Mathematics, Volume 14, Issue 4

Mathematical modeling of heat and mass transfer processes in porous media using fractional derivative equations is of great practical importance. Within the framework of such models, obtaining analytical solutions to the corresponding initial–b...

Accurate time series forecasting of sea surface temperature (SST) is essential for understanding the ocean climate system and large-scale ocean circulation, yet it remains challenging due to regime-dependent variability and correlated errors across h...

We present a comprehensive framework for estimating heterogeneous treatment effects and evaluating decision-making policies in high-dimensional settings. Our approach combines nonlinear manifold learning techniques—UMAP, t-SNE, and Isomap&mdash...

We propose a coupled gas–particle two-phase model for particle transport in a compressible carrier gas with interphase momentum and energy exchange, and we incorporate a diffusion-based mechanism to represent gas–particle reactions. The g...

Electromechanical Actuators (EMAs) are critical components in More-Electric Aircraft (MEA) and Reusable Launch Vehicles (RLVs), yet they remain vulnerable to jamming and fatigue failures under high-stress flight maneuvers. Existing Health-Aware Fligh...

We derive an asymptotic expansion for the tail function of the product of $n(n\in \mathbb{N})$ independent identically distributed Weibull random variables. The coefficients of the expansion are obtained using a recursive formula arising from the Laplace meth...

This study examines the $\delta$-complements of graphs—a specific type of graph complement whose adjacency depends on the adjacency of the vertices with identical degrees in the original graph. More specifically, we study this type of complement...

An exact formula $B\left(n\right)={\displaystyle \frac{n}{2}}(\lfloor lgn\rfloor +1)-{\sum }_{k=0}^{\lfloor lgn\rfloor }{2}^k\mathit{Zigzag}\left({\displaystyle \frac{n}{2^{k+1}}}\right),$ where $\mathit{Zigzag}\left(x\right)=min(x-\lfloor x\rfloor ,\lceil x\rceil -x),$ for the minimum number $B\left(n\right)$ of comparisons of keys performed by $\mathtt{MergeSort}$ on an...

This study presents a theoretical analysis of the slow translation of a soft sphere through an unbounded micropolar fluid under steady, low Reynolds number conditions, accounting for the influence of interfacial stress jump. The soft sphere is modele...

We study the optimal extraction of a non-renewable resource under an endogenous risk of irreversible degradation. The extractor faces a stochastic switching time at which extraction costs permanently increase, with the hazard rate of this transition...

This paper develops classical and Bayesian inferential procedures for Weibull exponential lifetime models under joint progressive Type-II censoring, motivated by comparative reliability analysis of products manufactured across multiple production lin...

We establish a version of Pontryagin’s maximum principle for optimal control problems with impulses and phase constraints. Using the Dubovitskii–Milyutin theory, we construct a conic variational framework that handles impulsive dynamics a...

Accurate derivative information is central to sensitivity analysis and optimization, yet standard finite differences can lose many digits when the step size is small because of subtractive cancellation. Complex-step differentiation largely resolves t...

This paper presents a comprehensive study of statistical tests for comparing temporal point processes in general, with a particular focus on Poisson processes. We explore three key approaches: (1) an intensity-based test specifically for Poisson proc...

Graph-based clustering is a fundamental task in unsupervised machine learning and has been extensively applied to complex data mining scenarios, such as pattern recognition and data classification. However, most existing graph clustering algorithms s...

The Cohen–Grossberg neural network is studied in the case when the dynamics of the neurons are modeled by generalized Caputo fractional derivatives with respect to another function (GCFDF). We consider a time-dependent delay and a switching rul...

Accurate inversion of the deep initial in situ stress field is a fundamental prerequisite for stability analysis of surrounding rock in underground engineering, roadway support design, and prevention and control of dynamic disasters. To address the p...

The assessment of reliability in non-repairable subsystems of mining electronic equipment represents a computationally challenging problem, particularly for complex and highly connected structures. This study presents a systematic comparative analysi...

This work analyzes the non-Newtonian electromagnetohydrodynamic (EMHD) flow in an irregular circular porous microchannel while incorporating the consequences of surface charge-dependent slip boundary conditions. The Jeffrey fluid is employed to exami...

This article provides a geometric characterization of the geodesic boundary for surfaces invariant under parabolic isometries in ${\mathbb{H}}^2\times \mathbb{R}$. We present an alternative, constructive proof for the existence of minimal surfaces with rectangular asymptot...

The majority of breast malignancies arise from breast ducts at the small-scale level. Understanding the wave characteristics of breast ducts may assist in developing new technologies to detect very early changes that precede breast cancer. In this st...

Modern information security relies heavily on symmetric-key cryptography such as AES. As quantum computing advances, these classical schemes face increasing pressure from quantum key-search attacks, most notably Grover’s algorithm. To evaluate...

The q-calculus framework has emerged as a powerful tool in geometric function theory, enabling refined analysis of analytic and bi-univalent functions. Inspired by the versatility of the q-derivative operator, this paper introduces a new generalized...

We develop a function theory on a three-dimensional reduced quaternionic model endowed with a projected (and, therefore, non-associative) product, together with its natural dual extension generated by a nilpotent infinitesimal unit. After introducing...

In this study, a comprehensive mathematical method for modeling the operational reliability of mine hoisting equipment under conditions of incomplete and heavily censored data is developed. The analyzed dataset includes 259 observations collected ove...

The rapid expansion of the Internet of Things (IoT) has led to billions of interconnected devices generating and exchanging sensitive data across diverse domains, which introduces challenges in identity management (IdM) regarding privacy, scalability...

Differential equations are usually employed to accurately represent the ongoing relationships between tumor cells and immune effector populations, enabling scientists to discover how variation in growth and response rates affects tumor development or...

Producer share indicators summarize how value is distributed along agrifood supply chains, yet their temporal dynamics remain difficult to compare across products and periods. This paper proposes a reproducible time-series analytics framework to char...

Depression poses a major worldwide health burden, necessitating advanced diagnostic tools based on reliable and authentic assessment. While multimodal AI systems offer promising results by integrating diverse data sources, existing approaches often r...

Taylor–Young and Maclaurin series are widely used for approximating smooth functions around a given point. This study investigates a unified stochastic framework for Taylor-type expansions of functions by means of independent random variables....

The Kudryashov–Sinelshchikov equation (KSE) is crucial in modeling pressure waves in liquids containing gas bubbles, capturing both nonlinear wave phenomena and dispersion effects. This article applies the reproducing kernel Hilbert space metho...

A class of self-similar solutions to the model of a cylindrical shock wave in non-uniform atmosphere in the presence of monochromatic radiation and gravitation in magneto gas dynamics has been obtained by using a similarity method. The propagation of...

Secure compressive sensing (SCS) mostly benefits scenes such as IoT with finite computer resources, the fields of spaceflight and medicine, etc. Recently, research on SCS has aroused widespread interest. Nevertheless, existing work on embedding secur...

Despite the significant interest from research communities in understanding the squeezing flow of fluid between two plates, important qualitative and quantitative questions regarding solutions to these squeezing flow models still remain unanswered, i...

Stock return prediction for quantitative trading in U.S. equity markets has evolved from parametric econometric modeling toward data-driven deep learning systems that must jointly capture temporal dynamics, discontinuous jumps, and evolving cross-ass...

This study presents a statistical modeling approach for predicting the operational reliability of induction motors used in dump truck drives. The proposed method uses censored data, including both time to failure and data on properly operating engine...

Residuals play a central role in linear regression, yet their geometry is often hidden by inverse- and pseudoinverse-based formulas. We develop a rank-aware framework for residual projection that makes the underlying orthogonality explicit. When the...

Dental caries is an example of an oral infectious disease that affects many people worldwide, but it is not well studied in deterministic mathematical modeling. Therefore, we are interested in studying the dynamics of tooth cavity disease using a det...

This study introduces a novel four-parameter lifetime distribution constructed within the Topp–Leone Power Gompertz framework. Owing to its flexible structure, the proposed model accommodates a wide range of density shapes and hazard-rate patte...

In this paper, we examine Ricci–Bourguignon solitons on locally decomposable golden Riemannian manifolds of constant golden sectional curvature. First, we establish an explicit expression for the soliton constant in terms of the golden structur...

Seismic wavefield simulation is the primary technique used to study the effects of vertical transverse isotropy (VTI) on the propagation of Rayleigh waves. However, conventional Rayleigh wave dispersion equations are based on isotropic assumptions an...

In this study, we statistically analyze the performance of a threshold-based multiple optical signal selection scheme (TMOS) for wavelength division multiplexing (WDM) and adaptive coded modulation (ACM); this is achieved using free space optical (FS...

Sound source localization in dynamic environments with multiple moving speakers presents significant challenges due to reverberation, noise, and unknown source counts. To address these issues, this paper proposes an integrated deep-learning framework...

This paper presents a set of survey-style notes linking core themes of pure algebra with central topics in algebraic and analytic number theory. We begin with finite extensions of $\mathbb{Q}$ and describe algebraic number fields through their realization as fi...

In this paper, we prove that, on the one hand, a duality relationship between different types of modular T-transitive relations and the reciprocal modular generalized metrics exists and, on the other hand, that, based on this duality, a construction...

The use of integral and differential operators in geometric function theory has continued to gain interest among researchers in the field of study in recent times. This is due to the wide range of its applications in science, technology and engineeri...

In this study, we developed an SIR-like mathematical model of disease transmission dynamics. Hantavirus is a neglected tropical disease, and this paper presents a mathematical model of hantavirus transmission among rodents and its effect on the numbe...

We conduct a numerical study of integral algebraic equations (IAEs) with singular points, which pose significant challenges for standard computational methods. The presence of singular points often renders classical discretization schemes unstable an...

Pre-sale mechanisms are widely used by e-tailers to manage demand uncertainty and stimulate early purchases, yet existing research has largely emphasized economic incentives while giving limited attention to consumers’ psychological responses t...

Maximum entropy adversarial inverse reinforcement learning (ME-AIRL) has garnered widespread attention for its ability to learn rewards and optimize policies from expert demonstrations. In complex multi-task environments, applying meta-learning ME-AI...