Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (1,477)
  • Open Access

    REVIEW

    Deciphering resistance mechanisms and novel strategies to overcome drug resistance in ovarian cancer: a comprehensive review

    EFFAT ALEMZADEH1, LEILA ALLAHQOLI2, AFROOZ MAZIDIMORADI3, ESMAT ALEMZADEH1,4, FAHIMEH GHASEMI4,5, HAMID SALEHINIYA6, IBRAHIM ALKATOUT7,*

    Oncology Research, Vol.32, No.5, pp. 831-847, 2024, DOI:10.32604/or.2024.031006

    Abstract Ovarian cancer is among the most lethal gynecological cancers, primarily due to the lack of specific symptoms leading to an advanced-stage diagnosis and resistance to chemotherapy. Drug resistance (DR) poses the most significant challenge in treating patients with existing drugs. The Food and Drug Administration (FDA) has recently approved three new therapeutic drugs, including two poly (ADP-ribose) polymerase (PARP) inhibitors (olaparib and niraparib) and one vascular endothelial growth factor (VEGF) inhibitor (bevacizumab) for maintenance therapy. However, resistance to these new drugs has emerged. Therefore, understanding the mechanisms of DR and exploring new approaches to overcome them is crucial for effective… More >

  • Open Access

    ARTICLE

    NFHP-RN: A Method of Few-Shot Network Attack Detection Based on the Network Flow Holographic Picture-ResNet

    Tao Yi1,3, Xingshu Chen1,2,*, Mingdong Yang3, Qindong Li1, Yi Zhu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 929-955, 2024, DOI:10.32604/cmes.2024.048793

    Abstract Due to the rapid evolution of Advanced Persistent Threats (APTs) attacks, the emergence of new and rare attack samples, and even those never seen before, make it challenging for traditional rule-based detection methods to extract universal rules for effective detection. With the progress in techniques such as transfer learning and meta-learning, few-shot network attack detection has progressed. However, challenges in few-shot network attack detection arise from the inability of time sequence flow features to adapt to the fixed length input requirement of deep learning, difficulties in capturing rich information from original flow in the case of insufficient samples, and the… More >

  • Open Access

    ARTICLE

    A Coupled Thermomechanical Crack Propagation Behavior of Brittle Materials by Peridynamic Differential Operator

    Tianyi Li1,2, Xin Gu2, Qing Zhang2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 339-361, 2024, DOI:10.32604/cmes.2024.047566

    Abstract This study proposes a comprehensive, coupled thermomechanical model that replaces local spatial derivatives in classical differential thermomechanical equations with nonlocal integral forms derived from the peridynamic differential operator (PDDO), eliminating the need for calibration procedures. The model employs a multi-rate explicit time integration scheme to handle varying time scales in multi-physics systems. Through simulations conducted on granite and ceramic materials, this model demonstrates its effectiveness. It successfully simulates thermal damage behavior in granite arising from incompatible mineral expansion and accurately calculates thermal crack propagation in ceramic slabs during quenching. To account for material heterogeneity, the model utilizes the Shuffle algorithm… More >

  • Open Access

    ARTICLE

    Perception Enhanced Deep Deterministic Policy Gradient for Autonomous Driving in Complex Scenarios

    Lyuchao Liao1,2, Hankun Xiao2,*, Pengqi Xing2, Zhenhua Gan1,2, Youpeng He2, Jiajun Wang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 557-576, 2024, DOI:10.32604/cmes.2024.047452

    Abstract Autonomous driving has witnessed rapid advancement; however, ensuring safe and efficient driving in intricate scenarios remains a critical challenge. In particular, traffic roundabouts bring a set of challenges to autonomous driving due to the unpredictable entry and exit of vehicles, susceptibility to traffic flow bottlenecks, and imperfect data in perceiving environmental information, rendering them a vital issue in the practical application of autonomous driving. To address the traffic challenges, this work focused on complex roundabouts with multi-lane and proposed a Perception Enhanced Deep Deterministic Policy Gradient (PE-DDPG) for Autonomous Driving in the Roundabouts. Specifically, the model incorporates an enhanced variational… More >

  • Open Access

    ARTICLE

    Study of the Ballistic Impact Behavior of Protective Multi-Layer Composite Armor

    Dongsheng Jia, Yingjie Xu*, Liangdi Wang, Jihong Zhu, Weihong Zhang

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 171-199, 2024, DOI:10.32604/cmes.2024.046703

    Abstract The abalone shell, a composite material whose cross-section is composed of inorganic and organic layers, has high strength and toughness. Inspired by the abalone shell, several multi-layer composite plates with different layer sequences and thicknesses are studied as bullet-proof material in this paper. To investigate the ballistic performance of this multi-layer structure, the complete characterization model and related material parameters of large deformation, failure and fracture of Al2O3 ceramics and Carbon Fiber Reinforced Polymer (CFRP) are studied. Then, 3D finite element models of the proposed composite plates with different layer sequences and thicknesses impacted by a 12.7 mm armor-piercing incendiary… More >

  • Open Access

    ARTICLE

    An Image Fingerprint and Attention Mechanism Based Load Estimation Algorithm for Electric Power System

    Qing Zhu1,*, Linlin Gu1,2, Huijie Lin1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 577-591, 2024, DOI:10.32604/cmes.2023.043307

    Abstract With the rapid development of electric power systems, load estimation plays an important role in system operation and planning. Usually, load estimation techniques contain traditional, time series, regression analysis-based, and machine learning-based estimation. Since the machine learning-based method can lead to better performance, in this paper, a deep learning-based load estimation algorithm using image fingerprint and attention mechanism is proposed. First, an image fingerprint construction is proposed for training data. After the data preprocessing, the training data matrix is constructed by the cyclic shift and cubic spline interpolation. Then, the linear mapping and the gray-color transformation method are proposed to… More >

  • Open Access

    ARTICLE

    Scheme Based on Multi-Level Patch Attention and Lesion Localization for Diabetic Retinopathy Grading

    Zhuoqun Xia1, Hangyu Hu1, Wenjing Li2,3, Qisheng Jiang1, Lan Pu1, Yicong Shu1, Arun Kumar Sangaiah4,5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 409-430, 2024, DOI:10.32604/cmes.2024.030052

    Abstract Early screening of diabetes retinopathy (DR) plays an important role in preventing irreversible blindness. Existing research has failed to fully explore effective DR lesion information in fundus maps. Besides, traditional attention schemes have not considered the impact of lesion type differences on grading, resulting in unreasonable extraction of important lesion features. Therefore, this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator (MPAG) and a lesion localization module (LLM). Firstly, MPAG is used to predict patches of different sizes and generate a weighted attention map based on the prediction score and the types of lesions contained… More >

  • Open Access

    REVIEW

    Do tensile and shear forces exerted on cells influence mechanotransduction through stored energy considerations?

    FREDERICK H. SILVER1,2,*, TANMAY DESHMUKH2

    BIOCELL, Vol.48, No.4, pp. 525-540, 2024, DOI:10.32604/biocell.2024.047965

    Abstract All tissues in the body are subjected externally to gravity and internally by collagen fibril and cellular retractive forces that create stress and energy equilibrium required for homeostasis. Mechanotransduction involves mechanical work (force through a distance) and energy storage as kinetic and potential energy. This leads to changes in cell mitosis or apoptosis and the synthesis or loss of tissue components. It involves the application of energy directly to cells through integrin-mediated processes, cell-cell connections, stretching of the cell cytoplasm, and activation of the cell nucleus via yes-associated protein (YAP) and transcriptional coactivator with PDZ-motif (TAZ). These processes involve numerous… More >

  • Open Access

    ARTICLE

    Matrix Assisted Laser Desorption Ionization Time of Flight (MALDI-TOF)-Mass Spectrometry and 13C-NMR-Identified New Compounds in Paraberlinia bifoliolata (Ekop-Beli) Bark Tannins

    Liliane Nga1, Benoit Ndiwe1,2, Achille Bernard Biwolé1, Antonio Pizzi3,*, Jean Jalin Eyinga Biwole1, Joseph Zobo Mfomo1

    Journal of Renewable Materials, Vol.12, No.3, pp. 553-568, 2024, DOI:10.32604/jrm.2023.046568

    Abstract Extracts of plant origin, particularly tannins, are attracting growing interest for the sustainable development of materials in the industrial sector. The discovery of new tannins is therefore necessary. The aim of this work was to contribute to the understanding of the properties of Paraberlinia bifoliolata tannin by Matrix Assisted Laser Desorption Ionization Time of Flight Mass Spectroscopy MALDI-TOF/MS and Carbon 13 Nuclear Magnetic Resonance (13C NMR). The chemical composition of tannin extracted from Paraberlinia bifoliolata bark was determined, as was the mechanical strength of the resin hardened with Acacia nilotica extracts. Yield by successive water extraction was 35%. MALDI-TOF/MS analysis… More >

  • Open Access

    REVIEW

    Sustainable Biocomposites Materials for Automotive Brake Pad Application: An Overview

    Joseph O. Dirisu1,*, Imhade P. Okokpujie2,3,*, Olufunmilayo O. Joseph1, Sunday O. Oyedepo1, Oluwasegun Falodun4, Lagouge K. Tartibu3, Firdaussi D. Shehu1

    Journal of Renewable Materials, Vol.12, No.3, pp. 485-511, 2024, DOI:10.32604/jrm.2024.045188

    Abstract Research into converting waste into viable eco-friendly products has gained global concern. Using natural fibres and pulverized metallic waste becomes necessary to reduce noxious environmental emissions due to indiscriminately occupying the land. This study reviews the literature in the broad area of green composites in search of materials that can be used in automotive brake pads. Materials made by biocomposite, rather than fossil fuels, will be favoured. A database containing the tribo-mechanical performance of numerous potential components for the future green composite was established using the technical details of bio-polymers and natural reinforcements. The development of materials with diverse compositions… More > Graphic Abstract

    Sustainable Biocomposites Materials for Automotive Brake Pad Application: An Overview

Displaying 21-30 on page 3 of 1477. Per Page