Oswaldo González-Gaxiola¹, Yakup Yildirim^2,3,4, Luminita Moraru^5,6, Anjan Biswas^7,8,9,10,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.9, pp. 2273-2287, 2025, DOI:10.32604/fdmp.2025.067959 - 30 September 2025

Abstract This study presents a numerical investigation of shallow water wave dynamics with particular emphasis on the role of surface tension. In the absence of surface tension, shallow water waves are primarily driven by gravity and are well described by the classical Boussinesq equation, which incorporates fourth-order dispersion. Under this framework, solitary and shock waves arise through the balance of nonlinearity and gravity-induced dispersion, producing waveforms whose propagation speed, amplitude, and width depend largely on depth and initial disturbance. The resulting dynamics are comparatively smoother, with solitary waves maintaining coherent structures and shock waves displaying gradual… More > Graphic Abstract

Mian Muhammad Kamal^1,*, Syed Zain Ul Abideen², M. A. Al-Khasawneh^3,4, Alaa M. Momani⁴, Hala Mostafa⁵, Mohammed Salem Atoum⁶, Saeed Ullah⁷, Jamil Abedalrahim Jamil Alsayaydeh^8,*, Mohd Faizal Bin Yusof⁹, Suhaila Binti Mohd Najib⁸

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3053-3083, 2025, DOI:10.32604/cmes.2025.067430 - 30 September 2025

Abstract Accurate detection of small objects is critically important in high-stakes applications such as military reconnaissance and emergency rescue. However, low resolution, occlusion, and background interference make small object detection a complex and demanding task. One effective approach to overcome these issues is the integration of multimodal image data to enhance detection capabilities. This paper proposes a novel small object detection method that utilizes three types of multimodal image combinations, such as Hyperspectral–Multispectral (HS-MS), Hyperspectral–Synthetic Aperture Radar (HS-SAR), and HS-SAR–Digital Surface Model (HS-SAR-DSM). The detection process is done by the proposed Jaccard Deep Q-Net (JDQN), which More >

Luyao Jiang^1,#, Longsheng Fu^2,#, Shaofeng Xiong^2,3, Guosheng Cao⁴, Yanqin Mei^2,3, Yaoqi Wu², Jin Chen^1,*, Yanni LV^2,5,6,*

BIOCELL, Vol.49, No.9, pp. 1749-1769, 2025, DOI:10.32604/biocell.2025.068507 - 25 September 2025

Abstract Background: After ischemic stroke, neutrophils hyperactivate, increasing in number and worsening inflammation, causing neural damage. Prior scRNA-seq showed Lrg1 modulates cells subsentence to cerebral ischemia-reperfusion injury, but its mechanism in regulating neutrophil accumulation/differentiation post-injury is unclear. Methods: Lrg1 knockout impact on neutrophil accumulation was assessed via immunofluorescence and western blot. Three-dimensional reconstruction of immunofluorescent staining analyzed cell-cell interactions among neutrophils and microglia. scRNA-seq of WT and Lrg1^-/- mice from GSE245386 and GSE279462 was conducted. Each group conducted oxidative phosphorylation scoring via Gene Set Enrichment Analysis (GSEA), while Metascape was employed to perform GO and KEGG enrichment… More > Graphic Abstract

Fatima Abu Siryeh^*, Hussein Alrammahi, Abdullahi Abdu İbrahim

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5021-5046, 2025, DOI:10.32604/cmc.2025.065206 - 30 July 2025

Abstract Biometric template protection is essential for finger-based authentication systems, as template tampering and adversarial attacks threaten the security. This paper proposes a DCT-based fragile watermarking scheme incorporating AI-based tamper detection to improve the integrity and robustness of finger authentication. The system was tested against NIST SD4 and Anguli fingerprint datasets, wherein 10,000 watermarked fingerprints were employed for training. The designed approach recorded a tamper detection rate of 98.3%, performing 3–6% better than current DCT, SVD, and DWT-based watermarking approaches. The false positive rate (≤1.2%) and false negative rate (≤1.5%) were much lower compared to previous… More >

Kassymbek Ozhikenov¹, Zhadyra Alimbayeva^1,*, Chingiz Alimbayev^1,2,*, Aiman Ozhikenova¹, Yeldos Altay¹

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5257-5284, 2025, DOI:10.32604/cmc.2025.061508 - 06 March 2025

Abstract Myocardial infarction (MI) is one of the leading causes of death globally among cardiovascular diseases, necessitating modern and accurate diagnostics for cardiac patient conditions. Among the available functional diagnostic methods, electrocardiography (ECG) is particularly well-known for its ability to detect MI. However, confirming its accuracy—particularly in identifying the localization of myocardial damage—often presents challenges in practice. This study, therefore, proposes a new approach based on machine learning models for the analysis of 12-lead ECG data to accurately identify the localization of MI. In particular, the learning vector quantization (LVQ) algorithm was applied, considering the contribution… More >

Jiacheng Luo, Jiahao Wen, Jian Yang^*

Computer Systems Science and Engineering, Vol.49, pp. 301-316, 2025, DOI:10.32604/csse.2025.060757 - 27 February 2025

Abstract Mitigating tag collisions is paramount for enhancing throughput in Radio Frequency Identification (RFID) systems. However, traditional algorithms encounter challenges like slot wastage and inefficient frame length adjustments. To tackle these challenges, the Slot Prediction Q (SPQ) algorithm was introduced, integrating the Vogt-II prediction algorithm and slot grouping to improve the initial Q value by predicting the first frame. This method quickly estimates the number of tags based on slot utilization, accelerating Q value adjustments when slot utilization is low. Furthermore, a Markov decision chain is used to optimize the relationship between the number of slot groupings (x) More >

Yameng Yin¹, Lieping Zhang^2,*, Xiaoxu Shi¹, Yilin Wang³, Jiansheng Peng⁴, Jianchu Zou⁴

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2769-2790, 2024, DOI:10.32604/cmc.2024.056791 - 18 November 2024

Abstract By integrating deep neural networks with reinforcement learning, the Double Deep Q Network (DDQN) algorithm overcomes the limitations of Q-learning in handling continuous spaces and is widely applied in the path planning of mobile robots. However, the traditional DDQN algorithm suffers from sparse rewards and inefficient utilization of high-quality data. Targeting those problems, an improved DDQN algorithm based on average Q-value estimation and reward redistribution was proposed. First, to enhance the precision of the target Q-value, the average of multiple previously learned Q-values from the target Q network is used to replace the single Q-value… More >

S. M. Hosseinalipour^*, S. Asiaei^*, Ammar A. Hussain Al-Taee

Frontiers in Heat and Mass Transfer, Vol.22, No.3, pp. 747-767, 2024, DOI:10.32604/fhmt.2024.051541 - 11 July 2024

Abstract This paper is part of a series addressing the urgent need for effective technologies to reduce energy demand and mitigate climate impact. This study focused on the implementation and development of dynamic insulation technology for a sustainable and energy-efficient future in the region, especially in Iraq. The study assessed the energy efficiency of dynamic insulation technology by analyzing three wall models (static, dynamic, and modified) during the winter season. This paper expands the analysis to include a hot, dry summer scenario, providing valuable insights into the year-round performance of dynamic walls and enabling sustainable and More >

YUNBAO GUO^1,#, XU LIU^1,#, QI XU², XIAOTONG ZHOU³, JIAWEI LIU³, YANYAN XU², YAN LU^2,*, HAIYAN LIU^2,*

BIOCELL, Vol.48, No.6, pp. 945-958, 2024, DOI:10.32604/biocell.2024.049748 - 10 June 2024

Abstract Background: Glioma is a kind of tumor that easily deteriorates and originates from glial cells in nerve tissue. Honokiol is a bisphenol compound that is an essential monomeric compound extracted from the roots and bark of Magnoliaceae plants. It also has anti-infection, antitumor, and immunomodulatory effects. In this study, we found that honokiol induces cell apoptosis in the human glioma cell lines U87-MG and U251-MG. However, the mechanism through which honokiol regulates glioma cell apoptosis is still unknown. Methods: We performed RNA-seq analysis of U251-MG cells treated with honokiol and control cells. Protein-protein interaction (PPI)… More > Graphic Abstract

Sepehr Soltani¹, Ehsan Ghafourian², Reza Salehi³, Diego Martín^3,*, Milad Vahidi⁴

Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 93-108, 2024, DOI:10.32604/iasc.2024.042693 - 29 March 2024

Abstract For many years, researchers have explored power allocation (PA) algorithms driven by models in wireless networks where multiple-user communications with interference are present. Nowadays, data-driven machine learning methods have become quite popular in analyzing wireless communication systems, which among them deep reinforcement learning (DRL) has a significant role in solving optimization issues under certain constraints. To this purpose, in this paper, we investigate the PA problem in a -user multiple access channels (MAC), where transmitters (e.g., mobile users) aim to send an independent message to a common receiver (e.g., base station) through wireless channels. To… More >