Search Results (242)

This paper develops a novel modeling framework that integrates time-varying quantile-based spillover effects into a regime-switching realized volatility model. A dynamic spillover factor is constructed by identifying the most influential contributors to Bitcoin’s realized volatility across different quantile levels. This quantile-layered structure enables the model to capture heterogeneous spillover paths under varying market conditions at a macro level while also enhancing the sensitivity of volatility regime identification via its incorporation into a time-varying transition probability (TVTP) Markov-switching mechanism at a micro level. Empirical results based on the cryptocurrency market demonstrate the superior forecasting performance of the proposed TVTP-MS-HAR model relative to standard benchmark models. The model exhibits strong capability in identifying state-dependent spillovers and capturing nonlinear market dynamics. The findings further reveal an asymmetric dual-tail amplification and time-varying interconnectedness in the spillover effects, along with a pronounced asymmetry between market capitalization and systemic importance. Compared to decomposition-based approaches, the X-RV type of models—especially when combined with the proposed quantile-driven factor—offers improved robustness and predictive accuracy in the presence of extreme market behavior. This paper offers a coherent approach that bridges phenomenon identification, source localization, and predictive mechanism construction, contributing to both the academic understanding and practical risk assessment of cryptocurrency markets. Full article

Gas–water two-phase flow in horizontal and inclined wells is significantly influenced by gravitational forces and spatial asymmetry around the wellbore, resulting in complex and variable flow patterns. Accurate measurement of water holdup is essential for analyzing phase distribution and understanding multiphase flow behavior. Water holdup imaging provides a valuable means for visualizing the spatial distribution and proportion of gas and water phases within the wellbore. In this study, air and tap water were used to simulate downhole gas and formation water, respectively. An array capacitance arraay tool (CAT) was employed to measure water holdup under varying total flow rates and water cuts in a horizontal well experimental setup. A total of 228 datasets were collected, and the measurements were processed in MATLAB (2020 version) using three interpolation algorithms: simple linear interpolation, inverse distance interpolation, and Lagrangian nonlinear interpolation. Water holdup across the wellbore cross-section was also calculated using arithmetic averaging and integration methods. The results obtained from the three imaging algorithms were compared with these reference values to evaluate accuracy and visualize imaging performance. The CAT demonstrated reliable measurement capabilities under low- to medium-flow conditions, accurately capturing fluid distribution. For stratified flow regimes, the linear interpolation algorithm provided the clearest depiction of the gas–water interface. Under low- to medium-flow rates with high water content, both inverse distance and Lagrangian methods produced more refined images of phase distribution. In dispersed flow conditions, the Lagrangian nonlinear interpolation algorithm delivered the highest accuracy, effectively capturing subtle variations within the complex flow field. Full article

This article concerns a Cournot duopoly game with homogeneous expectations. The cost functions of the two players are assumed to be asymmetric to capture possible asymmetries in firms’ technologies or firms’ input costs. Large values of the speed of adjustment of the players destabilize the Nash Equilibrium (N.E.) and cause the appearance of a chaotic trajectory in the Discrete Dynamical System (D.D.S.). The scope of this article is to control the chaotic dynamics that appear outside the stability field, assuming asymmetric cost functions of the two players. Specifically, one player uses linear costs, while the other uses nonlinear costs (quadratic or cubic). The cubic cost functions are widely used in the Economic Dispatch Problem. The delayed feedback control method is applied by introducing a new control parameter at the D.D.S. It is shown that larger values of the control parameter keep the N.E. locally asymptotically stable even for higher values of the speed of adjustment. Full article

The symmetry of the interparticle interaction potential (IIP) plays a critical role in determining the thermodynamic and transport properties of solids. This study investigates the isolated effect of IIP asymmetry on thermalization. Asymmetry and nonlinearity are typically intertwined. To isolate the effect of asymmetry, we introduce a one-dimensional asymmetric harmonic (AH) model whose IIP possesses asymmetry but no nonlinearity, evidenced by energy-independent vibrational frequencies. Extensive numerical simulations confirm a power-law relationship between thermalization time (T_eq) and perturbation strength for the AH chain, revealing an exponent larger than the previously observed inverse-square law in the thermodynamic limit. Upon adding symmetric quartic nonlinearity into the AH model, we systematically study thermalization under combined asymmetry and nonlinearity. Matthiessen’s rule provides a good estimate of T_eq in this case. Our results demonstrate that asymmetry plays a distinct role in enhancing higher-order effects and governing relaxation dynamics. Full article

This study investigates the solution structure of the nonlinear Rayleigh oscillator equation through two widely used semi-analytical techniques: the Laplace–Adomian Decomposition Method (LADM) and the Homotopy Perturbation Method (HPM). The Rayleigh oscillator exhibits inherent asymmetry in its nonlinear damping term, which disrupts the time-reversal symmetry present in linear oscillatory systems. Applying the LADM and HPM, we derive approximate solutions for the Rayleigh oscillator. Due to the absence of exact analytical solutions in the literature, these approximations are benchmarked against high-precision numerical results obtained using Mathematica’s NDSolve function. We perform a detailed error analysis across different damping parameter values ε and time intervals. Our results reveal how the asymmetric damping influences the accuracy and convergence behavior of each method. This study highlights the role of nonlinear asymmetry in shaping the solution dynamics and provides insight into the suitability of the LADM and HPM under varying conditions. Full article

A nonlinear incremental time history analysis is performed on plan and vertical asymmetric reinforced concrete (RC) buildings under sequential events of the 2011 Great Japan earthquake and tsunami. The symmetric and plan asymmetric buildings with a unidirectional eccentricity of 6 m to 18 m with an interval of 6 m are considered. The vertical mass and stiffness asymmetric structures are also analyzed considering material nonlinearity. Maximum inundation depths of 6.0 m and 3.0 m are simulated to account for the near-shore and far-shore conditions. A total time duration of 58.69 min. is taken for the earthquake and tsunami, including a time gap of 30 min. between the earthquake and tsunami. The symmetric structure showed structural adequacy against earthquakes and tsunamis, with a maximum inundation depth of 3.0 m. The plan asymmetric structure with 6.0 m eccentricity has shown displacements below the yield displacement (i.e., the maximum lateral displacement before inelastic behavior) under the earthquake, but yielded under the tsunami a time of structural adequacy (the time duration during which the building remains within elastic limits under sequential loading) of up to 42.56 min. In comparison to the symmetric building, the buildings with higher eccentricities (12.0 m and 18.0 m) failed under seismic loading alone, exhibiting 94.12% and 45.94% greater displacements, respectively, both exceeding the yield threshold. Vertical stiffness asymmetric structures displaced more than yield displacement under the earthquake, whereas mass asymmetric structures with asymmetry at the first or second floors have been found resilient under the sequential earthquake and tsunami up to the inundation depth of 3.0 m. From this, it is concluded that vertical evacuation is limited to the first or second floors of the studied building. It is recommended to construct the RC buildings away from the seashore to ensure the safety of the occupants. The construction of the plan and stiffness of asymmetric structures shall be avoided in the seashore locations. Full article

A spectrogram is one of the most effective tools for visualizing dynamic signal changes in industrial processes. In many cases, these signals exhibit certain forms of symmetry—whether in time, frequency, or statistical properties. This paper proposes a novel visualization methodology based on an adaptive nonlinear quantization framework, which intentionally introduces asymmetry to enhance diagnostic-critical features of the power spectrum. Unlike conventional linear quantizers that preserve uniform sensitivity across the range, the nonlinear approach enables selective emphasis of transient or low-energy components, improving visibility under varying signal-to-noise conditions. The design of both symmetric (linear) and asymmetric (nonlinear) quantizers is presented, including their mathematical foundations and visual effects on deterministic, stochastic, and pulsed signals. Entropy-based metrics are used to evaluate information content in the visualized spectrograms. The results demonstrate the proposed technique’s potential for enhancing fault detection, monitoring, and industrial diagnostics. Full article

Detection gain asymmetry error is one of the primary errors of the hemispherical resonator gyroscope (HRG) in whole-angle (WA) mode. This paper analyzes the influence of detection gain asymmetry error and its coupling error with damping and stiffness asymmetry on the performance of HRG and proposes a novel compensation method for detection gain asymmetry error. Firstly, the nonlinear error model of HRG considering the detection gain asymmetry error and its coupling error is established by using the average method. The influence of the angle-dependent scale factor error (ADS) and angle-dependent bias error (ADB) caused by the detection gain asymmetry error is analyzed by numerical simulation. Secondly, a parameter estimation algorithm based on force-to-rebalance (FTR) mode is proposed to decouple and identify the detection gain asymmetry error and damping asymmetry error. The identified parameters are used for the calibration of the HRG. Finally, the method is applied to the HRG operating in WA mode. The effectiveness of the proposed method is verified by experiments. After compensation, the bias instability is reduced from 3.6°/h to 0.6°/h, the scale factor nonlinearity is reduced from 646.57 ppm to 207.43 ppm, and the maximum pattern angle deviation is reduced from 0.6° to 0.05°. Full article

The Asymmetric Double Cantilever Beam (ADCB) is a common test configuration used to produce mixed mode I/II in composite materials. It consists of two sublaminates with different thicknesses or elastic properties, a situation that usually occurs in bimaterial adhesive joints. During this test, the sample undergoes rotation. In this work, the influence of this rotation on the calculation of the energy release rate (ERR) in modes I and II was studied using the Finite Element Method (FEM). Several models with different degrees of asymmetry (different thickness ratio and/or elastic modulus ratio) and different applied displacements were prepared to obtain different levels of rotation during the test. As is known, the concept of modes I and II refers to the components of the energy release rate calculated in the direction perpendicular and tangential to the delamination plane, respectively. If the model experiences significant rotation during the application of the load, this non-linearity must be considered in the calculation of the mode partition I/II. In this work, appreciable differences were observed in the values of modes I and II, depending on their calculation in a global system or a local system that rotates with the sample. When performing crack growth calculations, the difference between critical loads can be in the order of 4%, while the difference between mode I and mode II results can reach 4% and 14%, respectively, for an applied displacement of only 5 mm. Currently, this correction is not usually implemented in Finite Element calculation codes or in analytical developments. The purpose of this article is to draw attention to this aspect when the rotation of the specimen is not negligible. Full article

This work presents the performance projection of a metal-insulator-graphene diode as the building block of a radiofrequency power detector, highlighting its rectifying figures of merit. The analysis was performed by means of a computer-aided design tool validated with experimental measurements of fabricated devices. Transient simulations were used to accurately determine the detector output voltage, while particular consideration was given to suitable convergence of the non-linear circuit response. The diode was analyzed in both ideal and non-ideal cases, with the latter accounting for its parasitic effects. In the non-ideal case, the diode exhibited a tangential responsivity of 26.9 V/W at 2.45 GHz and 31.9 V/W at 1.225 GHz. However, when parasitic elements were neglected in the ideal case, the responsivity significantly increased to 47.3 V/W at 2.45 GHz and 38.7 V/W at 1.225 GHz. Additionally, the diode demonstrated a non-linearity of 6.64 at 0.7 V and an asymmetry of 806.6 in a bias window of ±1 V, which resulted in a competitive value compared to other state-of-the-art rectifying technologies. Tangential responsivities (${\beta }_{\mathrm{v}}$) of graphene diodes at less-studied frequencies in the gigahertz band are presented, showing a high ${\beta }_{\mathrm{v}}$ value of 63.7 V/W at 1 GHz. Full article

In realistic hyperspectral image (HSI) cross-scene classification tasks, it is ideal to obtain target domain samples during the training phase. Therefore, a model needs to be trained on one or more source domains (SD) and achieve robust domain generalization (DG) performance on an unknown target domain (TD). Popular DG strategies constrain the model’s predictive behavior in synthetic space through deep, nonlinear source expansion, and an HSI generation model is usually adopted to enrich the diversity of training samples. However, recent studies have shown that the activation functions of neurons in a network exhibit asymmetry for different categories, which results in the learning of task-irrelevant features while attempting to learn task-related features (called “feature contamination”). For example, even if some intrinsic features of HSIs (lighting conditions, atmospheric environment, etc.) are irrelevant to the label, the neural network still tends to learn them, resulting in features that make the classification related to these spurious components. To alleviate this problem, this study replaces the common nonlinear generative network with a specific linear projection transformation, to reduce the number of neurons activated nonlinearly during training and alleviate the learning of contaminated features. Specifically, this study proposes a dimensionally decoupled spatial spectral linear extrapolation (SSLE) strategy to achieve sample augmentation. Inspired by the weakening effect of water vapor absorption and Rayleigh scattering on band reflectivity, we simulate a common spectral drift based on Markov random fields to achieve linear spectral augmentation. Further considering the common co-occurrence phenomenon of patch images in space, we design spatial weights combined with label determinism of the center pixel to construct linear spatial enhancement. Finally, to ensure the cognitive unity of the high-level features of the discriminator in the sample space, we use inter-class contrastive learning to align the back-end feature representation. Extensive experiments were conducted on four datasets, an ablation study showed the effectiveness of the proposed modules, and a comparative analysis with advanced DG algorithms showed the superiority of our model in the face of various spectral and category shifts. In particular, on the Houston18/Shanghai datasets, its overall accuracy was 0.51%/0.83% higher than the best results of the other methods, and its Kappa coefficient was 0.78%/2.07% higher, respectively. Full article

This paper examines the impact of various uncertainty channels on stock market returns in Saudi Arabia, with a focus on the Tadawul All Share Index (TASI). It examines factors such as Saudi-specific Geopolitical Risk, Global Oil Price Uncertainty, Climate Policy Uncertainty, and U.S. Monetary Policy Uncertainty. Using monthly data from November 1998 to June 2024 and the Local Projections (LP) methodology, the study examines how these uncertainties impact market returns across various time horizons, taking into account potential structural breaks and nonlinear dynamics. Our findings indicate significant variations in the market’s response to the uncertainty measures across two distinct periods. During the first period, geopolitical risks have a strong positive impact on market returns. Conversely, the second period reveals a reversal, with negative cumulative effects, suggesting a shift in risk–return dynamics. Oil Price Uncertainty consistently exhibits a negative impact in both periods, highlighting the changing nature of oil dependency in the Saudi market. Additionally, Climate Policy Uncertainty is becoming more significant, reflecting increased market sensitivity to global environmental policy changes. Our analysis reveals significant asymmetries in the effects of various uncertainty shocks, with Monetary Policy Uncertainty exhibiting nonlinear effects that peak at intermediate horizons, while commodity-related uncertainties exhibit more persistent impacts. These findings, which remain robust across various tests, offer critical insights for portfolio management, policy formulation, and risk assessment in emerging markets undergoing substantial economic changes. Full article

Accurately simulating wave breaking is crucial for modeling hydrodynamics over steep coral reef slopes, yet it remains a challenge for Boussinesq-type models like FUNWAVE-TVD. The model’s standard hybrid breaking mechanism, triggered by a fixed free surface elevation-to-depth ratio ($\eta /d>0.8$), often lacks physical sensitivity to local slope and wave conditions prevalent in reef environments and suffers from inaccuracies associated with using η as a direct proxy for wave height (H). This study introduces and validates a novel, enhanced hybrid breaking module within FUNWAVE-TVD, specifically designed to overcome these limitations on steep slopes. The core novelty lies in the synergistic implementation of two key components: (1) replacing the fixed threshold with a dynamic, physically-based criterion derived from the Modified Goda formula (MGO) by Rattanapitikon and Shibayama, which calculates the breaking wave height ($H_b$) based on local depth, slope, and deep-water wavelength; and (2) developing and applying a practical method, using the wave vertical asymmetry relationship proposed by Yu and Li, to dynamically convert the calculated $H_b$ into an equivalent breaking surface elevation threshold (${\eta }_b$). This derived dynamic threshold (${\eta }_b/d$) is then used to trigger the model’s existing switch from Boussinesq to Nonlinear Shallow Water Equations (NSWE), allowing for energy dissipation via shock-capturing while retaining the physical basis of the MGO criterion. The performance of this enhanced module was rigorously evaluated against five laboratory experiments of regular waves breaking on impermeable slopes ranging from mild (1:10) to extremely steep (1:1), contrasting results with the original FUNWAVE-TVD. The modified model demonstrates significantly improved accuracy (model skill increases ranging from 10.16% to 42.49%) compared to the original model for breaking location and wave height prediction on steeper slopes ($m\ge 1:6$). Conversely, tests on the 1:1 slope confirmed the inherent limitations of the MGO criterion itself under surging breaker conditions ($m\ge 1:2.3$), highlighting the applicability range. This work provides a validated methodology for incorporating slope-aware, dynamic breaking criteria effectively into hybrid Boussinesq models, offering a more robust tool for simulating wave processes on steep reef topographies. Full article

As an emerging marketing tool, virtual influencers (VIs) have attracted increasing scholarly attention. However, existing research predominantly adopts linear causal analysis models, which fail to capture the complex, nonlinear interaction between consumers and VIs. Grounded in the 5W communication model and utilizing a fuzzy-set qualitative comparative analysis (fsQCA), this study systematically explores how different configurational paths influence consumer engagement, drawing on empirical data from 205 participants. The findings reveal that (1) the synergy of entertainment, information, and credibility is a core prerequisite for achieving high engagement; (2) two equivalent paths—namely, the technology-driven path (media richness + content synergy) and the cognition-driven path (technology acceptance + content synergy)—lead to high engagement, both with a solution consistency of 0.98; and (3) the joint absence of content, media richness, and audience cognition results in low engagement. Theoretically, this study challenges traditional linear approaches by validating causal asymmetry and revealing configurational interdependencies among communication elements. It also extends the Media Richness Theory (MRT) and the Technology Acceptance Model (TAM) into the context of virtual influencer (VI) marketing. Practically, the proposed dynamic configuration model offers marketers a novel framework for optimizing VI campaigns through resource-adaptive strategies. Full article

In the contemporary global educational environment, the automatic assessment of students’ online engagement has garnered widespread attention. A substantial number of studies have demonstrated that facial expressions are a crucial indicator for measuring engagement. However, due to the asymmetry inherent in facial expressions and the varying degrees of deviation of students’ faces from a camera, significant challenges have been posed to accurate emotion recognition in the online learning environment. To address these challenges, this work proposes a novel VGG-SwishNet model, which is based on the VGG-16 model and aims to enhance the recognition ability of asymmetric facial expressions, thereby improving the reliability of student engagement assessment in online education. The Swish activation function is introduced into the model due to its smoothness and self-gating mechanism. Its smoothness aids in stabilizing gradient updates during backpropagation and facilitates better handling of minor variations in input data. This enables the model to more effectively capture subtle differences and asymmetric variations in facial expressions. Additionally, the self-gating mechanism allows the function to automatically adjust its degree of nonlinearity. This helps the model to learn more effective asymmetric feature representations and mitigates the vanishing gradient problem to some extent. Subsequently, this model was applied to the assessment of engagement and provided a visualization of the results. In terms of performance, the proposed method achieved high recognition accuracy on the JAFFE, KDEF, and CK+ datasets. Specifically, under 80–20% and 10-fold cross-validation (CV) scenarios, the recognition accuracy exceeded 95%. According to the obtained results, the proposed approach demonstrates higher accuracy and robust stability. Full article