- Article
On a p(x)-Biharmonic Kirchhoff Problem with Logarithmic Nonlinearity
- Dongyun Pan and
- Changmu Chu
This paper is devoted to the study of a class of the
2025 September-2 - 150 articles
This paper is devoted to the study of a class of the
In cooperative coevolution (CC) frameworks, it is essential to identify the subproblems that can significantly contribute to finding the optimal solutions of the objective function. In traditional CC frameworks, subproblems are selected either sequen...
This paper proposes a mixed-integer linear programming (MILP) model for the consistent vehicle routing problem with time windows (ConVRPTW), motivated by the need to enhance customer satisfaction in the last-mile logistics industry. The problem invol...
Coastal regions are among the areas most affected by climate change, facing rising sea levels, frequent flooding, and accelerated erosion that place renewable energy infrastructures under serious threat. Solar farms, which are often built along shore...
Vehicle Routing Problems are central to logistics and operational research, arising in diverse contexts such as transportation planning, manufacturing systems, and military operations. While Deep Reinforcement Learning has been successfully applied t...
Process monitoring plays a vital role in ensuring quality stability, and, operational efficiency across fields such as manufacturing, finance, biomedical science, and environmental monitoring. Among statistical tools, control charts are widely adopte...
Nonlinear complex systems exhibit emergent behavior, sensitivity to initial conditions, and rich dynamics arising from interactions among their components. A classical example of such a system is the Troesch problem—a nonlinear boundary value p...
While core-periphery (CP) structures are a fundamental property of many social networks, their influence on information diffusion remains insufficiently understood, especially for complex contagions that require social reinforcement. To address this...
In RNA-seq data analysis, a primary objective is the identification of differentially expressed genes, which are genes that exhibit varying expression levels across different conditions of interest. It is widely known that hidden factors, such as bat...
Remote sensing visual question answering (RSVQA) involves interpreting complex geospatial information captured by satellite imagery to answer natural language questions, making it a vital tool for observing and analyzing Earth’s surface without...
The volatile nature of cryptocurrency markets demands real-time analytical capabilities that traditional centralized computing architectures struggle to provide. This paper presents a novel hybrid cloud–edge computing framework for cryptocurren...
This article investigates a mathematical model with the Caputo derivative for the transient unidirectional flow of an incompressible viscous fluid with pressure-dependent viscosity. The fluid flows in the spatial domain bounded by two parallel plates...
This paper investigates the quasi-concircular curvature tensor on sequential warped product manifolds, which extend the classical singly warped product structure. We examine various curvature conditions associated with this tensor, including quasi-co...
The analysis of high-dimensional count data presents a unique set of challenges, including overdispersion, zero-inflation, and complex nonlinear relationships that traditional generalized linear models and standard machine learning approaches often f...
Survival analysis is a fundamental tool for modeling time-to-event data in healthcare, engineering, and finance, where censored observations pose significant challenges. While traditional methods like the Beran estimator offer nonparametric solutions...
Characterizingthe spatial variability of agricultural data is a fundamental step in precision agriculture, especially in soil management and the creation of differentiated management units for increasing productivity. Modeling the spatial dependence...
The goal of this manuscript is to introduce a new Stancu generalization of the modified Szász–Kantorovich operator connecting Riemann–Liouville fractional operators via Charlier polynomials. Further, some estimates are calculated as test functions an...
Quadratic programming (QP) formulations are widely used in optimal investment portfolio selection, a central problem in financial decision-making. In practice, asset allocation decisions operate at two interconnected levels: the strategic level, whic...
To solve problems on a positive-dimensional ideal,
Using equivalent transformations, complicated circuits in physics that need numerous mathematical operations to analyze can be broken down into simpler equivalent circuits. It is also possible to determine the number of spanning trees—graph fam...
The law of the iterated logarithm precisely refines the law of large numbers and plays a fundamental role in probability limit theory. The framework of sub-linear expectation spaces substantially extends the classical concept of probability spaces. I...
This paper investigates the synchronization problem of singularly perturbed complex networks with time delays, in which a novel event-triggered delayed impulsive control strategy is developed. To conserve limited communication bandwidth, a dynamic ev...
This work presents a numerical investigation of Richtmyer–Meshkov instability (RMI) in shock-driven single-mode stratified heavy fluid layers, with emphasis on the influence of the Atwood number. High-order modal discontinuous Galerkin simulati...
As a multirobot system grows in its number of agents, contention over shared resources poses a more significant risk of deadlock and operational deficiencies. When integrating with buildings, one of the most common pieces of equipment that robots hav...
This study presents a novel framework for uncertainty propagation in power-law, Bingham, and Casson fluids through rectangular ducts under stochastic viscosity (Case I) and pressure gradient conditions (Case II). Using the computationally efficient S...
Progressive first-failure censoring is a flexible and cost-efficient strategy that captures real-world testing scenarios where only the first failure is observed at each stage while randomly removing remaining units, making it ideal for biomedical an...
The traditional boundary knot method (BKM) has certain advantages in solving Helmholtz equations, but it still faces the difficulty of solving ill-posed problems when dealing with inverse problems. This work proposes a novel deep learning framework,...
Nonparametric control charts are widely used in many manufacturing processes when there is a lack of knowledge about the distribution that the quality characteristic of interest follows. If there is evidence that the unknown distribution is symmetric...
In image classification, convolutional neural networks (CNNs) remain vulnerable to visually imperceptible perturbations, often called adversarial examples. Although various hypotheses have been proposed to explain this vulnerability, a clear cause ha...
Complex problems usually require the simultaneous consideration of multiple performance criteria within multidisciplinary environments [...]
In this paper, we establish a fixed-point theorem for mixed monotone operators in ordered Banach algebras by introducing a novel contraction condition formulated in terms of the product law, which represents a significant departure from the tradition...
This study investigates the adoption of blockchain technology (BCT) and financing decisions for capital-constrained manufacturers in live streaming supply chains, where product quality information is asymmetric. Although BCT can improve information t...
Blood cell detection and enumeration play a crucial role in medical diagnostics. However, traditional methods often face limitations in accurately detecting smaller or overlapping cells, which can result in misclassifications and reduced reliability....
The conditional Feynman integral provides solutions to integral equations equivalent to heat and Schrödinger equations. The Cameron–Martin translation theorem illustrates how the Wiener measure changes under translation via Cameron–M...
This study investigates the evolution of online public opinion during the COVID-19 pandemic by integrating topic mining with sentiment analysis. To overcome the limitations of traditional short-text models and improve the accuracy of sentiment detect...
Predictive maintenance (PdM) is essential for reducing equipment downtime and enhancing operational efficiency. However, PdM datasets frequently suffer from significant class imbalance and are often limited to single-label classification, which fails...
The automotive and agricultural industries face increasingly stringent demands with technological advancements and rising living standards, resulting in substantially heightened engineering complexity. In this background, optimization methods become...
We study a class of circular restricted planar Newtonian four-body problems in which three masses are positioned at the vertices of a Lagrange equilateral triangle configuration, each mass revolving around the center of mass in circular orbits. Assum...
Accurate air quality prediction (AQP) is crucial for safeguarding public health and guiding smart city management. However, reliable assessment remains challenging due to complex emission patterns, meteorological variability, and chemical interaction...
Feature map pooling in convolutional neural networks (CNNs) serves the dual purpose of reducing spatial dimensions and enhancing feature invariance. Current pooling approaches face a fundamental trade-off: deterministic methods (e.g., MaxPool and Avg...
This study, grounded in traveling wave theory, develops a cross-scale reaction-diffusion model to describe nutrient-dependent bacterial growth on agar surfaces and applies it to in silico investigations of microbial population dynamics. The approach...
In the original publication [...]
Forecasting Bitcoin prices remains a complex task due to the asset’s inherent and significant volatility. Traditional reinforcement learning (RL) models often rely on a single observation from the time series, potentially missing out on short-t...
(1) Background: Soccer action recognition (SAR) is essential in modern sports analytics, supporting automated performance evaluation, tactical strategy analysis, and detailed player behavior modeling. Although recent advances in deep learning and com...
Industrial symbiosis network (ISN) is crucial to improving resource utilization efficiency and promoting sustainable development. In order to mitigate the damage caused to symbiotic systems by risk propagation, this paper constructs a directed weight...
Hepatitis C virus (HCV) remains a critical public health concern globally, including in Bangladesh. In this study, we employed a mathematical modeling framework to analyze the national dynamics of HCV infections and associated mortality in Bangladesh...
This paper presents a Neural Network-Based Symbolic Computation Algorithm (NNSCA) for solving the (2+1)-dimensional Yu-Toda-Sasa-Fukuyama (YTSF) equation. By combining neural networks with symbolic computation, NNSCA bypasses traditional method limit...
Resonance self-shielding in multi-resonant nuclide media is a dominant physical process in reactor neutronics analysis. This study proposes an improved subgroup method (ISM) based on Padé rational approximation, constructing a high-order ratio...
A high-precision coal seam model is crucial to improving the adaptability of unmanned mining technology to geological conditions. However, the accuracy of a coal seam model constructed with boreholes and geophysical data is far from the required accu...
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