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  • Open Access


    CircTHSD4 promotes the malignancy and docetaxel (DTX) resistance in prostate cancer by regulating miR-203/HMGA2 axis


    Oncology Research, Vol.32, No.3, pp. 529-544, 2024, DOI:10.32604/or.2023.031511

    Abstract Objective: Circular ribose nucleic acids (circRNAs) are implicated in tumor progression and drug resistance of prostate cancer (PCa). The current work explored the function of circ_0005203 (circTHSD4) in the malignancy and docetaxel (DTX) resistance of PCa. Methods: circTHSD4 expression within PCa as well as matched non-carcinoma samples was measured through real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR). In addition, a subcellular fraction assay was conducted to determine circTHSD4 subcellular localization within PCa cells. In addition, we performed a Western blot (WB) assay to detect high-mobility-group A2 protein (HMGA2) levels. Besides, functional associations of two molecules… More >

  • Open Access


    A Novel Fractional Dengue Transmission Model in the Presence of Wolbachia Using Stochastic Based Artificial Neural Network

    Zeshan Faiz1, Iftikhar Ahmed1, Dumitru Baleanu2,3,4, Shumaila Javeed1,5,6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1217-1238, 2024, DOI:10.32604/cmes.2023.029879

    Abstract The purpose of this research work is to investigate the numerical solutions of the fractional dengue transmission model (FDTM) in the presence of Wolbachia using the stochastic-based Levenberg-Marquardt neural network (LM-NN) technique. The fractional dengue transmission model (FDTM) consists of 12 compartments. The human population is divided into four compartments; susceptible humans (Sh), exposed humans (Eh), infectious humans (Ih), and recovered humans (Rh). Wolbachia-infected and Wolbachia-uninfected mosquito population is also divided into four compartments: aquatic (eggs, larvae, pupae), susceptible, exposed, and infectious. We investigated three different cases of vertical transmission probability (η), namely when Wolbachia-free mosquitoes persist only… More >

  • Open Access


    CHDTEPDB: Transcriptome Expression Profile Database and Interactive Analysis Platform for Congenital Heart Disease

    Ziguang Song1,2, Jiangbo Yu1, Mengmeng Wang3, Weitao Shen4, Chengcheng Wang1, Tianyi Lu1, Gaojun Shan1, Guo Dong1, Yiru Wang1, Jiyi Zhao1,*

    Congenital Heart Disease, Vol.18, No.6, pp. 693-701, 2023, DOI:10.32604/chd.2024.048081

    Abstract CHDTEPDB (URL: ) is a manually integrated database for congenital heart disease (CHD) that stores the expression profiling data of CHD derived from published papers, aiming to provide rich resources for investigating a deeper correlation between human CHD and aberrant transcriptome expression. The development of human diseases involves important regulatory roles of RNAs, and expression profiling data can reflect the underlying etiology of inherited diseases. Hence, collecting and compiling expression profiling data is of critical significance for a comprehensive understanding of the mechanisms and functions that underpin genetic diseases. CHDTEPDB stores the expression profiles of… More >

  • Open Access


    A Lightweight Deep Learning-Based Model for Tomato Leaf Disease Classification

    Naeem Ullah1, Javed Ali Khan2,*, Sultan Almakdi3, Mohammed S. Alshehri3, Mimonah Al Qathrady4, Eman Abdullah Aldakheel5,*, Doaa Sami Khafaga5

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3969-3992, 2023, DOI:10.32604/cmc.2023.041819

    Abstract Tomato leaf diseases significantly impact crop production, necessitating early detection for sustainable farming. Deep Learning (DL) has recently shown excellent results in identifying and classifying tomato leaf diseases. However, current DL methods often require substantial computational resources, hindering their application on resource-constrained devices. We propose the Deep Tomato Detection Network (DTomatoDNet), a lightweight DL-based framework comprising 19 learnable layers for efficient tomato leaf disease classification to overcome this. The Convn kernels used in the proposed (DTomatoDNet) framework is 1 × 1, which reduces the number of parameters and helps in more detailed and descriptive feature extraction for… More >

  • Open Access


    Modeling Geometrically Nonlinear FG Plates: A Fast and Accurate Alternative to IGA Method Based on Deep Learning

    Se Li1, Tiantang Yu1,*, Tinh Quoc Bui2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2793-2808, 2024, DOI:10.32604/cmes.2023.030278

    Abstract Isogeometric analysis (IGA) is known to show advanced features compared to traditional finite element approaches. Using IGA one may accurately obtain the geometrically nonlinear bending behavior of plates with functional grading (FG). However, the procedure is usually complex and often is time-consuming. We thus put forward a deep learning method to model the geometrically nonlinear bending behavior of FG plates, bypassing the complex IGA simulation process. A long bidirectional short-term memory (BLSTM) recurrent neural network is trained using the load and gradient index as inputs and the displacement responses as outputs. The nonlinear relationship between More >

  • Open Access


    New Antenna Array Beamforming Techniques Based on Hybrid Convolution/Genetic Algorithm for 5G and Beyond Communications

    Shimaa M. Amer1, Ashraf A. M. Khalaf2, Amr H. Hussein3,4, Salman A. Alqahtani5, Mostafa H. Dahshan6, Hossam M. Kassem3,4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2749-2767, 2024, DOI:10.32604/cmes.2023.029138

    Abstract Side lobe level reduction (SLL) of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service (QOS) in recent and future wireless communication systems starting from 5G up to 7G. Furthermore, it improves the array gain and directivity, increasing the detection range and angular resolution of radar systems. This study proposes two highly efficient SLL reduction techniques. These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm (GA) to develop the Conv/GA and DConv/GA, respectively. The convolution process determines the element’s… More >

  • Open Access


    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

    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


    Mechanism of Thermally Radiative Prandtl Nanofluids and Double-Diffusive Convection in Tapered Channel on Peristaltic Flow with Viscous Dissipation and Induced Magnetic Field

    Yasir Khan1, Safia Akram2,*, Maria Athar3, Khalid Saeed4, Alia Razia2, A. Alameer1

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1501-1520, 2024, DOI:10.32604/cmes.2023.029878

    Abstract The application of mathematical modeling to biological fluids is of utmost importance, as it has diverse applications in medicine. The peristaltic mechanism plays a crucial role in understanding numerous biological flows. In this paper, we present a theoretical investigation of the double diffusion convection in the peristaltic transport of a Prandtl nanofluid through an asymmetric tapered channel under the combined action of thermal radiation and an induced magnetic field. The equations for the current flow scenario are developed, incorporating relevant assumptions, and considering the effect of viscous dissipation. The impact of thermal radiation and double… More >

  • Open Access


    Experimental Study on Gas Flow Uniformity in a Diesel Particulate Filter Carrier

    Zhengyong Wang1, Jianhua Zhang2, Guoliang Su3, Peixing Yang4, Xiantao Fan4, Shuzhan Bai1, Ke Sun1,*, Guihua Wang1,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.1, pp. 193-204, 2024, DOI:10.32604/fdmp.2023.030561

    Abstract A Diesel Particulate Filter (DPF) is a critical device for diesel engine exhaust products treatment. When using active-regeneration purification methods, on the one hand, a spatially irregular gas flow can produce relatively high local temperatures, potentially resulting in damage to the carrier; On the other hand, the internal temperature field can also undergo significant changes contributing to increase this risk. This study explores the gas flow uniformity in a DPF carrier and the related temperature behavior under drop-to-idle (DTI) condition by means of bench tests. It is shown that the considered silicon carbide carrier exhibits… More >

  • Open Access


    DTHN: Dual-Transformer Head End-to-End Person Search Network

    Cheng Feng*, Dezhi Han, Chongqing Chen

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 245-261, 2023, DOI:10.32604/cmc.2023.042765

    Abstract Person search mainly consists of two submissions, namely Person Detection and Person Re-identification (re-ID). Existing approaches are primarily based on Faster R-CNN and Convolutional Neural Network (CNN) (e.g., ResNet). While these structures may detect high-quality bounding boxes, they seem to degrade the performance of re-ID. To address this issue, this paper proposes a Dual-Transformer Head Network (DTHN) for end-to-end person search, which contains two independent Transformer heads, a box head for detecting the bounding box and extracting efficient bounding box feature, and a re-ID head for capturing high-quality re-ID features for the re-ID task. Specifically,… More >

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