Amine Batbat^1,2, Mohamed El Fadili³, Naoufal El Hachlafi^4,*, Amine Elbouzidi^5,*, Chaymae Hmimen⁶, Hiba Yahyaoui^2,7, Samir Jeddi⁶, Abdellatif Benbouazza², Kawtar Fikri-Benbrahim⁶, Mohamed Addi⁵, Samiah Hamad Al-Mijalli⁸, Khaoula Habbadi², Hassane Greche¹

Phyton-International Journal of Experimental Botany, Vol.94, No.2, pp. 481-501, 2025, DOI:10.32604/phyton.2025.059841 - 06 March 2025

Abstract This study highlights the regulatory potential antibacterial and antiradical of Origanum elongatum essential oil (EO), an endemic medicinal plant of Morocco used for its various properties. The chemical composition of the EO was characterized using gas chromatography-mass spectrometry (GC-MS). The antibacterial activity against different agricultural phytopathogens was determined by disc diffusion and microatmosphere methods, as well as by the determination of minimum inhibitory concentrations (MIC) and minimum bactericidal concentration (MBC), while the antioxidant activity was evaluated by DPPH and FRAP assays. To complement the experimental analyses, a molecular docking approach was used to predict and elucidate… More >

Ahmed Abbas Jasim Al-Hchaimi¹, Yousif Raad Muhsen^2,3,*, Wisam Hazim Gwad⁴, Entisar Soliman Alkayal⁵, Riyadh Rahef Nuiaa Al Ogaili⁶, Zaid Abdi Alkareem Alyasseri^7,8, Alhamzah Alnoor⁹

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2661-2689, 2025, DOI:10.32604/cmes.2025.061318 - 03 March 2025

Abstract The implementation of Countermeasure Techniques (CTs) in the context of Network-On-Chip (NoC) based Multiprocessor System-On-Chip (MPSoC) routers against the Flooding Denial-of-Service Attack (F-DoSA) falls under Multi-Criteria Decision-Making (MCDM) due to the three main concerns, called: traffic variations, multiple evaluation criteria-based traffic features, and prioritization NoC routers as an alternative. In this study, we propose a comprehensive evaluation of various NoC traffic features to identify the most efficient routers under the F-DoSA scenarios. Consequently, an MCDM approach is essential to address these emerging challenges. While the recent MCDM approach has some issues, such as uncertainty, this… More >

Yaoxuan Zhu, Hua Yang, Bin Zhu^*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 1947-1968, 2025, DOI:10.32604/cmc.2024.057866 - 17 February 2025

Abstract The emergence of adversarial examples has revealed the inadequacies in the robustness of image classification models based on Convolutional Neural Networks (CNNs). Particularly in recent years, the discovery of natural adversarial examples has posed significant challenges, as traditional defense methods against adversarial attacks have proven to be largely ineffective against these natural adversarial examples. This paper explores defenses against these natural adversarial examples from three perspectives: adversarial examples, model architecture, and dataset. First, it employs Class Activation Mapping (CAM) to visualize how models classify natural adversarial examples, identifying several typical attack patterns. Next, various common… More >

Jiewen Liu¹, Bing Chen^1,2,*, Baolu Xue¹, Mengya Guo¹, Yuntao Xu¹

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 1857-1877, 2025, DOI:10.32604/cmc.2024.057814 - 17 February 2025

Abstract Federated Graph Neural Networks (FedGNNs) have achieved significant success in representation learning for graph data, enabling collaborative training among multiple parties without sharing their raw graph data and solving the data isolation problem faced by centralized GNNs in data-sensitive scenarios. Despite the plethora of prior work on inference attacks against centralized GNNs, the vulnerability of FedGNNs to inference attacks has not yet been widely explored. It is still unclear whether the privacy leakage risks of centralized GNNs will also be introduced in FedGNNs. To bridge this gap, we present PIAFGNN, the first property inference attack… More >

Slim Chaoui^1,*, Omar Alruwaili¹, Faeiz Alserhani¹, Haifa Harrouch²

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1933-1954, 2025, DOI:10.32604/cmes.2025.059346 - 27 January 2025

Abstract In this paper, we propose a hybrid decode-and-forward and soft information relaying (HDFSIR) strategy to mitigate error propagation in coded cooperative communications. In the HDFSIR approach, the relay operates in decode-and-forward (DF) mode when it successfully decodes the received message; otherwise, it switches to soft information relaying (SIR) mode. The benefits of the DF and SIR forwarding strategies are combined to achieve better performance than deploying the DF or SIR strategy alone. Closed-form expressions for the outage probability and symbol error rate (SER) are derived for coded cooperative communication with HDFSIR and energy-harvesting relays. Additionally,… More >

KSENIA S. STAFEEVA¹, NATALIA A. SAMOYLOVA¹, OLGA A. KARANDEEVA¹, VERONIKA V. NESTEROVA¹, KIRILL A. STARODUBTSEV¹, EVGENY V. MIKHAILOV², ILYA O. KRUTOV², EVGENY S. POPOV³, NATALIA S. RODIONOVA⁴, ANASTASIA V. KOKINA^1,5, ARTEM P. GUREEV^1,5,*

BIOCELL, Vol.49, No.1, pp. 7-20, 2025, DOI:10.32604/biocell.2024.058339 - 24 January 2025

Abstract Objective: The objective of this study was to determine the level of methotrexate (MTX) toxicity in the intestines of mice and to evaluate the protective effect of probiotics composed of Streptococcus, Bifidobacterium, and Lactobacillus species on intestinal cells during MTX treatment. Methods: Mice were divided into three groups: control, MTX group (received MTX injections), and MTX + probiotics group (received MTX injections along with a diet containing probiotics). Morphological and histological changes, the level of mitochondrial DNA (mtDNA) damage, the level of lipid peroxidation products, and gene expression in the mice’s small intestine were assessed. Results: We… More > Graphic Abstract

Jing Guo^*, Ziying Wang, Yajuan Guo, Haitao Jiang

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 427-442, 2025, DOI:10.32604/cmc.2024.057045 - 03 January 2025

Abstract The rapid proliferation of electric vehicle (EV) charging infrastructure introduces critical cybersecurity vulnerabilities to power grids system. This study presents an innovative anomaly detection framework for EV charging stations, addressing the unique challenges posed by third-party aggregation platforms. Our approach integrates node equations-based on the parameter identification with a novel deep learning model, xDeepCIN, to detect abnormal data reporting indicative of aggregation attacks. We employ a graph-theoretic approach to model EV charging networks and utilize Markov Chain Monte Carlo techniques for accurate parameter estimation. The xDeepCIN model, incorporating a Compressed Interaction Network, has the ability… More >

HASSAN M. OTIFI^*

Oncology Research, Vol.33, No.1, pp. 235-243, 2025, DOI:10.32604/or.2024.055677 - 20 December 2024

Abstract Background: Gastric cancer (GC) remains a global health burden and is often characterized by heterogeneous molecular profiles and resistance to conventional therapies. The phosphoinositide 3-kinase and PI3K and Janus kinase (JAK) signal transducer and activator of transcription (JAK-STAT) pathways play pivotal roles in GC progression, making them attractive targets for therapeutic interventions. Methods: This study applied a computational and molecular dynamics simulation approach to identify and characterize SBL-JP-0004 as a potential dual inhibitor of JAK2 and PI3KCD kinases. KATOIII and SNU-5 GC cells were used for in vitro evaluation. Results: SBL-JP-0004 exhibited a robust binding affinity for… More >

AMOURA M. ABOU-EL-NAGA¹, SHAKER A. MOUSA², FAYEZ ALTHOBAITI³, EMAN FAYAD^3,*, ENGY S. FAHIM¹

BIOCELL, Vol.48, No.12, pp. 1835-1837, 2024, DOI:10.32604/biocell.2024.054569 - 30 December 2024

Abstract This article has no abstract. More >

Saad Awadh Alanazi^*

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4049-4080, 2024, DOI:10.32604/cmc.2024.057211 - 19 December 2024

Abstract Spear Phishing Attacks (SPAs) pose a significant threat to the healthcare sector, resulting in data breaches, financial losses, and compromised patient confidentiality. Traditional defenses, such as firewalls and antivirus software, often fail to counter these sophisticated attacks, which target human vulnerabilities. To strengthen defenses, healthcare organizations are increasingly adopting Machine Learning (ML) techniques. ML-based SPA defenses use advanced algorithms to analyze various features, including email content, sender behavior, and attachments, to detect potential threats. This capability enables proactive security measures that address risks in real-time. The interpretability of ML models fosters trust and allows security… More >