Lei Han^1,*, Wanyu Ye¹, Chunfang Liu², Shihua Huang¹, Chun Chen³, Luxin Zhan³, Siyuan Liang³

Energy Engineering, Vol.122, No.12, pp. 4947-4969, 2025, DOI:10.32604/ee.2025.069040 - 27 November 2025

Abstract In contemporary medium-voltage distribution networks heavily penetrated by distributed energy resources (DERs), the harmonic components injected by power-electronic interfacing converters, together with the inherently intermittent output of renewable generation, distort the zero-sequence current and continuously reshape its frequency spectrum. As a result, single-line-to-ground (SLG) faults exhibit a pronounced, strongly non-stationary behaviour that varies with operating point, load mix and DER dispatch. Under such circumstances the performance of traditional rule-based algorithms—or methods that rely solely on steady-state frequency-domain indicators—degrades sharply, and they no longer satisfy the accuracy and universality required by practical protection systems. To overcome… More >

Kavita Bodke^1,*, Sunil Bhirud¹, Keshav Kashinath Sangle²

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1547-1562, 2025, DOI:10.32604/sdhm.2025.069239 - 17 November 2025

Abstract Structural Health Monitoring (SHM) systems play a key role in managing buildings and infrastructure by delivering vital insights into their strength and structural integrity. There is a need for more efficient techniques to detect defects, as traditional methods are often prone to human error, and this issue is also addressed through image processing (IP). In addition to IP, automated, accurate, and real- time detection of structural defects, such as cracks, corrosion, and material degradation that conventional inspection techniques may miss, is made possible by Artificial Intelligence (AI) technologies like Machine Learning (ML) and Deep Learning… More > Graphic Abstract

Yuan Mei^1,2, Daokui Li^1,2, Shiming Zhou^1,2,*, Zhibin Shen^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 153-187, 2025, DOI:10.32604/cmes.2025.070252 - 30 October 2025

Abstract Viscoelastic solids, such as composite propellants, exhibit significant time and rate dependencies, and their fracture processes display high levels of nonlinearity. However, the correlation between crack propagation and viscoelastic energy dissipation in these materials remains unclear. Therefore, accurately modeling and understanding of their fracture behavior is crucial for relevant engineering applications. This study proposes a novel viscoelastic phase-field model. In the numerical implementation, the adopted adaptive time-stepping iterative strategy effectively accelerates the coupling iteration efficiency between the phase-field and the displacement field. Moreover, all unknown parameters in the model, including the form of the phase-field More >

Hui Qi¹, Jingyi Lian², Congjun Rao^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 995-1028, 2025, DOI:10.32604/cmes.2025.069722 - 30 October 2025

Abstract For the past few years, the prevalence of cardiovascular disease has been showing a year-on-year increase, with a death rate of 2/5. Coronary heart disease (CHD) rates have increased 41% since 1990, which is the number one disease endangering human health in the world today. The risk indicators of CHD are complicated, so selecting effective methods to screen the risk characteristics can make the risk prediction more efficient. In this paper, we present a comprehensive analysis of CHD risk indicators from both data and algorithmic levels, propose a method for CHD risk indicator identification based… More >

Mubeen Sabir¹, Zeshan Aslam Khan^2,*, Muhammad Waqar², Khizer Mehmood¹, Muhammad Junaid Ali Asif Raja³, Naveed Ishtiaq Chaudhary⁴, Khalid Mehmood Cheema⁵, Muhammad Asif Zahoor Raja⁴, Muhammad Farhan Khan⁶, Syed Sohail Ahmed⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 807-855, 2025, DOI:10.32604/cmes.2025.068131 - 30 October 2025

Abstract Fingerprint classification is a biometric method for crime prevention. For the successful completion of various tasks, such as official attendance, banking transactions, and membership requirements, fingerprint classification methods require improvement in terms of accuracy, speed, and the interpretability of non-linear demographic features. Researchers have introduced several CNN-based fingerprint classification models with improved accuracy, but these models often lack effective feature extraction mechanisms and complex multineural architectures. In addition, existing literature primarily focuses on gender classification rather than accurately, efficiently, and confidently classifying hands and fingers through the interpretability of prominent features. This research seeks to… More >

Mujeebu Rehman¹, Qinghua Liu¹, Ali Ghulam², Tariq Ahmad³, Jawad Khan^4,*, Dildar Hussain^5,*, Yeong Hyeon Gu⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 779-805, 2025, DOI:10.32604/cmes.2025.067412 - 30 October 2025

Abstract Identifying druggable proteins, which are capable of binding therapeutic compounds, remains a critical and resource-intensive challenge in drug discovery. To address this, we propose CEL-IDP (Comparison of Ensemble Learning Methods for Identification of Druggable Proteins), a computational framework combining three feature extraction methods Dipeptide Deviation from Expected Mean (DDE), Enhanced Amino Acid Composition (EAAC), and Enhanced Grouped Amino Acid Composition (EGAAC) with ensemble learning strategies (Bagging, Boosting, Stacking) to classify druggable proteins from sequence data. DDE captures dipeptide frequency deviations, EAAC encodes positional amino acid information, and EGAAC groups residues by physicochemical properties to generate… More >

Mingxin Zhong^1,#, Yuanyuan Zhang^1,#, Xinlei Guo¹, Bainian Zhang², Chengjia Tan¹, Zhuo Xu¹, Xin Hu¹, Daren Feng³, Zhenpeng Xi⁴, Qian Wang^1,*, Hui Tian^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.10, pp. 3061-3084, 2025, DOI:10.32604/phyton.2025.070560 - 29 October 2025

Abstract Magnolia officinalis is a perennial deciduous tree that has medicinal properties. The AP2/ERF gene family has a number of roles in long-term growth and metabolism. The expression of this function varies with the growth period. In this work, based on the transcriptome data of Magnolia officinalis, the complete coding gene of Magnolia officinalis was obtained, and the corresponding protein sequence was retrieved from NCBI and compared with the model plant Arabidopsis thaliana. After screening, 75 protein sequences from the AP2/ERF gene family were identified and called MoAP2/ERF1–MoAP2/ERF75, followed by bioinformatics analysis. 75 AP2/ERF gene families were found and classified into four… More >

Abdil Hakan Eren^*

Phyton-International Journal of Experimental Botany, Vol.94, No.10, pp. 3085-3107, 2025, DOI:10.32604/phyton.2025.069506 - 29 October 2025

Abstract The FAR1-related sequence (FAR1) gene family consists of transcription factors that originated from transposases and is crucial for light signaling and stress adaptation in plants. Despite the recognized importance of FAR1 genes in model organisms, their genomic architecture, structural variability, and expression patterns in Phaseolus vulgaris have yet to be investigated. This study offers the inaugural comprehensive genome-wide identification and characterization of the FAR1 gene family in P. vulgaris. A total of 27 PvulFAR1 genes were identified, and their chromosomal distribution, gene structures, conserved domains, and phylogenetic relationships were analyzed systematically. The promoter regions of these genes were discovered… More >

Jinghua Yang¹, Bin Gong^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-2, 2025, DOI: 10.32604/icces.2025.011889

Abstract Geological stratification interpretation divides geological strata based on acquired well-logging data, providing comparative analysis results for strata and structures. This process serves as a fundamental framework for subsequent drilling and development design plans, making it a crucial step in oil exploration and development process. Traditional geological stratification interpretation methods are based primarily on geological, logging, and experimental data, with manual determination of strata boundaries to obtain interpretation results. However, manual interpretation is characterized by strong subjectivity and reliance on experience, which may compromise the quality and consistency of the results. To eliminate the dependency on… More >

Long Zhao^1,*, Qi Zhao¹, Siyuan Zhou¹, Chenyang Fan², Chao Ji¹

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1455-1475, 2025, DOI:10.32604/fhmt.2025.069512 - 31 October 2025

Abstract The temperature prediction of the Clamp-conductor coupling zone plays a crucial role in ensuring the safe and stable operation of overhead transmission lines and optimizing the thermal stability margin of transmission lines. While existing research in this field has thoroughly explored temperature rise prediction, the focus has been relatively narrow, either targeting conductors exclusively or focusing solely on clamps, with little attention given to the temperature rise in the conductor-clamp coupling zone or the influence of clamp temperature on conductor temperature rise. Based on this, considering axial heat transfer between the clamp and the conductor,… More >