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  • Open Access

    ARTICLE

    OPOR-Bench: Evaluating Large Language Models on Online Public Opinion Report Generation

    Jinzheng Yu1, Yang Xu2, Haozhen Li2, Junqi Li3, Ligu Zhu1, Hao Shen1,*, Lei Shi1,*

    CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073771 - 10 February 2026

    Abstract Online Public Opinion Reports consolidate news and social media for timely crisis management by governments and enterprises. While large language models (LLMs) enable automated report generation, this specific domain lacks formal task definitions and corresponding benchmarks. To bridge this gap, we define the Automated Online Public Opinion Report Generation (OPOR-Gen) task and construct OPOR-Bench, an event-centric dataset with 463 crisis events across 108 countries (comprising 8.8 K news articles and 185 K tweets). To evaluate report quality, we propose OPOR-Eval, a novel agent-based framework that simulates human expert evaluation. Validation experiments show OPOR-Eval achieves a More >

  • Open Access

    ARTICLE

    Segment-Conditioned Latent-Intent Framework for Cooperative Multi-UAV Search

    Gang Hou1,#, Aifeng Liu1,#, Tao Zhao1, Wenyuan Wei2, Bo Li1, Jiancheng Liu3,*, Siwen Wei4,5,*

    CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2026.073202 - 10 February 2026

    Abstract Cooperative multi-UAV search requires jointly optimizing wide-area coverage, rapid target discovery, and endurance under sensing and motion constraints. Resolving this coupling enables scalable coordination with high data efficiency and mission reliability. We formulate this problem as a discounted Markov decision process on an occupancy grid with a cellwise Bayesian belief update, yielding a Markov state that couples agent poses with a probabilistic target field. On this belief–MDP we introduce a segment-conditioned latent-intent framework, in which a discrete intent head selects a latent skill every K steps and an intra-segment GRU policy generates per-step control conditioned on More >

  • Open Access

    REVIEW

    Melatonin as a Neuroprotective Agent in Ischemic Stroke: Mechanistic Insights Centralizing Mitochondria as a Potential Therapeutic Target

    Mayuri Shukla1, Soraya Boonmag2, Parichart Boontem1, Piyarat Govitrapong1,*

    BIOCELL, Vol.50, No.1, 2026, DOI:10.32604/biocell.2025.072557 - 23 January 2026

    Abstract Ischemic stroke is one of the major causes of long-term disability and mortality worldwide. It results from an interruption in the cerebral blood flow, triggering a cascade of detrimental events like oxidative stress, mitochondrial dysfunction, neuroinflammation, excitotoxicity, and apoptosis, causing neuronal injury and cellular death. Melatonin, a pleiotropic indoleamine produced by the pineal gland, has multifaceted neuroprotective effects on stroke pathophysiology. Interestingly, the serum melatonin levels are associated with peroxidation and antioxidant status, along with mortality score in patients with severe middle cerebral artery infarction. Melatonin exhibits strong antioxidant, anti-inflammatory, and anti-apoptotic properties and preserves More >

  • Open Access

    ARTICLE

    Research on UAV–MEC Cooperative Scheduling Algorithms Based on Multi-Agent Deep Reinforcement Learning

    Yonghua Huo1,2, Ying Liu1,*, Anni Jiang3, Yang Yang3

    CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072681 - 12 January 2026

    Abstract With the advent of sixth-generation mobile communications (6G), space–air–ground integrated networks have become mainstream. This paper focuses on collaborative scheduling for mobile edge computing (MEC) under a three-tier heterogeneous architecture composed of mobile devices, unmanned aerial vehicles (UAVs), and macro base stations (BSs). This scenario typically faces fast channel fading, dynamic computational loads, and energy constraints, whereas classical queuing-theoretic or convex-optimization approaches struggle to yield robust solutions in highly dynamic settings. To address this issue, we formulate a multi-agent Markov decision process (MDP) for an air–ground-fused MEC system, unify link selection, bandwidth/power allocation, and task… More >

  • Open Access

    ARTICLE

    MultiAgent-CoT: A Multi-Agent Chain-of-Thought Reasoning Model for Robust Multimodal Dialogue Understanding

    Ans D. Alghamdi*

    CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-35, 2026, DOI:10.32604/cmc.2025.071210 - 09 December 2025

    Abstract Multimodal dialogue systems often fail to maintain coherent reasoning over extended conversations and suffer from hallucination due to limited context modeling capabilities. Current approaches struggle with cross-modal alignment, temporal consistency, and robust handling of noisy or incomplete inputs across multiple modalities. We propose MultiAgent-Chain of Thought (CoT), a novel multi-agent chain-of-thought reasoning framework where specialized agents for text, vision, and speech modalities collaboratively construct shared reasoning traces through inter-agent message passing and consensus voting mechanisms. Our architecture incorporates self-reflection modules, conflict resolution protocols, and dynamic rationale alignment to enhance consistency, factual accuracy, and user engagement. More >

  • Open Access

    ARTICLE

    Research on Vehicle Joint Radar Communication Resource Optimization Method Based on GNN-DRL

    Zeyu Chen1, Jian Sun2,*, Zhengda Huan1, Ziyi Zhang1

    CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-17, 2026, DOI:10.32604/cmc.2025.071182 - 09 December 2025

    Abstract To address the issues of poor adaptability in resource allocation and low multi-agent cooperation efficiency in Joint Radar and Communication (JRC) systems under dynamic environments, an intelligent optimization framework integrating Deep Reinforcement Learning (DRL) and Graph Neural Network (GNN) is proposed. This framework models resource allocation as a Partially Observable Markov Game (POMG), designs a weighted reward function to balance radar and communication efficiencies, adopts the Multi-Agent Proximal Policy Optimization (MAPPO) framework, and integrates Graph Convolutional Networks (GCN) and Graph Sample and Aggregate (GraphSAGE) to optimize information interaction. Simulations show that, compared with traditional methods More >

  • Open Access

    REVIEW

    AI Agents in Finance and Fintech: A Scientific Review of Agent-Based Systems, Applications, and Future Horizons

    Maryan Rizinski1,2,*, Dimitar Trajanov1,2

    CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-34, 2026, DOI:10.32604/cmc.2025.069678 - 10 November 2025

    Abstract Artificial intelligence (AI) is reshaping financial systems and services, as intelligent AI agents increasingly form the foundation of autonomous, goal-driven systems capable of reasoning, learning, and action. This review synthesizes recent research and developments in the application of AI agents across core financial domains. Specifically, it covers the deployment of agent-based AI in algorithmic trading, fraud detection, credit risk assessment, robo-advisory, and regulatory compliance (RegTech). The review focuses on advanced agent-based methodologies, including reinforcement learning, multi-agent systems, and autonomous decision-making frameworks, particularly those leveraging large language models (LLMs), contrasting these with traditional AI or purely… More >

  • Open Access

    ARTICLE

    DAUNet: Unsupervised Neural Network Based on Dual Attention for Clock Synchronization in Multi-Agent Wireless Ad Hoc Networks

    Haihao He1,2, Xianzhou Dong1,*, Shuangshuang Wang1, Chengzhang Zhu1, Xiaotong Zhao1,2

    CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-23, 2026, DOI:10.32604/cmc.2025.069513 - 10 November 2025

    Abstract Clock synchronization has important applications in multi-agent collaboration (such as drone light shows, intelligent transportation systems, and game AI), group decision-making, and emergency rescue operations. Synchronization method based on pulse-coupled oscillators (PCOs) provides an effective solution for clock synchronization in wireless networks. However, the existing clock synchronization algorithms in multi-agent ad hoc networks are difficult to meet the requirements of high precision and high stability of synchronization clock in group cooperation. Hence, this paper constructs a network model, named DAUNet (unsupervised neural network based on dual attention), to enhance clock synchronization accuracy in multi-agent wireless ad hocMore >

  • Open Access

    ARTICLE

    Lightweight Multi-Agent Edge Framework for Cybersecurity and Resource Optimization in Mobile Sensor Networks

    Fatima Al-Quayed*

    CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-16, 2026, DOI:10.32604/cmc.2025.069102 - 10 November 2025

    Abstract Due to the growth of smart cities, many real-time systems have been developed to support smart cities using Internet of Things (IoT) and emerging technologies. They are formulated to collect the data for environment monitoring and automate the communication process. In recent decades, researchers have made many efforts to propose autonomous systems for manipulating network data and providing on-time responses in critical operations. However, the widespread use of IoT devices in resource-constrained applications and mobile sensor networks introduces significant research challenges for cybersecurity. These systems are vulnerable to a variety of cyberattacks, including unauthorized access,… More >

  • Open Access

    ARTICLE

    Chemical Composition and Antifungal Efficacy of Mentha rotundifolia Essential Oil against Fusarium oxysporum f. sp. albedinis in Date Palm: Valorisation of Plant Biomass for Natural Antifungal Agents

    Hafida Khelafi1, Wassima Lakhdari2, Mustapha Mounir Bouhenna3, Said Boudeffeur4, Hayet Meamiche1, Salah Neghmouche Nacer5,*, Meriam Laouar6

    Phyton-International Journal of Experimental Botany, Vol.94, No.12, pp. 3975-3989, 2025, DOI:10.32604/phyton.2025.073210 - 29 December 2025

    Abstract Essential oils (EOs) derived from medicinal plants are gaining recognition as sustainable alternatives to synthetic fungicides in the management of plant pathogens. This study investigates the chemical composition, chromatographic profile, and antifungal of Mentha rotundifolia essential oil against Fusarium oxysporum f. sp. albedinis (Foa), the pathogen responsible for Bayoud disease in date palm. The oil was extracted through hydrodistillation and characterized using thin-layer chromatography (TLC) and gas chromatography–mass spectrometry (GC-MS), revealing multiple fractions corresponding to terpenoid constituents and 23 chemical constituents, predominantly oxygenated monoterpenes (68.51%), with piperitenone oxide as the major component (62.53%). The antifungal efficacy was evaluated… More >

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