Mathematics, Volume 13, Issue 20

This paper aims to establish fixed point theorems in a complete strong b-metric space under the $\alpha$-$\psi$-contractive condition imposed on single-valued mappings. Subsequently, we prove certain fixed point theorems, both locally and globally, und...

We discuss the complex-analytic subsets of the moduli spaces of rank 2 vector bundles on a classical Hopf surface formed by irregular bundles. We stratify the set of irregular bundles by weight (and irregular profiles). We provide the topological res...

This study introduces SHAP-Rule, a novel explainable artificial intelligence method that integrates Shapley additive explanations with fuzzy logic to automatically generate interpretable linguistic IF-THEN rules for diagnostic tasks. Unlike purely nu...

Let p be a prime and ${\mathbb{F}}_p$ a finite field of order p. This paper investigates cyclic codes over the ring $R_{p^2,u}={\mathbb{Z}}_{p^2}+u{\mathbb{Z}}_{p^2}$ of order $p^4$, where the nilpotent element u satisfies $u^2=0$ and $pu\ne 0.$ The condition $u^2=0$ with $pu\ne 0$ is crucial, as it creates a no...

We prove in this paper some existence and uniqueness results of weak solutions for some nonlinear degenerate parabolic problems arising from capillarity phenomena with the Dirichlet type boundary condition.

Arabic automatic speech recognition (ASR) faces distinct challenges due to its complex morphology, dialectal variations, and the presence of diacritical marks that strongly influence pronunciation and meaning. This study introduces a lightweight appr...

Object detection in airport surface surveillance presents significant challenges, primarily due to the extreme variation in object scales and the critical need for contextual information. To address these issues, we propose a novel deep learning arch...

Belief Propagation (BP) is a fundamental heuristic for solving Constraint Optimization Problems (COPs), yet its practical applicability is constrained by slow convergence and instability in loopy factor graphs. While Damped BP (DBP) improves converge...

Uncertainty quantification (UQ) for open-ended language generation remains a critical yet underexplored challenge, particularly in settings where token-level log-probabilities are available during decoding. We present Token-Entropy Conformal Predicti...

Adaptive filtering algorithms often suffer from biased parameter estimation and performance degradation in the presence of colored input noise and impulsive observation noise, both of which are common in practical sensor and communication systems. Ex...

We propose a class of coupled dynamical systems for solving linear inverse problems, treating both the unknown variable and an auxiliary variable representing measurement dynamics as state variables. This framework does not rely on probabilistic mode...

We propose State-DynAttn, a hybrid architecture for robust air traffic flow prediction under weather disruptions, which integrates state-space models (SSMs) with dynamic graph attention to address the challenges of long-range dependency modeling and...

In the context of industrial transitions and tariff frictions, financial markets are experiencing frequent defaults, emphasizing the urgency of upgrading credit scoring methodologies. A novel credit risk identification model integrating generative ad...

Packing approaches enhance training efficiency by filling the padding space in each batch with shorter sequences, thereby reducing the total number of batches per epoch. This approach has proven effective in both pre-training and supervised fine-tuni...

Improving robustness under distributional shifts remains a central challenge in machine learning. Although Sharpness-Aware Minimization (SAM) has proven effective in finding flatter minima for better generalization, it overlooks the heterogeneity in...

In this paper, we study majorization-type inequalities for n-convex (specifically 3-convex) functions. Numerous papers deal with such integral inequalities, in which n-convex functions are defined on compact intervals and nonnegative measures are use...

This article proposes a novel application of the Bayesian variable selection framework for driver telematics data. Unlike the traditional LASSO, the Bayesian variable selection framework allows us to incorporate the importance of certain features in...

In this paper, we unify and extend the linear quadratic pursuit–evasion games to dynamic equations on time scales. A mixed strategy for a single pursuer and evader is studied in two settings. In the open-loop setting, the corresponding controls...

Aiming at the problems of high complexity in source domain data, inaccessibility of target domain data, and unknown fault patterns in real-world industrial scenarios for mechanical fault diagnosis, this paper proposes a Feature Decomposition-based So...

In this work, we investigate quantum correlations, including entanglement and quantum discord, within the hyperfine structure of the hydrogen atom using the Lindblad master equation to model its dynamics as an open quantum system interacting with an...

In this paper, we develop a delayed malaria model that integrates a discrete time delay and a non-smooth threshold-based control strategy. Using the time delay τ as a bifurcation parameter, we investigate the local stability of the endemic equili...

An assembly line is a manufacturing process commonly used in the production of commodity goods. The assembly process is divided into elementary tasks that are sequentially performed at serially arranged workstations. Among the various challenges that...

To investigate the contact performances and meshing characteristics of gears systematically, an improved comprehensive meshing stiffness model of spur gears with consideration of the tooth surface morphology, lubrication, friction, and thermal effect...

Elucidating drug response mechanisms in human melanoma is crucial for improving treatment outcomes. Moreover, the existing tools intended to provide deeper insight into melanoma drug resistance have notable limitations. Therefore, we propose a deep l...

This study aims to evaluate the environmental performance of G7 countries using the Environmental Performance Index. To do this, we introduce a novel ranking multi-criteria method, Alternative Prioritization and Assessment System, for the first time...

Modeling stock returns and option pricing in the presence of jumps remains a central challenge in financial economics. This paper employs a novel score-driven GARCH-jump model to analyze SSE (Shanghai Stock Exchange) 50 ETF returns and option pricing...

Understanding the nonlinear mechanical behaviour of mitral valve chordae tendineae is critical for accurate biomechanical modelling in cardiac simulations. This study integrates high-resolution 3D finite element analysis with experimentally derived C...

In recent years, SLAM, visual odometry, and structure-from-motion approaches have widely addressed the problems of 3D reconstruction and ego-motion estimation. Of the many input modalities that can be used to solve these ill-posed problems, the pure...

High-quality image restoration (IR) is a fundamental task in computer vision, aiming to recover a clear image from its degraded version. Prevailing methods typically employ a static inference pipeline, neglecting the spatial variability of image cont...

Motivation. Analytic function theory on commutative complex extensions calls for an operator–theoretic calculus that simultaneously sees the algebra-induced coupling among components and supports boundary-to-interior mechanisms. Gap. While Dira...

In this paper, we investigate the behavior of solutions to a nonlinear system of rational difference equations of order two, defined by $x_{n+1}={\displaystyle \frac{x_n{y}_{n-1}}{y_n(a+b{x}_n{y}_{n-1})}},y_{n+1}={\displaystyle \frac{y_n{z}_{n-1}}{z_n(c+d{y}_n{z}_{n-1})}},z_{n+1}={\displaystyle \frac{z_n{x}_{n-1}}{x_n(e+f{z}_n{x}_{n-1})}},$ wh...

The environmental pollution problem in the textile and garment industry has become increasingly severe, necessitating urgent mitigation. This study examines which supply chain member’s pollution abatement investment generates greater benefits f...

As information plays an ever more central role across disciplines, the lack of a precise and reusable definition of state impedes comparison, measurement, and verification. Building on Objective Information Theory (OIT), this paper proposes a logic-b...

Accurate pedestrian detection from a robotic perspective has become increasingly critical, especially in complex environments such as crowded and high-density populations. Existing methods have low accuracy due to multi-scale pedestrians and dense oc...

Self-oscillating systems are capable of transforming ambient energy directly into mechanical output, and exploring novel designs is of great value for energy harvesters, actuators, and engine applications. The inspiration for this study is drawn from...

This paper investigates the existence and multiplicity of positive solutions for a system of generalized Laplacian problems. By analyzing the asymptotic behavior of nonlinearity, we establish conditions for the existence of positive solutions and the...

Against the backdrop of incomplete evaluation information prevalent in real-world decision-making scenarios and the limited application of Fermatean fuzzy numbers (FFNs) in the domain of two-sided matching (TSM) models, this paper proposes a Fermatea...

Some large language models (LLMs) are open source and are therefore fully open for scientific study. However, many LLMs are proprietary, and their internals are hidden, which hinders the ability of the research community to study their behavior under...

A high-order single-step implicit method, the Legendre–Darboux Method of order six (LDM6), is introduced for solving both linear and nonlinear initial value problems. Unlike classical Taylor expansions, LDM6 systematically constructs higher-ord...

Glioblastoma is the most aggressive and treatment-resistant form of primary brain tumors, characterized by rapid invasion and a poor prognosis. Its complex behavior continues to challenge both clinical interventions and research efforts. Mathematical...

Due to computational constraints, ocean numerical models are often executed on low-resolution (LR) grids. To maintain consistency between LR simulations and coarsened high-resolution (HR) solutions, a subgrid forcing term is commonly integrated into...

This paper addresses green supply chain financing decisions based on inter-chain competition and implicit equity considerations. First, considering the different situations of green supply chain members when facing green investment costs, it separate...

In increasingly networked environments, artificial agents are required to operate not with fixed roles but with identities that adapt, evolve, and emerge through interaction. Traditional identity modeling approaches, whether symbolic or statistical,...

The approximate pole/zero expressions are computed starting from the state or the “state-like” matrix. The attempts of open-circuit and short-circuit replacement of circuit elements are combined with those to cut row and column groups of...

In the context of increasingly strong digital transformation and production automation, choosing the right palletizing robot plays a key role in optimizing operational efficiency in industrial chains. However, the wide variety of robot types and spec...

Stochastic geometry provides a powerful analytical framework for evaluating interference-limited cellular networks with randomly deployed base stations (BSs). While prior studies have examined limited channel state information at the transmitter (CSI...

Portfolio optimization is a cornerstone of modern financial decision-making, traditionally based on the mean–variance model introduced by Markowitz. However, this framework relies on restrictive assumptions—such as normally distributed re...

This study proposes a lightweight double-encryption cryptosystem for 3D medical images such as Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET) scans, and Computed Tomography scans (CT). The first encryption process uses chaotic p...

Accurate hippocampal segmentation in 3D MRI is essential for neurodegenerative disease research and diagnosis. Preprocessing pipelines can strongly influence segmentation accuracy, yet their impact across datasets and in transfer learning scenarios r...

In this paper, we tackle a bi-objective optimization problem in which we aim to maximize the portfolio diversification and, at the same time, minimize the portfolio volatility, where the ESG (Environmental, Social, and Governance) information is inco...