Expiratory ventilation assistance versus pressure-controlled ventilation with ambient oxygen in a hemorrhagic trauma model: a prehospital rescue option? by Tomas Karlsson, Jenny Gustavsson, Katrin Wellfelt, Mattias Günther

“…Conclusion Both EVA and PCV effectively maintained oxygen delivery and sufficient oxygenation after trauma hemorrhage and whole blood resuscitation. Lower intratracheal pressures and reduced lactate accumulation with EVA suggest it may be a viable prehospital rescue method, especially in scenarios with limited oxygen supply. …”
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Frequency-Decoupled Dual-Stage Inverse Lithography Optimization via Hierarchical Sampling and Morphological Enhancement by Jie Zhou, Qingyan Zhang, Haifeng Sun, Chuan Jin, Ji Zhou, Junbo Liu

“…However, traditional gradient-based ILT methods often struggle with the trade-off between imaging fidelity and mask manufacturability due to coupled optimization objectives. …”
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Optimal Controller Design for a Mobile Robot Using Genetic Algorithm and Adaptive PID Controller by Jin-Hyun Park

“…Simulation results show that the kinematic controller generates optimal trajectories more effectively than traditional techniques, while the adaptive PID controller maintains optimal performance despite disturbances and mass variations. …”
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Optimizing Acidic Reductive Leaching for Lithium Recovery: Enhancing Sustainable Lithium Supply for Energy Markets by Agnieszka Sobianowska-Turek, Amelia Zielińska, Weronika Urbańska, Anna Mielniczek, Agnieszka Fornalczyk, Szymon Pawlak, Tomasz Małysa, Janusz Cebulski

“…The growing demand for lithium, driven by its crucial role in energy storage technologies such as lithium-ion batteries for electric vehicles, renewable energy storage, and portable electronics, is intensifying the need for sustainable extraction methods. While lithium is sourced from both primary and secondary resources, particularly from recycled materials, the recovery from spent lithium-ion batteries remains challenging. …”
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A novel research on network security situation prediction based on iteratively optimized RBF-NN by Yuqin Wu, Congqi Shen, Shungen Xiao, Wei Feng, Yexian Fan, Xiuzhuang Zhou

“…In this paper, we propose a novel iterative optimized RBF-NN method for NSS prediction. Our proposed method leverages a resource allocation network (RAN) to dynamically determine the optimal number of neurons in the hidden layer, ensuring a balance between model complexity and prediction accuracy. …”
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Morphing and control of airfoils for optimum lift-to-drag ratio using shape-memory alloy with particle swarm optimization of PARSEC parameters by Raed Bourisli, Nesrin Ibrahim, Mohammed Alajmi

“…Airfoils are parameterized using the PARSEC method and optimized using particle swarm optimization (PSO), with CFD evaluations conducted in COMSOL. …”
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Fast and Accurate Direct Position Estimation Using Low-Complexity Correlation and Swarm Intelligence Optimization by Yuze Duan, Zuping Tang, Jiaolong Wei, Jie Sun, Kaixian Ying

“…Furthermore, an adaptive Dung Beetle Optimization (ADBO) algorithm is developed. By leveraging insights from fitness landscape analysis, the ADBO algorithm dynamically adjusts subpopulation proportions and the convergence factor while incorporating hybrid mutation strategies for effective adaptation to various types of optimization problems. …”
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QELPS Algorithm: A Novel Dynamic Optimization Technology for Quantum Circuits Scheduling Engineering Problems by Zuoqiang Du, Xingjie Li, Hui Li

“…This approach effectively reduces quantum gate conflicts found in traditional methods and optimizes execution order, leading to better computational efficiency and circuit performance. …”
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Multimodal representative answer extraction in community question answering by Ming Li, Yating Ma, Ying Li, Yixue Bai

“…The improved Beluga whale optimization algorithm (MTRL-BWO), based on tent mapping, reinforcement learning, and multiple swarm strategy, is designed to increase the diversity of the population while avoiding local optima to improve the search capability and solution accuracy of the algorithm. …”
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A seismic random noise suppression method based on CNN-Mamba by Xiujuan WEI, Xingye LIU, Huailai ZHOU

“…However, mainstream random noise intelligent methods based on convolutional neural networks (CNNs) are constrained by their local receptive fields. …”
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Interpretability-Oriented Adjustment of K-Means: A Multiple-Objective Particle Swarm Optimization Framework by Liang Chen, Leming Sun, Caiming Zhong

“…While numerous methods in the literature attempt to explain clustering results, the explanation rules provided by these models are fixed and sacrificing clustering quality for the sake of making the rules easier to understand. …”
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Advanced Noise Reduction for In-Cylinder Combustion Pressure Data Using ICEEMDAN and Optimal Wavelet Selection by Van-Trung Nguyen, Minh-Tien Nguyen

“…Results consistently demonstrate superior denoising performance across various metrics compared to traditional infinite impulse response (IIR) filters, empirical mode decomposition (EMD) and conventional ICEEMDAN-wavelet methods. By dynamically adapting wavelet selection and decomposition levels to varying signal and noise characteristics, this method achieves optimal noise suppression with high signal fidelity. …”
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Energy-Based Optimal Ranking of the Interior Modes for Reduced-Order Models under Periodic Excitation by Ilaria Palomba, Dario Richiedei, Alberto Trevisani

“…The aim of the method is to provide an effective ranking of such modes and hence an optimal sequence according to which the interior modes should be progressively included to achieve a desired accuracy of the reduced-order model at the frequencies of interest, while keeping model dimensions to a minimum. …”
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The RBF-FDTD Method for Computing Lightning-Transient Voltages on Grounding Systems by Xuan-Binh Nguyen, Nhat-Nam Nguyen, Tinh-Minh T. Le, Phan-Tu Vu

“…This study not only confirms the method’s superiority in modeling intricate grounding responses but also offers critical insights for enhancing the design and optimization of grounding systems under lightning and fast-transient conditions.…”
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Method for designing specialized computing systems on the basis of hardware and software cooptimization by I. E. Tarasov, P. N. Sovietov, D. V. Lulyava, N. A. Duksin

“…Pipelining is an effective method for increasing the clock frequency of digital circuits. …”
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Combined Scheduling and Configuration Optimization of Power-to-Methanol System Considering Feedback Control of Thermal Power by Junjie Ye, Yinghui Liu, Li Sun, Ke Chen

“…Most of the traditional methods for the optimal configuration of IES use the steady-state model of the equipment, while ignoring the dynamic deviation of the thermal power unit under variable operating conditions. …”
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Multi-Agent Deep Reinforcement Learning for Scheduling of Energy Storage System in Microgrids by Sang-Woo Jung, Yoon-Young An, BeomKyu Suh, YongBeom Park, Jian Kim, Ki-Il Kim

“…The comparative evaluations against baseline DRL algorithms (TD3, SAC, PPO) demonstrate that the proposed MAPPO method significantly reduces electricity costs while minimizing battery-switching events. …”
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Building Change Detection Network Based on Multilevel Geometric Representation Optimization Using Frame Fields by Fachuan He, Hao Chen, Shuting Yang, Zhixiang Guo

“…To address the challenges of accurately segmenting irregular building boundaries in complex urban environments faced by existing remote sensing change detection methods, this paper proposes a building change detection network based on multilevel geometric representation optimization using frame fields called BuildingCDNet. …”
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A Multi-Objective PSO-GWO Approach for Smart Grid Reconfiguration with Renewable Energy and Electric Vehicles by Tung Linh Nguyen, Quynh Anh Nguyen

“…While the Particle Swarm Optimization algorithm is renowned for its rapid convergence and effective exploitation of solution spaces, its capacity to thoroughly explore complex search domains remains limited, particularly in multifaceted optimization challenges. …”
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Support Vector Regression-Based Optimization for Triple Friction Pendulum Bearings: Achieving Computational Efficiency by Mahnaz Akbarzaghi, Behrooz Ahmadi Nedushan, Hamed Tajammolian

“…Additionally, no single kernel function consistently outperforms others across all optimization problems within the SVR method. In this study, the Gaussian kernel yielded superior results for the peak floor acceleration objective, while the Matérn 5/2 kernel provided better performance for the inter-story drift objective. …”
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