Dynamics of Antimonene–Graphene Van Der Waals Growth

Van der Waals (vdW) heterostructures have recently been introduced as versatile building blocks for a variety of novel nanoscale and quantum technologies. Harnessing the unique properties of these heterostructures requires a deep understanding of the involved interfacial interactions and a meticulous control of the growth of 2D materials on weakly interacting surfaces. Although several epitaxial vdW heterostructures have been achieved experimentally, the mechanisms governing their synthesis are still nebulous. With this perspective, herein, the growth dynamics of antimonene on graphene are investigated in real time. In situ low‐energy electron microscopy reveals that nucleation predominantly occurs on 3D nuclei followed by a self‐limiting lateral growth with morphology sensitive to the deposition rate. Large 2D layers are observed at high deposition rates, whereas lower growth rates trigger an increased multilayer nucleation at the edges as they become aligned with the Z2 orientation leading to atoll‐like islands with thicker, well‐defined bands. This complexity of the vdW growth is elucidated based on the interplay between the growth rate, surface diffusion, and edges orientation. This understanding lays the groundwork for a better control of the growth of vdW heterostructures, which is critical to their large‐scale integration.     

Cyber security methods for aerial vehicle networks: taxonomy,challenges and solution

Aerial vehicle networks (AVNs) compose a large number of heterogeneous aerial nodes, such as unmanned aerial vehicles, aircrafts and helicopters. The main characteristics of these networks are the high mobility of aerial nodes and the dynamic network topology. AVNs represent attractive targets for attackers due to the fact that aerial nodes could be connected to an untrusted network and hence lead the attackers to launch lethal threats, e.g., aircraft crash. Therefore, the security of AVNs is mandatory. In this article, we examine the challenges of cyber detection methods to secure AVNs and review exiting security schemes proposed in the current literature. Furthermore, we propose a security framework to protect an aircraft (SFA) against malicious behaviors that target aircrafts communication systems. Numerical results show that SFA achieves a high accuracy detection and prediction rates as compared to the current intrusion detection for aircrafts communication system.     

Complexation of Tolane by Fluorinated Organomercurials—Structures and Luminescence Properties of an Unusual Class of Supramolecular π-Coordination Polymers

The interaction of the Hg(II) derivatives bis(pentafluoro)phenyl mercury (1), (pentafluoro)phenyl mercury chloride (2) and trimeric perfluoro-ortho-phenylene mercury (3) with tolane (diphenylacetylene) in CH₂Cl₂ leads to the formation of [1·tolane], [2 ₂·tolane], and [3·tolane·CH₂Cl₂]. These adducts have been characterized by elemental analysis, X-ray crystallography, and luminescence spectroscopy. In the solid state of these adducts, the tolane molecules interact with the molecules of 1, 2 and 3 via secondary Hg–π interactions and arene–fluoroarene interactions. As a result of an external mercury heavy atom effect, adducts [1·tolane] and [2 ₂·tolane] are phosphorescent at room temperature.     

Transparent Inband Feedback for Training-Based MIMO Systems

Recently, Echo-MIMO, a delay-free feedback scheme has been proposed for Closed-Loop MIMO systems, where the receiver echoes the received signal on the fly to the transmitter without any processing. While this reduced feedback latency allows for more use of the channel’s coherence time for data transmission, it comes at high power-and-bandwidth costs, as two MIMO transmissions are required in the feedback phase. In this paper, we present a feedback scheme that preserves the advantages of Echo-MIMO while requiring only one feedback transmission. The echoed signals are judiciously combined with the receiver’s signals such that their separation at the transmitter be lossless, and that no extra transmit power nor bandwidth be required. In addition, we highlight the estimation accuracy degradation in Echo-MIMO owing to the echoed noise, and analytically confirm the intuition that removing the noise prior to echoing the received signal provides better estimation than echoing the noisy received signal as is and later account for the noise effect upon echo reception. Simulation results show that the proposed scheme outperforms Echo-MIMO in terms of channel estimation accuracy and achievable capacity.     

Mapping the "forbidden" transverse-optical phonon in single strained silicon (100) nanowire

The accurate manipulation of strain in silicon nanowires can unveil new fundamental properties and enable novel or enhanced functionalities. To exploit these potentialities, it is essential to overcome major challenges at the fabrication and characterization levels. With this perspective, we have investigated the strain behavior in nanowires fabricated by patterning and etching of 15 nm thick tensile strained silicon (100) membranes. To this end, we have developed a method to excite the "forbidden" transverse-optical (TO) phonons in single tensile strained silicon nanowires using high-resolution polarized Raman spectroscopy. Detecting this phonon is critical for precise analysis of strain in nanoscale systems. The intensity of the measured Raman spectra is analyzed based on three-dimensional field distribution of radial, azimuthal, and linear polarizations focused by a high numerical aperture lens. The effects of sample geometry on the sensitivity of TO measurement are addressed. A significantly higher sensitivity is demonstrated for nanowires as compared to thin layers. In-plane and out-of-plane strain profiles in single nanowires are obtained through the simultaneous probe of local TO and longitudinal-optical (LO) phonons. New insights into strained nanowires mechanical properties are inferred from the measured strain profiles.     

A CMOS adaptive RF front-end receiver for wireless applications

The performance of signal-processing algorithms implemented in hardware depends on the efficiency of datapath, memory speed and address computation. Pattern of data access in signal-processing applications is complex and it is desirable to execute the innermost loop of a kernel in a single-clock cycle. This necessitates the generation of typically three addresses per clock: two addresses for data sample/coefficient and one for the storage of processed data. Most of the Reconfigurable Processors, designed for multimedia, focus on mapping the multimedia applications written in a high-level language directly on to the reconfigurable fabric, implying the use of same datapath resources for kernel processing and address generation. This results in inconsistent and non-optimal use of finite datapath resources. Presence of a set of dedicated, efficient Address Generator Units (AGUs) helps in better utilisation of the datapath elements by using them only for kernel operations; and will certainly enhance the performance. This article focuses on the design and application-specific integrated circuit implementation of address generators for complex addressing modes required by multimedia signal-processing kernels. A novel algorithm and hardware for AGU is developed for accessing data and coefficients in a bit-reversed order for fast Fourier transform kernel spanning over log?₂ N stages, AGUs for zig-zag-ordered data access for entropy coding after Discrete Cosine Transform (DCT), convolution kernels with stored/streaming data, accessing data for motion estimation using the block-matching technique and other conventional addressing modes. When mapped to hardware, they scale linearly in gate complexity with increase in the size.     

Optimizing Postdisaster Reconstruction Planning for Damaged Transportation Networks

The limited availability of reconstruction resources is one of the main challenges that often confront postdisaster recovery of damaged transportation networks. This requires an effective and efficient deployment and utilization of these limited resources in order to minimize both the performance loss of the damaged transportation network and the reconstruction costs. This paper presents the development of a robust model for planning postdisaster reconstruction efforts that is capable of: (1) optimizing the allocation of limited reconstruction resources to competing recovery projects; (2) assessing and quantifying the overall functional loss of damaged transportation networks during the recovery efforts; (3) evaluating the impact of limited availability of resources on the reconstruction costs; and (4) minimizing the performance loss of transportation networks and reconstruction costs. The model utilizes the user equilibrium algorithm to enable the assessment of the transportation network performance losses and a multiobjective genetic algorithm to enable the generation of optimal tradeoffs between the two recovery planning objectives. An application example is analyzed to demonstrate the use and capabilities of the recovery planning model.     

Call admission control in cellular networks: A reinforcement learning solution

In this paper, we address the call admission control (CAC) problem in a cellular network that handles several classes of traffic with different resource requirements. The problem is formulated as a semi‐Markov decision process (SMDP) problem. We use a real‐time reinforcement learning (RL) [neuro‐dynamic programming (NDP)] algorithm to construct a dynamic call admission control policy. We show that the policies obtained using our TQ‐CAC and NQ‐CAC algorithms, which are two different implementations of the RL algorithm, provide a good solution and are able to earn significantly higher revenues than classical solutions such as guard channel. A large number of experiments illustrates the robustness of our policies and shows how they improve quality of service (QoS) and reduce call‐blocking probabilities of handoff calls even with variable traffic conditions. Copyright © 2004 John Wiley & Sons, Ltd.