: low‐noise pre‐amplifier, quadrature down‐converter, and a band pass filter (BPF). These components are used to receive the nuclear magnetic resonance signals from a 3 × 3 array of micro coils. These signals are combined using frequency domain multiplexing (FDM) method in the pre‐amplifier and BPF stages, then amplified and filtered to remove any out‐of‐band noise before providing it to an analog‐to‐digital converter at the low intermediate frequency stage. The receiver is designed using a 90 nm CMOS technology to operate at the main B₀ magnetic field of 9.4 T, which corresponds to 400 MHz. The receiver has an input referred noise voltage of 1.1 nV/√Hz, a total voltage gain of 87 dB, a power consumption of 69 mA from a 1 V supply voltage, and an area of 305 µm × 530 µm including the reference current and bias voltage circuits. Copyright © 2013 John Wiley & Sons, Ltd.     

A Complete Separation of Hexane Isomers by a Functionalized Flexible Metal Organic Framework

The separation ability of branched alkane isomers (nHEX, 3MP, 22DMB) of the flexible and functionalized microporous iron(III) dicarboxylate MIL‐53(Fe)‐(CF₃)₂ solid is evaluated through a combination of breakthrough experiments (binary or ternary mixtures), adsorption isotherms, X‐ray diffraction temperature analysis, quasi‐elastic neutron scattering measurements and molecular dynamics simulations. A kinetically controlled molecular sieve separation between the di‐branched isomer of hexane 22DMB from a mixture of paraffins is achieved. The reported total separation between mono‐ and di‐branched alkanes which was neither predicted nor observed so far in any class of porous solids is spectacular and paves the way towards a potential unprecedented upgrading of the RON of gasoline.     

Error rates of DPSK systems with MIMO EGC diversity reception over Rayleigh fading channels

This paper analyzes the average bit error probability (BEP) of the differential binary and quaternary phase-shift keying (DBPSK and DQPSK respectively) with multiple-input multiple-output (MIMO) systems employing postdetection equal gain combining (MIMO EGC) diversity reception over Rayleigh fading channels. Finite closed-form expressions for the average BEP of DBPSK and DQPSK are presented. Two approaches are introduced to analyze the error rate of DQPSK. The proposed structure for the differential phase-shift keying (DPSK) with MIMO EGC provides a reduced-complexity and low-cost receiver for MIMO systems compared to the coherent phase-shift keying system (PSK) with MIMO employing maximal ratio combining (MIMO MRC) diversity reception. Finally, a useful procedure for computing the associated Legendre functions of the second kind with half-odd-integer order and arbitrarily degree is presented.     

The Role of Antibodies in the Treatment of SARS-CoV-2 Virus Infection,and Evaluating Their Contribution to Antibody-Dependent Enhancement of Infection

Antibodies play a crucial role in the immune response, in fighting off pathogens as well as helping create strong immunological memory. Antibody-dependent enhancement (ADE) occurs when non-neutralising antibodies recognise and bind to a pathogen, but are unable to prevent infection, and is widely known and is reported as occurring in infection caused by several viruses. This narrative review explores the ADE phenomenon, its occurrence in viral infections and evaluates its role in infection by SARS-CoV-2 virus, which causes coronavirus disease 2019 (COVID-19). As of yet, there is no clear evidence of ADE in SARS-CoV-2, though this area is still subject to further study.     

A novel energy‐aware routing mechanism for SDN‐enabled WSAN

Energy consumption is one of the most important design constraints when building a wireless sensor and actuator network since each device in the network has a limited battery capacity, and prolonging the lifetime of the network depends on saving energy. Overcoming this challenge requires a smart and reconfigurable network energy management strategy. The Software‐Defined Networking (SDN) paradigm aims at building a flexible and dynamic network structure, especially in wireless sensor networks. In this study, we propose an SDN‐enabled wireless sensor and actuator network architecture that has a new routing discovery mechanism. To build a flexible and energy‐efficient network structure, a new routing decision approach that uses a fuzzy‐based Dijkstra's algorithm is developed in the study. The proposed architecture can change the existing path during data transmission, which is the key property of our model and is achieved through the adoption of the SDN approach. All the components and algorithms of the proposed system are modeled and simulated using the Riverbed Modeler software for more realistic performance evaluation. The results indicate that the proposed SDN‐enabled structure with fuzzy‐based Dijkstra's algorithm outperforms the one using the regular Dijkstra's and the ZigBee‐based counterpart, in terms of the energy consumption ratio, and the proposed architecture can provide an effective cluster routing while prolonging the network lifetime.