Hao Yue¹, Di Gao², Jin Gao¹, Chengmei Wei¹, Jiali Duan³, Shaocheng Mei^3,*

Energy Engineering, Vol.122, No.12, pp. 5091-5109, 2025, DOI:10.32604/ee.2025.069140 - 27 November 2025

Abstract Against the backdrop of regional coordinated development and China’s “dual carbon” strategic objectives, the Beijing-Tianjin-Hebei (BTH) region faces an urgent need to transition from its traditional economic growth model, which is heavily reliant on resource consumption. This study investigates the decoupling dynamics among economic growth, energy consumption, and carbon emissions in the BTH region, along with the underlying driving forces, aiming to provide valuable insights for achieving the “dual carbon” targets and fostering high-quality regional development. First, the Tapio decoupling model is employed to analyze the decoupling relationships between economic growth, energy consumption, and carbon… More >

Kangjie Li, Wenjing Ye^*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1665-1688, 2025, DOI:10.32604/cmes.2025.072447 - 26 November 2025

Abstract Recent progress in topology optimization (TO) has seen a growing integration of machine learning to accelerate computation. Among these, online learning stands out as a promising strategy for large-scale TO tasks, as it eliminates the need for pre-collected training datasets by updating surrogate models dynamically using intermediate optimization data. Stress-constrained lightweight design is an important class of problem with broad engineering relevance. Most existing frameworks use pixel or voxel-based representations and employ the finite element method (FEM) for analysis. The limited continuity across finite elements often compromises the accuracy of stress evaluation. To overcome this… More >

Xinjian Li¹, Yu Zhang^1,2,*, Zewen Wang¹, Zhenyun Song¹

Energy Engineering, Vol.122, No.11, pp. 4603-4619, 2025, DOI:10.32604/ee.2025.065799 - 27 October 2025

Abstract Power prediction has been critical in large-scale wind power grid connections. However, traditional wind power prediction methods have long suffered from problems, for instance low prediction accuracy and poor reliability. For this purpose, a hybrid prediction model (VMD-LSTM-Attention) has been proposed, which integrates the variational modal decomposition (VMD), the long short-term memory (LSTM), and the attention mechanism (Attention), and has been optimized by improved dung beetle optimization algorithm (IDBO). Firstly, the algorithm’s performance has been significantly enhanced through the implementation of three key strategies, namely the elite group strategy of the Logistic-Tent map, the nonlinear… More >

Thomas Hanne^1,*, Mohammad Jahani Moghaddam²

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4203-4236, 2025, DOI:10.32604/cmc.2025.068087 - 23 October 2025

Abstract Multi-Objective Evolutionary Algorithms (MOEAs) have significantly advanced the domain of Multi-Objective Optimization (MOO), facilitating solutions for complex problems with multiple conflicting objectives. This review explores the historical development of MOEAs, beginning with foundational concepts in multi-objective optimization, basic types of MOEAs, and the evolution of Pareto-based selection and niching methods. Further advancements, including decom-position-based approaches and hybrid algorithms, are discussed. Applications are analyzed in established domains such as engineering and economics, as well as in emerging fields like advanced analytics and machine learning. The significance of MOEAs in addressing real-world problems is emphasized, highlighting their More >

Oswaldo González-Gaxiola¹, Yakup Yildirim^2,3,4, Luminita Moraru^5,6, Anjan Biswas^7,8,9,10,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.9, pp. 2273-2287, 2025, DOI:10.32604/fdmp.2025.067959 - 30 September 2025

Abstract This study presents a numerical investigation of shallow water wave dynamics with particular emphasis on the role of surface tension. In the absence of surface tension, shallow water waves are primarily driven by gravity and are well described by the classical Boussinesq equation, which incorporates fourth-order dispersion. Under this framework, solitary and shock waves arise through the balance of nonlinearity and gravity-induced dispersion, producing waveforms whose propagation speed, amplitude, and width depend largely on depth and initial disturbance. The resulting dynamics are comparatively smoother, with solitary waves maintaining coherent structures and shock waves displaying gradual… More > Graphic Abstract

Qi Chen^1,2, Yizhuo Du¹, Yingsheng Liu¹, Yue Li¹, Chuang Li¹, Zhelun Xu^1,3, Congyan Wang^1,4,5,*

Phyton-International Journal of Experimental Botany, Vol.94, No.9, pp. 2873-2891, 2025, DOI:10.32604/phyton.2025.065970 - 30 September 2025

Abstract The leaves of multiple invasive plants can coexist and intermingle within the same environment. As species number of invasive plants increases, variations may occur in decomposition processes of invasive plants, soil nutrient contents, soil enzyme activities, and soil microbial community structure. Existing progress have predominantly focused on the ecological effects of one species of invasive plant compared to native species, with limited attention paid to the ecological effects of multiple invasive plants compared to one species of invasive plant. This study aimed to determine the differences in the effects of mono- and co-decomposition of four… More >

Shih-Lin Lin^*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1365-1382, 2025, DOI:10.32604/cmc.2025.067764 - 29 August 2025

Abstract This paper proposes an integrated multi-stage framework to enhance frequency modulated continuous wave (FMCW) automotive radar performance under high noise and interference. The four-stage pipeline is applied consecutively: (i) an improved independent component analysis (ICA) blindly separates the two-channel echoes, isolating target and interference components; (ii) a recursive least-squares (RLS) filter compensates amplitude- and phase-mismatches, restoring signal fidelity; (iii) variational mode decomposition (VMD) followed by the Hilbert-Huang Transform (HHT) extracts noise-free intrinsic mode functions (IMFs) and sharpens their time-frequency signatures; and (iv) HHT-based beat-frequency estimation reconstructs a clean echo and delivers accurate range information. Finally, More >

Muhammad Osama¹, Sarwar Shah Khan^2,*, Sajid Khan², Muzammil Khan³, Mian Muhammad Danyal⁴, Reshma Khan¹

Digital Engineering and Digital Twin, Vol.3, pp. 17-34, 2025, DOI:10.32604/dedt.2025.066344 - 19 August 2025

Abstract Image fusion is a technique used to combine essential information from two or more source images into a single, more informative output image. The resulting fused image contains more meaningful details than any individual source image. This study focuses on multi-focus image fusion, a crucial area in image processing. Due to the limited depth of field of optical lenses, it is often challenging to capture an image where all areas are in focus simultaneously. As a result, multi-focus image fusion plays a key role in integrating and extracting the necessary details from different focal regions.… More >

Isra Mohammed¹, Mohamed Elhafiz M. Musa², Murtada K. Elbashir^3,*, Ayman Mohamed Mostafa³, Amin Ibrahim Adam⁴, Mahmood A. Mahmood³, Areeg S. Faggad⁵

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3749-3763, 2025, DOI:10.32604/cmc.2025.063880 - 03 July 2025

Abstract Sonic Hedgehog Medulloblastoma (SHH-MB) is one of the four primary molecular subgroups of Medulloblastoma. It is estimated to be responsible for nearly one-third of all MB cases. Using transcriptomic and DNA methylation profiling techniques, new developments in this field determined four molecular subtypes for SHH-MB. SHH-MB subtypes show distinct DNA methylation patterns that allow their discrimination from overlapping subtypes and predict clinical outcomes. Class overlapping occurs when two or more classes share common features, making it difficult to distinguish them as separate. Using the DNA methylation dataset, a novel classification technique is presented to address… More >

Guangfei Jia^*, Jinqiu Yang, Hanwen Liang

Structural Durability & Health Monitoring, Vol.19, No.4, pp. 1057-1072, 2025, DOI:10.32604/sdhm.2025.061805 - 30 June 2025

Abstract Considering the noise problem of the acquisition signals from mechanical transmission systems, a novel denoising method is proposed that combines Variational Mode Decomposition (VMD) with wavelet thresholding. The key innovation of this method lies in the optimization of VMD parameters K and using the improved Horned Lizard Optimization Algorithm (IHLOA). An inertia weight parameter is introduced into the random walk strategy of HLOA, and the related formula is improved. The acquisition signal can be adaptively decomposed into some Intrinsic Mode Functions (IMFs), and the high-noise IMFs are identified based on a correlation coefficient-variance method. Further noise… More > Graphic Abstract