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  • Open Access

    ARTICLE

    Energy Optimization Strategy for Reconfigurable Distribution Network with High Renewable Penetration Based on Bald Eagle Search Algorithm

    Jian Wang, Hui Qi, Lingyi Ji*, Zhengya Tang, Hui Qian

    Energy Engineering, Vol.122, No.11, pp. 4635-4651, 2025, DOI:10.32604/ee.2025.068667 - 27 October 2025

    Abstract This paper proposes a cost-optimal energy management strategy for reconfigurable distribution networks with high penetration of renewable generation. The proposed strategy accounts for renewable generation costs, maintenance and operating expenses of energy storage systems, diesel generator operational costs, typical daily load profiles, and power balance constraints. A penalty term for power backflow is incorporated into the objective function to discourage undesirable reverse flows. The Bald Eagle Search (BES) meta-heuristic is adopted to solve the resulting constrained optimization problem. Numerical simulations under multiple load scenarios demonstrate that the proposed method effectively reduces operating cost while preventing More >

  • Open Access

    ARTICLE

    Equivalent Design Methodology for Ship-Stiffened Steel Plates under Ogival-Nosed Projectile Penetration

    Yezhi Qin*, Qinglin Chen*, Ying Wang, Yingqiang Cai

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1883-1906, 2025, DOI:10.32604/cmes.2025.066844 - 31 August 2025

    Abstract The penetration of ogival-nosed projectiles into ship plates represents a complex impact dynamics issue essential for analyzing structural failure mechanisms. Although stiffened plates are vital in ship construction, few studies have addressed the issue of model equivalence under penetration loading. This study employs numerical simulation to validate an experiment with an ogival-nosed projectile penetrating a Q345 steel plate. Four equivalent stiffened plate methods are proposed based on the area, flexural modulus, moment of inertia, and thickness. The results indicate that thickness equivalence (DM4) is unsuitable for penetration-loaded stiffened plates, except under low-speed, non-penetrating through impacts, More >

  • Open Access

    ARTICLE

    Human-Derived Low-Molecular-Weight Protamine (hLMWP) Conjugates Enhance Skin Cell Penetration and Physiological Activity

    Seo Yeon Shin1, Nu Ri Song1, Sa Rang Choi1, Ki Min Kim1, Jae Hee Byun1, Su Jung Kim2, Dai Hyun Jung2, Seong Sim Kim2, Seong Ju Park2, So Jeong Chu2, Kyung Mok Park1,*

    BIOCELL, Vol.49, No.8, pp. 1435-1448, 2025, DOI:10.32604/biocell.2025.065199 - 29 August 2025

    Abstract Background: The efficient transdermal delivery of biologically active molecules remains a major challenge because of the structural barrier of the stratum corneum, which limits the penetration of large or hydrophilic molecules. Low-molecular-weight protamine (LMWP) has a structure similar to that of the HIV TAT protein-derived peptide and is a representative cell-penetrating peptide (CPP) used to increase cell permeability. However, protamine has been reported to have many toxicities and side effects. Objectives: We developed human-derived low-molecular-weight protamine (hLMWP), which is based on fish-derived LMWP but designed using human protein sequences to improve safety and functionality. As… More > Graphic Abstract

    Human-Derived Low-Molecular-Weight Protamine (hLMWP) Conjugates Enhance Skin Cell Penetration and Physiological Activity

  • Open Access

    ARTICLE

    Random Forest and Order Parameters: A Combined Framework for Scenario Recognition for Power Systems with Renewable Penetration

    Xiaolong Xiao1, Xiaoxing Lu1,*, Ziran Guo1, Jian Liu1, Shenglong Wu2, Ye Cai2

    Energy Engineering, Vol.122, No.8, pp. 3117-3132, 2025, DOI:10.32604/ee.2025.065631 - 24 July 2025

    Abstract With the popularization of microgrid construction and the connection of renewable energy sources to the power system, the problem of source and load uncertainty faced by the coordinated operation of multi-microgrid is becoming increasingly prominent, and the accuracy of typical scenario predictions is low. In order to improve the accuracy of scenario prediction under source and load uncertainty, this paper proposes a typical scenario identification model based on random forests and order parameters. Firstly, a method for ordinal parameter identification and quantification is provided for the coordinated operating mode of multi-microgrids, taking into account source-load… More >

  • Open Access

    ARTICLE

    Short-Term Penetration beyond Diffusion Spinodal of a Mixture: Interaction of Liquid-Liquid and Liquid-Vapour Transitions

    Alexey Melkikh1,2, Sergey Rutin2, Dmitrii V. Antonov3, Pavel Skripov2,*

    Frontiers in Heat and Mass Transfer, Vol.23, No.3, pp. 721-737, 2025, DOI:10.32604/fhmt.2025.066528 - 30 June 2025

    Abstract The article considers a relaxation of the water/polypropylene glycol-425 solution with a lower critical solution temperature (LCST) following its pulsed superheating concerning liquid-liquid and liquid-vapor equilibrium lines, as well as the liquid-liquid spinodal. Superheating was performed using the pulsed heat generation method in a micro-sized wire probe. The main heating mode was the constant (over the pulse length) power mode. Characteristic heating rates ranged from 0.05 × 105 to 2 × 105 K/s, while the degree of superheating concerning the spinodal was up to 200 K. The temperature of spontaneous boiling-up and the amplitude of the… More > Graphic Abstract

    Short-Term Penetration beyond Diffusion Spinodal of a Mixture: Interaction of Liquid-Liquid and Liquid-Vapour Transitions

  • Open Access

    ARTICLE

    Utilizing Fine-Tuning of Large Language Models for Generating Synthetic Payloads: Enhancing Web Application Cybersecurity through Innovative Penetration Testing Techniques

    Stefan Ćirković1, Vladimir Mladenović1, Siniša Tomić2, Dalibor Drljača2, Olga Ristić1,*

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4409-4430, 2025, DOI:10.32604/cmc.2025.059696 - 06 March 2025

    Abstract With the increasing use of web applications, challenges in the field of cybersecurity are becoming more complex. This paper explores the application of fine-tuned large language models (LLMs) for the automatic generation of synthetic attacks, including XSS (Cross-Site Scripting), SQL Injections, and Command Injections. A web application has been developed that allows penetration testers to quickly generate high-quality payloads without the need for in-depth knowledge of artificial intelligence. The fine-tuned language model demonstrates the capability to produce synthetic payloads that closely resemble real-world attacks. This approach not only improves the model’s precision and dependability but… More >

  • Open Access

    PROCEEDINGS

    Fragment Penetration Damage Characteristics of Typical Composite Armor

    Yuan Li1,3,*, Zhiqiang Fan1,2, Tao Suo1,3

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.013336

    Abstract Light armored vehicles, as the primary means of force transport on contemporary battlefields, require not only high mobility but also better protection to meet the complex battlefield environment and mission requirements. Composite armor is widely used in the design of light armored vehicles due to its lightweight and excellent defensible performance. In this paper, the damage law of the composite armor of an infantry fighting vehicle, when penetrated by fragment-simulated projectiles (FSP), is studied by numerical simulation, and the homogeneous equivalent targets surrogating a combination of local protective armor and vulnerable parts are constructed based More >

  • Open Access

    ARTICLE

    Tree-Based Solution Frameworks for Predicting Tunnel Boring Machine Performance Using Rock Mass and Material Properties

    Danial Jahed Armaghani1,*, Zida Liu2, Hadi Khabbaz1, Hadi Fattahi3, Diyuan Li2, Mohammad Afrazi4

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2421-2451, 2024, DOI:10.32604/cmes.2024.052210 - 31 October 2024

    Abstract Tunnel Boring Machines (TBMs) are vital for tunnel and underground construction due to their high safety and efficiency. Accurately predicting TBM operational parameters based on the surrounding environment is crucial for planning schedules and managing costs. This study investigates the effectiveness of tree-based machine learning models, including Random Forest, Extremely Randomized Trees, Adaptive Boosting Machine, Gradient Boosting Machine, Extreme Gradient Boosting Machine (XGBoost), Light Gradient Boosting Machine, and CatBoost, in predicting the Penetration Rate (PR) of TBMs by considering rock mass and material characteristics. These techniques are able to provide a good relationship between input(s)… More >

  • Open Access

    PROCEEDINGS

    Influence of Syringe Needle Configuration on Micro Particle Generation During Penetration

    Tingting Zhu1, Pei Lian1, Wenxuan Du2,3, Chenxu Zhang2,3, Yinggang Miao2,3, Haiying Wang1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.011281

    Abstract Penetration of syringe needles into the rubber plug of vials occurs daily in usual medical operation, but in nature, it is a complex mechanical process concerning the deformation, friction and failure of materials. Micro particles could be generated during the fracture process of plug and needle friction during penetration. Actually, the structural configuration of needle pin plays an important role besides of plug itself. In this work, mechanical behaviors of butyl rubber and needle material are obtained firstly, after performing various strain rate experiments based on Instron 5848 machine and Hopkinson bar technique. And their… More >

  • Open Access

    ARTICLE

    Efficient Penetration Testing Path Planning Based on Reinforcement Learning with Episodic Memory

    Ziqiao Zhou1, Tianyang Zhou1,*, Jinghao Xu2, Junhu Zhu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2613-2634, 2024, DOI:10.32604/cmes.2023.028553 - 08 July 2024

    Abstract Intelligent penetration testing is of great significance for the improvement of the security of information systems, and the critical issue is the planning of penetration test paths. In view of the difficulty for attackers to obtain complete network information in realistic network scenarios, Reinforcement Learning (RL) is a promising solution to discover the optimal penetration path under incomplete information about the target network. Existing RL-based methods are challenged by the sizeable discrete action space, which leads to difficulties in the convergence. Moreover, most methods still rely on experts’ knowledge. To address these issues, this paper… More >

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