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  • Open Access

    ARTICLE

    Optimizing In Vitro Regeneration of Wheat via Somatic Embryogenesis Using Endosperm-Supported Mature Embryos

    Sumeyra Ucar1, Muhammed Aldaif 2, Esra Yaprak1, Esma Yigider 2, Murat Aydin2,*, Emre Ilhan1, Abdulkadir Ciltas2, Ertan Yildirim3

    Phyton-International Journal of Experimental Botany, Vol.94, No.8, pp. 2461-2477, 2025, DOI:10.32604/phyton.2025.068383 - 29 August 2025

    Abstract Wheat is a crucial crop for global food security, and effective in vitro plant regeneration techniques are considered a precondition for genetic engineering in wheat breeding programs. A practical approach for in vitro regeneration of the Kırik bread wheat cultivar via somatic embryogenesis was investigated using endosperm-supported mature embryos. Callus cultures were initiated from mature embryos supported by endosperm, cultured on phytagel-based Murashige and Skoog (MS) basal medium containing dicamba (12 mg/L) and indole-3-acetic acid (IAA) (0.5 mg/L) under dark conditions. This research was designed to examine the impact of putrescine (Put) (0.0 and 1.0 mM) on… More >

  • Open Access

    ARTICLE

    Renovated Random Attribute-Based Fennec Fox Optimized Deep Learning Framework in Low-Rate DoS Attack Detection in IoT

    Prasanalakshmi Balaji1,2, Sangita Babu3, Maode Ma4, Zhaoxi Fang2, Syarifah Bahiyah Rahayu5,6,*, Mariyam Aysha Bivi1, Mahaveerakannan Renganathan7

    CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5831-5858, 2025, DOI:10.32604/cmc.2025.065260 - 30 July 2025

    Abstract The rapid progression of the Internet of Things (IoT) technology enables its application across various sectors. However, IoT devices typically acquire inadequate computing power and user interfaces, making them susceptible to security threats. One significant risk to cloud networks is Distributed Denial-of-Service (DoS) attacks, where attackers aim to overcome a target system with excessive data and requests. Among these, low-rate DoS (LR-DoS) attacks present a particular challenge to detection. By sending bursts of attacks at irregular intervals, LR-DoS significantly degrades the targeted system’s Quality of Service (QoS). The low-rate nature of these attacks confuses their… More >

  • Open Access

    ARTICLE

    Eco-Friendly Particleboards Produced with Banana Tree (Musa paradisiaca) Pseudostem Fibers Bonded with Cassava Starch and Urea-Formaldehyde Adhesives

    Prosper Mensah1, Rafael Rodolfo de Melo2, Edgley Alves de Oliveira Paula2, Alexandre Santos Pimenta3, Juliana de Moura2, Fernando Rusch2,*

    Journal of Renewable Materials, Vol.13, No.7, pp. 1475-1489, 2025, DOI:10.32604/jrm.2025.02025-0047 - 22 July 2025

    Abstract The increase in wood and wood-based products in the construction and furniture sectors has grown exponentially, generating severe environmental and socioeconomic impacts. Particleboard panels have been the main cost-benefit option on the market due to their lightness and lower cost compared to solid wood. However, the synthetic adhesives used in producing traditional particleboard panels cause serious harm to human health. Developing particleboard panels with fibrous waste and natural adhesives could be a sustainable alternative for these sectors. The work aimed to create particleboards with fibrous wastes from the pseudostem of the banana tree (Musa paradisiaca) and… More > Graphic Abstract

    Eco-Friendly Particleboards Produced with Banana Tree (<i>Musa paradisiaca</i>) Pseudostem Fibers Bonded with Cassava Starch and Urea-Formaldehyde Adhesives

  • Open Access

    ARTICLE

    Preventing IP Spoofing in Kubernetes Using eBPF

    Absar Hussain1, Abdul Aziz1, Hassan Jamil Syed2,*, Shoaib Raza1

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3105-3124, 2025, DOI:10.32604/cmc.2025.062628 - 03 July 2025

    Abstract Kubernetes has become the dominant container orchestration platform, with widespread adoption across industries. However, its default pod-to-pod communication mechanism introduces security vulnerabilities, particularly IP spoofing attacks. Attackers can exploit this weakness to impersonate legitimate pods, enabling unauthorized access, lateral movement, and large-scale Distributed Denial of Service (DDoS) attacks. Existing security mechanisms such as network policies and intrusion detection systems introduce latency and performance overhead, making them less effective in dynamic Kubernetes environments. This research presents PodCA, an eBPF-based security framework designed to detect and prevent IP spoofing in real time while minimizing performance impact. PodCA… More >

  • Open Access

    REVIEW

    Lynch syndrome and colorectal cancer: A review of current perspectives in molecular genetics and clinical strategies

    RAQUEL GÓMEZ-MOLINA1,*, RAQUEL MARTÍNEZ2,3,4, MIGUEL SUÁREZ2,3,4,*, ANA PEÑA-CABIA1, MARíA CONCEPCIóN CALDERÓN1, JORGE MATEO3,4

    Oncology Research, Vol.33, No.7, pp. 1531-1545, 2025, DOI:10.32604/or.2025.063951 - 26 June 2025

    Abstract Lynch syndrome (LS), also known as hereditary non-polyposis colorectal cancer (HNPCC), is an inherited condition associated with a higher risk of colorectal cancer (CRC) and other cancers. It is caused by germline mutations in DNA mismatch repair (MMR) genes, including MLH1, MSH2, MSH6 and PMS2. These mutations lead to microsatellite instability (MSI) and defective DNA repair mechanisms, resulting in increased cancer risk. Early detection of LS is crucial for effective management and cancer prevention. Endoscopic surveillance, particularly regular colonoscopy, is recommended for individuals with LS to detect CRC at early stages. Additionally, universal screening of CRC for More > Graphic Abstract

    Lynch syndrome and colorectal cancer: A review of current perspectives in molecular genetics and clinical strategies

  • Open Access

    ARTICLE

    TIDS: Tensor Based Intrusion Detection System (IDS) and Its Application in Large Scale DDoS Attack Detection

    Hanqing Sun1, Xue Li2,*, Qiyuan Fan3, Puming Wang3

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1659-1679, 2025, DOI:10.32604/cmc.2025.061426 - 09 June 2025

    Abstract The era of big data brings new challenges for information network systems (INS), simultaneously offering unprecedented opportunities for advancing intelligent intrusion detection systems. In this work, we propose a data-driven intrusion detection system for Distributed Denial of Service (DDoS) attack detection. The system focuses on intrusion detection from a big data perceptive. As intelligent information processing methods, big data and artificial intelligence have been widely used in information systems. The INS system is an important information system in cyberspace. In advanced INS systems, the network architectures have become more complex. And the smart devices in… More >

  • Open Access

    ARTICLE

    A NAS-Based Risk Prediction Model and Interpretable System for Amyloidosis

    Chen Wang1,2, Tiezheng Guo1, Qingwen Yang1, Yanyi Liu1, Jiawei Tang1, Yingyou Wen1,2,*

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5561-5574, 2025, DOI:10.32604/cmc.2025.063676 - 19 May 2025

    Abstract Primary light chain amyloidosis is a rare hematologic disease with multi-organ involvement. Nearly one-third of patients with amyloidosis experience five or more consultations before diagnosis, which may lead to a poor prognosis due to delayed diagnosis. Early risk prediction based on artificial intelligence is valuable for clinical diagnosis and treatment of amyloidosis. For this disease, we propose an Evolutionary Neural Architecture Searching (ENAS) based risk prediction model, which achieves high-precision early risk prediction using physical examination data as a reference factor. To further enhance the value of clinic application, we designed a natural language-based interpretable… More >

  • Open Access

    ARTICLE

    Detecting and Mitigating Distributed Denial of Service Attacks in Software-Defined Networking

    Abdullah M. Alnajim1,*, Faisal Mohammed Alotaibi2,#, Sheroz Khan3,#

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4515-4535, 2025, DOI:10.32604/cmc.2025.063139 - 19 May 2025

    Abstract Distributed denial of service (DDoS) attacks are common network attacks that primarily target Internet of Things (IoT) devices. They are critical for emerging wireless services, especially for applications with limited latency. DDoS attacks pose significant risks to entrepreneurial businesses, preventing legitimate customers from accessing their websites. These attacks require intelligent analytics before processing service requests. Distributed denial of service (DDoS) attacks exploit vulnerabilities in IoT devices by launching multi-point distributed attacks. These attacks generate massive traffic that overwhelms the victim’s network, disrupting normal operations. The consequences of distributed denial of service (DDoS) attacks are typically… More >

  • Open Access

    ARTICLE

    Enhancing Salt Stress Tolerance in Portulaca oleracea L. Using Ascophyllum nodosum Biostimulant

    Zahra Alhawsa*, Rewaa Jalal, Nouf Asiri

    Phyton-International Journal of Experimental Botany, Vol.94, No.4, pp. 1319-1337, 2025, DOI:10.32604/phyton.2025.061918 - 30 April 2025

    Abstract Salinity stress is a major constraint on agricultural productivity, particularly in arid and semi-arid regions. This study evaluated the potential of Ascophyllum nodosum extract (ANE) in mitigating salinity-induced stress and enhancing the growth and physiological performance of Portulaca oleracea L. under NaCl concentrations of 0, 50, 70, and 100 mM for 50 days. A two-way ANOVA assessed the effects of NaCl concentration, ANE treatment, and their interaction. The results showed that ANE significantly increased plant height at 50 mM NaCl (p = 0.0011) but had no effect at higher salinity levels (p > 0.05). Shoot dry weight was… More >

  • Open Access

    ARTICLE

    Evaluation and Benchmarking of Cybersecurity DDoS Attacks Detection Models through the Integration of FWZIC and MABAC Methods

    Alaa Mahmood, İsa Avcı*

    Computer Systems Science and Engineering, Vol.49, pp. 401-417, 2025, DOI:10.32604/csse.2025.062413 - 25 April 2025

    Abstract A Distributed Denial-of-Service (DDoS) attack poses a significant challenge in the digital age, disrupting online services with operational and financial consequences. Detecting such attacks requires innovative and effective solutions. The primary challenge lies in selecting the best among several DDoS detection models. This study presents a framework that combines several DDoS detection models and Multiple-Criteria Decision-Making (MCDM) techniques to compare and select the most effective models. The framework integrates a decision matrix from training several models on the CiC-DDOS2019 dataset with Fuzzy Weighted Zero Inconsistency Criterion (FWZIC) and Multi-Attribute Boundary Approximation Area Comparison (MABAC) methodologies.… More >

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