Isam Bahaa Aldallal¹, Abdullahi Abdu Ibrahim^1,*, Saadaldeen Rashid Ahmed^2,3

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.075212 - 10 February 2026

Abstract The rapid growth of IoT networks necessitates efficient Intrusion Detection Systems (IDS) capable of addressing dynamic security threats under constrained resource environments. This paper proposes a hybrid IDS for IoT networks, integrating Support Vector Machine (SVM) and Genetic Algorithm (GA) for feature selection and parameter optimization. The GA reduces the feature set from 41 to 7, achieving a 30% reduction in overhead while maintaining an attack detection rate of 98.79%. Evaluated on the NSL-KDD dataset, the system demonstrates an accuracy of 97.36%, a recall of 98.42%, and an F1-score of 96.67%, with a low false More >

Kirubavathi Ganapathiyappan¹, Chahana Ravikumar¹, Raghul Alagunachimuthu Ranganayaki¹, Ayman Altameem², Ateeq Ur Rehman^3,*, Ahmad Almogren^4,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.072840 - 10 February 2026

Abstract Android smartphones have become an integral part of our daily lives, becoming targets for ransomware attacks. Such attacks encrypt user information and ask for payment to recover it. Conventional detection mechanisms, such as signature-based and heuristic techniques, often fail to detect new and polymorphic ransomware samples. To address this challenge, we employed various ensemble classifiers, such as Random Forest, Gradient Boosting, Bagging, and AutoML models. We aimed to showcase how AutoML can automate processes such as model selection, feature engineering, and hyperparameter optimization, to minimize manual effort while ensuring or enhancing performance compared to traditional… More >

Kirti A. Yadav¹, Yachana Jha¹, Haiam O. Elkatry², Heba I. Mohamed^3,*, Ahmed Mahmoud Ismail⁴, Abdelrahman R. Ahmed^2,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.074570 - 30 January 2026

Abstract Phytophthora blight is a devastating disease of pigeon pea (Cajanus cajan) that severely impacts plant growth and productivity. This study investigates the morphological, anatomical, and biochemical responses of a susceptible variety (ICPL 11260) and a resistant variety (IPAC-02) following infection by Phytophthora. Morphological analyses showed that infection caused a drastic reduction in root length, shoot length, leaf number, fresh weight, and dry weight in the susceptible ICPL 11260 variety, with reductions ranging from 0.5- to 2-fold compared to non-infected controls. Anatomical observations revealed pronounced cellular damage and mycelial invasion in infected ICPL 11260 plants by 30… More >

Xiaoqing Jiang^1,2,#, Pengchong Li^1,2,#, Hongchuang Liu^1,2, Wenjie Dong^1,2, Wenjing Liu^1,2, Di Wu^1,2, Jianping Xue^1,2, Fenglan Zhao^1,2,*, Yongbo Duan^1,2,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.074434 - 30 January 2026

Abstract As its tuberous alkaloids induce valuable pharmacological effects, Pinellia ternata has considerable clinical value. However, its production currently fails to meet its demand. In vitro microtuber culture, combined with salicylic acid (SA) elicitation, may provide an effective alternative to traditional field production. In this study, an in vitro P. ternata microtuber induction system was developed and used to evaluate SA-induced elicitation of alkaloid accumulation. The quality of in vitro microtubers was assessed by total alkaloid measurement, a cytotoxicity assay, and transcriptomic analysis. With or without SA treatment, P. ternata microtuber induction was achieved within 60 d using petiole-derived explants, with… More >

Min Hee Kim¹, Boyoon Huh¹, Joo-Won Park^1,*, Woo-Jae Park^2,*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.071523 - 19 January 2026

Abstract Breast cancer is one of the most prevalent malignancies among women and comprises a heterogeneous spectrum of molecular subtypes with distinct biological behaviors. Among various regulatory molecules, sphingolipids play pivotal roles in dynamically modulating fundamental cellular processes such as proliferation, apoptosis, and metastasis through metabolic interconversions, including phosphorylation, glycosylation, and the generation of sphingosine-1-phosphate. This review aims to elucidate the mechanisms through which sphingolipid metabolism orchestrates cancer cell fate and drives breast cancer progression. Particular emphasis is placed on the balance between proapoptotic ceramides and pro-survival metabolites, such as sphingosine-1-phosphate, which collectively influence tumor growth More >

Samuel Acheme^*, Glory Nosawaru Edegbe

Journal of Cyber Security, Vol.8, pp. 1-31, 2026, DOI:10.32604/jcs.2026.073923 - 07 January 2026

Abstract Federated learning (FL) enables collaborative model training across decentralized datasets, thus maintaining the privacy of training data. However, FL remains vulnerable to malicious actors, posing significant risks in privacy-sensitive domains like healthcare. Previous machine learning trust frameworks, while promising, often rely on resource-intensive blockchain ledgers, introducing computational overhead and metadata leakage risks. To address these limitations, this study presents a novel Decentralized Identity (DID) framework for mutual authentication that establishes verifiable trust among participants in FL without dependence on centralized authorities or high-cost blockchain ledgers. The proposed system leverages Decentralized Identifiers (DIDs) and Verifiable Credentials… More >

Dongchi Cai^1,2,#, Jialin Ji^3,#, Chunhui Yang^1,*, Hong Cai^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.071152 - 30 December 2025

Abstract Metabolic reprogramming involving branched-chain amino acids (BCAAs)—leucine, isoleucine, and valine—is increasingly recognized as pivotal in cancer progression, metastasis, and immune modulation. This review comprehensively explores how cancer cells rewire BCAA metabolism to enhance proliferation, survival, and therapy resistance. Tumors manipulate BCAA uptake and catabolism via high expression of transporters like L-type amino acid transporter 1 (LAT1) and enzymes including branched chain amino acid transaminase 1(BCAT1), branched chain amino acid transaminase 2 (BCAT2), branched-chain alpha-keto acid dehydrogenase (BCKDH), and branched chain alpha-keto acid dehydrogenase kinase (BCKDK). These alterations sustain energy production, biosynthesis, redox homeostasis, and oncogenic… More >

Nikhil S. Mane¹, Sheetal Kumar Dewangan^2,*, Sayantan Mukherjee³, Pradnyavati Mane⁴, Deepak Kumar Singh¹, Ravindra Singh Saluja⁵

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-16, 2026, DOI:10.32604/cmc.2025.072090 - 10 November 2025

Abstract The thermal conductivity of nanofluids is an important property that influences the heat transfer capabilities of nanofluids. Researchers rely on experimental investigations to explore nanofluid properties, as it is a necessary step before their practical application. As these investigations are time and resource-consuming undertakings, an effective prediction model can significantly improve the efficiency of research operations. In this work, an Artificial Neural Network (ANN) model is developed to predict the thermal conductivity of metal oxide water-based nanofluid. For this, a comprehensive set of 691 data points was collected from the literature. This dataset is split More >

Misbah Anwer^1,*, Ghufran Ahmed¹, Maha Abdelhaq², Raed Alsaqour³, Shahid Hussain⁴, Adnan Akhunzada^5,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-15, 2026, DOI:10.32604/cmc.2025.068673 - 10 November 2025

Abstract The exponential growth of the Internet of Things (IoT) has introduced significant security challenges, with zero-day attacks emerging as one of the most critical and challenging threats. Traditional Machine Learning (ML) and Deep Learning (DL) techniques have demonstrated promising early detection capabilities. However, their effectiveness is limited when handling the vast volumes of IoT-generated data due to scalability constraints, high computational costs, and the costly time-intensive process of data labeling. To address these challenges, this study proposes a Federated Learning (FL) framework that leverages collaborative and hybrid supervised learning to enhance cyber threat detection in… More >

Hameed H. Ahmed¹, Thaer A. Mezher^2,*, Marwan R. Rashid³

Chalcogenide Letters, Vol.22, No.12, pp. 1055-1066, 2025, DOI:10.15251/CL.2025.2212.1055 - 10 December 2025

Abstract Laser ablation in liquids (LAL), a hygienic and effective method for creating high-purity nanomaterials, was used in this study to create cadmium sulfide (CdS) and silver oxide (Ag₂O) nanoparticles. The sputtering process was used to deposit the produced nanomaterials on porous silicon (PSi) substrates, and a number of assays were used to examine the samples’ structural, optical, and electrical characteristics. The CdS sample had a hexagonal crystal structure, according to X-ray diffraction (XRD) data, whereas the AgO sample had a cubic structure. The diameters of the nanoparticles in the two samples ranged from 22.64 nm for… More >