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  • Open Access

    ARTICLE

    Delocalized Nonlinear Vibrational Modes in Bcc Lattice for Testing and Improving Interatomic Potentials

    Denis S. Ryabov1, Igor V. Kosarev2,3, Daxing Xiong4, Aleksey A. Kudreyko5, Sergey V. Dmitriev2,6,*

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 3797-3820, 2025, DOI:10.32604/cmc.2025.062079 - 06 March 2025

    Abstract Molecular dynamics (MD) is a powerful method widely used in materials science and solid-state physics. The accuracy of MD simulations depends on the quality of the interatomic potentials. In this work, a special class of exact solutions to the equations of motion of atoms in a body-centered cubic (bcc) lattice is analyzed. These solutions take the form of delocalized nonlinear vibrational modes (DNVMs) and can serve as an excellent test of the accuracy of the interatomic potentials used in MD modeling for bcc crystals. The accuracy of the potentials can be checked by comparing the… More >

  • Open Access

    ARTICLE

    A Novel Dynamic Residual Self-Attention Transfer Adaptive Learning Fusion Approach for Brain Tumor Diagnosis

    Tawfeeq Shawly1, Ahmed A. Alsheikhy2,*

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4161-4179, 2025, DOI:10.32604/cmc.2025.061497 - 06 March 2025

    Abstract A healthy brain is vital to every person since the brain controls every movement and emotion. Sometimes, some brain cells grow unexpectedly to be uncontrollable and cancerous. These cancerous cells are called brain tumors. For diagnosed patients, their lives depend mainly on the early diagnosis of these tumors to provide suitable treatment plans. Nowadays, Physicians and radiologists rely on Magnetic Resonance Imaging (MRI) pictures for their clinical evaluations of brain tumors. These evaluations are time-consuming, expensive, and require expertise with high skills to provide an accurate diagnosis. Scholars and industrials have recently partnered to implement… More >

  • Open Access

    ARTICLE

    A Base Station Deployment Algorithm for Wireless Positioning Considering Dynamic Obstacles

    Aiguo Li1, Yunfei Jia2,*

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4573-4591, 2025, DOI:10.32604/cmc.2025.059184 - 06 March 2025

    Abstract In the context of security systems, adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel. Most studies focus on optimizing base station deployment under the assumption of static obstacles, aiming to maximize the perception coverage of wireless RF (Radio Frequency) signals and reduce positioning blind spots. However, in practical security systems, obstacles are subject to change, necessitating the consideration of base station deployment in dynamic environments. Nevertheless, research in this area still needs to be conducted. This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm (DIE-BDA)… More >

  • Open Access

    ARTICLE

    Real-Time Identity Authentication Scheme Based on Dynamic Credentials for Power AIGC System

    Feng Wei*, Zhao Chen, Yin Wang, Dongqing Liu, Xun Zhang, Zhao Zhou

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5325-5341, 2025, DOI:10.32604/cmc.2025.058802 - 06 March 2025

    Abstract The integration of artificial intelligence (AI) with advanced power technologies is transforming energy system management, particularly through real-time data monitoring and intelligent decision-making driven by Artificial Intelligence Generated Content (AIGC). However, the openness of power system channels and the resource-constrained nature of power sensors have led to new challenges for the secure transmission of power data and decision instructions. Although traditional public key cryptographic primitives can offer high security, the substantial key management and computational overhead associated with these primitives make them unsuitable for power systems. To ensure the real-time and security of power data… More >

  • Open Access

    ARTICLE

    Reactive Power Optimization Model of Active Distribution Network with New Energy and Electric Vehicles

    Chenxu Wang*, Jing Bian, Rui Yuan

    Energy Engineering, Vol.122, No.3, pp. 985-1003, 2025, DOI:10.32604/ee.2025.059559 - 07 March 2025

    Abstract Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load, a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed. Firstly, the k-medoids clustering algorithm is used to divide the reduced power scene into periods. Then, the discrete variables and continuous variables are optimized in the same period of time. Finally, the number of input groups of parallel capacitor banks (CB) in multiple periods is fixed, and then the secondary static reactive power optimization correction is carried out by… More >

  • Open Access

    ARTICLE

    Effect of Railway Spacing on Aerodynamic Performance of 600 km/h Maglev Trains Passing Each Other

    Bailong Sun1, Tian Li1,*, Deng Qin1, Yan Li2

    FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.2, pp. 371-385, 2025, DOI:10.32604/fdmp.2024.055519 - 06 March 2025

    Abstract High-speed maglev trains (HSMTs) can run at high running speeds due to their unique design. The pressure waves that these trains generate while passing each other are therefore very intense, and can even have safety implications. In order to reduce the transient impact of such waves, the standard k-ε turbulence model is used in this work to assess the effect of railway spacing on the aerodynamic loads, pressure and surrounding flow field of 600 km/h maglev trains passing each other in open air. The sliding mesh technique is used to determine the relative motion between the More >

  • Open Access

    REVIEW

    Smoothed Particle Hydrodynamics (SPH) Simulations of Drop Evaporation: A Comprehensive Overview of Methods and Applications

    Leonardo Di G. Sigalotti*, Carlos A. Vargas

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2281-2337, 2025, DOI:10.32604/cmes.2025.060497 - 03 March 2025

    Abstract The evaporation of micrometer and millimeter liquid drops, involving a liquid-to-vapor phase transition accompanied by mass and energy transfer through the liquid-vapor interface, is encountered in many natural and industrial processes as well as in numerous engineering applications. Therefore, understanding and predicting the dynamics of evaporating flows have become of primary importance. Recent efforts have been addressed using the method of Smoothed Particle Hydrodynamics (SPH), which has proven to be very efficient in correctly handling the intrinsic complexity introduced by the multiscale nature of the evaporation process. This paper aims to provide an overview of… More > Graphic Abstract

    Smoothed Particle Hydrodynamics (SPH) Simulations of Drop Evaporation: A Comprehensive Overview of Methods and Applications

  • Open Access

    ARTICLE

    Dibenzo [a, c] phenazin-11-yl(phenyl) methanone (SBLJ23), a novel selective inhibitor targeting JAK2V617F mutation in myeloproliferative neoplasms

    MOHAMMAD ABOHASSAN, MESFER MOHAMMAD AL SHAHRANI, SARAH KHALED ALOUDA, PRASANNA RAJAGOPALAN*

    Oncology Research, Vol.33, No.3, pp. 675-685, 2025, DOI:10.32604/or.2024.056256 - 28 February 2025

    Abstract Background: The JAK2V617F mutation plays a crucial part in the pathogenesis of myeloproliferative neoplasms (MPN), which includes polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF) leading to aberrant proliferation and survival of hematopoietic cells. Alongside the challenges of drug resistance and side effects, identifying novel compounds that selectively target JAK2V617F could provide more effective and safer therapeutic options for patients with MPNs. Materials and Methods: We employed computational approaches like high-throughput virtual screening, molecular dynamics simulations (MDS), and binding free energy calculations to identify inhibitors targeting wild and mutant JAK2 kinases. JAK2V617F positive HEL, wild… More >

  • Open Access

    ARTICLE

    Numerical Investigation of the Influence of a Magnetic Field on the Laminar Flow of a Yield-Stress Nanofluid over a Backward Facing Step

    Karim Amrani1,*, Eugenia Rossi di Schio2,*, Mohamed Bouzit3, Abderrahim Mokhefi1,4, Abdelkader Aris1, Cherif Belhout3, Paolo Valdiserri2

    Frontiers in Heat and Mass Transfer, Vol.23, No.1, pp. 185-206, 2025, DOI:10.32604/fhmt.2025.059833 - 26 February 2025

    Abstract The present study focuses on the flow of a yield-stress (Bingham) nanofluid, consisting of suspended Fe3O4 nanoparticles, subjected to a magnetic field in a backward-facing step duct (BFS) configuration. The duct is equipped with a cylindrical obstacle, where the lower wall is kept at a constant temperature. The yield-stress nanofluid enters this duct at a cold temperature with fully developed velocity. The aim of the present investigation is to explore the influence of flow velocity (Re = 10 to 200), nanoparticle concentration ( = 0 to 0.1), magnetic field intensity (Ha = 0 to 100), and… More >

  • Open Access

    ARTICLE

    Bayesian Stochastic INLA Application to the SIR-SI Model for Investigating Dengue Transmission Dynamics

    Mukhsar1,*, Andi Tenriawaru2, Gusti Ngurah Adhi Wibawa1, Bahriddin Abapihi1, Sitti Wirdhana Ahmad3, I Putu Sudayasa4

    Intelligent Automation & Soft Computing, Vol.40, pp. 177-193, 2025, DOI:10.32604/iasc.2025.058884 - 24 February 2025

    Abstract Despite extensive prevention efforts and research, dengue hemorrhagic fever (DHF) remains a major public health challenge, particularly in tropical regions, with significant social, economic, and health consequences. Statistical models are crucial in studying infectious DHF by providing a structured framework to analyze transmission dynamics between humans (hosts) and mosquitoes (vectors). Depending on the disease characteristics, different stochastic compartmental models can be employed. This research applies Bayesian Integrated Nested Laplace Approximation (INLA) to the SIR-SI model for DHF data. The method delivers accurate parameter estimates, improved computational efficiency, and effective integration with early warning systems. The… More >

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