Siti Ramadhani^1,2, Lestari Handayani², Theam Foo Ng³, Sumayyah Dzulkifly¹, Roziana Ariffin^4,5, Haldi Budiman⁶, Shir Li Wang^1,7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 2711-2765, 2025, DOI:10.32604/cmes.2025.062709 - 30 June 2025

Abstract In recent years, feature selection (FS) optimization of high-dimensional gene expression data has become one of the most promising approaches for cancer prediction and classification. This work reviews FS and classification methods that utilize evolutionary algorithms (EAs) for gene expression profiles in cancer or medical applications based on research motivations, challenges, and recommendations. Relevant studies were retrieved from four major academic databases–IEEE, Scopus, Springer, and ScienceDirect–using the keywords ‘cancer classification’, ‘optimization’, ‘FS’, and ‘gene expression profile’. A total of 67 papers were finally selected with key advancements identified as follows: (1) The majority of papers… More > Graphic Abstract

Mohammed Moawad Alenazi^*

Journal on Artificial Intelligence, Vol.7, pp. 143-176, 2025, DOI:10.32604/jai.2025.066067 - 27 June 2025

Abstract This paper presents a novel machine learning (ML) enhanced energy management framework for residential microgrids. It dynamically integrates solar photovoltaics (PV), wind turbines, lithium-ion battery energy storage systems (BESS), and bidirectional electric vehicle (EV) charging. The proposed architecture addresses the limitations of traditional rule-based controls by incorporating ConvLSTM for real-time forecasting, a Twin Delayed Deep Deterministic Policy Gradient (TD3) reinforcement learning agent for optimal BESS scheduling, and federated learning for EV charging prediction—ensuring both privacy and efficiency. Simulated in a high-fidelity MATLAB/Simulink environment, the system achieves 98.7% solar/wind forecast accuracy and 98.2% Maximum Power Point… More >

Nurlan Zhangabay^1,*, Ulanbator Suleimenov¹, Marco Bonopera^2,*, Ulzhan Ibraimova¹, Shairbek Yeshimbetov³

Structural Durability & Health Monitoring, Vol.19, No.4, pp. 773-787, 2025, DOI:10.32604/sdhm.2025.064980 - 30 June 2025

Abstract This research presents a numerical simulation methodology for optimizing circular composite overlays’ dimensions and pressure characteristics with orthotropic mechanical properties, specifically, for metal conduits with temperature-dependent elastoplastic behavior. The primary objective of the proposed method is to prevent crack propagation during pressure surges from operational to critical levels. This study examines the “Beineu-Bozoy-Shymkent” steel gas conduit, examining its performance across a temperature range of −40 to +50°C. This work builds on prior research on extended avalanche destruction in steel gas conduits and crack propagation prevention techniques. The analysis was conducted using a dynamic finite-element approach… More >

Sergio Cassese¹, Riccardo Guida^2,3,*, Daniele Trincone¹, Stefano Mungiguerra¹, Raffaele Savino¹

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.6, pp. 1299-1337, 2025, DOI:10.32604/fdmp.2025.065605 - 30 June 2025

Abstract Robust numerical tools are essential for enabling the use of hybrid rocket engines (HREs) in future space applications. In this context, Computational Fluid Dynamics (CFD) transient simulations can be employed to analyse and predict relevant fluid dynamics phenomena within the thrust chamber of small-scale HREs. This work applies such techniques to investigate two unexpected behaviours observed in a 10 N-class hydrogen peroxide-based hybrid thruster: an uneven regression rate during High-Density Polyethylene (HDPE) and Acrylonitrile Butadiene Styrene (ABS) fuel tests, and non-negligible axial consumption in the ABS test case. The present study seeks to identify their… More >

Shourui Wang, Yibo Wang^*, Kun Yang, Yu Li, Xin Su

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.6, pp. 1439-1457, 2025, DOI:10.32604/fdmp.2025.062295 - 30 June 2025

Abstract Hydrocolloids are widely used in meat products and pureed foods as they offer thickening and viscosity-enhancing effects that facilitate shaping and improve stability. In this study, the static shear rheological and dynamic viscoelastic properties of pumpkin puree (S) and pork mince (P) with the addition of various hydrocolloids were considered. Dedicated material printing experiments were conducted by means of a three-dimensional printing platform by using a coaxial dual-nozzle for sandwich composite printing of four different materials. In particular, the impact of different process parameters (printing speed 10~30 mm/s, filling density 10%~50%) was assessed in terms… More >

Basima Salman Khalaf^*, Abeer H. Falih, Basim Freegah

Frontiers in Heat and Mass Transfer, Vol.23, No.3, pp. 943-956, 2025, DOI:10.32604/fhmt.2025.065366 - 30 June 2025

Abstract The main purpose of this research is to optimize the hydrothermal performance of a dimpled tube by augmenting the surface area for heat transmission and thermal layer cracking. To achieve that, the impact of different dimple diameters and their distribution along the dimpled tube was investigated numerically using the ANSYS Fluent 2022 R1 software by considering two models, A and B. Both models consist of three regions; the first, second, and third have dimple diameters of 3, 2, & 1 mm, respectively. Model A included an in-line dimple arrangement, while model B involved a staggered… More >

Yinguo Yang¹, Lifu Ding^2,*, Yang Liu¹, Bingchen Wang², Weihua Wang¹, Ying Chen²

Energy Engineering, Vol.122, No.7, pp. 2571-2587, 2025, DOI:10.32604/ee.2025.065716 - 27 June 2025

Abstract This paper addresses the complexity of wake control in large-scale wind farms by proposing a partitioning control algorithm utilizing the FLORIDyn (FLOW Redirection and Induction Dynamics) dynamic wake model. First, the impact of wakes on turbine effective wind speed is analyzed, leading to a quantitative method for assessing wake interactions. Based on these interactions, a partitioning method divides the wind farm into smaller, computationally manageable zones. Subsequently, a heuristic control algorithm is developed for yaw optimization within each partition, reducing the overall computational burden associated with multi-turbine optimization. The algorithm’s effectiveness is evaluated through case More >

Chun Xiao^1,2,*

Energy Engineering, Vol.122, No.7, pp. 2719-2750, 2025, DOI:10.32604/ee.2025.063782 - 27 June 2025

Abstract In contemporary power systems, delving into the flexible regulation potential of demand-side resources is of paramount significance for the efficient operation of power grids. This research puts forward an innovative multivariate flexible load aggregation control approach that takes dynamic demand response into full consideration. In the initial stage, using generalized time-domain aggregation modelling for a wide array of heterogeneous flexible loads, including temperature-controlled loads, electric vehicles, and energy storage devices, a novel calculation method for their maximum adjustable capacities is devised. Distinct from conventional methods, this newly developed approach enables more precise and adaptable quantification… More >

Salim Lachkar^*, Ahmed Ibrahimi, Imad Boualaoui, Hachem El Sayegh, Yassine Nouini

Canadian Journal of Urology, Vol.32, No.3, pp. 145-165, 2025, DOI:10.32604/cju.2025.064912 - 27 June 2025

Abstract Introduction: When conservative treatments fail, botulinum toxin A (BoNT-A) is an option for refractory idiopathic overactive bladder (OAB). This review evaluates the efficacy, safety, and predictive factors for BoNT-A in this situation. Material and Methods: A literature search up to January 2025 was performed using PubMed, Google Scholar, and Embase to assess efficacy, safety, and predictors of adverse events (AE) related to BoNT-A. The risk of bias was assessed using the Risk of Bias 2 (RoB 2) tool for randomized studies and the Critical Appraisal Skills Programme (CASP) checklist for cohort studies. The quality of the… More >

Xiaoguang Lv^1,2, Tao Liu^1,2,*, Han Qin^1,2, Ying Guo^1,2, Jingshan Pan^1,2, Dawei Zhao^1,2, Xiaoming Wu^1,2, Meihong Yang^1,2

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1417-1436, 2025, DOI:10.32604/cmc.2025.063852 - 09 June 2025

Abstract The Dynamical Density Functional Theory (DDFT) algorithm, derived by associating classical Density Functional Theory (DFT) with the fundamental Smoluchowski dynamical equation, describes the evolution of inhomogeneous fluid density distributions over time. It plays a significant role in studying the evolution of density distributions over time in inhomogeneous systems. The Sunway Bluelight II supercomputer, as a new generation of China’s developed supercomputer, possesses powerful computational capabilities. Porting and optimizing industrial software on this platform holds significant importance. For the optimization of the DDFT algorithm, based on the Sunway Bluelight II supercomputer and the unique hardware architecture… More >