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  • Open Access

    ARTICLE

    PHLDA2 reshapes the immune microenvironment and induces drug resistance in hepatocellular carcinoma

    KUN FENG1,#, HAO PENG2,#, QINGPENG LV1, YEWEI ZHANG1,*

    Oncology Research, Vol.32, No.6, pp. 1063-1078, 2024, DOI:10.32604/or.2024.047078

    Abstract Hepatocellular carcinoma (HCC) is a malignancy known for its unfavorable prognosis. The dysregulation of the tumor microenvironment (TME) can affect the sensitivity to immunotherapy or chemotherapy, leading to treatment failure. The elucidation of PHLDA2’s involvement in HCC is imperative, and the clinical value of PHLDA2 is also underestimated. Here, bioinformatics analysis was performed in multiple cohorts to explore the phenotype and mechanism through which PHLDA2 may affect the progression of HCC. Then, the expression and function of PHLDA2 were examined via the qRT-PCR, Western Blot, and MTT assays. Our findings indicate a substantial upregulation of… More >

  • Open Access

    ARTICLE

    Improving Channel Estimation in a NOMA Modulation Environment Based on Ensemble Learning

    Lassaad K. Smirani1, Leila Jamel2,*, Latifah Almuqren2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1315-1337, 2024, DOI:10.32604/cmes.2024.047551

    Abstract This study presents a layered generalization ensemble model for next generation radio mobiles, focusing on supervised channel estimation approaches. Channel estimation typically involves the insertion of pilot symbols with a well-balanced rhythm and suitable layout. The model, called Stacked Generalization for Channel Estimation (SGCE), aims to enhance channel estimation performance by eliminating pilot insertion and improving throughput. The SGCE model incorporates six machine learning methods: random forest (RF), gradient boosting machine (GB), light gradient boosting machine (LGBM), support vector regression (SVR), extremely randomized tree (ERT), and extreme gradient boosting (XGB). By generating meta-data from five… More >

  • Open Access

    ARTICLE

    Optimizing Sustainability: Exergoenvironmental Analysis of a Multi-Effect Distillation with Thermal Vapor Compression System for Seawater Desalination

    Zineb Fergani1, Zakaria Triki1, Rabah Menasri1, Hichem Tahraoui1,2,*, Meriem Zamouche3, Mohammed Kebir4, Jie Zhang5, Abdeltif Amrane6,*

    Frontiers in Heat and Mass Transfer, Vol.22, No.2, pp. 455-473, 2024, DOI:10.32604/fhmt.2024.050332

    Abstract Seawater desalination stands as an increasingly indispensable solution to address global water scarcity issues. This study conducts a thorough exergoenvironmental analysis of a multi-effect distillation with thermal vapor compression (MED-TVC) system, a highly promising desalination technology. The MED-TVC system presents an energy-efficient approach to desalination by harnessing waste heat sources and incorporating thermal vapor compression. The primary objective of this research is to assess the system’s thermodynamic efficiency and environmental impact, considering both energy and exergy aspects. The investigation delves into the intricacies of energy and exergy losses within the MED-TVC process, providing a holistic… More >

  • Open Access

    ARTICLE

    A Novel Scheduling Framework for Multi-Programming Quantum Computing in Cloud Environment

    Danyang Zheng, Jinchen Xv, Feng Yue, Qiming Du, Zhiheng Wang, Zheng Shan*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1957-1974, 2024, DOI:10.32604/cmc.2024.048956

    Abstract As cloud quantum computing gains broader acceptance, a growing quantity of researchers are directing their focus towards this domain. Nevertheless, the rapid surge in demand for cloud-based quantum computing resources has led to a scarcity, which in turn hampers users from achieving optimal satisfaction. Therefore, cloud quantum computing service providers require a unified analysis and scheduling framework for their quantum resources and user jobs to meet the ever-growing usage demands. This paper introduces a new multi-programming scheduling framework for quantum computing in a cloud environment. The framework addresses the issue of limited quantum computing resources More >

  • Open Access

    ARTICLE

    CARD11 serves as a therapeutic biomarker for the drug therapies of ccRCC

    KAIWEN TIAN#, HANZHONG CHEN#, QIANQIAN WANG, FENGLIAN JIANG, CHUNXIANG FENG, TENG LI, XIAOYONG PU, YANLIN TANG*, JIUMIN LIU*

    BIOCELL, Vol.48, No.5, pp. 817-834, 2024, DOI:10.32604/biocell.2024.048737

    Abstract Background: The incidence of clear cell renal cell carcinoma (ccRCC) is globally high; however, despite the introduction of innovative drug therapies, there remains a lack of effective biomarkers for evaluating treatment response. Recently, Caspase recruiting domain-containing protein 11 (CARD11) has garnered attention due to its significant association with tumor development and the immune system. Methods: The expression of CARD11 mRNA and protein in ccRCC were analyzed by public database and immunohistochemistry. The focus of this study is on the epigenomic modifications of CARD11, its expression of ccRCC immunophenotype, and its correlation with response to immunotherapy… More > Graphic Abstract

    CARD11 serves as a therapeutic biomarker for the drug therapies of ccRCC

  • Open Access

    ARTICLE

    Sepsis Prediction Using CNNBDLSTM and Temporal Derivatives Feature Extraction in the IoT Medical Environment

    Sapiah Sakri1, Shakila Basheer1, Zuhaira Muhammad Zain1, Nurul Halimatul Asmak Ismail2,*, Dua’ Abdellatef Nassar1, Manal Abdullah Alohali1, Mais Ayman Alharaki1

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1157-1185, 2024, DOI:10.32604/cmc.2024.048051

    Abstract Background: Sepsis, a potentially fatal inflammatory disease triggered by infection, carries significant health implications worldwide. Timely detection is crucial as sepsis can rapidly escalate if left undetected. Recent advancements in deep learning (DL) offer powerful tools to address this challenge. Aim: Thus, this study proposed a hybrid CNNBDLSTM, a combination of a convolutional neural network (CNN) with a bi-directional long short-term memory (BDLSTM) model to predict sepsis onset. Implementing the proposed model provides a robust framework that capitalizes on the complementary strengths of both architectures, resulting in more accurate and timelier predictions. Method: The sepsis prediction… More >

  • Open Access

    ARTICLE

    Smartphone-Based Wi-Fi Analysis for Bus Passenger Counting

    Mohammed Alatiyyah*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 875-907, 2024, DOI:10.32604/cmc.2024.047790

    Abstract In the contemporary era of technological advancement, smartphones have become an indispensable part of individuals’ daily lives, exerting a pervasive influence. This paper presents an innovative approach to passenger counting on buses through the analysis of Wi-Fi signals emanating from passengers’ mobile devices. The study seeks to scrutinize the reliability of digital Wi-Fi environments in predicting bus occupancy levels, thereby addressing a crucial aspect of public transportation. The proposed system comprises three crucial elements: Signal capture, data filtration, and the calculation and estimation of passenger numbers. The pivotal findings reveal that the system demonstrates commendable… More >

  • Open Access

    ARTICLE

    Multi-cohort comprehensive analysis unveiling the clinical value and therapeutic effect of GNAL in glioma

    ZHEN LIU1,#, LIANGWANG YANG2,#, ZHENGXING XIE1, HUI YU3, TIANYI GU3, DAOMING SHI4, NING CAI1,*, SHENGHUA ZHUO2,*

    Oncology Research, Vol.32, No.5, pp. 965-981, 2024, DOI:10.32604/or.2024.045769

    Abstract Clinical data indicates that glioma patients have poor treatment outcomes and clinical prognosis. The role of olfactory signaling pathway-related genes (OSPRGs) in glioma has not been fully elucidated. In this study, we aimed to investigate the role and relationship between OSPRGs and glioma. Univariate and multivariate Cox regression analyses were performed to assess the relationship between OSPRGs and the overall survival of glioma based on public cohorts, and the target gene (G Protein Subunit Alpha L, GNAL) was screened. The association of GNAL expression with clinicopathological characteristics, gene mutation landscape, tumor immune microenvironment (TIME), deoxyribonucleic acid… More >

  • Open Access

    ARTICLE

    Detection of Student Engagement in E-Learning Environments Using EfficientnetV2-L Together with RNN-Based Models

    Farhad Mortezapour Shiri1,*, Ehsan Ahmadi2, Mohammadreza Rezaee1, Thinagaran Perumal1

    Journal on Artificial Intelligence, Vol.6, pp. 85-103, 2024, DOI:10.32604/jai.2024.048911

    Abstract Automatic detection of student engagement levels from videos, which is a spatio-temporal classification problem is crucial for enhancing the quality of online education. This paper addresses this challenge by proposing four novel hybrid end-to-end deep learning models designed for the automatic detection of student engagement levels in e-learning videos. The evaluation of these models utilizes the DAiSEE dataset, a public repository capturing student affective states in e-learning scenarios. The initial model integrates EfficientNetV2-L with Gated Recurrent Unit (GRU) and attains an accuracy of 61.45%. Subsequently, the second model combines EfficientNetV2-L with bidirectional GRU (Bi-GRU), yielding More >

  • Open Access

    ARTICLE

    Improved Corrosion Resistance of Carbon Reinforced Aluminium Laminates in Atmospheric Environment: Role of Environment Friendly Jute Fibre/ Alumina nano Coating

    M. VASUMATHI1,a,*, VELA MURALI2,b, S. RASHIA BEGUM1,c, N. RAJENDRAN2,d

    Journal of Polymer Materials, Vol.36, No.1, pp. 1-11, 2019, DOI:10.32381/JPM.2019.36.01.1

    Abstract In the Fibre Metal Laminate (FML), Carbon Reinforced Aluminium laminate (CARALL), aluminium is placed next to carbon fibres. The potential difference between the aluminium and carbon is larger, leads to galvanic corrosion, which tries to bring down the durability of the FML. To bring down the effect of corrosion, a material layer is introduced between fibres and aluminium so as to separate them thus lowering the possibility of occurrence of corrosion. Another approach is to coat the surfaces of aluminium with different proportions of aluminium oxide nano particles prior to fabrication of the FML. For More >

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