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  • Open Access

    ARTICLE

    Various Organic Nutrient Sources in Combinations with Inorganic Fertilizers Influence the Yield and Quality of Sweet Corn (Zea mays L. saccharata) in New Alluvial Soils of West Bengal, India

    Anindita Das1, Kanu Murmu2, Biplab Mitra3, Pintoo Bandopadhyay2, Ritesh Kundu4, Moupiya Roy5, Saleh Alfarraj6, Mohammad Javed Ansari7, Marian Brestic8, Akbar Hossain9,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 763-776, 2024, DOI:10.32604/phyton.2024.049473

    Abstract Nutrient management plays a crucial role in the yield and quality of sweet corn. A field experiment was conducted in consecutive two kharif seasons in 2018 and 2019 to investigate the effect of various organic sources of nutrients in combination with inorganic sources on the yield and quality of sweet corn under new alluvial soils of West Bengal, India. Treatments were: T: Control (without fertilizers); T: 100% recommended dose (RDF) of chemical fertilizers (CF) (RDF CF); T: 100% recommended dose of N (RDN) through vermicompost (VC) (RDN VC); T: 50 RDN through CF + 50% RDN through VC (RDN CF… More >

  • Open Access

    ARTICLE

    Securing Forwarding Layers from Eavesdropping Attacks Using Proactive Approaches

    Jiajun Yan, Ying Zhou*, Anchen Dai, Tao Wang

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 563-580, 2024, DOI:10.32604/cmc.2024.048922

    Abstract As an emerging network paradigm, the software-defined network (SDN) finds extensive application in areas such as smart grids, the Internet of Things (IoT), and edge computing. The forwarding layer in software-defined networks is susceptible to eavesdropping attacks. Route hopping is a moving target defense (MTD) technology that is frequently employed to resist eavesdropping attacks. In the traditional route hopping technology, both request and reply packets use the same hopping path. If an eavesdropping attacker monitors the nodes along this path, the risk of 100% data leakage becomes substantial. In this paper, we present an effective route hopping approach, called two-day… More >

  • Open Access

    ARTICLE

    E2E-MFERC: A Multi-Face Expression Recognition Model for Group Emotion Assessment

    Lin Wang1, Juan Zhao2, Hu Song3, Xiaolong Xu4,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1105-1135, 2024, DOI:10.32604/cmc.2024.048688

    Abstract In smart classrooms, conducting multi-face expression recognition based on existing hardware devices to assess students’ group emotions can provide educators with more comprehensive and intuitive classroom effect analysis, thereby continuously promoting the improvement of teaching quality. However, most existing multi-face expression recognition methods adopt a multi-stage approach, with an overall complex process, poor real-time performance, and insufficient generalization ability. In addition, the existing facial expression datasets are mostly single face images, which are of low quality and lack specificity, also restricting the development of this research. This paper aims to propose an end-to-end high-performance multi-face expression recognition algorithm model suitable… More >

  • Open Access

    ARTICLE

    A Deep Learning Framework for Mass-Forming Chronic Pancreatitis and Pancreatic Ductal Adenocarcinoma Classification Based on Magnetic Resonance Imaging

    Luda Chen1, Kuangzhu Bao2, Ying Chen2, Jingang Hao2,*, Jianfeng He1,3,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 409-427, 2024, DOI:10.32604/cmc.2024.048507

    Abstract Pancreatic diseases, including mass-forming chronic pancreatitis (MFCP) and pancreatic ductal adenocarcinoma (PDAC), present with similar imaging features, leading to diagnostic complexities. Deep Learning (DL) methods have been shown to perform well on diagnostic tasks. Existing DL pancreatic lesion diagnosis studies based on Magnetic Resonance Imaging (MRI) utilize the prior information to guide models to focus on the lesion region. However, over-reliance on prior information may ignore the background information that is helpful for diagnosis. This study verifies the diagnostic significance of the background information using a clinical dataset. Consequently, the Prior Difference Guidance Network (PDGNet) is proposed, merging decoupled lesion… More >

  • Open Access

    ARTICLE

    Pervasive Attentive Neural Network for Intelligent Image Classification Based on N-CDE’s

    Anas W. Abulfaraj*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1137-1156, 2024, DOI:10.32604/cmc.2024.047945

    Abstract The utilization of visual attention enhances the performance of image classification tasks. Previous attention-based models have demonstrated notable performance, but many of these models exhibit reduced accuracy when confronted with inter-class and intra-class similarities and differences. Neural-Controlled Differential Equations (N-CDE’s) and Neural Ordinary Differential Equations (NODE’s) are extensively utilized within this context. N-CDE’s possesses the capacity to effectively illustrate both inter-class and intra-class similarities and differences with enhanced clarity. To this end, an attentive neural network has been proposed to generate attention maps, which uses two different types of N-CDE’s, one for adopting hidden layers and the other to generate… More >

  • Open Access

    ARTICLE

    Intelligent Machine Learning Based Brain Tumor Segmentation through Multi-Layer Hybrid U-Net with CNN Feature Integration

    Sharaf J. Malebary*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1301-1317, 2024, DOI:10.32604/cmc.2024.047917

    Abstract Brain tumors are a pressing public health concern, characterized by their high mortality and morbidity rates. Nevertheless, the manual segmentation of brain tumors remains a laborious and error-prone task, necessitating the development of more precise and efficient methodologies. To address this formidable challenge, we propose an advanced approach for segmenting brain tumor Magnetic Resonance Imaging (MRI) images that harnesses the formidable capabilities of deep learning and convolutional neural networks (CNNs). While CNN-based methods have displayed promise in the realm of brain tumor segmentation, the intricate nature of these tumors, marked by irregular shapes, varying sizes, uneven distribution, and limited available… More >

  • Open Access

    ARTICLE

    Multimodal Social Media Fake News Detection Based on Similarity Inference and Adversarial Networks

    Fangfang Shan1,2,*, Huifang Sun1,2, Mengyi Wang1,2

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 581-605, 2024, DOI:10.32604/cmc.2024.046202

    Abstract As social networks become increasingly complex, contemporary fake news often includes textual descriptions of events accompanied by corresponding images or videos. Fake news in multiple modalities is more likely to create a misleading perception among users. While early research primarily focused on text-based features for fake news detection mechanisms, there has been relatively limited exploration of learning shared representations in multimodal (text and visual) contexts. To address these limitations, this paper introduces a multimodal model for detecting fake news, which relies on similarity reasoning and adversarial networks. The model employs Bidirectional Encoder Representation from Transformers (BERT) and Text Convolutional Neural… More >

  • Open Access

    ARTICLE

    The Epstein-Barr virus-miRNA-BART6-5p regulates TGF-β/SMAD4 pathway to induce glycolysis and enhance proliferation and metastasis of gastric cancer cells

    XUHUI ZHAO1,2, XIAOMIN HUANG1, CHUNYAN DANG2, XIA WANG1, YUJIAO QI3, HONGLING LI2,*

    Oncology Research, Vol.32, No.5, pp. 999-1009, 2024, DOI:10.32604/or.2024.046679

    Abstract Background: EBV-miR-BARTs exhibit significant relevance in epithelial tumors, particularly in EBV-associated gastric and nasopharyngeal cancers. However, their specific mechanisms in the initiation and progression of gastric cancer remain insufficiently explored. Material and Methods: Initially, EBV-miRNA-BART6-5p and its target gene SMAD4 expression were assessed in EBV-associated gastric cancer tissues and cell lines. Subsequent transfection induced overexpression of EBV-miRNA-BART6-5p in AGS and MKN-45, and downregulation in EBV-positive cells (SUN-719). The subsequent evaluation aimed to observe their impact on gastric cancer cell proliferation, migration, and glycolytic processes, with the TGF-β/SMAD4 signaling pathway value clarified using a TGF-β inhibitor. Results: EBV-miRNA-BART6-5p exhibits pronounced upregulation… More >

  • Open Access

    ARTICLE

    Hydroxysafflor yellow A induced ferroptosis of Osteosarcoma cancer cells by HIF-1α/HK2 and SLC7A11 pathway

    YIWEN ZHU1, LIU YANG1, YING YU1, YING XIONG2, PING XIAO2, XIAO FU2, XIN LUO2,*

    Oncology Research, Vol.32, No.5, pp. 899-910, 2024, DOI:10.32604/or.2023.042604

    Abstract Osteosarcoma is a very serious primary bone cancer with a high death rate and a dismal prognosis. Since there is no permanent therapy for this condition, it is necessary to develop a cure. Therefore, this investigation was carried out to assess the impacts and biological functions of hydroxysafflor yellow A (HYSA) in osteosarcoma cell lines (MG63). In this investigational study, MG63 cells were utilized. Microarray experiments, quantitative polymerase chain reaction (qPCR), immunofluorescent staining, extracellular acidification rate (ECAR), oxygen consumption rate (OCR), glucose consumption, lactate production, and ATP levels, proliferation assay, 5-Ethynyl-2′-deoxyuridine (EDU) staining, and Western blot were performed. In MG63… More >

  • Open Access

    ARTICLE

    Circ_0003855 involvement of esophageal cancer progression through miR-622/FLOT1

    JINGJING TIAN1,*, XIBAO HU2, XINRONG ZHANG1

    Oncology Research, Vol.32, No.5, pp. 925-931, 2024, DOI:10.32604/or.2023.042447

    Abstract To confirm the relationship between Circ_0003855 and EC, we purchased the Human esophageal carcinoma cell line Eca109 and normal human esophageal epithelial cells HEEC, and the expression levels of Circ_0003855, miR-622, and FLOT1 were detected. The results show that Circ_0003855 and FLOT1 were highly expressed in Eca109 cells, while miR-622 was lowly expressed (p < 0.05). Subsequently, Circ_0003855 small interfering RNA (si-Circ_0003855) and its negative control (si-NC) were used to detect changes in cellular biological behaviors. We found that the activity of Eca109 cells was reduced after interfering with the expression of Circ_0003855, and miR-622 expression was elevated, while FLOT1… More >

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