The fabrication of nanostructures from polycyclic aromatic hydrocarbons (PAHs) is highly attractive owing to their unique optical, electrical, and magnetic properties. However, the creation uniform well-defined PAH by self-assembly still remains a significant challenge. Herein, we report that hexagonal rods can be obtained triphenylene (TP)-derived monomers synchronized polymerization (SPSA). These have single-domain columnar liquid crystalline structure in which columns formed stacked TPs...

The synthesis of anisotropic colloidal building blocks is essential for their self-assembly into hierarchical materials. Here, a highly efficient stabilizer-assisted liquid-crystallization-driven (SA-LCDSA) strategy was developed to achieve monodisperse polymer rods. This does not require the use block copolymers, but only homopolymers or random copolymers. resulting rods have tunable size and aspect ratios, as well well-defined columnar liquid crystal structures. integrated triphenylene...

Abstract Anisotropic colloidal particles have attracted great attention over the past few decades because of their significant properties that differ from isotropic particles. Molecular self‐assembly provides possibility to design and construct anisotropic single‐molecule level, molecular assemblies can both inherit molecules in single states integrate functions collective states, which has interest researchers. Even recent years, strategy been greatly developed. This review article briefly...

Based on the impulse radar and spread-spectrum (SS) radar, through-wall imaging with three stationary targets or a moving target in room are obtained, respectively, compared this paper. We then analyze influences of different analog-to-digital converters (ADCs) noise levels quality. Results show that SS has great advantage over some ways, such as covert waveform, engineering realization, excellent anti-noise performance, accurate tracking. Furthermore, localization accuracy is much easier to...

There is a contradiction in classical adaptive filtering algorithm that fast convergence speed comparing with low steady state error. In order to improve this contradiction, paper presents new non-parametric Variable Step-Size NLMS algorithm. The uses gradient vector's features achieve the step iteration and certain approximation process was made for it. Software simulation hardware implementation verify effectiveness of

The explosive growth of mobile data demand is becoming an increasing burden on current cellular network. To address this issue, we propose a solution opportunistic offloading for alleviating overloaded traffic. principle behind it to select few important users as seeds sharing. three critical steps are detailed follows. We first explore individual interests by the construction user profiles, which interest graph built Gaussian graphical modeling. then apply extreme value theory threshold...

Because existing time-reversal (TR) algorithms are mostly suitable for energy focusing of a single target, it is difficult to accurately locate scenes containing multiple targets. In this study, based on the temporal and spatial morphological characteristics various echo signals in B-scan single-transmission multireceiver antenna system, high-resolution hyperbolic Radon transform (HRT) applied integrate different target represent them sparsely. The domain separately independently...

Abstract The synthesis of anisotropic colloidal building blocks is essential for their self‐assembly into hierarchical materials. Here, a highly efficient stabilizer‐assisted liquid‐crystallization‐driven (SA‐LCDSA) strategy was developed to achieve monodisperse polymer rods. This does not require the use block copolymers, but only homopolymers or random copolymers. resulting rods have tunable size and aspect ratios, as well well‐defined columnar liquid crystal structures. integrated...

Network coding allows network Intermediate nodes to encode on top of data forwarding, which can improve transmission efficiency, robustness and security. However, traditional nonlinear suffers from the problems decoding complexity implementation difficulties, while real environment is often nonlinear. Machine learning-based utilizes neural networks activation functions for decoding, solves difficulties coding, where functions, as main factor introducing nonlinearity, are crucial machine...

Selective recognition of short oligonucleotides at the single-molecule level is particularly important for early disease detection and treatment. In this work, polydopamine (PDA)-coated nanopores were prepared via self-polymerization as a solid-state nanopore sensing platform oligonucleotide C (PolyC). The PDA coating possesses abundant active sites, such indole, amino, carboxyl, catechol, quinone structures, which had interactions with to slow down translocation rate. PDA-coated selectively...

High-resolution radar imaging has to be accomplished within the constraints of aperture size, frequency, and acquisition time. To achieve effective reliable imaging, we introduce a compressed sensing (CS) technology spread spectrum through-the-wall imaging. Using sparseness echo in correlation domain sparsity target information region, feasibility CS for reducing number observation points samples per point is verified. Moreover, considering high sensitivity clutter, receiver cancellation...

Real-time and accurate temperature monitoring during microwave hyperthermia (MH) remains a critical challenge for ensuring treatment efficacy patient safety. This study presents novel approach to simulate real MH precisely determine the of target region within biological tissues using temporal-informed neural network. We conducted experiments on 30 sets phantoms 10 ex vivo pork tissues. proposed perspective: evolving tissue responses continuous electromagnetic radiation stimulation are joint...

Abstract Ground Moving Target Indication is a critical field within synthetic aperture radar (SAR) research, as traditional SAR images are defocused and displaced due to the target’s trajectory-direction velocity radial velocity, respectively. Therefore, an accurate estimation of motion parameters required. This study introduces two-dimensional method for estimating target using vortex SAR. It utilises Bessel magnitude spatial phase term from echo data calculate pitch azimuth angle, which...

Abstract Ground-penetrating radar (GPR) is an effective geophysical-electromagnetic method for detecting subsurface targets. However, target echoes are often flooded by strong clutter, which affects the detection performance. Clutter suppression active area in GPR research, and current trend to use methods based on low-rank sparse decomposition (LRSD), has significant advantages over traditional methods. In recent years, tensor robust principal component analysis (TRPCA) been proposed...

Abstract A vortex synthetic aperture radar (SAR) can obtain more target information when combined with orbital angular momentum (OAM). However, ground-moving targets cause image defocusing owing to their azimuthal velocity component and imaging position offset issues due range component. on moving be acquired for analysis using SAR. This study first established an model extract from echo signals. The Doppler parameters were then estimated, improved range-Doppler algorithm was applied...

As cryptocurrency is widely used in the financial field, detecting anomalous trading behavior of blockchain-based cryptocurrencies has become increasingly important. Researchers have utilized graph convolutional neural networks (GCN) for transactions. However, GCN fails to fully capture spatial information correlation between neighboring nodes when processing data, which limits utilization structural features model. Therefore, performance may be constrained dealing with complex,...

Abstract In order to reduce the wind abandonment rate during winter heating period in “Three North” region and environmental pollution caused by carbon emissions power generation, this paper proposes a low-carbon economic dispatching model that takes into account multiple types of energy storage for electric-heating combined systems. First, multi-type with electric boilers, storage, heat as core is proposed, its internal conversion, output links are refined. Then, trading mechanism...

A spread spectrum (SS) radar is compared with a conventional impulse for through wall imaging in this paper. In order to simulate the real electromagnetic environment, all echoes are generated via modeling and simulation of finite-different time-domain (FDTD) method. Results show that SS has great advantage over some ways, such as targets recognition, engineering realization immunity from interference. The can still be recognized accurately image, even when receiving signals added -0.83dB...

A time-reversal imaging method, based on frequency-domain data sampling and the estimation of signal parameters via rotational invariance techniques (ESPRIT), is proposed to obtain with higher resolution in this paper. The algorithm obtained, which firstly applies coarse fine frequencies all received scatter signal, thus forming plurality frequency-frequency multistatic matrices (FF-MDM); subsequently, subspace obtained through application singular value decomposition (SVD) FF-MDM; finally,...

Neural style transfer has been demonstrated to be powerful in creating artistic image with help of Convolutional Networks (CNN). However, there is still lack computational analysis perceptual components the style. Different from some early attempts which studied by pre-processing or post-processing techniques, we investigate characteristics systematically based on feature map produced CNN. First, computationally decompose into basic elements using not only spectrum methods including Fast...