Asymmetric Decomposition Research Articles

Asymmetric Decomposition of Single Carrier QAM for Efficiency Enhancement of PAs

Asymmetric Decomposition of Single Carrier QAM for Efficiency Enhancement of PAs

Multiscale Feature Search-Based Graph Convolutional Network for Hyperspectral Image Classification

With the development of hyperspectral sensors, the availability of hyperspectral images (HSIs) has increased significantly, prompting advancements in deep learning-based hyperspectral image classification (HSIC) methods. Recently, graph convolutional networks (GCNs) have been proposed to process graph-structured data in non-Euclidean domains, and have been used for HSIC. The superpixel segmentation should be implemented first in the GCN-based methods, however, it is difficult to manually select the optimal superpixel segmentation sizes to obtain the useful information for classification. To solve this problem, we constructed a HSIC model based on a multiscale feature search-based graph convolutional network (MFSGCN) in this study. Firstly, pixel-level features of HSIs are extracted sequentially using 3D asymmetric decomposition convolution and 2D convolution. Then, superpixel-level features at different scales are extracted using multilayer GCNs. Finally, the neural architecture search (NAS) method is used to automatically assign different weights to different scales of superpixel features. Thus, a more discriminative feature map is obtained for classification. Compared with other GCN-based networks, the MFSGCN network can automatically capture features and obtain higher classification accuracy. The proposed MFSGCN model was implemented on three commonly used HSI datasets and compared to some state-of-the-art methods. The results confirm that MFSGCN effectively improves accuracy.

Can geopolitical risk stably predict crude oil prices? A multi-dimensional perspective

This study aims to examine the stability of the lead-lag relationship between geopolitical risk and crude oil prices. To this end, a Granger causality test is conducted, using a lag-augmented vector autoregression model and monthly data from 1997 to 2022. The results show a significant full-sample bilateral Granger causality. The recursive expanding window method and the asymmetric decomposition technique are also used to find that the relationship between geopolitical risk and crude oil prices is complex and time-varying, with asymmetry. The wavelet decomposition analysis shows that this complexity is mainly due to short-term structural changes. When these fluctuations are excluded, the impact of geopolitical risk on crude oil prices (and vice versa) no longer shows time-varying characteristics or asymmetry. This stable relationship provides a new perspective for predicting crude oil prices in the face of geopolitical risk. Given the importance of both geopolitical risk and crude oil prices in the fields of economy, finance, and politics, this research and the accompanying results have implications for informed decision-making by investors and policy makers.

An ISAR and Visible Image Fusion Algorithm Based on Adaptive Guided Multi-Layer Side Window Box Filter Decomposition

Traditional image fusion techniques generally use symmetrical methods to extract features from different sources of images. However, these conventional approaches do not resolve the information domain discrepancy from multiple sources, resulting in the incompleteness of fusion. To solve the problem, we propose an asymmetric decomposition method. Firstly, an information abundance discrimination method is used to sort images into detailed and coarse categories. Then, different decomposition methods are proposed to extract features at different scales. Next, different fusion strategies are adopted for different scale features, including sum fusion, variance-based transformation, integrated fusion, and energy-based fusion. Finally, the fusion result is obtained through summation, retaining vital features from both images. Eight fusion metrics and two datasets containing registered visible, ISAR, and infrared images were adopted to evaluate the performance of the proposed method. The experimental results demonstrate that the proposed asymmetric decomposition method could preserve more details than the symmetric one, and performed better in both objective and subjective evaluations compared with the fifteen state-of-the-art fusion methods. These findings can inspire researchers to consider a new asymmetric fusion framework that can adapt to the differences in information richness of the images, and promote the development of fusion technology.

Microdynamics of active particles in defect-rich colloidal crystals

Hypothesis. Because they are self-propulsive, active colloidal particles can interact with their environment in ways that differ from passive, Brownian particles. Here, we explore how interactions in different microstructural regions may contribute to colloidal crystal annealing.Experiments. We investigate active particles propagating in a quasi-2D colloidal crystal monolayer produced by alternating current electric fields (active-to-passive particle ratio ∼ 1:720). The active particle is a platinum Janus sphere propelled by asymmetric decomposition of hydrogen peroxide. Crystals are characterized for changes in void properties. The mean-squared-displacement of Janus particles are measured to determine how active microdynamics depend on the local microstructure, which is comprised of void regions, void-adjacent regions (defined as within three particle diameters of a void), and interstitial regions.Findings. At active particle energy EA = 2.55 kBT, the average void size increases as much as three times and the average void anisotropy increases about 40% relative to the passive case. The average microdynamical enhancement, <δ(t)>, of Janus particles in the crystal relative to an equivalent passive Janus particle is reduced compared to that of a free, active particle (<δ(t) > is 1.88 ± 0.04 and 2.66 ± 0.08, respectively). The concentration of active particles is enriched in void and void-adjacent regions. Active particles exhibit the greatest change in dynamics relative to the passive control in void-adjacent regions (<δ(t)> = 2.58 ± 0.06). The results support the conjecture that active particle microdynamical enhancement in crystal lattices is affected by local defect structure.

Metal‐Organic‐Framework based Catalytic Micromotor for Enhanced Water Decontamination

AbstractThis work demonstrates the application of a Fe3O4/zeolitic imidazolate framework 67 (ZIF67) micromotor for improved catalytic degradation of organic pollutants. The micromotors were fabricated by simple adsorption of Fe3O4 nanoparticles on the surface of ZIF67 microparticles, which were synthesized by wet chemistry method. Both Fe3O4 and ZIF67 perform asymmetric decomposition of H2O2 to achieve bubble propulsion of the micromotors. The ferromagnetism of Fe3O4 enables easy directional control of the micromotor. The porous structure of ZIF67 benefits the enrichment of pollutant molecules around the micromotors, facilitating the efficient catalytic degradation. With intensified interaction between active sites and pollutant molecules due to self‐propelled motion and synergistic catalysis of iron in Fe3O4 and zinc ions in ZIF67, the micromotors exhibit enhanced degradation activity of methylene blue as compared to the pure Fe3O4 or ZIF67 counterparts without autonomous motion. This research can be extended to developing other metal‐organic frameworks (MOF)‐integrated micromotors for the environmental applications.

TiO2@carbon microsphere core–shell micromotors for photocatalytic water remediation

Photocatalytic micromotors hold considerable promise for use in water remediation owing to the synergistic effect of a combination of photocatalytic activity and self-propulsive behavior. We designed a symmetric TiO2@carbon microsphere (CMS) core–shell micromotor with photocatalytic TiO2 for enhanced degradation of organic contaminants. TiO2@CMS micromotors were obtained via a facile sol–gel method and subsequent heat treatment to obtain an anatase TiO2 shell. The self-propulsion of TiO2@CMS micromotors is governed by asymmetric decomposition of H2O2 via asymmetric illumination of the spherical particles. The photocatalytic propulsion can be switched on and off by modulating the incident light. The speed of the photocatalytic TiO2@CMS core–shell micromotors can be increased by increasing either the light intensity or concentration of the chemical fuel, i.e., H2O2. In the degradation of rhodamine B, the photocatalytic performance of the micromotors was higher than those achieved with control group photocatalysts. The degradation efficiency reached ∼100% in approximately 60 min when all necessary conditions, i.e., use of micromotors, UV irradiation, and H2O, were applied. TiO2@CMS core–shell micromotors have the advantages of facile preparation, a simple structure, self-propulsion, and a high degradation efficiency and photocatalytic performance. They will therefore be important in the development of methods for water purification and wastewater treatment.

Injectable Micromotor@Hydrogel System for Antibacterial Therapy.

The drug delivery system based on nano/micromotors has become a research hot spot in recent years. However, naked micromotors may be ruptured or passivated under the complex biological environment, which will result in the leakage of drugs in advance or limited self-propulsion performance. Herein, an injectable micromotor@hydrogel drug delivery system to protect micromotors from the external environment is proposed. The micromotors were prepared through layer-by-layer assembly technology. The asymmetric decomposition of hydrogen peroxide catalyzed by the locally distributed platinum nanoparticles enabled efficient propulsion of the micromotors in low concentration of hydrogen peroxide. In order to protect micromotors, they were loaded into the Schiff base hydrogel. The micromotor@hydrogel system can be injected directly into the lesion to release micromotors in response to the environment, reducing external influence on micromotors and improving the sustained-release effect. Erythromycin (Ery) loaded into the micromotors and the micromotor@hydrogel system demonstrated excellent antibacterial effect. Micromotors released from the hydrogel underwent enhanced diffusion in the surroundings of bacteria without addition of exogenous hydrogen peroxide, which was manifested by their appearance in edge of the inhibition zone. The proposed micromotor@hydrogel drug delivery system offers a new strategy for the treatment of bacterial infections.

Active, Yet Little Mobility: Asymmetric Decomposition of H2O2 Is Not Sufficient in Propelling Catalytic Micromotors.

A popular principle in designing chemical micromachines is to take advantage of asymmetric chemical reactions such as the catalytic decomposition of H2O2. Contrary to intuition, we use Janus micromotors half-coated with platinum (Pt) or catalase as an example to show that this ingredient is not sufficient in powering a micromotor into self-propulsion. In particular, by annealing a thin Pt film on a SiO2 microsphere, the resulting microsphere half-decorated with discrete Pt nanoparticles swims ∼80% more slowly than its unannealed counterpart in H2O2, even though they both catalytically produce comparable amounts of oxygen. Similarly, SiO2 microspheres half-functionalized with the enzyme catalase show negligible self-propulsion despite high catalytic activity toward decomposing H2O2. In addition to highlighting how surface morphology of a catalytic cap enables/disables a chemical micromotor, this study offers a refreshed perspective in understanding how chemistry powers nano- and microscopic objects (or not): our results are consistent with a self-electrophoresis mechanism that emphasizes the electrochemical decomposition of H2O2 over nonelectrochemical pathways. More broadly, our finding is a critical piece of the puzzle in understanding and designing nano- and micromachines, in developing capable model systems of active colloids, and in relating enzymes to active matter.

3-D-ANAS: 3-D Asymmetric Neural Architecture Search for Fast Hyperspectral Image Classification

Hyperspectral images (HSIs) provide abundant spectral and spatial information, playing an irreplaceable role in land-cover classification. Recently, based on deep learning (DL) technologies, an increasing number of HSI classification approaches have been proposed, which demonstrate promising performance. However, previous studies suffer from two major drawbacks: 1) the architecture of most DL models is manually designed, relies on specialized knowledge, and is relatively tedious. Moreover, in HSI classifications, datasets captured by different sensors have different physical properties. Correspondingly, different models need to be designed for different datasets, which further increases the workload of designing architectures and 2) the mainstream framework is a patch-to-pixel framework. The overlap regions of patches of adjacent pixels are calculated repeatedly, which increases computational cost and time cost. In addition, the classification accuracy is sensitive to the patch size, which is artificially set based on extensive investigation experiments. To overcome the issues mentioned above, we first propose a 3-D asymmetric neural network search algorithm and leverage it to automatically search for efficient architectures for HSI classifications. By analyzing the characteristics of HSIs, we specifically build a 3-D asymmetric decomposition search space, where spectral and spatial information is processed with different decomposition convolutions. Furthermore, we propose a new fast classification framework, i.e., pixel-to-pixel classification framework, which has no repetitive operations and reduces the overall cost. Experiments on three public HSI datasets captured by different sensors demonstrate the networks designed by our 3-D asymmetric neural architecture search (3-D-ANAS) achieve competitive performance compared to several state-of-the-art methods, while having a much faster inference speed. Code is available at: <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/hkzhang91/3D-ANAS</uri> .

Trotter errors in digital adiabatic quantum simulation of quantum ℤ2 lattice gauge theory

Trotter decomposition is the basis of the digital quantum simulation. Asymmetric and symmetric decompositions are used in our GPU demonstration of the digital adiabatic quantum simulations of (2[Formula: see text]+[Formula: see text]1)-dimensional quantum [Formula: see text] lattice gauge theory. The actual errors in Trotter decompositions are investigated as functions of the coupling parameter and the number of Trotter substeps in each step of the variation of coupling parameter. The relative error of energy is shown to be equal to the Trotter error usually defined in terms of the evolution operators. They are much smaller than the order-of-magnitude estimation. The error in the symmetric decomposition is much smaller than that in the asymmetric decomposition. The features of the Trotter errors obtained here are useful in the experimental implementation of digital quantum simulation and its numerical demonstration.

Simple and Continuous Fabrication of Self-Propelled Micromotors with Photocatalytic Metal-Organic Frameworks for Enhanced Synergistic Environmental Remediation.

This work reports on a simple and general strategy for continuous fabrication of self-propelled micromotors with photocatalytic metal-organic frameworks (MOFs) for enhanced synergistic degradation of organic contaminants. With emulsion microdroplets from microfluidics as templates, uniform porous micromotors decorated with Fe3O4@Ag nanoparticles (Fe3O4@AgNPs) at the bottom and zeolitic imidazolate framework-8@ZnO nanoparticles (ZIF-8@ZnONPs) on the surface can be synthesized. The spatial location of ZIF-8@ZnONPs and Fe3O4@AgNPs in micromotors is accurately controlled in one step via their directional migration in the confined microspace of emulsion droplets driven by interfacial energy and magnetic field. The nanoengines Fe3O4@AgNPs enable asymmetric decomposition of H2O2 for bubble-propelled motion and easy magnetic recycling of the micromotor. The porous structures of micromotors provide a large surface area, benefiting decoration of Fe3O4@AgNPs and their contact with H2O2 for promoting bubble generation and reduced micromotor weight for promoting bubble-propelled motion. The nanophotocatalysts ZIF-8@ZnONPs allow enrichment of organic contaminant molecules via adsorption for efficient photocatalytic degradation. With synergistic coupling of the photocatalysis of ZIF-8@ZnONPs and advanced oxidation of the H2O2/UV system, the micromotors with bubble-propelled motion for improved mixing can achieve enhanced degradation of organic contaminants via dual synergistic degradation mechanisms. As highlighted by degradation of rhodamine B, the micromotors exhibit the highest degradation performance as compared to control groups with a single degradation mechanism and with dual degradation mechanisms but without self-propelled motion. This simple fabrication strategy is general and can be flexibly extended to other MOF materials, which may open up new avenues for developing advanced MOF-integrated micromotors for myriad applications.

Study on the Movements of Organometallic Halide Perovskite Crystals on their Films

AbstractRecently, organometallic halide perovskites (OMHPs) have attracted significant attention due to their high light absorption coefficient, high charge carrier mobility, and long carrier lifetime. One of the key shortcomings of the OMHP device application is its poor stability under humid conditions. Thus, it is important to study the relationship between humidity and OMHP crystals in their thin films. In this work, the large‐scale movement behavior of CH3NH3PbI3‐xClx crystals in their films is discovered. It is concluded that the number of moving CH3NH3PbI3‐xClx crystals can be controlled by the humidity of the external environment. The movement behavior of the perovskite grains is attributed to the asymmetric decomposition of perovskite under high relative humidity (RH) conditions.

Hollow mesoporous carbon@Pt Janus nanomotors with dual response of H2O2 and near-infrared light for active cargo delivery

Mesoporous carbon nanoparticles (NPs) are widely used to construct nano-theranostic systems due to their excellent physicochemical properties. Herein, we introduce these mesoporous NPs as nanocarriers to build self-propelled transport systems. Such nanocarriers are successfully fabricated by depositing Pt NPs onto the half-sphere surface. Compared with conventional silica-based nanomotors, hollow mesoporous carbon nanospheres (HMCNs) based nanomotors can achieve a high loading efficiency (1370 mg/g) of anticancer drug doxorubicin hydrochloride (DOX) due to its hydrophobic nature. The enhanced motion is observed by introducing the NIR-light irradiation due to the local thermophoresis from the upward temperature of HMCNs and also observed by introducing H2O2 that drives the HMCNs@Pt by the asymmetric decomposition. Interestingly, such enhanced motion also results in the increase of the amount of HMCNs adhering to the surface of living cancer cells, which is beneficial for enhancing the efficiency of drug delivery. This synergetic carbon-based transport system with high cargo loading capacity and dual actuated autonomous motion ability displays immense potential for further functional “smart” devices.

Potential Uncertainties in the Analysis of Low-Wavenumber Asymmetries Caused by Aliasing Center in Tropical Cyclones

Variations in both symmetric wind components and asymmetric wave amplitudes of a tropical cyclone depend on the location of its center. Because the radial structure of asymmetries is critical to the wave–mean interaction, this study, under idealized conditions, examines the influences of a center location on the radial structure of the diagnosed asymmetries. It has been found that the amplitudes of aliasing asymmetries are mainly affected by the initial symmetric fields. Meanwhile, the radial structure of asymmetry is controlled by the aliasing direction. Sensitivity tests on the location of the center were employed to emphasize the importance of the aliasing direction using angular momentum equations. With a small displacement, the tendencies of azimuthal tangential wind are found to reverse completely when the center shifts to a different direction. This work concludes that the diagnostic results related to asymmetric decomposition should be treated rigorously, as they are prone to inaccuracies, which in turn affect cyclone prediction.

Bound-State Soliton Solutions of the Nonlinear Schrödinger Equation and Their Asymmetric Decompositions* *Supported by the National Natural Science Foundation of China under Grant Nos 11671219 and 11801510.

We study the asymmetric decompositions of bound-state (BS) soliton solutions to the nonlinear Schrödinger equation. Assuming that the BS solitons are split into multiple solitons with different displacements, we obtain more accurate decompositions compared to the symmetric decompositions. Through graphical techniques, the asymmetric decompositions are shown to overlap very well with the real trajectories of the BS soliton solutions.

Distributed multi‐area load flow for multi‐microgrid systems

Due to deregulation of distribution network investment businesses, geographically divided microgrids may be owned and operated by different entities. In this study, distributed multi-area load flow (LF) calculation method that can preserve the operational independence of each entity is necessary. However, conventional fixed-point iteration-based distributed LF (DLF) algorithm may encounter convergence problems in active distribution networks integrated with high penetration of distributed generators (DGs). In this work, the authors propose a more general and novel DLF algorithm to better accommodate the integration of DGs. In this algorithm, the original non-convex LF model for multi-microgrid systems is convexified into a second-order conic LF problem and then decomposed into a regional LF subproblem using a modified alternating direction method of multipliers (ADMM). The conventional ADMM is enhanced by asymmetric decomposition and partial boundary penalty relaxation with regard to the specific LF problem structure to accelerate the convergence procedure. Numerical tests on an IEEE 69-bus distribution system and a 345-bus system show that the proposed method outperforms the fixed-point iteration-based DLF method.

Greyscale image encoding and watermarking based on optical asymmetric cryptography and variational image decomposition

ABSTRACTIn this paper, a novel greyscale image encoding and a watermarking scheme based on optical asymmetric cryptography and variational image decomposition (VID) are proposed. In this proposed scheme, the greyscale watermark is encoded into a noise-like pattern by the phase-truncated Fresnel transform (PT-FrT)-based optical asymmetric cryptography. The greyscale host image is decomposed into its cartoon part and texture part by the VID technique. After that, the encoded watermark is embedded into the host image’s texture part by a discrete wavelet transform (DWT) based fusion approach. The proposed scheme can achieve a better watermark invisibility and a higher robustness by embedding the watermark into the host image’s texture part. Additionally, the proposed scheme can achieve a high security, because the PT-FrT-based optical asymmetric cryptography can resist some common cryptographic attacks. The feasibility, robustness and security of the proposed scheme have been demonstrated by extensive experiments and comparison with other relevant image encoding and watermarking schemes.

Color information verification system based on singular value decomposition in gyrator transform domains

A new color image security system based on singular value decomposition (SVD) in gyrator transform (GT) domains is proposed. In the encryption process, a color image is decomposed into red, green and blue channels. Each channel is independently modulated by random phase masks and then separately gyrator transformed at different parameters. The three gyrator spectra are joined by multiplication to get one gray ciphertext. The ciphertext is separated into U, S, and V parts by SVD. All the three parts are individually gyrator transformed at different transformation angles. The three encoded information can be assigned to different authorized users for highly secure verification. Only when all the authorized users place the U, S, and V parts in correct multiplication order in the verification system, the correct information can be obtained with all the right keys. In the proposed method, SVD offers one-way asymmetrical decomposition algorithm and it is an optimal matrix decomposition in a least-square sense. The transformation angles of GT provide very sensitive additional keys. The pre-generated keys for red, green and blue channels are served as decryption (private) keys. As all the three encrypted parts are the gray scale ciphertexts with stationary white noise distributions, which have camouflage property to some extent. These advantages enhance the security and robustness. Numerical simulations are presented to support the viability of the proposed verification system.

An Asymmetric Proximal Decomposition Method for Convex Programming with Linearly Coupling Constraints

The problems studied are the separable variational inequalities with linearly coupling constraints. Some existing decomposition methods are very problem specific, and the computation load is quite costly. Combining the ideas of proximal point algorithm (PPA) and augmented Lagrangian method (ALM), we propose an asymmetric proximal decomposition method (AsPDM) to solve a wide variety separable problems. By adding an auxiliary quadratic term to the general Lagrangian function, our method can take advantage of the separable feature. We also present an inexact version of AsPDM to reduce the computation load of each iteration. In the computation process, the inexact version only uses the function values. Moreover, the inexact criterion and the step size can be implemented in parallel. The convergence of the proposed method is proved, and numerical experiments are employed to show the advantage of AsPDM.