Narrow Results

This study describes the impact of leverage on earnings management and determines varying relationships with the moderating effect of firm size in linear and nonlinear setting. Results from selected firms of members’ countries of Asia Pacific Trade Agreement (APTA) unequivocally revealed that in all countries the relationship between the leverage and earnings management is sigmoid in nature. Firms can limit the managers reporting of income-increasing accruals through debt creation up to a certain threshold after which further debt creation challenges the debt covenants. The firm size substantially moderates the relationship of leverage and earnings management and systematically converses the relationship through moderation. The relationship between accruals and firm size is also sigmoid in nature. The specific behavior is seen in Indian firms in which relationship between leverage and accruals is like Richard’s curve in nature due to higher agency cost issue. In Pakistan, firm size has been found as a major factor that guides the accrual due to higher political cost. Additionally, in the setting of comparative static analysis, at the first place, we examine cash flows-risk determining liquidity-risk position of the firms in Pakistan and Bangladesh. At the second place, in the case of China, India and Pakistan, this study reveals an increasing relationship between the effective tax rate and the probability of reporting negative accruals which may create attitude of tax evasion among the firms in these countries. In the third place, in the case of China, India and Bangladesh, sales growth depicts an increasing relationship with the likelihood of reporting positive accruals. However, decreasing relationship is observed for Pakistan and Sri Lanka between the sales growth and the possibility of positive accruals. This study has major implications for funding institutions, debt manager and regulatory bodies of Asian Economies.

Inconsistent results of the impacts of intellectual capital (IC) investments on firm performance have raised question regarding the pros and cons of IC investments. However, analyzing the relationship between IC and firm performance from a nonlinear perspective remains under-researched. Hence, this paper aims to examine whether IC investments have a nonlinear relationship with firm performance. This study also examines the interaction effects of IC components on firm performance. We undertake the data that ranges from 2009–2022 on Malaysian public listed firms. The study separates the data into two periods, one without COVID-19 impact (2009–2018) and the other with COVID-19 impact (2019–2022), to examine the potential impact of IC to firm performance with and without the presence of COVID-19 pandemic. The study utilizes panel data regression method to analyze the hypothesized relationships. The results indicate that the relationship between IC components and firm performance is nonlinear when COVID-19 is not present, but this relationship changes in the presence of COVID-19 impact. That is, although continuous IC investments can be a safe investment strategy, their positive impacts on firm performance lose initial strength after a certain critical level of IC investments. Based on the findings, Malaysian public listed firms need to have skilled and intellectual labor force to support the transition from labor intensive industries to knowledge-intensive industries. Moreover, tangible investments play a contributing role in intangible investments. Managers should be careful in investing both physical and financial resources as their marginal costs may outweigh marginal benefits. Overall, this study is helpful to the managers and policy makers in deciding the optimal level of IC investments. The advice can also be taken with respect to combinations of elements of IC.

Eddy current dampers (ECDs), which employ magnetic induction to produce eddy current damping for energy dissipation, demonstrate superior sensitivity and durability in comparison to traditional viscous dampers. However, the inherent, velocity-dependent nonlinearity of ECDs poses significant challenges in research and engineering implementations. The present study addresses this challenge by exploring the stochastic linearization of ECDs, innovatively incorporating the non-Gaussian distribution of velocity responses. Central to our analysis, we proposed four closed-form expressions for the equivalent damping ratios of ECDs, derived from both Gaussian and non-Gaussian distributions. This achievement is facilitated by the utilization of the statistical linearization technique (SLT), which integrates both force-based and energy-based equivalent criteria. To validate the accuracy of these expressions, Monte Carlo simulation (MCS) was employed. Our results demonstrate that, regardless of soil conditions and velocity distributions, the force-based criteria, in most cases, outperform the energy-based criteria in assessing the stochastic linearization of ECDs. Notably, in scenarios where ECD nonlinearity is prominent, the probability density of the exact velocity response of ECDs in firm soil exhibits a significantly steeper profile near zero, resembling an exponential-like distribution more closely than the Gaussian distribution. Conversely, in soft soil conditions, the actual velocity distribution lies intermediate between Gaussian and exponential-like distributions. Additionally, a series of parameter studies were conducted, further revealing that the force-based Gaussian SLT method offers the highest accuracy in soft soil and firm soil with critical velocities exceeding 0.05m/s. In contrast, the force-based non-Gaussian SLT method proves to be the more precise approach in firm soil with critical velocities below 0.05m/s.

Quartz crystals are widely used in sensors, auctors, filters, and resonators due to their excellent piezoelectric properties and operational stability. As electronic devices continue to miniaturize, understanding the nonlinearity in quartz crystal structures becomes increasingly important. This study aims to support the design of high-sensitivity piezoelectric sensors by analyzing the thickness-mode nonlinear vibration of randomly cut quartz crystals, incorporating the effects of initial stress. Specifically, a theoretical framework is developed to determine the nonlinear vibration frequencies of the fast and slow thickness-shear modes, as well as the thickness-stretch mode in a randomly cut quartz crystal. The study explores the dependence of vibration frequencies on nonlinear vibration amplitude and initial stress. To ensure that frequency variations are attributed to initial stress, the nonlinear vibration amplitude is maintained at a reasonable value. Furthermore, the effects of cut orientation on frequency variation under a given initial stress are examined to identify the optimal cut for frequency sensitivity. Our results demonstrate that quartz crystals exhibit high sensitivity to initial stress, with the fundamental vibration mode showing the largest frequency shift despite having the lowest frequency. This mode proves particularly suitable for sensor applications. The study identifies the cut orientation with the optimal frequency sensitivity and provides insights that could guide the design of piezoelectric sensors and expand their application.

In this paper we generalize two remarkable results on cryptographic properties of Boolean functions given by Tu and Deng [8] to the vectorial case. Firstly we construct vectorial bent Boolean functions with good algebraic immunity for all cases 1 ⩽ m ⩽ n, and with maximum algebraic immunity for some cases (n,m). Then by modifying F, we get vectorial balanced functions with optimum algebraic degree, good nonlinearity and good algebraic immunity for all cases , and with maximum algebraic immunity for some cases (n,m). Moreover, while Tu-Deng's results are valid under a combinatorial hypothesis, our results (Theorems 4 and 5) are true without this hypothesis.

It is a difficult task to compute the r-th order nonlinearity of a given function with algebraic degree strictly greater than r > 1. Though lower bounds on the second order nonlinearity are known only for a few particular functions, the majority of which are cubic. We investigate lower bounds on the second order nonlinearity of cubic Boolean functions , where , d_l = 2^il + 2^jl + 1, m, i_l and j_l are positive integers, n > i_l > j_l. Furthermore, for a class of Boolean functions we deduce a tighter lower bound on the second order nonlinearity of the functions, where , d_l = 2^i_lγ + 2^j_lγ + 1, i_l > j_l and γ ≠ 1 is a positive integer such that gcd(n,γ) = 1.

Lower bounds on the second order nonlinearity of cubic monomial Boolean functions, represented by f_μ(x) = Tr(μx^2i+2j+1), , i and j are positive integers such that i > j, were obtained by Gode and Gangopadhvay in 2009. In this paper, we first extend the results of Gode and Gangopadhvay from monomial Boolean functions to Boolean functions with more trace terms. We further generalize and improve the results to a wider range of n. Our bounds are better than those of Gode and Gangopadhvay for monomial functions f_μ(x). Especially, our lower bounds on the second order nonlinearity of some Boolean functions F(x) are better than the existing ones.

In this paper, we study the nonexistence of bent functions in the class of Boolean functions without monomials of degree less than d in their algebraic normal forms (ANF). We prove that n-variable Boolean functions in such class are not bent when there are not more than n + d - 3 monomials in their ANFs. We also show that an n-variable Boolean function is not bent if it has no monomial of degree less than ⌈3n/8 + 3/4⌉ in its ANF.

Vectorial Boolean functions play an important role in cryptography. How to construct vectorial Boolean functions with good cryptographic properties is a nice problem that worth to be investigated. In this paper we present several constructions of balanced vectorial Boolean functions with high algebraic immunity, high(or optimum) algebraic degree, and very high nonlinearity. In some cases, the constructed functions also achieve optimum algebraic immunity.

Based on Carlet-Feng functions, we present a method to construct odd variable Boolean functions with optimal algebraic immunity in this paper. The proposed functions can have the highest algebraic degree and a lower bound on the nonlinearity is also established.

Constructing 2m-variable Boolean functions with optimal algebraic immunity based on decomposition of additive group of the finite field seems to be a promising approach since Tu and Deng's work. In this paper, we consider the same problem in a new way. Based on polar decomposition of the multiplicative group of , we propose a new construction of Boolean functions with optimal algebraic immunity. By a slight modification of it, we obtain a class of balanced Boolean functions achieving optimal algebraic immunity, which also have optimal algebraic degree and high nonlinearity. Computer investigations imply that this class of functions also behaves well against fast algebraic attacks.

Recently, Tang, Carlet and Tang presented a combinatorial conjecture about binary strings, allowing proving that all balanced functions in some infinite class they introduced have optimal algebraic immunity. Later, Cohen and Flori completely proved that the conjecture is true. These functions have good (provable or at least observable) cryptographic properties but they are not 1-resilient, which represents a drawback for their use as filter functions in stream ciphers. We propose a construction of an infinite class of 1-resilient Boolean functions with optimal algebraic immunity by modifying the functions in this class. The constructed functions have optimal algebraic degree, that is, meet the Siegenthaler bound, and high nonlinearity. We prove a lower bound on their nonlinearity, but as for the Carlet-Feng functions and for the functions mentioned above, this bound is not enough for ensuring a nonlinearity sufficient for allowing resistance to the fast correlation attack. Nevertheless, as for previously found functions with the same features, there is a gap between the bound that we can prove and the actual values computed for small numbers of variables. Our computations show that the functions in this class have very good nonlinearity and also good immunity to fast algebraic attacks. This is the first time that an infinite class of functions gathers all of the main criteria allowing these functions to be used as filters in stream ciphers.

In this paper, we present nonsingular permutation polynomials from nonsingular feedback shift registers and examine nonlinearity and algebraic degree of nonsingular polynomials of certain forms. The upper bound on the nonlinearity of nonsingular Boolean functions is investigated. We also present $n$-variable nonsingular Boolean functions with algebraic degree $n-1$ and highest possible nonlinearity for odd $n$.

Rotation symmetric Boolean functions are good candidates for stream ciphers because they have such advantages as simple structure, high operational speed and low implement cost. Recently, Mesnager et al. proposed for the first time an efficient method to construct balanced rotation symmetric Boolean functions with optimal algebraic immunity and good nonlinearity for an arbitrary even number of variables. However, the algebraic degree of their constructed $n$-variable ($n>4$) function is always less than the maximum value $n-1$. In this paper, by modifying the support of Boolean functions from Mesnager et al.’s construction, we present two new constructions of balanced even-variable rotation symmetric Boolean functions with optimal algebraic immunity as well as higher algebraic degree and nonlinearity. The algebraic degree of Boolean functions in the first construction reaches the maximum value $n-1$ if $\frac{n}{2}$ is odd and $\frac{n}{2}\ne {(2k+1)}^2$ or ${(2k+1)}^2+2$ for integer $k$, while that of the second construction reaches the maximum value for all $n$. Moreover, the nonlinearities of Boolean functions in both two constructions are higher than that of Mesnager et al.’s construction.

In this work, the development of an Artificial Neural Network (ANN) based soft estimator is reported for the estimation of static-nonlinearity associated with the transducers. Under the realm of ANN based transducer modeling, only two neural models have been suggested to estimate the static-nonlinearity associated with the transducers with quite successful results. The first existing model is based on the concept of a functional link artificial neural network (FLANN) trained with μ-LMS (Least Mean Squares) learning algorithm. The second one is based on the architecture of a single layer linear ANN trained with α-LMS learning algorithm. However, both these models suffer from the problem of slow convergence (learning). In order to circumvent this problem, it is proposed to synthesize the direct model of transducers using the concept of a Polynomial-ANN (polynomial artificial neural network) trained with Levenberg-Marquardt (LM) learning algorithm. The proposed Polynomial-ANN oriented transducer model is implemented based on the topology of a single-layer feed-forward back-propagation-ANN. The proposed neural modeling technique provided an extremely fast convergence speed with increased accuracy for the estimation of transducer static nonlinearity. The results of convergence are very stimulating with the LM learning algorithm.

Keeping a basic tenet of economic theory, rational expectations, we model the nonlinear positive feedback between agents in the stock market as an interplay between nonlinearity and multiplicative noise. The derived hyperbolic stochastic finite-time singularity formula transforms a Gaussian white noise into a rich time series possessing all the stylized facts of empirical prices, as well as accelerated speculative bubbles preceding crashes. We use the formula to invert the two years of price history prior to the recent crash on the Nasdaq (April 2000) and prior to the crash in the Hong Kong market associated with the Asian crisis in early 1994. These complex price dynamics are captured using only one exponent controlling the explosion, the variance and mean of the underlying random walk. This offers a new and powerful detection tool of speculative bubbles and herding behavior.

We study the nature of collective excitations in classical anharmonic lattices with aperiodic and pseudo-random harmonic spring constants. The aperiodicity was introduced in the harmonic potential by using a sinusoidal function whose phase varies as a power-law, ϕ ∝ n^ν, where n labels the positions along the chain. In the absence of anharmonicity, we numerically demonstrate the existence of extended states and energy propagation for a sufficiently large degree of aperiodicity. Calculations were done by using the transfer matrix formalism (TMF), exact diagonalization and numerical solution of the Hamilton's equations. When nonlinearity is switched on, we numerically obtain a rich framework involving stable and unstable solitons.

In this paper, we investigate the influence of electron-lattice interaction on the stability of uniform electronic wavepackets on chains as well as on several types of fullerenes. We will use an effective nonlinear Schrödinger equation to mimic the electron–phonon coupling in these topologies. By numerically solving the nonlinear dynamic equation for an initially uniform electronic wavepacket, we show that the critical nonlinear coupling above which it becomes unstable continuously decreases with the chain size. On the other hand, the critical nonlinear strength saturates on a finite value in large fullerene buckyballs. We also provide analytical arguments to support these findings based on a modulational instability analysis.

We study the oscillatory behavior of a gene regulatory network with interlinked positive and negative feedback loop. The frequency and amplitude are two important properties of oscillation. The studied network produces two different modes of oscillation. In one mode (mode-I), frequency of oscillation remains constant over a wide range of amplitude and in the other mode (mode-II) the amplitude of oscillation remains constant over a wide range of frequency. Our study reproduces both features of oscillations in a single gene regulatory network and shows that the negative plus positive feedback loops in gene regulatory network offer additional advantage. We identified the key parameters/variables responsible for different modes of oscillation. The network is flexible in switching between different modes by choosing appropriately the required parameters/variables.

In this work, we consider a one-electron moving on a Fermi, Pasta, Ulam disordered chain under effect of electron–phonon interaction and a Gaussian acoustic pulse pumping. We describe electronic dynamics using quantum mechanics formalism and the nonlinear atomic vibrations using standard classical physics. Solving numerical equations related to coupled quantum/classical behavior of this system, we study electronic propagation properties. Our calculations suggest that the acoustic pumping associated with the electron–lattice interaction promote a sub-diffusive electronic dynamics.

We discuss the effects of spatial interference between two infectious hotspots as a function of the mobility of individuals (wind speed) between the two and their relative degree of infectivity. As long as the upstream hotspot is less contagious than the downstream one, increasing the wind speed leads to a monotonic decrease of the infection peak in the downstream hotspot. Once the upstream hotspot becomes about between twice and five times more infectious than the downstream one, an optimal wind speed emerges, whereby a local minimum peak intensity is attained in the downstream hotspot, along with a local maximum beyond which the beneficial effect of the wind is restored. Since this nonmonotonic trend is reminiscent of the equation of state of nonideal fluids, we dub the above phenomena “epidemic condensation”. When the relative infectivity of the upstream hotspot exceeds about a factor five, the beneficial effect of the wind above the optimal speed is completely lost: any wind speed above the optimal one leads to a higher infection peak. It is also found that spatial correlation between the two hotspots decay much more slowly than their inverse distance. It is hoped that the above findings may offer a qualitative clue for optimal confinement policies between different cities and urban agglomerates.