Symmetric Behavior Research Articles

Discretionary dissemination on Twitter

AbstractThe study provides large‐scale descriptive evidence on the timing and nature of corporate financial tweeting. Using an unsupervised machine learning approach to analyze 24 million tweets posted by S&P 1500 firms from 2012 to 2020, we find that firms are more likely to tweet financial information around significantly negative or positive news events, such as earnings announcements and the filing of financial statements. This convex U‐shaped relation between the likelihood of posting financial tweets and the materiality of accounting events becomes stronger over time. Whereas research based on early samples concludes that firms are less likely to disseminate financial information on Twitter when the news is bad and material, the symmetric dissemination behavior we find suggests that these conclusions should be revised. We also show that a machine learning algorithm (Twitter‐Latent Dirichlet Allocation) is superior to a dictionary approach in classifying short messages like tweets.

The Time Series Classification of Discrete-Time Chaotic Systems Using Deep Learning Approaches

Discrete-time chaotic systems exhibit nonlinear and unpredictable dynamic behavior, making them very difficult to classify. They have dynamic properties such as the stability of equilibrium points, symmetric behaviors, and a transition to chaos. This study aims to classify the time series images of discrete-time chaotic systems by integrating deep learning methods and classification algorithms. The most important innovation of this study is the use of a unique dataset created using the time series of discrete-time chaotic systems. In this context, a large and unique dataset representing various dynamic behaviors was created for nine discrete-time chaotic systems using different initial conditions, control parameters, and iteration numbers. The dataset was based on existing chaotic system solutions in the literature, but the classification of the images representing the different dynamic structures of these systems was much more complex than ordinary image datasets due to their nonlinear and unpredictable nature. Although there are studies in the literature on the classification of continuous-time chaotic systems, no studies have been found on the classification of discrete-time chaotic systems. The obtained time series images were classified with deep learning models such as DenseNet121, VGG16, VGG19, InceptionV3, MobileNetV2, and Xception. In addition, these models were integrated with classification algorithms such as XGBOOST, k-NN, SVM, and RF, providing a methodological innovation. As the best result, a 95.76% accuracy rate was obtained with the DenseNet121 model and XGBOOST algorithm. This study takes the use of deep learning methods with the graphical representations of chaotic time series to an advanced level and provides a powerful tool for the classification of these systems. In this respect, classifying the dynamic structures of chaotic systems offers an important innovation in adapting deep learning models to complex datasets. The findings are thought to provide new perspectives for future research and further advance deep learning and chaotic system studies.

Chiral whispering gallery modes and chirality-dependent symmetric optical force induced by a spin-polarized surface wave of photonic Dirac semimetal.

Dirac degeneracy is a fourfold band crossing point in a three-dimensional momentum space, which possesses Fermi-arc-like surface states, and has extensive application prospects. In this work, we systematically study the exceptional effects of the robust chiral surface wave supported by photonic Dirac semimetal acts on the dielectric particles. Theoretical results show that orthogonal electromagnetic modes and helical or chiral whispering gallery modes (WGMs) of dielectric particles can be efficiently excited by the unidirectional spin-polarized surface wave. More importantly, optical forces exerted by the spin-polarized surface wave exhibit chirality-dependent symmetric behavior and high chiral Q factor with precise size selectivity. Our findings may provide potential applications in the area of chiral microcavity, spin optical devices, and optical manipulations.

Origin of the up/down poloidal asymmetric dependence of ELM control in ITER-like RMP configuration in KSTAR

Recent edge-localized modes (ELM) control experiments via resonant magnetic perturbation (RMP) in KSTAR have shown a strong up/down poloidal asymmetric coupling dependence. Specifically, in lower single null (LSN) plasmas at q95 ≳ 5, the lower two-row (middle/bottom) RMPs among ITER-like three-row (top/middle/bottom) in-vessel control coils (IVCC) in KSTAR were more effective in suppressing ELM-crashes than the upper two-row (top/middle) RMPs. In contrast, at q 95 ∼ 4, the upper two-row RMPs turned out to be more effective than the lower counterpart. Since the ITER baseline scenario is planned to operate at q 95 ∼ 3, the understanding of the origin of such up/down poloidal asymmetric coupling dependence, as well as the prediction about ITER-relevant conditions at a lower q 95, would be quite important and potentially impactful to the RMP ELM control in ITER. A linear, resistive, single-fluid MHD code MARS-F has been utilized to address and model the up/down poloidal asymmetric RMP coupling dependence. Specifically, based on two contrasting exemplary discharges with up/down poloidal (i) asymmetric at q 95 ∼ 4 and (ii) symmetric behavior at q 95 ∼ 5, among tens of otherwise similar discharges, a systematic MARS-F modeling has been thoroughly conducted. As a result, the plasma response investigation suggests that the X-point displacement (ξ X), rather than any other figures of merit, would be a directly relevant metric for the up/down poloidal asymmetric coupling in RMP-driven, ELM-crash suppression in KSTAR. Based on a sensitivity study of the edge safety factor in MARS-F modeling, the ξ X variation follows the same quantitative trend as observed in experiments. However, no or little plasma pressure dependence has been found, though ξ X increases with plasma pressure. At the ITER-relevant low q 95 ∼ 3 in a scaled KSTAR equilibrium, such modeling predicts the upper two-row RMPs would be more favorable in suppressing the ELM-crashes than the lower counterpart.

Spacing distribution for quantum Rabi models * *Dedicated to Mr. Hiromichi Shinohara, who was instrumental in establishing NTT-IFM, on his 70th birthday.

The asymmetric quantum Rabi model (AQRM) is a fundamental model in quantum optics describing the interaction of light and matter. Besides its immediate physical interest, the AQRM possesses an intriguing mathematical structure which is far from being completely understood. In this paper, we focus on the distribution of the level spacing, the difference between consecutive eigenvalues of the AQRM in the limit of high energies, i.e. large quantum numbers. In the symmetric case, that is the quantum Rabi model (QRM), the spacing distribution for each parity (given by the Z2 -symmetry) is fully clarified by an asymptotic expression derived by de Monvel and Zielinski, though some questions remain for the full spectrum spacing. However, in the general AQRM case, there is no parity decomposition for the eigenvalues. In connection with numerically exact studies and recent theoretical results, we describe the spacing distribution for the AQRM which is characterized by a new type of periodicity and symmetric behavior of the distribution with respect to the bias parameter, reflecting the hidden symmetry of the AQRM. In addition, we observe in the AQRM the excited state quantum phase transition for large values of the bias parameter, analogous to the QRM with large qubit energy, and an internal symmetry of the level spacing distribution for fixed bias. This novel symmetry is independent from the symmetry for half-integer bias and not explained by current theoretical knowledge.

Convergence-Related Serviceability Limit States of Segmental Tunnel Rings: Lessons Learned from Structural Analysis of Real-Scale Tests

An extended hybrid method for the analysis of the symmetric structural behavior of segmental tunnel linings is proposed. Their deformations cannot be determined by the traditional hybrid methods when the convergences are close to the serviceability limit states (SLSs). Two real-scale tests are employed for the validation of the proposed method. It involves structural analysis that is based on transfer relations. They represent analytical solutions of the linear theory of thin circular arches, and they contain the symmetric mode of rigid-body displacements. The method is termed hybrid because it is based on two types of input, namely the external loading and experimental data of displacements monitored during the test. It is termed extended because, additionally, the vertical and horizontal convergences are employed to produce more accurate structural deformations than obtained by the traditional hybrid method. The latter is found to be unsuitable for structural analysis after sudden failure has occurred in the vicinity of segmental interfaces. At the respective load steps, the structures were in convergence-related serviceability class C, referring to endangered serviceability. The local failures occurring at these load steps resulted in a rapid increase in the structural deformations and fast attainment of the SLS. If, in convergence-related serviceability class C, local failures at segmental interfaces are detected, the strengthening of the structure is necessary. This cannot be delayed to the attainment of serviceability class D, i.e., to reaching the SLS.

Fabrication of in situ polymerized polyaniline‐based functional nanofibrous structures for flexible electromechanical devices

AbstractRecently, flexible electromechanical devices (EMDs) emerged as alternatives to rigid electronics, promoting polymeric materials over traditional semiconductors. This study develops EMDs using conductive nanofibrous membranes of thermoplastic polyurethane (TPU), polyaniline (PANI), and multi‐walled carbon nanotubes (MWCNTs) in various structures. The fabrication technique included the combination of electrospinning and in situ polymerization to create random and aligned conductive membranes. Morphological, mechanical, thermomechanical, and electrical characterizations were conducted to assess their potential in EMDs applications. Mechanical testing revealed that, in comparison to aligned pure TPU mats, aligned TPU/PANI and TPU/MWCNTs/PANI membranes exhibited maximum strains of 26% and 19%, respectively. Meanwhile, randomly oriented mats, TPU/PANI and TPU/MWCNTs/PANI demonstrated maximum strains of 18% and 27%, respectively. Moreover, incorporating PANI and/or MWCNTs increased the Young's modulus. Thermogravimetric analysis showed thermal stability up to 250°C for all mats, with TPU/PANI mats demonstrating superior stability. Dynamic mechanical analysis revealed that PANI incorporation increased the storage modulus from 119 and 180 MPa to 2012 and 1367 MPa for aligned and random mats, respectively, compared with pure TPU mats. The combination of MWCNTs and PANI yielded moduli of 1501 and 1096 MPa, respectively. All conductive mats exhibited symmetric ohmic behavior, with conductivities varying based on orientation and composition. Specifically, TPU/PANI and TPU/MWCNTs/PANI mats exhibited conductivities of 0.83 and 1.78 S/cm for aligned mats, and 0.35 and 0.67 S/cm for random mats, respectively. Pure TPU, on the other hand, displayed a conductivity of 1.8 × 10−10 S/cm, indicating a significantly lower conductivity compared with the other mats.

Effect of geometry on the coefficient of performance of Ni–Ti elastocaloric parts manufactured via powder bed fusion

This study investigates the greater coefficient of Performance (COP) exhibited by the Ni–Ti lattice geometry (LS) over the solid geometry (SS) for solid-state heating and cooling. The LS's advantageous COP can be attributed to factors including variations in phase transformation behavior, a larger surface area facilitating enhanced heat transfer, and a greater volume of water heated per cycle owing to the cavities. Moreover, the LS demands lower compression forces due to its lower mass and geometry, which contribute to its heightened energy efficiency. Remarkably, the LS achieved a maximum temperature span of 11.2 °C at 40 kN compression force, whereas the SS required 80 kN to attain a similar 12.9 °C span. Both the SS and LS showcased a non-linear correlation with compression force which was attributed to Lauder's transformation and pseudo-elastic behaviors. Additionally, the temperature span of the SS exhibited symmetrical behavior during heating-cooling cycles. Conversely, the LS displayed asymmetry, with a more substantial temperature change during the cooling phase than the heating phase.

Willis coupling in one-dimensional poroelastic laminates

We employ the Baker–Campbell–Hausdorff formula to derive closed-form expressions for the effective properties, including emergent Willis coupling, of a one-dimensional heterogeneous poroelastic medium consisting of a periodically repeating two-layer unit-cell. In contrast to the elastic and fluidic analogs, the Willis coupling of this periodic poroelastic medium does not vanish in the low-frequency limit. However, the effective wavenumber and impedance of this asymmetric lamellar material demonstrate symmetric reflection and absorption behavior that is indicative of symmetric structures in the low-frequency limit due to the effect of Darcy’s law on the dynamic effective density, which is inversely proportional to frequency. These closed-form expressions are validated against results obtained by direct numerical evaluation. The scattering coefficients, particularly the two reflection coefficients for incidence from either side of a finite length asymmetric structure, are different at non-zero frequencies but still in the metamaterial limit and are correct when the Willis coupling is included. The results show that asymmetry in poroelastic layers results in direction-dependent absorption coefficients, one of which could be optimized based on layer properties and asymmetry factors. As a consequence, the frequency range of validity of these scattering coefficients is wider when the Willis coupling matrix is accounted for than in its absence. This work paves the way for better control of elastic and acoustic waves in multiphase materials by considering poroelastic behavior.

Dynamics of a bubble-pair between two parallel rigid walls

The dynamics of two gas bubbles placed side-by-side in liquid between parallel rigid plates is studied numerically using the multiphase volume of fluid (VOF) model in OpenFOAM. This model solves a single set of Navier–Stokes equations for both the gas in the bubbles and the surrounding liquid. Being initially stationary, the bubbles first expand to their maximum volume due to the high gas pressure inside them and then collapse. Both phases are treated as viscous and immiscible without any phase change. The model is validated against available experimental data of a single bubble oscillation between parallel plates and a bubble-pair oscillation near a single rigid wall. Parametric studies are then performed, with the main variables being the initial sizes of the bubbles and their standoff distances from the rigid plates. The bubbles exhibit symmetric or asymmetric behavior depending on these two variables. Three distinct scenarios are identified in the symmetric case based on the relative influence of bubble-bubble and bubble-wall interactions. The jet strength and direction, bubble oscillation period, coalescence, and early asymmetric bubble collapse are characterized by initial distances and radii. This study provides valuable insights into intricate hydrodynamic interactions and behaviors of bubble pairs bounded by rigid surfaces.

The anisotropic transport properties of the three-terminal ballistic junction based on α−T 3 lattice

The three-terminal ballistic junction (TBJ) has promising applications in nanoelectronics. We investigate the transport properties of a α−T 3-based TBJ, where two typical configurations are considered, i.e. the A- and Z-TBJ. It is found that both A- and Z-TBJ exhibit transmission anisotropy, and the transmission of the A-TBJ has stronger anisotropy than that of the Z-TBJ. The amplitude of the rectification coefficient is smaller than that of phosphorene TBJ, but larger than that of graphene TBJ. When the symmetrical input is applied, the output voltage curve exhibits symmetric behavior. While in the case of asymmetric input, the symmetric behavior is broken, and the maximum value of the output voltage can reach a positive value. Interestingly, the voltage output shows a dramatic nonlinear response which may be useful for the voltage diode application with a push-pull input voltage. In addition, the heat fluxes of the asymmetric input are much smaller than those of the symmetric input. The maximum value of the heat flux under the symmetric input exceeds twice of that under the asymmetric input. Our results are useful to design nanoelectronic devices based on α−T 3 TBJ.

Fourier transformation based analysis routine for intermixed longitudinal and transversal hysteretic data for the example of a magnetic topological insulator

We present a symmetrization routine that optimizes and eases the analysis of imperfect, experimental data featuring the anomalous Hall hysteresis. This technique can be transferred to any hysteresis with (point-)symmetric behavior. The implementation of the method is demonstrated exemplarily using intermixed longitudinal and transversal data obtained from a chromium-doped ternary topological insulator revealing a clear hysteresis. Furthermore, by introducing a mathematical description of the anomalous Hall hysteresis based on the error function precise values of the height and coercive field are determined.

Investigation on Germanium Transistors with HfOx-Based Gate Stacks for CMOS Operations

Germanium (Ge) FinFETs with HfOx-based gate stacks are fabricated to study the CMOS applications. To evaluate the logic circuit operation, the associated CMOS inverters are characterized. Compared to the HfO2, the Hf0.5Zr0.5Ox (HZO) gate stack provides higher drive currents and more symmetric Vth behaviors, which should be associated with the polarization effect. Through cyclic voltage transfer characteristic (VTC) operation and systematical analysis, it is found that both polarization and charge trapping in the gate stack impact the device characteristics. The HZO devices show a negative VTC shift with cycling, while the HfO2 devices reveal a positive shift. This opposite VTC behavior for both gate stack schemes indicates that the interaction of interface states and dipoles significantly influences the device operation. The results revealed in this work present a comprehensive understanding of HfOx-based device optimization.

On the double-sided shock diffractions in quiescent and supersonic crossflows

Shock diffraction is a widespread phenomenon in aerospace applications, such as shock tunnel nozzle and jet exciter exit, impacting their performance significantly. This paper focuses on the transient evolution of double-sided shock diffraction in both quiescent and supersonic crossflows by unsteady numerical simulations. The characteristics of the shock wave and the vortex are revealed. In the quiescent flow, the double-sided shock diffraction exhibits remarkable symmetry. The diffracted shock retains a self-similar nature, but its intensity distribution displays non-uniform characteristics, which gradually weakens from the center to both sides. The vortices on both sides also exhibit symmetrical behavior, with their trajectory behaving in linear tendency. When the supersonic crossflow interacts with the diffracted shock, an upward-moving separation shock and an asymmetric diffracted shock are generated. The vortices remain confined beneath the boundary layer and exhibit different shapes. Moreover, due to the rapid motion of the separation shock, the relative Mach number is introduced into the free-interaction theory (FIT) to predict the shock angle of the separation shock. The F(x¯) values corresponding to the separation point and pressure plateau are determined to be 3.04 and 4.68, respectively. The results evaluated by modified FIT show a good agreement with the values of simulation and experiment.

Improvement in capacitive performance of ZnS with MnO2 via composite (ZnS/MnO2) strategy developed by hydrothermal technique

Nanocomposites based on manganese oxide (MnO2) exhibit a significantly wide working potential window, rendering them highly appealing for utilization in advanced energy transformation and storage technologies. The following article describes a simple method for synthesizing pure manganese oxide (MnO2), zinc sulfide (ZnS) and ZnS/MnO2 nanocomposites (NCs) for electrochemical supercapacitor applications. Various physiochemical approaches were employed to depict the structure and chemical features of the synthesized materials and electrochemical performance was determined with multiple electrochemical tests under 2.0 M KOH. The high pseudocapacitive nature and good conduction of the MnO2 in ZnS/MnO2 display a high specific capacitance (Cs) of 1002 F g−1 @ 1.0 A g−1. The ZnS/MnO2 display a higher discharge time of 467 s @ 1 A g−1 than 2 A g−1 (159 s) and 3 A g−1 (65 s). The symmetric behavior of the ZnS/MnO2 electrode materials displays the specific capacitance of 373 F g−1 and specific energy of 15.45 Wh kg−1 @ 1 A g−1. Hence, the synergistic behavior of ZnS/MnO2 nanocomposite produced via an effective and environment friendly hydrothermal method displays powerful performance toward energy storage application.

A New Cosine-Originated Probability Distribution with Symmetrical and Asymmetrical Behaviors: Repetitive Acceptance Sampling with Reliability Application

Several new acceptance sampling plans using various probability distribution methods have been developed in the literature. However, there is no published work on the design of new sampling plans using trigonometric-based probability distributions. In order to cover this amazing and fascinating research gap, we first introduce a novel probabilistic method called a new modified cosine-G method. A special member of the new modified cosine-G method, namely, a new modified cosine-Weibull distribution, is examined and implemented. The density function of the new model possesses symmetrical as well as asymmetrical behaviors. The usefulness and superior fitting power of the new modified cosine-Weibull distribution are demonstrated by analyzing an asymmetrical data set. Furthermore, based on the new modified cosine-Weibull distribution, we develop a new repetitive acceptance sampling strategy for attributes with specified shape parameters. Finally, a real-world application is presented to illustrate the proposed repetitive acceptance sampling strategy.

Programming Techniques of Resistive Random-Access Memory Devices for Neuromorphic Computing

Neuromorphic computing offers a promising solution to overcome the von Neumann bottleneck, where the separation between the memory and the processor poses increasing limitations of latency and power consumption. For this purpose, a device with analog switching for weight update is necessary to implement neuromorphic applications. In the diversity of emerging devices postulated as synaptic elements in neural networks, RRAM emerges as a standout candidate for its ability to tune its resistance. The learning accuracy of a neural network is directly related to the linearity and symmetry of the weight update behavior of the synaptic element. However, it is challenging to obtain such a linear and symmetrical behavior with RRAM devices. Thus, extensive research is currently devoted at different levels, from material to device engineering, to improve the linearity and symmetry of the conductance update of RRAM devices. In this work, the experimental results based on different programming pulse conditions of RRAM devices are presented, considering both voltage and current pulses. Their suitability for application as analog RRAM-based synaptic devices for neuromorphic computing is analyzed by computing an asymmetric nonlinearity factor.

Dynamic Analysis and FPGA Implementation of a New Fractional-Order Hopfield Neural Network System under Electromagnetic Radiation.

Fractional calculus research indicates that, within the field of neural networks, fractional-order systems more accurately simulate the temporal memory effects present in the human brain. Therefore, it is worthwhile to conduct an in-depth investigation into the complex dynamics of fractional-order neural networks compared to integer-order models. In this paper, we propose a magnetically controlled, memristor-based, fractional-order chaotic system under electromagnetic radiation, utilizing the Hopfield neural network (HNN) model with four neurons as the foundation. The proposed system is solved by using the Adomain decomposition method (ADM). Then, through dynamic simulations of the internal parameters of the system, rich dynamic behaviors are found, such as chaos, quasiperiodicity, direction-controllable multi-scroll, and the emergence of analogous symmetric dynamic behaviors in the system as the radiation parameters are altered, with the order remaining constant. Finally, we implement the proposed new fractional-order HNN system on a field-programmable gate array (FPGA). The experimental results show the feasibility of the theoretical analysis.

Experimental characterization and phase-field modeling of anisotropic brittle fracture in silicon

We employ experiments and phase-field modeling to characterize the four-fold anisotropic elastic and fracture response of solar-grade monocrystalline silicon on the macro-scale using thin silicon wafers. Tension tests on unnotched and double edge-notched specimens are performed to characterize the in-plane four-fold symmetric elastic behavior of the material and its fracture toughness along the weak directions. Single edge-notched tension tests with the notch oriented along the strong direction are performed to induce crack zigzagging and qualitatively capture the inherent stochastic nature of crack propagation in this setting. With the experimental results, we calibrate two deterministic anisotropic fourth-order phase-field models considering anisotropy in both elastic and fracture energies, as well as their stochastic extension proposed in our previous work. Overall, the very good agreement between experimental and numerical results demonstrates the ability of phase-field modeling to quantitatively predict anisotropic brittle fracture in monocrystalline silicon. Remarkably, very different zigzagging crack patterns obtained on nominally identical specimens are naturally reproduced by the stochastic model.

An anisotropic electromagnetic hydrogel promotes cardiomyocyte maturation and post-infarction cardiac repair

Effective therapies for myocardial infarction (MI) are essential in lowering associated mortality rates. While hydrogel-based patch therapy has shown promise in improving post-MI cardiac function; it falls short in terms of mature stimulation and lacks the necessary combination of conductive, mechanical, and anisotropic cues for optimal efficacy. In this study, we developed an anisotropic hydrogel by incorporating polydopamine-reduced graphene oxide-ferric oxide (PDA-rGO-Fe3O4) nanohybrids into gelatin methacrylate (GelMA) hydrogels under a direct current-driven magnetic field. Cardiomyocytes (CMs) cultured on anisotropic hydrogels demonstrated oriented growth and exhibited symmetrical contraction-relaxation behaviors, surpassing the performance of cells cultured on pure GelMA and isotropic ones. Moreover, both external electrical and alternating magnetic field stimulations enhanced sarcomere functionality, gap junction protein expression, and electrophysiological activities in CMs within the anisotropic hydrogel group. In an acute MI rat model, the application of the anisotropic hydrogel patch significantly improved cardiac function, mitigated adverse left ventricular (LV) dilation and remodeling, reduced infarct size, increased LV wall thickness, promoted angiomyogenesis, and preserved the structural and connected features between CMs. Overall, our findings highlight the potential of electromagnetic, conductive, and anisotropic GelMA-based hydrogels as scaffolds for mimicking the natural functional myocardium layer and developing effective cardiac patches.