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  • Open Access

    REVIEW

    Application of exosomal miRNA mediated macrophage polarization in colorectal cancer: Current progress and challenges

    YUN ZHANG1,2,#, SHALING TANG1,2,#, YUBO GAO1,2, ZHONGTING LU1,2, YUAN YANG1,2, JING CHEN3, TAO LI4,*

    Oncology Research, Vol.32, No.1, pp. 61-71, 2024, DOI:10.32604/or.2023.043481 - 15 November 2023

    Abstract Colorectal cancer (CRC) is a major global health problem with high morbidity and mortality rates. Surgical resection is the main treatment for early-stage CRC, but detecting it early is challenging. Therefore, effective therapeutic targets for advanced patients are still lacking. Exosomes, tiny vesicles in body fluids, play a crucial role in tumor metastasis, immune regulation, and drug resistance. Interestingly, they can even serve as a biomarker for cancer diagnosis and prognosis. Studies have shown that exosomes can carry miRNA, mediate the polarization of M1/M2 macrophages, promote the proliferation and metastasis of cancer cells, and affect More > Graphic Abstract

    Application of exosomal miRNA mediated macrophage polarization in colorectal cancer: Current progress and challenges

  • Open Access

    ARTICLE

    Mathematical Modelling and Simulations of Active Direct Methanol Fuel Cell

    RABIRANJAN MURMUa,b, DEBASHIS ROYa, HAREKRUSHNA SUTARb

    Journal of Polymer Materials, Vol.40, No.3-4, pp. 125-139, 2023, DOI:10.32381/JPM.2023.40.3-4.1

    Abstract A one dimensional isothermal model is proposed by modelling the kinetics of methanol transport at anode flow channel (AFC), membrane and cathode catalyst layer of direct methanol fuel cell (DMFC). Analytical model is proposed to predict methanol cross-over rate through the electrolyte membrane and cell performance. The model presented in this paper considered methanol diffusion and electrochemical oxidation at the anode and cathode channels. The analytical solution of the proposed model was simulated in a MATLAB environment to obtain the polarization curve and leakage current. The effect of methanol concentration on cell voltage and leakage More >

  • Open Access

    ARTICLE

    Design Optimization of Permanent Magnet Eddy Current Coupler Based on an Intelligence Algorithm

    Dazhi Wang*, Pengyi Pan, Bowen Niu

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1535-1555, 2023, DOI:10.32604/cmc.2023.042286 - 29 November 2023

    Abstract The permanent magnet eddy current coupler (PMEC) solves the problem of flexible connection and speed regulation between the motor and the load and is widely used in electrical transmission systems. It provides torque to the load and generates heat and losses, reducing its energy transfer efficiency. This issue has become an obstacle for PMEC to develop toward a higher power. This paper aims to improve the overall performance of PMEC through multi-objective optimization methods. Firstly, a PMEC modeling method based on the Levenberg-Marquardt back propagation (LMBP) neural network is proposed, aiming at the characteristics of… More >

  • Open Access

    ARTICLE

    Fake News Classification: Past, Current, and Future

    Muhammad Usman Ghani Khan1, Abid Mehmood2, Mourad Elhadef2, Shehzad Ashraf Chaudhry2,3,*

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2225-2249, 2023, DOI:10.32604/cmc.2023.038303 - 29 November 2023

    Abstract The proliferation of deluding data such as fake news and phony audits on news web journals, online publications, and internet business apps has been aided by the availability of the web, cell phones, and social media. Individuals can quickly fabricate comments and news on social media. The most difficult challenge is determining which news is real or fake. Accordingly, tracking down programmed techniques to recognize fake news online is imperative. With an emphasis on false news, this study presents the evolution of artificial intelligence techniques for detecting spurious social media content. This study shows past,… More >

  • Open Access

    VIEWPOINT

    Future of the current anticoronaviral agents: A viewpoint on the validation for the next COVIDs and pandemics

    AMGAD M. RABIE*

    BIOCELL, Vol.47, No.10, pp. 2133-2139, 2023, DOI:10.32604/biocell.2023.030057 - 08 November 2023

    Abstract Despite the global decline in the severity of the coronavirus disease 2019 (COVID-19) cases, the disease still represents a major concern to the relevant scientific and medical communities. The primary concern of drug scientists, virologists, and other concerned specialists in this respect is to find ready-to-use suitable and potent anticoronaviral therapies that are broadly effective against the different species/strains of the coronaviruses in general, not only against the current and previous coronaviruses (e.g., the recently-appeared severe acute respiratory syndrome coronavirus 2 “SARS-CoV-2”), i.e., effective antiviral agents for treatment and/or prophylaxis of any coronaviral infections, including More > Graphic Abstract

    Future of the current anticoronaviral agents: A viewpoint on the validation for the next COVIDs and pandemics

  • Open Access

    ARTICLE

    Soil NOx Emission Prediction via Recurrent Neural Networks

    Zhaoan Wang1, Shaoping Xiao1,*, Cheryl Reuben2, Qiyu Wang2, Jun Wang2

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 285-297, 2023, DOI:10.32604/cmc.2023.044366 - 31 October 2023

    Abstract This paper presents designing sequence-to-sequence recurrent neural network (RNN) architectures for a novel study to predict soil NOx emissions, driven by the imperative of understanding and mitigating environmental impact. The study utilizes data collected by the Environmental Protection Agency (EPA) to develop two distinct RNN predictive models: one built upon the long-short term memory (LSTM) and the other utilizing the gated recurrent unit (GRU). These models are fed with a combination of historical and anticipated air temperature, air moisture, and NOx emissions as inputs to forecast future NOx emissions. Both LSTM and GRU models can… More >

  • Open Access

    ARTICLE

    A Smart Heart Disease Diagnostic System Using Deep Vanilla LSTM

    Maryam Bukhari1, Sadaf Yasmin1, Sheneela Naz2, Mehr Yahya Durrani1, Mubashir Javaid3, Jihoon Moon4, Seungmin Rho5,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1251-1279, 2023, DOI:10.32604/cmc.2023.040329 - 31 October 2023

    Abstract Effective smart healthcare frameworks contain novel and emerging solutions for remote disease diagnostics, which aid in the prevention of several diseases including heart-related abnormalities. In this context, regular monitoring of cardiac patients through smart healthcare systems based on Electrocardiogram (ECG) signals has the potential to save many lives. In existing studies, several heart disease diagnostic systems are proposed by employing different state-of-the-art methods, however, improving such methods is always an intriguing area of research. Hence, in this research, a smart healthcare system is proposed for the diagnosis of heart disease using ECG signals. The proposed… More >

  • Open Access

    ARTICLE

    Deep Learning Model for Big Data Classification in Apache Spark Environment

    T. M. Nithya1,*, R. Umanesan2, T. Kalavathidevi3, C. Selvarathi4, A. Kavitha5

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2537-2547, 2023, DOI:10.32604/iasc.2022.028804 - 11 September 2023

    Abstract Big data analytics is a popular research topic due to its applicability in various real time applications. The recent advent of machine learning and deep learning models can be applied to analyze big data with better performance. Since big data involves numerous features and necessitates high computational time, feature selection methodologies using metaheuristic optimization algorithms can be adopted to choose optimum set of features and thereby improves the overall classification performance. This study proposes a new sigmoid butterfly optimization method with an optimum gated recurrent unit (SBOA-OGRU) model for big data classification in Apache Spark. More >

  • Open Access

    PROCEEDINGS

    Direct FE2 Method For Concurrent Multilevel Modeling of Piezoelectric Structures

    Leilei Chen2,3, Haozhi Li3,4, Lu Meng5, Pan Chen3, Pei Li1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-2, 2023, DOI:10.32604/icces.2023.010584

    Abstract In this paper, a Direct FE2 method is proposed to simulate the electromechanical coupling problem of inhomogeneous materials. The theoretical foundation for the proposed method, downscaling and upscaling principles, is the same as that of the FE2 method. The two-level simulation in the Direct FE2 method may be addressed in an integrative framework where macroscopic and microscopic degrees of freedom (DOFs) are related by multipoint constraints (MPCs) [1]. This critical characteristic permits simple implementation in commercial FE software, eliminating the necessity for recurrent data transfer between two scales [2-4]. The capabilities of Direct FE2 are validated using More >

  • Open Access

    PROCEEDINGS

    An Acceleration Scheme for the Phase Field Fatigue Fracture Simulation with a Concurrent Temporal Homogenization Method

    Shuo Yang1, Yongxing Shen1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09207

    Abstract Fatigue refers to repeated cyclic loading well below the ultimate failure stress of the structure. It accounts for most mechanical failures, and thus deserves serious consideration in engineering practice. Phase field approach is a powerful tool for fracture simulation, which tracks arbitrary and complicated crack paths without extra criterion. This approach has been widely applied to various cracking problems, such as shell fracture, beam fracture , etc. The phase field approach for fracture has been adapted for fatigue fracture in recent years. Due to the mesh requirement of the phase field approach and the large… More >

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