This study focuses on the single-objective day-ahead economic dispatch of grid-connected microgrids. It proposes an asymmetric GE-RTH-SH framework that integrates gradient-guided elite search (GE), Red-Tailed Hawk Optimization (RTH), and SHADE-lite a...
The Graduate Student Evolutionary Algorithm (GSEA) provides a simple population-based optimization framework, but its performance may be limited by unreliable mentor selection, insufficient adaptation of learning behavior, and inadequate utilization...
Fossil fuels are crucial to the global energy supply, with pipelines being a vital transportation method. However, these vital assets are highly susceptible to pitting corrosion, an insidious form of degradation that can lead to catastrophic failures...
Research on unmanned aerial vehicle (UAV) path planning technology in urban operation scenarios faces the challenge of multi-objective collaborative optimization. Currently, mainstream path planning algorithms, including the multi-objective particle...
Searchable encryption (SE) is one of the effective techniques for searching encrypted data without decrypting it. This technique can provide a secure indexing mechanism for encrypted data and utilize a secure trapdoor to search for the encrypted data...
Generative AI-enabled teaching increasingly requires evaluation mechanisms that can process large candidate indicator sets without being dominated by uneven category frequencies or redundant variables. Existing filter methods are computationally inex...
The lack of positive results in searches for supersymmetric (SUSY) particles at the Large Hadron Collider (LHC) and in direct searches for Weakly Interacting Massive Particles (WIMPs) in the underground experiments may hint to a super-high energy sca...
Data clustering is a complex data mining problem that clusters a massive amount of data objects into a predefined number of clusters; in other words, it finds symmetric and asymmetric objects. Various optimization methods have been used to solve diff...
The molecular approach to understanding the mechanisms of emerging diseases, like COVID-19, has largely accelerated the search for successful therapeutical strategies. In this work, we present an extensive molecular dynamics (MD) analysis of two form...
As a classical combinatorial optimization problem, the traveling salesman problem (TSP) has been extensively investigated in the fields of Artificial Intelligence and Operations Research. Due to being NP-complete, it is still rather challenging to so...
The review is devoted to the theoretical and synthetic aspects of the stereochemistry of organophosphorus compounds. Organophosphorus compounds are not only widely exist in biologically active pharmaceuticals and agrochemicals, but also have widespre...
Lack of public funding and environmental deterioration are promoting the search for innovative mechanisms enabling to boost farmers’ provision of agri-environmental climate public goods. This work aims to contribute to the current debate by highlight...
Aiming at the time-dependent green vehicle routing problem with fuzzy demand, this paper comprehensively considers the dispatch costs, time window penalty costs, fuel costs, and the effects of vehicle travel speed, road gradient, and vehicle load on...
Adaptive decisions are often based on algorithm-specific feedback or simple indicators that provide limited information about the evolving search dynamics. This work investigates explicit pattern-based analysis of the search trajectory as a source of...
This paper addresses the issue of safe trajectory tracking for robotic manipulators operating in confined spaces that often exhibit asymmetric geometric structures, such as narrow passages or cluttered obstacle fields. We introduce an innovative mode...
The distinction between whether a shock to the market of any asset is a valuation event or a financial stability event lies in the mechanism through which such a shock is translated into demand for liquidity. The aim of this integrative review is to...
Classical vehicle routing models assume flat, symmetric road networks, yet mountain cities exhibit gravitational asymmetry and steep gradients that invalidate two-dimensional cost estimates and may produce mechanically infeasible routes. This study f...
A Multi-Layer Perceptron (MLP), as the basic structure of neural networks, is an important component of various deep learning models such as CNNs, RNNs, and Transformers. Nevertheless, MLP training faces significant challenges, with a large number of...
Path planning is one of the main focal points and challenges in mobile robotics research. Traditional ant colony optimization (ACO) algorithms encounter issues such as low efficiency, slow convergence, and a tendency to become stuck in local optima a...
Division of labor in self-organized groups is a problem of both theoretical significance and application value. Many application problems in the real world require efficient task allocation. We propose a model combining bio-inspiration and evolutiona...
To enhance the operational performance of mobile manipulators in textile workshops and address the difficulty of inverse kinematics (IK) for this class of redundant manipulators, this paper leverages the robot’s structural symmetries and propos...
Hyperhomocysteinemia (HHcy) influences the development and progression of neurodegenerative disorders in different ways. Homocysteine (Hcy) metabolism is related to that of asymmetric dimethylarginine (ADMA) and group B vitamins. The breakdown of the...
To address the limitations of the traditional Balancing Composite Motion Optimization (BCMO) algorithm—namely weak directional global exploration, insufficient local exploitation accuracy, and a tendency to fall into local optima with reduced p...
Bilateral robotic rehabilitation has emerged as a technological approach for promoting coordinated upper-limb training after stroke. This state-of-the-art review critically analyzes bilateral upper-limb rehabilitation robots with emphasis on mechanic...
Eukaryotic cells have distinct membrane-enclosed organelles, each with a unique biochemical signature and specialized function. The unique identity of each organelle is greatly governed by the asymmetric distribution and regulated intracellular movem...
Siamese networks have proven to be suitable for many computer vision tasks, including single object tracking. These trackers leverage the siamese structure to benefit from feature cross-correlation, which measures the similarity between a target temp...
To address the issue of hysteresis nonlinearity adversely affecting the tracking accuracy of piezoelectric actuators, an improved particle swarm optimization (PSO) algorithm is proposed to improve the accuracy of hysteresis model parameter identifica...
Objective: To identify and summarize biomechanical assessment approaches in interlimb coordination on poststroke gait. Introduction: Interlimb coordination involves complex neurophysiological mechanisms that can be expressed through the biomechanical...
Background/Objectives: Varicocele is usually clinically left-sided, but imaging and mechanistic studies suggest that contralateral venous reflux or bilateral testicular effects may be more common than physical examination indicates. This narrative re...
Lithology prediction is a fundamental component of geological exploration and hydrocarbon reservoir characterization, playing a critical role in improving subsurface structural interpretation and enhancing resource prediction accuracy. However, well...
In this study, a hybrid heading control framework for unmanned surface vehicles (USVs) is proposed, combining variable domain fuzzy Proportional–Integral–Derivative (VUF-PID) with an improved algorithmic Beetle Antennae Search–Parti...
Photovoltaic (PV) power generation is characterized by high fluctuation and intermittency. The accurate forecasting of PV power is crucial for optimizing grid operation and scheduling. Thus, a novel short-term PV power-forecasting method based on gen...
For the past few years, centralized decision-making is being used for malicious node identification in wireless sensor networks (WSNs). Generally, WSN is the primary technology used to support operations, and security issues are becoming progressivel...
Ant Colony Optimization (ACO) encompasses a family of metaheuristics inspired by the foraging behaviour of ants. Since the introduction of the first ACO algorithm, called Ant System (AS), several ACO variants have been proposed in the literature. Owi...
An improved equilibrium optimizer (EO) algorithm is proposed in this paper to address premature and slow convergence. Firstly, a highly stochastic chaotic mechanism is adopted to initialize the population for range expansion. Secondly, the capability...
Efficient exploitation of evolutionary knowledge while preserving population diversity remains a central challenge in optimization. Existing knowledge-learning evolutionary algorithms primarily rely on successful experiences, overlooking structural i...
Conversational systems based on large language models (LLMs) are being increasingly used as advisors in mental health and self-regulation contexts, yet causal evidence remains limited about whether such guidance strengthens human agency rather than s...
Background/Objectives: Free riding in healthcare occurs when actors benefit from health-related public goods, risk-pooling arrangements, common resources, or cooperative institutions while contributing less than is socially optimal. This review clari...
Oral mucosal diseases often lead to structural damage and functional impairment due to high recurrence and malignant progression. Current therapeutic outcomes remain unsatisfactory owing to the complex oral microenvironment. Recent reviews have cover...
Background: This scoping review systematically maps and synthesises contemporary literature on the biomechanics of active below-knee prosthetic devices, focusing on gait kinematics, kinetics, energy expenditure, and muscle activation. It further eval...
Multi-objective particle swarm optimization (MOPSO) algorithms based on angle preference provide a set of preferred solutions by incorporating a user’s preference. However, since the search mechanism is stochastic and asymmetric, traditional MO...
A dwarf mutant (dwf1) was obtained among 15 transgenic lines, when TaLEA (Tamarix androssowii late embryogenesis abundant gene) was introduced into Populus simonii × Populus nigra by Agrobacterium tumefaciens-mediated transformation. Under the same g...
In multi-variety, small-batch electric oven manufacturing, sequence-dependent setup times (SDST) and worker skill heterogeneity jointly affect makespan, labor cost, and energy consumption. This study addresses a multi-objective hybrid flow shop sched...
The standard Grey Wolf Optimizer (GWO) suffers from rapid population diversity loss when solving the Traveling Salesman Problem (TSP), leading to premature convergence. This paper proposes the Closed-Loop Adaptive Grey Wolf Optimizer (CLA-GWO), which...
Incorrect sitting posture, characterized by asymmetrical or uneven positioning of the body, often leads to spinal misalignment and muscle tone imbalance. The prolonged maintenance of such postures can adversely impact well-being and contribute to the...
Background: The spike is a key action in volleyball, and the landing technique and its asymmetries are commonly associated with an increased risk of injury. Objectives: The aim of this systematic review was to assess how male and female volleyball pl...
Biomarker, the short form of “biological marker”, appeared in the scientific literature in the 1940s. Since then, many different definitions have been suggested, but a generally applicable explanation of the term biomarker in science is e...
Background/Objectives: The evidence base for anticoagulation moved substantially between 2023 and 2026: a reframed atrial fibrillation (AF) guideline, new randomized data on extended treatment of cancer-associated venous thromboembolism (VTE), the fi...
This paper addresses the insufficient speed control accuracy observed in traditional seeding systems. This paper proposes an electric drive seeding control method that incorporates a composite control strategy combining the Rime optimization algorith...
The emergence of quantum computing poses significant threats to conventional public-key cryptography, driving the urgent need for quantum-resistant cryptographic solutions. While quantum key distribution addresses secure key exchange, its dependency...
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