Dapeng Zou^1,2, Jun Wang^1,*

Journal of Polymer Materials, Vol.43, No.2, 2026, DOI:10.32604/jpm.2026.081141 - 30 June 2026

Abstract Reducing the oil-to-water ratio (OWR) of oil-based drilling fluids (OBDFs) to ultra-low levels (e.g., 55:45) exacerbates barite sag—a failure mode driven by barite’s inherent hydrophilicity and the weakened suspending capacity of the oil phase. Conventional low-molecular-weight wetting agents fail under these demanding conditions due to weak adsorption and thermal instability. In direct response to the solid-phase control challenge described above, we designed and synthesized a new hyperbranched polymeric wetting agent (HP-Wet) via a deliberate molecular topology strategy. The HP-Wet architecture incorporates phosphonate groups for robust anchoring onto barite surfaces and long alkyl chains to confer… More >

Tamer Y. A. Fahmy¹, Samir Kamel¹, Ahmed M. Khalil^2,*

Journal of Renewable Materials, Vol.14, No.6, 2026, DOI:10.32604/jrm.2025.02025-0180 - 29 June 2026

Abstract The growing threat of viral pandemics necessitates innovative antiviral strategies that are effective, sustainable, and scalable. This review highlights nanocellulose as a renewable, biocompatible nanomaterial and a promising multifunctional antiviral platform. We examine cellulose nanocrystals, nanofibrils, and bacterial nanocellulose, emphasizing their synergistic antiviral mechanisms, including nanoscale viral entrapment and surface-mediated inactivation via sulfation, cationic groups, and metal nanoparticles. Key advances include photothermally active nanocellulose-graphene composites for on-demand viral deactivation, sulfated nanocellulose mimicking heparin’s virus-trapping properties, and engineered biopolymer hybrids for targeted drug delivery and mucosal immunity. Translational applications span antiviral coatings, self-sterilizing filters, and regenerative More > Graphic Abstract

Kanyang Jiang¹, Yingkai Kang², Ming Li^2,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.083294 - 15 June 2026

Abstract The Internet of Vehicular Agents (IoVA) interconnects distributed AI agents across vehicular networks to deliver real-time intelligent services for vehicular users. Due to the limited computing capacity of vehicles, AI agents are deployed on nearby RoadSide Units (RSUs) to perform computation-intensive inference. As vehicles traverse RSU coverage boundaries, AI agents must migrate to target RSUs to maintain service continuity. However, the communication and computing resources at each RSU are shared among multiple co-served vehicles, creating coupled allocation decisions that jointly determine system latency and energy consumption. To address this challenge, we propose a low-latency and… More >

Pan Li^1,2, Zhi Li³, Yingyou Wen^2,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.083087 - 15 June 2026

Abstract The rapid advancement of edge intelligence in Industrial Internet of Things (IIoT) is transforming human–computer interaction from conventional “command execution” to complex “human–AI deep collaboration”. Within such safety-critical industrial environments, establishing robust mutual understanding and trust mechanisms becomes a significant prerequisite for decision reliability and efficiency. However, existing industrial interaction systems predominantly focus on task progression and explicit command responses, lacking fine-grained, dynamic tracking of operators’ trust states, cognitive evolution, and behavioral dynamics. Moreover, current LLM-based user simulation in evaluation often exhibit an “over-cooperation” bias, failing to capture the cognitive conflicts and trust crises characteristic… More >

Leonidas Theodorakopoulos, Alexandra Theodoropoulou^*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.082270 - 15 June 2026

Abstract Auditable autonomy is becoming a practical requirement for deploying large language model (LLM) agents in operational workflows where recommendations can trigger consequential actions. Many autonomy claims remain hard to evaluate because studies emphasize task completion or fluent explanations while underreporting tool privileges, verification conditions, rollback feasibility, and trace completeness. This review develops a decision-making–centered framework that treats autonomy as an auditable engineering property. It introduces a three-plane big data foundation: an evidence plane with provenance and freshness constraints; a decision-trace plane that records retrieval identifiers, tool invocations, intermediate checks, and policy evaluations; and an outcomes More >

Yejin Kwon¹, Jeongcheol Lee¹, Youngbom Park^2,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.080249 - 15 June 2026

Abstract The web-based High-Performance Computing (HPC) platform provides a simulation environment that enables users to perform computational science and engineering tasks through web services, thereby eliminating the need for complex terminal-based environments. Notwithstanding the aforementioned advantages, extant platforms frequently necessitate a considerable degree of user expertise, whilst the intricacy of simulation configuration and execution engenders limitations in terms of accessibility and usability. Furthermore, while Retrieval-Augmented Generation (RAG)-based systems are effective for information retrieval, they are insufficient for accurately constructing and invoking executable service tools. In order to address these limitations, this study proposes a user agent… More >

AKM Bahalul Haque^1,*, Al Amin Islam Ridoy², Mohammad Rayhan³, Ivan Porres¹

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.079525 - 15 June 2026

Abstract Agentic AI is gaining new insights and advancements in the field of Artificial Intelligence, fostering significant potential to enable rapid transformation across various domains. This rapid advancement and the potential to revolutionize various domains advocate the need for a deeper understanding and firm grasp of the technology. Moreover, an investigation into state-of-the-art research directions in agentic AI needs to be conducted to comprehensively assess the potential scope for improvement and application. Therefore, to address these objectives, a comprehensive review can provide researchers and practitioners with valuable insights into the current state and future research scopes… More >

Karlo Borovčak¹, Marina Bagić Babac^1,*, Vedran Mornar²

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.078330 - 15 June 2026

Abstract This study examines the potential of open-source foundation models for structured data analytics, with particular emphasis on SQL generation and business-oriented interpretation in single-agent and multi-agent large language model (LLM) systems. The proposed framework addresses a practical problem in analytics-intensive environments, where natural-language requests must be translated into executable, semantically appropriate SQL queries and subsequently interpreted in a form useful for business decision-making. The system is evaluated in two complementary settings: a custom SQL test suite designed around realistic marketing and e-commerce analytics tasks, and the public Spider benchmark, which supports comparison with prior text-to-SQL… More >

I. Nur Azreena^*, H. A. Aisyah, A. W. Noorshamsiana

Journal of Renewable Materials, Vol.14, No.5, 2026, DOI:10.32604/jrm.2025.02025-0178 - 28 May 2026

Abstract This study examined the impact of various pre-treatment techniques on the physical and mechanical characteristics of particleboards derived from oil palm trunks (OPT). Thermal and chemical pre-treatments of the fibers, including hot water, sodium hydroxide (NaOH), and acetic acid, were applied prior to board production. In addition, antifungal agents were incorporated as supplementary additives during the manufacturing process at varying percentages to evaluate their effect on panel performance. Morphology of the treated OPT fibers was examined, and panel properties such as thermal behavior, bending strength, bonding strength, and dimensional stability were evaluated. Statistically significant improvements (p… More >

Yenjou Wang¹, Chihtan Cheng², Jia-Wei Chang^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.080888 - 27 May 2026

Abstract As large language models (LLMs) become increasingly integrated into enterprise decision-making processes, structural pressures such as version drift, cross-source evidence integration, and regulatory accountability have shifted the primary challenge from isolated generative performance to system-level consistency, traceability, and governability. This paper systematically reviews key technological developments relevant to enterprise requirements, including document perception, retrieval-augmented generation (RAG), hybrid RAG-KG architectures, fine-grained attribution evaluation, and multi-agent coordination. The analysis demonstrates that the main obstacle to enterprise LLM adoption is not model capability, but rather the structural gap between fragmented technical modules and the need for high-reliability decision-making. More >