Taimoor Hassan¹, Ibrar Hussain^1,*, Hafiz Mahfooz Ul Haque², Hamid Turab Mirza³, Muhammad Nadeem Ali⁴, Byung-Seo Kim^4,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 2071-2094, 2025, DOI:10.32604/cmc.2025.068533 - 29 August 2025

Abstract Smart learning environments have been considered as vital sources and essential needs in modern digital education systems. With the rapid proliferation of smart and assistive technologies, smart learning processes have become quite convenient, comfortable, and financially affordable. This shift has led to the emergence of pervasive computing environments, where user’s intelligent behavior is supported by smart gadgets; however, it is becoming more challenging due to inconsistent behavior of Artificial intelligence (AI) assistive technologies in terms of networking issues, slow user responses to technologies and limited computational resources. This paper presents a context-aware predictive reasoning based… More >

Lei Lei¹, Chengfu Wu^2,*, Huaimin Chen²

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1339-1363, 2025, DOI:10.32604/cmc.2025.067117 - 29 August 2025

Abstract This paper proposes a Multi-Agent Attention Proximal Policy Optimization (MA2PPO) algorithm aiming at the problems such as credit assignment, low collaboration efficiency and weak strategy generalization ability existing in the cooperative pursuit tasks of multiple unmanned aerial vehicles (UAVs). Traditional algorithms often fail to effectively identify critical cooperative relationships in such tasks, leading to low capture efficiency and a significant decline in performance when the scale expands. To tackle these issues, based on the proximal policy optimization (PPO) algorithm, MA2PPO adopts the centralized training with decentralized execution (CTDE) framework and introduces a dynamic decoupling mechanism,… More >

Qamar H. Naith^1,*, H. Mancy^2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 387-405, 2025, DOI:10.32604/cmes.2025.066917 - 31 July 2025

Abstract Effective water distribution and transparency are threatened with being outrightly undermined unless the good name of urban infrastructure is maintained. With improved control systems in place to check leakage, variability of pressure, and conscientiousness of energy, issues that previously went unnoticed are now becoming recognized. This paper presents a grandiose hybrid framework that combines Multi-Agent Deep Reinforcement Learning (MADRL) with Shapley Additive Explanations (SHAP)-based Explainable AI (XAI) for adaptive and interpretable water resource management. In the methodology, the agents perform decentralized learning of the control policies for the pumps and valves based on the real-time… More >

Bismillah Mubeen^1,2,#, Ammarah Hasnain^2,3,#,*, Syed Atif Hasan Naqvi⁴, Fahad Hakim⁵, Syed Sheharyar Hassan Naqvi⁶, Muhammad Zeeshan Hassan⁴, Muhammad Umer Iqbal⁷, Mahmoud Moustafa⁸, Mohammed O. Alshaharni⁸, Mingzheng Duan^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.7, pp. 1941-1971, 2025, DOI:10.32604/phyton.2025.064056 - 31 July 2025

Abstract Plants have long served as a cornerstone for drug discovery, offering a vast repertoire of bioactive compounds with proven efficacy in combating oxidative stress, a pivotal driver of chronic diseases such as cancer, diabetes, cardiovascular disorders, and neurodegenerative conditions. This review synthesizes current knowledge on plant-derived antioxidants, emphasizing their mechanisms, therapeutic potential, and quantitative efficacy validated through standardized assays. Key phytochemicals, including polyphenols, carotenoids, flavonoids, and terpenoids, neutralize reactive oxygen species (ROS) through radical scavenging, enzyme modulation, and gene regulation. For instance, lutein, a carotenoid found in leafy greens, demonstrates potent antioxidant activity with IC₅₀ values… More >

Evren Daglarli^*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4511-4537, 2025, DOI:10.32604/cmc.2025.065572 - 30 July 2025

Abstract This study aims to develop a quantum computing-based neurocognitive architecture that allows an agent to perform autonomous behaviors. Therefore, we present a brain-inspired cognitive architecture for autonomous agents that integrates a prefrontal cortex–inspired model with modern deep learning (a transformer-based reinforcement learning module) and quantum algorithms. In particular, our framework incorporates quantum computational routines (Deutsch–Jozsa, Bernstein–Vazirani, and Grover’s search) to enhance decision-making efficiency. As a novelty of this research, this comprehensive computational structure is empowered by quantum computing operations so that superiority in speed and robustness of learning compared to classical methods can be demonstrated.… More >

Yan-Jyun Lin^1,#, I-Ta Lee^2,#, Wen-Bin Wu^3,4, Chien-Chung Yang^5,6, Chiang-Wen Lee^7,8,9, Fuu-Jen Tsai^10,11,12, Hui-Ching Tseng¹³, Wei-Ning Lin⁴, Li-Der Hsiao⁴, Chuen-Mao Yang^4,*

BIOCELL, Vol.49, No.7, pp. 1265-1290, 2025, DOI:10.32604/biocell.2025.066223 - 25 July 2025

Abstract Background: Silica nanoparticles (SiNPs), commonly utilized in industrial and biomedical fields, are known to provoke pulmonary inflammation by elevating cyclooxygenase-2 (COX-2) levels in human pulmonary alveolar epithelial cells (HPAEpiCs). Salvianolic acid A (SAA), a water-soluble polyphenol extracted from Salvia miltiorrhiza (Danshen), possesses well-documented antioxidant and anti-inflammatory activities. Nevertheless, its potential to counteract SiNP-induced inflammatory responses in the lung has not been thoroughly explored. Objective: This study aimed to evaluate the protective role and mechanistic actions of SAA against SiNP-triggered inflammation in both cellular and animal models. Methods: HPAEpiCs were pre-incubated with SAA prior to SiNP exposure to… More >

BHAVYADHARSHINI ARUN^1,#, PRARTHANA GOPINATH^1,2,#, ANUP JHA^1,3, NISHTHA TRIPATHI¹, SYED G DASTAGER^4,*, SYED K HASAN^1,3,*

Oncology Research, Vol.33, No.8, pp. 2161-2174, 2025, DOI:10.32604/or.2025.062951 - 18 July 2025

Abstract Background: Acute Myeloid Leukemia (AML) is a highly aggressive clonal hematological malignancy with limited treatment options. This study aimed to evaluate the therapeutic potential of nigericin, a polyether ionophore derived from Streptomyces DASNCL-29, as a mitochondrial-targeted agent for AML treatment. Methods: Nigericin was isolated from Streptomyces DASNCL-29 and characterized via chromatography and NMR. Its cytotoxicity was tested in MOLM13 (sensitive and venetoclax-resistant) and HL60 (sensitive and cytarabine-resistant) cells using the MTT assay. Mitochondrial dysfunction was assessed by measuring reactive oxygen species (ROS), mitochondrial membrane potential (Δψm), and mitochondrial mass. Apoptosis was evaluated with Annexin V/PI assays… More > Graphic Abstract

Xuan Huo¹, Bingchen Wu¹, Yuanmeng Lou¹, Junlin Zhu¹, Cui Li¹, Lili Ma¹, Ye-Tang Pan², Chuncheng Hao^1,*, Xin Wen^1,*

Journal of Polymer Materials, Vol.42, No.2, pp. 517-530, 2025, DOI:10.32604/jpm.2025.065320 - 14 July 2025

Abstract Power cables are important pieces of equipment for energy transmission, but achieving a good balance between flame retardancy and mechanical properties of cable sheaths remains a challenge. In this work, a novel intumescent flame retardant (IFR) system containing silicone-containing macromolecular charring agent (Si-MCA) and ammonium polyphosphate (APP) was designed to synergistically improve the flame retardancy and mechanical properties of ethylene-butyl acrylate copolymer (EBA) composites. The optimal mass ratio of APP/Si-MCA was 3/1 in EBA composites (EBA/APP-Si-31), corresponding to the best flame retardancy with 31.2% of limited oxygen index (LOI), V-0 rating in UL-94 vertical burning More > Graphic Abstract

Rongbo Sun, Jinlong Fei^*, Yuefei Zhu, Zhongyu Guo

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3765-3786, 2025, DOI:10.32604/cmc.2025.064849 - 03 July 2025

Abstract Moving Target Defense (MTD) necessitates scientifically effective decision-making methodologies for defensive technology implementation. While most MTD decision studies focus on accurately identifying optimal strategies, the issue of optimal defense timing remains underexplored. Current default approaches—periodic or overly frequent MTD triggers—lead to suboptimal trade-offs among system security, performance, and cost. The timing of MTD strategy activation critically impacts both defensive efficacy and operational overhead, yet existing frameworks inadequately address this temporal dimension. To bridge this gap, this paper proposes a Stackelberg-FlipIt game model that formalizes asymmetric cyber conflicts as alternating control over attack surfaces, thereby capturing More >

Chao Li^1,3,#, Quanzhi Feng^1,3,#, Caichang Ding^2,*, Zhiwei Ye^1,3

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3605-3621, 2025, DOI:10.32604/cmc.2025.063703 - 03 July 2025

Abstract The increasing adoption of unmanned aerial vehicles (UAVs) in urban low-altitude logistics systems, particularly for time-sensitive applications like parcel delivery and supply distribution, necessitates sophisticated coordination mechanisms to optimize operational efficiency. However, the limited capability of UAVs to extract state-action information in complex environments poses significant challenges to achieving effective cooperation in dynamic and uncertain scenarios. To address this, we presents an Improved Multi-Agent Hybrid Attention Critic (IMAHAC) framework that advances multi-agent deep reinforcement learning (MADRL) through two key innovations. Firstly, a Temporal Difference Error and Time-based Prioritized Experience Replay (TT-PER) mechanism that dynamically adjusts… More >