Resonance Theory Research Articles

Isometric Extensions of Anosov Flows via Microlocal Analysis

The aim of this note is to revisit the classical framework developed by Brin, Pesin and others to study ergodicity and mixing properties of isometric extensions of volume-preserving Anosov flows, using the microlocal framework developed in the theory of Pollicott-Ruelle resonances. The approach developed in the present note is reinvested in the companion paper [arXiv:2111.14811] in order to show ergodicity of the frame flow on negatively-curved Riemannian manifolds under nearly $1/4$-pinched curvature assumption (resp. nearly $1/2$-pinched) in dimension $4$ and $4\ell+2, \ell > 0$ (resp. dimension $4\ell, \ell > 0$).

Analysis of Induced Current on Power Transmission Lines for the Reradiation Interference in Medium Wave Based on Characteristic Modes

The reradiation interference from power transmission lines (PTL) on the adjacent wireless stations is directly caused by the induced current on metal parts, which means the interference could be suppressed by reducing the induced current. In order to effectively analyze the induced current of PTL, a method for analyzing induced current on PTL based on characteristic modes is proposed combining MoM with intrinsic modes. This method breaks through the traditional antenna resonance theory proposed by IEEE and could effectively avoid model equivalent defects and frequency limitations of traditional methods. Firstly, a generalized characteristic equation about the characteristic mode currents of PTL is constructed, and the numerical solutions of the characteristic mode currents are obtained by the idea of a discrete solution. Then, through the weighted orthogonal relationship between different characteristic mode currents, the expansion coefficients of the characteristic mode currents are obtained; finally, combined with the Poynting theorem, the physical meaning of the expansion coefficients and their related quantities are explained from the perspective of energy and the analysis of the induced current is realized from the physical level. The results of the example analysis show that the error between the peak frequencies of the induced current calculated by the method in this paper and the peak frequencies calculated by MoM does not exceed 2.46% and the method in this paper can well explain the disappearance of the “double wavelength loop resonance frequency” under the excitation of a vertically polarized plane wave.

Scattering of kinks in the [formula omitted] model

In this study, based on the φ4 model, a new model (called the Bφ4 model) is introduced in which the potential form for the values of the field whose magnitudes are greater than 1 is multiplied by the positive number B. All features related to a single kink (antikink) solution remain unchanged and are independent of parameter B. However, when a kink interacts with an antikink in a collision, the results will significantly depend on parameter B. Hence, for kink–antikink collisions, many features such as the critical speed, output velocities for a fixed initial speed, two-bounce escape windows, extreme values, and fractal structure in terms of parameter B are considered in detail numerically. The role of parameter B in the emergence of a nearly soliton behavior in kink–antikink collisions at some initial speed intervals is clearly confirmed. The fractal structure in the diagrams of escape windows is seen for the regime B≤1. However, for the regime B>1, this behavior gradually becomes fuzzing and chaotic as it approaches B=3.3. The case B=3.3 is obtained again as the minimum of the critical speed curve as a function of B. For the regime 3.3<B≤10, the chaotic behavior gradually decreases. However, a fractal structure is never observed. Nevertheless, it is shown that despite the fuzzing and shuffling of the escape windows, they follow the rules of the resonant energy exchange theory.

Determination of single-crystal elastic moduli of LiREF4 (RE = Y, Gd, and Tb) by resonant ultrasound spectroscopy

The tetragonal fluoro-scheelite LiREF4 compounds (RE=rareearth) have been shown to exhibit a variety of useful optical and magnetic properties. While LiYF4 has been widely studied, many of the fundamental thermodynamic properties of other members of this family remain unknown. Here, we report the complete elastic tensors (Cij) of single-crystalline LiYF4, LiTbF4, and LiGdF4 using resonant ultrasound spectroscopy and density functional theory (DFT). We compare the results for LiYF4 with prior experimental results using time-of-flight ultrasound methods. This is the first report, however, of the experimental elastic tensors of LiTbF4 and LiGdF4. The present results point to a softening of the elastic moduli of the LiREF4 system when Y is replaced by the larger ionic radius of Tb or Gd. Furthermore, we find that just 0.3% doping with Nd on the Y site also leads to a slight softening of the moduli. The variation of the elastic moduli as a function of temperature up to 216°C was also measured. A nearly linear softening of all seven independent elastic moduli was observed with increasing temperature. Phonon dispersions and phonon density of states obtained by DFT support the experimental finding of a significantly higher sound velocity due to lighter Y atoms in LiYF4, as compared to heavier LiTbF4 and LiGdF4.

Coupling suppression study of miniaturized BDS/GPS multifunctional transceiver antenna based on quarter-mode substrate integrated waveguide

In this paper, a miniaturized BDS/GPS multifunctional antenna based on quarter-mode substrate integrated waveguide (QMSIW) is designed. Firstly, the dimension of the antenna is significantly reduced by using QMSIW technology. Secondly, the bandwidth of the antenna unit is widened by applying the multimode resonance theory. Thirdly, the four units are rotated and placed orthogonally with a reasonable layout to reduce the isolation between the units. Finally, the four units operating at 1268/1575/1616/2492 MHz are grouped in the array and loaded with the combined resonant structure to suppress the coupling between the units further. The designed antenna array covers the bands of BDS-2 B3, GPS L1, BDS-1 L and BDS-1 S, achieving 35 MHz (1255–1290 MHz), 50 MHz (1540–1590 MHz), 45 MHz (1605–1650 MHz) and 80 MHz (2480–2560 MHz) respectively, with the operating bandwidth and peak gain are 4.22, 5.68, 5.09 and 6.3 dBi. It is worth mentioning that after the decoupling process, the isolation degree between the antenna units is significantly improved. And the peak isolation degree between the four units finally drops to −34.3 dB (S12), −29.20 dB (S23 in GPS L1) and −30.29 dB (S23 in BDS-1 L) respectively.

Resonant growth of inertial oscillations from lee waves in the deep ocean

The interactions between inertial oscillations (IO) and lee waves (LW) close to the bottom of the ocean and the role of IO in energy dissipation are addressed for a range of physical parameters typical of Southern Ocean conditions. Idealized numerical simulations in a vertical plane and resonant interaction theory are combined for this purpose. The lee waves are emitted by a uniform geostrophic flow over a sinusoidal topography for a constant buoyancy frequency at mid-latitude. We show that IO can grow by triadic resonant interactions with the LW. Two triads are dominant, which involve waves with frequency , f and , where is the intrinsic frequency of the LW and f the Coriolis frequency (assumed positive). These triads differ by the sign and value of the IO vertical wavenumber. Results from the numerical simulations show that the triad associated with the upward phase propagation of the IO is selected, consistent with oceanic observations, that a good agreement is obtained with the IO growth rate predicted theoretically and that the IO develop in a bottom layer of height less than 1000 m. A quasi-steady flow regime is eventually reached, with the IO amplitude being of the same order as the geostrophic flow speed. During this regime, depending upon the flow parameters, the IO kinetic energy is equal to 30–70% of the LW energy flux during one inertial period. This large range of values is not reflected in the turbulent kinetic energy (TKE) dissipation rate, which is comprised between 10 and 30% of the LW energy flux, whatever the IO amplitude, even if vanishingly small. Therefore, for the set of parameters we consider, the TKE dissipation rate cannot be inferred from the IO amplitude. Yet, the nonlinear interactions between the lee waves and the IO are critical in setting the energy spectrum, and similarly for the internal tide and the IO at low latitudes according to the literature. This implies that IO should be taken into account in the parameterisation of mixing in the ocean.

Positivity resonance in long-term married couples: Multimodal characteristics and consequences for health and longevity.

The Positivity Resonance Theory of coexperienced positive affect describes moments of interpersonal connection characterized by shared positive affect, caring nonverbal synchrony, and biological synchrony. The construct validity of positivity resonance and its longitudinal associations with health have not been tested. The current longitudinal study examined whether positivity resonance in conflict interactions between 154 married couples predicts health trajectories over 13 years and longevity over 30 years. We used couples' continuous ratings of affect during the interactions to capture coexperienced positive affect and continuous physiological responses to capture biological synchrony between spouses. Video recordings were behaviorally coded for coexpressed positive affect, synchronous nonverbal affiliation cues (SNAC), and behavioral indicators of positivity resonance (BIPR). To evaluate construct validity, we conducted a confirmatory factor analysis to test a latent factor of positivity resonance encompassing coexperienced positive affect, coexpressed positive affect, physiological linkage of interbeat heart intervals, SNAC, and BIPR. The model showed excellent fit. To evaluate associations with health and longevity, we used dyadic latent growth curve modeling and Cox proportional hazards modeling, respectively, and found that greater latent positivity resonance predicted less steep declines in health and increased longevity. Associations were robust when accounting for initial health symptoms, sociodemographic characteristics, health-related behaviors, and individually experienced positive affect. We repeated health and longevity analyses, replacing latent positivity resonance with BIPR, and found consistent results. Findings validate positivity resonance as a multimodal construct, support the utility of the BIPR measure, and provide initial evidence for the characterization of positivity resonance as a positive health behavior. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Multiconfigurational short-range density functional theory for nuclear magnetic resonance shielding constants with gauge-including atomic orbitals.

In this paper, we present the theory and implementation of nuclear magnetic resonance shielding constants with gauge-including atomic orbitals for the hybrid multiconfigurational short-range density functional theory model. As a special case, this implementation also includes Hartree-Fock srDFT (HF-srDFT). Choosing a complete-active space (CAS) wave function as the multiconfigurational parameterization of the wave function, we investigate how well CAS-srDFT reproduces experimental trends of nuclear shielding constants compared to DFT and complete active space self-consistent field (CASSCF). Calculations on the nucleobases adenine and thymine show that CAS-srDFT performs on average the best of the tested methods, much better than CASSCF but only marginally better than HF-srDFT. The performance, compared to regular DFT, is similar when functionals containing exact exchange are used. We generally find that the inclusion of exact exchange is important for an accurate description of the shielding constants. In cases where no exact exchange is included, we observe that the HF- and CAS-srDFT often outperform regular DFT. For calculations on transition metal nuclei in organometallic compounds with significant static correlation, the CAS-srDFT method again outperforms CASSCF compared to experimental shielding constants, and the change from HF-srDFT is substantial. In conclusion, the static correlation posed by the metal complexes seems to be captured by CAS-srDFT, which is promising since this type of correlation is not well described by regular DFT.

Analytical Solutions to Fundamental Questions for Lossy Mode Resonance

AbstractLossy mode resonance (LMR) is an optical resonance phenomenon developed in the past decade, which has been researched for sensors and filters due to its high sensitivity, low loss, and broad tunable range. As a novel technology, if an analytical mathematical model for some fundamental questions like how to design the resonance wavelength, surrounding sensitivity, resonance width, and resonance depth, it will be guiding significance to its development. Herein, this paper develops a generalized Fabry–Perot resonance theory for LMR, where the oblique incidence, cavity loss, and dispersion of substrate and cavity are comprehensively considered, and the consistency of this model and a more rigorous guided wave optics model have been verified. Then, analytical mathematical models are established and analyzed, and the designing criterion for LMR‐based optical devices is proposed. After intensive reviewing the work of predecessors, the previous experimental results are consistent with the prediction of this model, and this model can also provide some new ideas that have not been researched yet. As an assistant to wave optics theory, this paper provides a second perspective to understand LMR phenomenon, and it is hoped the analytical solutions for LMR can be a guide for designing optical devices.

Underwater low frequency Helmholtz bubble resonator

Low-frequency sound sources have found application in oceanology and geoacoustic methods of remote sensing. An underwater low-frequency sound source with a pneumatically driven bubble resonator covered with an elastic membrane effectively provides a very high source level. However, it has a narrow bandwidth, and its resonant frequency is difficult to change without changing the size of the original system. Internal acoustic resonators included in a bubble filled with gas can change the frequency response of the entire source and expand its bandwidth. Internal resonant systems can be designed so that the bubble resonator can be tuned over a wide frequency range. Other systems may add one or more internal resonances and spread the emitted spectrum over a very wide frequency band. It is possible to consider various multipole resonant systems in combination with an underwater bubble. A simple and efficient system consists of a bubble resonator and an internal Helmholtz resonator. The addition of a Helmholtz resonator converts the single resonant bubble into a double resonant system and extends its bandwidth. The theory of the underwater bubble Helmholtz resonator and various applications of these resonators for practical systems are considered. The results of the experimental verification are discussed.

SR-EM: Episodic Memory Aware of Semantic Relations Based on Hierarchical Clustering Resonance Network.

An intelligent robot requires episodic memory that can retrieve a sequence of events for a service task learned from past experiences to provide a proper service to a user. Various episodic memories, which can learn new tasks incrementally without forgetting the tasks learned previously, have been designed based on adaptive resonance theory (ART) networks. The conventional ART-based episodic memories, however, do not have the adaptability to the changing environments. They cannot utilize the retrieved task episode adaptively in the working environment. Moreover, if a user wants to receive multiple services of the same kind in a given situation, the user should repeatedly command multiple times. To tackle these limitations, in this article, a novel hierarchical clustering resonance network (HCRN) is proposed, which has a high clustering performance on multimodal data and can compute the semantic relations between learned clusters. Using HCRN, a semantic relation-aware episodic memory (SR-EM) is designed, which can adapt the retrieved task episode to the current working environment to carry out the task intelligently. Experimental simulations demonstrate that HCRN outperforms the conventional ART in terms of clustering performance on multimodal data. Besides, the effectiveness of the proposed SR-EM is verified through robot simulations for two scenarios.

Experimental and theoretical investigation of waveguided plasmonic surface lattice resonances.

Plasmonic nanostructures are good candidates for refractive index sensing applications through the surface plasmon resonance due to their strong dependence on the surrounding dielectric media. However, typically low quality-factor limits their application in sensing devices. To improve the quality-factor, we have experimentally and theoretically investigated two-dimensional gold nanoparticle gratings situated on top of a waveguide. The coupling between the localized surface plasmon and waveguide modes results in Fano-type resonances, with high quality-factors, very similar to plasmonic surface lattice resonances. By combining plasmonic surface lattice resonance and waveguide theory, we present a theoretical framework describing the structures. By immersing the fabricated samples in three different media we find a sensitivity of ∼50 nm/RIU and figure of merit of 8.9, and demonstrate good agreement with the theory presented. Further analysis show that the sensitivity is very dependent on the waveguide parameters, grating constant and the dielectric environment, and by tuning these parameters we obtain a theoretical sensitivity of 887 nm/RIU.

Empirical Analysis of Data Streaming and Batch Learning Models for Network Intrusion Detection

Network intrusion, such as denial of service, probing attacks, and phishing, comprises some of the complex threats that have put the online community at risk. The increase in the number of these attacks has given rise to a serious interest in the research community to curb the menace. One of the research efforts is to have an intrusion detection mechanism in place. Batch learning and data streaming are approaches used for processing the huge amount of data required for proper intrusion detection. Batch learning, despite its advantages, has been faulted for poor scalability due to the constant re-training of new training instances. Hence, this paper seeks to conduct a comparative study using selected batch learning and data streaming algorithms. The batch learning and data streaming algorithms considered are J48, projective adaptive resonance theory (PART), Hoeffding tree (HT) and OzaBagAdwin (OBA). Furthermore, binary and multiclass classification problems are considered for the tested algorithms. Experimental results show that data streaming algorithms achieved considerably higher performance in binary classification problems when compared with batch learning algorithms. Specifically, binary classification produced J48 (94.73), PART (92.83), HT (98.38), and OBA (99.67), and multiclass classification produced J48 (87.66), PART (87.05), HT (71.98), OBA (82.80) based on accuracy. Hence, the use of data streaming algorithms to solve the scalability issue and allow real-time detection of network intrusion is highly recommended.

An ensemble deep learning model for cyber threat hunting in industrial internet of things

By the emergence of the fourth industrial revolution, interconnected devices and sensors generate large-scale, dynamic, and inharmonious data in Industrial Internet of Things (IIoT) platforms. Such vast heterogeneous data increase the challenges of security risks and data analysis procedures. As IIoT grows, cyber-attacks become more diverse and complex, making existing anomaly detection models less effective to operate. In this paper, an ensemble deep learning model that uses the benefits of the Long Short-Term Memory (LSTM) and the Auto-Encoder (AE) architecture to identify out-of-norm activities for cyber threat hunting in IIoT is proposed. In this model, the LSTM is applied to create a model on normal time series of data (past and present data) to learn normal data patterns and the important features of data are identified by AE to reduce data dimension. In addition, the imbalanced nature of IIoT datasets has not been considered in most of the previous literature, affecting low accuracy and performance. To solve this problem, the proposed model extracts new balanced data from the imbalanced datasets, and these new balanced data are fed into the deep LSTM AE anomaly detection model. In this paper, the proposed model is evaluated on two real IIoT datasets -Gas Pipeline (GP) and Secure Water Treatment (SWaT) that are imbalanced and consist of long-term and short-term dependency on data. The results are compared with conventional machine learning classifiers, Random Forest (RF), Multi-Layer Perceptron (MLP), Decision Tree (DT), and Super Vector Machines (SVM), in which higher performance in terms of accuracy is obtained, 99.3% and 99.7% based on GP and SWaT datasets, respectively. Moreover, the proposed ensemble model is compared with advanced related models, including Stacked Auto-Encoders (SAE), Naive Bayes (NB), Projective Adaptive Resonance Theory (PART), Convolutional Auto-Encoder (C-AE), and Package Signatures (PS) based LSTM (PS-LSTM) model.

A Dual-Band Guided-Laser Absorber Based on Silicon-Nickel Metasurface

Metasurface absorbers are already used in many laser applications. To achieve laser stealth, a dual-band guided-laser absorber is presented in this paper. The absorber is composed of periodic silicon squares on a silicon film and a nickel layer. Under normal incidence, the absorber has two absorption peaks at wavelengths of 1.55 μm and 1.064 μm, with absorption rates higher than 94.4%. For wavelength-tunable 1.55 μm lasers with a large wavelength tuning range of ±50 nm, the absorption rate is still as high as 90%. Plasmonic resonance theory, as well as FDTD simulations, are used to design and study the absorber. It is found that the absorber is independent of the incident polarization and tolerant to the incident angle. The design method is flexible, and the absorber is easy to manufacture.

Dynamic electrocatalysis: Examining resonant catalytic rate enhancement under oscillating electrochemical potential

A microkinetic analysis is presented for a generalized electrocatalytic reaction mechanism to evaluate whether oscillating electrochemical potential can be used to achieve resonant catalytic rate enhancement. It is illustrated that because changing the potential changes the free energy of reaction, this approach is conceptually distinct from oscillating binding energies of catalytic intermediates as within catalytic resonance theory. For faradaic reactions in series, no enhancements relative to the maximum steady-state turnover rate (within the potential range spanned by oscillation) are achievable, even in cases where the potential limits favor adsorption and desorption, respectively. It is possible to exceed a time-averaged steady-state rate (weighted by time at each condition), although only if the elementary reactions show disparate responses to potential. In contrast, if a faradaically driven parallel reaction controls surface coverage of a strongly adsorbed blocking species, significant dynamic enhancements over the maximum steady-state can be achieved, albeit at a cost of thermodynamic efficiency. • Electrocatalytic reactions are evaluated under conditions of oscillating potential • Pure series reactions cannot exceed the steady-state rate at the highest potential • Parallel reactions can allow dynamic enhancement, but energy efficiency is sacrificed Recent simulations have shown that heterogeneous catalysts with dynamic properties—for example, the ability to vary adsorbate binding energy with time—could, in principle, give higher rates than an optimized catalyst operating at steady state (i.e., the Sabatier principle or “volcano curve” maximum, assuming typical correlations shaping the energy landscape of the reaction). Enhancements may be realized by oscillating catalyst properties at frequencies near the timescales of the elementary steps. Variation of electrochemical potential has been proposed as a possible method to induce such rate enhancements in electrocatalytic systems, but the extent to which this method could be effective has not been fully explored. Deeper understanding of electrochemical systems is also broadly critical, as electrocatalysis is well suited to utilize energy from renewables such as wind and solar power for the production of fuels, chemicals, and materials with low carbon intensity. Certain electrocatalytic reactions can be accelerated by varying the applied potential with time. Requirements for this promotional effect are identified and contrasted with other approaches attempting to create catalysts that accelerate reaction rates with dynamically tunable surface properties.

Noisy Low-Illumination Image Enhancement Based on Parallel Duffing Oscillator and IMOGOA

In complex environment, the captured images face several kinds of problems, including low illumination and intensive noise, which deteriorates image quality and has a great impact on the follow-up work. In this work, inspired by stochastic resonance theory, we design a model that considers the spatial characteristics of image and noise reduction and enhancement are simultaneously realized. The 8-neighborhood pixel extraction method and the Duffing oscillator model are used to parallel process the image, and then the image details are restored by homomorphic filter. In order to optimize the parameters of parallel Duffing oscillator model and homomorphic filter adaptively, multiobjective grasshopper optimization algorithm is introduced into the method. Sobol sequence and differential mutation operators are used to improve the optimization algorithm, and the fitness function is constructed by using peak signal-to-noise ratio and standard deviation. To verify the effectiveness of the proposed method, low-illumination image data with Gaussian noise is used for subjective and objective evaluation. The experimental results show that the proposed algorithm gives prominence to useful information, which has smaller color distortion and better visual quality.

A new structure of a miniature and flexible printed UHF RFID TAG

A new Miniaturized RFID tag has been designed and optimized using meander theory and split ring resonator theory. The proposed RFID tag is designed and adapted for an UHF chip with Zchip=30.39-i*211Ohm. The proposed RFID tag is simulated using an EM solver and supported to operate in UHF sub-band [866.9-870.9MHz] with a band width of 4MHz. A prototype has been fabricated using inkjet method on a polyimide substrate and has been tested using a RFID base station which has proved an excellent agreement between theoretical reading range and experiment which is over up 4m.The miniaturized RFID tag is highly suitable for applications require a middle range between 4 and 8m and a flexible compact RFID tag for integration on items such clothing application and access control.

When “meaningless” means more: biographic resonance and audience appreciation of popular entertainment

Abstract Integrating predictions derived from the self-memory system and biographic resonance theory, the current project investigated the relationship between media-induced reminiscence and appreciation. In two experiments, undergraduates consumed popular entertainment from either their early adolescence or the present day. Study 1 (N = 406) featured music, and Study 2 (N = 405) featured movies. Both studies found that memory recall was more common in response to older (vs. recent) entertainment, and the memories activated by older entertainment were happier and produced more temporal comparisons. Although appreciation was higher for older entertainment in Study 1, this effect did not replicate in Study 2. However, both studies found that appreciation was higher for content that activated memories, especially memories that were more emotional and immersive. These patterns emerged regardless of when the content was released. These findings clarify why audiences sometimes perceive meaning in lighthearted entertainment, such as pop music or superhero films.

A review of the theory of 3‐D Alfvén (field line) resonances

This review article aims to summarise recent developments in Alfvén resonance theory, with a focus on applications to magnetospheric ultra-low frequency (ULF) waves, though many of the ideas are relevant for applications in other fields as well. The key aspect we treat is how Alfvén resonance manifests in a fully 3-D varying medium. The prerequisite ideas are developed in a reasonably comprehensive introduction, which would be a good starting point for any interested reader looking to gain an understanding of the Alfvén resonance process, as well as where to find associated reading. The main part of the review is split into three sections. We firstly consider results from numerical simulations of relatively simple magnetic field geometries, such as 2-D and 3-D dipoles, to develop the fundamental properties of 3-D Alfvén resonances. Secondly, we review previous simulations in more general magnetic field geometries, reconciling these results with those from the simpler dipole cases. Thirdly, in light of these numerical results, we review theoretical studies using various analytical methods to find approximate solutions to the pertinent magnetohydrodynamic (MHD) equations. The review is concluded with a discussion of these different approaches, as well as linking these ideas to their importance for observations. Finally, we discuss potential future developments in this research area.