Xi Li^1,2, Yuxin Li², Zhenhua Xiao^3,*, Zhenghua Huang¹, Lianying Zou¹

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3325-3349, 2024, DOI:10.32604/cmc.2024.056464 - 18 November 2024

Abstract Human pose estimation is a critical research area in the field of computer vision, playing a significant role in applications such as human-computer interaction, behavior analysis, and action recognition. In this paper, we propose a U-shaped keypoint detection network (DAUNet) based on an improved ResNet subsampling structure and spatial grouping mechanism. This network addresses key challenges in traditional methods, such as information loss, large network redundancy, and insufficient sensitivity to low-resolution features. DAUNet is composed of three main components. First, we introduce an improved BottleNeck block that employs partial convolution and strip pooling to reduce… More >

WEITAO ZHENG¹, DONG JIANG², SONGEN CHEN¹, MEILING WU¹, BAOQI YAN², JIAHUI ZHAI², YUNQIANG SHI², BIN XIE¹, XINGWANG XIE², KANGHONG HU^1,*, WENXUE MA^3,*

Oncology Research, Vol.32, No.12, pp. 1837-1850, 2024, DOI:10.32604/or.2024.056565 - 13 November 2024

Abstract Objectives: The Kirsten rat sarcoma virus (KRAS) G12D oncogenic mutation poses a significant challenge in treating solid tumors due to the lack of specific and effective therapeutic interventions. This study aims to explore innovative approaches in T cell receptor (TCR) engineering and characterization to target the KRAS G12D_7-16 mutation, providing potential strategies for overcoming this therapeutic challenge. Methods: In this innovative study, we engineered and characterized two T cell receptors (TCRs), KDA11-01 and KDA11-02 with high affinity for the KRAS G12D_7-16 mutation. These TCRs were isolated from tumor-infiltrating lymphocytes (TILs) derived from tumor tissues of patients More >

Mohammed A. Mahdi¹, Shahanawaj Ahamad², Sawsan A. Saad³, Alaa Dafhalla³, Alawi Alqushaibi⁴, Rizwan Qureshi^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2351-2373, 2024, DOI:10.32604/cmes.2024.055723 - 31 October 2024

Abstract The segmentation of head and neck (H&N) tumors in dual Positron Emission Tomography/Computed Tomography (PET/CT) imaging is a critical task in medical imaging, providing essential information for diagnosis, treatment planning, and outcome prediction. Motivated by the need for more accurate and robust segmentation methods, this study addresses key research gaps in the application of deep learning techniques to multimodal medical images. Specifically, it investigates the limitations of existing 2D and 3D models in capturing complex tumor structures and proposes an innovative 2.5D UNet Transformer model as a solution. The primary research questions guiding this study… More >

Oncology Research Editorial Office

Oncology Research, Vol.32, No.11, pp. 1815-1815, 2024, DOI:10.32604/or.2024.056890 - 16 October 2024

Abstract This article has no abstract. More >

Zhaojie Sun¹, Linlin Xing^1,*, Longbo Zhang¹, Hongzhen Cai², Maozu Guo³

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4325-4340, 2024, DOI:10.32604/cmc.2024.053588 - 12 September 2024

Abstract Extracting valuable information from biomedical texts is one of the current research hotspots of concern to a wide range of scholars. The biomedical corpus contains numerous complex long sentences and overlapping relational triples, making most generalized domain joint modeling methods difficult to apply effectively in this field. For a complex semantic environment in biomedical texts, in this paper, we propose a novel perspective to perform joint entity and relation extraction; existing studies divide the relation triples into several steps or modules. However, the three elements in the relation triples are interdependent and inseparable, so we… More >

Bingrui Ju^1,2, Wenxiang Sun², Wenzhen Qu^1,2,*, Yan Gu²

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 267-280, 2024, DOI:10.32604/cmes.2024.052159 - 20 August 2024

Abstract In this study, we propose an efficient numerical framework to attain the solution of the extended Fisher-Kolmogorov (EFK) problem. The temporal derivative in the EFK equation is approximated by utilizing the Crank-Nicolson scheme. Following temporal discretization, the generalized finite difference method (GFDM) with supplementary nodes is utilized to address the nonlinear boundary value problems at each time node. These supplementary nodes are distributed along the boundary to match the number of boundary nodes. By incorporating supplementary nodes, the resulting nonlinear algebraic equations can effectively satisfy the governing equation and boundary conditions of the EFK equation. More >

Jiaxiang Luo^1,2, Weien Zhou^2,3, Bingxiao Du^1,*, Daokui Li¹, Wen Yao^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1919-1947, 2024, DOI:10.32604/cmes.2024.048118 - 20 May 2024

Abstract In recent years, there has been significant research on the application of deep learning (DL) in topology optimization (TO) to accelerate structural design. However, these methods have primarily focused on solving binary TO problems, and effective solutions for multi-material topology optimization (MMTO) which requires a lot of computing resources are still lacking. Therefore, this paper proposes the framework of multiphase topology optimization using deep learning to accelerate MMTO design. The framework employs convolutional neural network (CNN) to construct a surrogate model for solving MMTO, and the obtained surrogate model can rapidly generate multi-material structure topologies… More >

Jai Hak Park^*

Digital Engineering and Digital Twin, Vol.2, pp. 79-101, 2024, DOI:10.32604/dedt.2024.047280 - 25 March 2024

Abstract A finite element alternating method has been known as a very convenient and accurate method to solve two and three-dimensional crack problems. In this method, a general crack problem is solved by a superposition of two solutions. One is a finite element solution for a finite body without a crack, and the other is an analytical solution for a crack in an infinite body. Since a crack is not considered in a finite element model, generating a model is very simple. The method is especially very convenient for a fatigue crack growth simulation. Over the More >

Muhammad Abaid Ur Rehman^1,*, Muhammad Asif Farooq¹, Ahmed M. Hassan²

Frontiers in Heat and Mass Transfer, Vol.22, No.1, pp. 263-286, 2024, DOI:10.32604/fhmt.2023.044587 - 21 March 2024

Abstract This paper proposes a mathematical modeling approach to examine the two-dimensional flow stagnates at over a heated stretchable sheet in a porous medium influenced by nonlinear thermal radiation, variable viscosity, and MHD. This study’s main purpose is to examine how thermal radiation and varying viscosity affect fluid flow motion. Additionally, we consider the convective boundary conditions and incorporate the gyrotactic microorganisms equation, which describes microorganism behavior in response to fluid flow. The partial differential equations (PDEs) that represent the conservation equations for mass, momentum, energy, and microorganisms are then converted into a system of coupled… More >

Zhiqing Dong¹, Zhao Zhang^1,*, Hongyan Zhou², Xuebo Chen²

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1977-1993, 2024, DOI:10.32604/cmc.2024.047233 - 27 February 2024

Abstract With the advent of the information security era, it is necessary to guarantee the privacy, accuracy, and dependable transfer of pictures. This study presents a new approach to the encryption and compression of color images. It is predicated on 2D compressed sensing (CS) and the hyperchaotic system. First, an optimized Arnold scrambling algorithm is applied to the initial color images to ensure strong security. Then, the processed images are concurrently encrypted and compressed using 2D CS. Among them, chaotic sequences replace traditional random measurement matrices to increase the system’s security. Third, the processed images are More >