AGC of a Multi‐Area Hydrothermal Interconnected Diverse Deregulated Power System Using a Proposed Novel SBOA‐Multi‐Level Fuzzy Logic‐Tilt Controller Incorporated With IPFC by Getaneh Mesfin Meseret, Nishant Kumar, Tarkesh Kumar Mahato, Rajesh Kumhar, Poonam Lakra, M. D. Mofeed Alam

“…Nonlinearities have been included in the system for a more realistic approach. The integration of the IPFC improves system performance, and the effectiveness and reliability of the SBOA‐MLF‐TD‐TI method are validated through sensitivity analysis, considering simultaneous variations in the DISCO Participation Matrix (DPM) values.…”
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Distributionally robust optimal scheduling of flexible distribution networks considering dynamic spatio-temporal correlation of renewable energy by Shunxiang Yu, Xiaoming Dong, Chengfu Wang, Tianguang Lu

“…Existing methods often treat spatio-temporal correlations among RESs in a static manner, neglecting their dynamic variations and resulting in suboptimal dispatch strategies. …”
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A morpho-density approach to estimating neural connectivity. by Michael P McAssey, Fetsje Bijma, Bernadetta Tarigan, Jaap van Pelt, Arjen van Ooyen, Mathisca de Gunst

“…Neuronal signal integration and information processing in cortical neuronal networks critically depend on the organization of synaptic connectivity. …”
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How to overcome local policy conflicts that hinder climate actions? A green roof planning dispute between politicization and de-politicization by Rima Almalla, Jani Vuolteenaho, Jukka Käyhkö

“…Abstract The integration of green infrastructure, such as green roofs (GR), in urban centres is considered crucial for climate change adaptation, and improving environmental quality. …”
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Reinforcement Learning for Stability-Guaranteed Adaptive Optimal Primary Frequency Control of Power Systems Using Partially Monotonic Neural Networks by Hamad Alduaij, Yang Weng

“…Recent studies propose using neural Lyapunov-based reinforcement learning for control. While this method can be trained offline with performance guarantees, it is only optimal for specific values of system parameters, as it omits critical modeling factors like decreasing inertia and damping variation over time. …”
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Offsetting Dense Particle Sedimentation in Microfluidic Systems by Tochukwu Dubem Anyaduba, Jesus Rodriguez-Manzano

“…Computational image analysis of multiplex metering efficiency using this method showed an average reduction in well-to-well variation in particle concentration from 45% (Q = 1 mL/min, n = 32 total wells) to 17% (Q = 10 mL/min, n = 48 total wells). …”
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DYNAMICS OF REINFORCED CONCRETE SLAB OF PEDESTRIAN BRIDGE WITH RIGID REINFORCEMENT by Anatoly Alekseytsev, Vincent Kvočak

“…In this case, an implicit integration method is used. The time variation of the dynamic load implies a residual mass of the impacting body that vibrates with the slab structure after the onset of impact. …”
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An Adaptive Control Strategy for a Virtual Synchronous Generator Based on Exponential Inertia and Nonlinear Damping by Huiguang Pian, Keqilao Meng, Hua Li, Yongjiang Liu, Zhi Li, Ligang Jiang

“…Simulation results in MATLAB/Simulink under step changes, load fluctuations, and single-phase faults demonstrate that the proposed method reduces the frequency deviation by over 26.15% compared to fixed-parameter and threshold-based adaptive VSG methods, effectively suppresses power overshoot, and eliminates secondary oscillations. …”
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Optimizing blood-brain barrier permeability in KRAS inhibitors: A structure-constrained molecular generation approach by Xia Sheng, Yike Gui, Jie Yu, Yitian Wang, Zhenghao Li, Xiaoya Zhang, Yuxin Xing, Yuqing Wang, Zhaojun Li, Mingyue Zheng, Liquan Yang, Xutong Li

“…Our approach utilizes a variational autoencoder (VAE) generative model integrated with reinforcement learning for multi-objective optimization. …”
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Modeling Electrical Potential in Multi-Dendritic Neurons Using Bessel Functions by Kaouther Selmi, Souhaila Khalfallah, Kais Bouallegue

“…The model successfully mimics the way electrical signals propagate and interact within dendritic structures, providing crucial insights into the underlying mechanisms of signal integration and transmission in neurons.…”
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Enhancing security in 6G-enabled wireless sensor networks for smart cities: a multi-deep learning intrusion detection approach by Waqar Khan, Muhammad Usama, Muhammad Shahbaz Khan, Oumaima Saidani, Hussam Al Hamadi, Noha Alnazzawi, Mohammed S. Alshehri, Jawad Ahmad

“…The model integrates a Transformer-based encoder, Convolutional Neural Networks (CNNs), and Variational Autoencoder-Long Short-Term Memory (VAE-LSTM) networks to enhance anomaly detection capabilities. …”
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Tailoring threshold voltage of R2R printed SWCNT thin film transistors for realizing 4 bit ALU by Sajjan Parajuli, Younsu Jung, Sagar Shrestha, Jinhwa Park, Chanyeop Ahn, Kiran Shrestha, Bijendra Bishow Maskey, Tae-Yeon Cho, Ji-Ho Eom, Changwoo Lee, Jeong-Taek Kong, Byung-Sung Kim, Taik-Min Lee, SoYoung Kim, Gyoujin Cho

“…Abstract Despite the roll-to-roll (R2R) gravure printing method emerging as an alternative sustainable technology for fabricating logic circuits based on p- and n-types of single-walled carbon nanotube thin film transistors (p,n-SWCNT-TFTs), the wide variation of large threshold voltage (V th > ~8) in the R2R printed p,n-SWCNT-TFTs prevents the integration of complementary logic circuit. …”
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Unmanned aerial vehicle based multi-person detection via deep neural network models by Mohammed Alshehri, Laiba Zahoor, Yahya AlQahtani, Abdulmonem Alshahrani, Dina Abdulaziz AlHammadi, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…The study supports the wider development of neural network systems utilized in complicated contexts while creating intelligent UAV applications utilizing neural networks.MethodThe proposed study uses deep learning and feature extraction approaches to create a novel method to recognize various actions in UAV-recorded video. …”
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Application of a Low-dissipation HLLD Approximate Riemann Solver to Solar Wind Simulations by Caixia Li, Zhenning Shen, Man Zhang, Xueshang Feng

“…A constrained transport method is employed to effectively preserve the divergence-free condition, with the relative divergence errors maintained at truncation level throughout the simulation. …”
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A Refined Fuzzy MARCOS Approach with Quasi-D-Overlap Functions for Intuitive, Consistent, and Flexible Sensor Selection in IoT-Based Healthcare Systems by Mahmut Baydaş, Safiye Turgay, Mert Kadem Ömeroğlu, Abdulkadir Aydin, Gıyasettin Baydaş, Željko Stević, Enes Emre Başar, Murat İnci, Mehmet Selçuk

“…The results demonstrate that the proposed method provides greater stability, enhanced discrimination, and improved responsiveness to weight variations compared to traditional fuzzy MCDM techniques. …”
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Frequency regulation of two-area thermal and photovoltaic power system via flood algorithm by Serdar Ekinci, Davut Izci, Cebrail Turkeri, Aseel Smerat, Absalom E. Ezugwu, Laith Abualigah

“…This becomes increasingly important with the integration of renewable energy sources, such as photovoltaic (PV) units, which introduce variability and complexity into power systems. …”
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Performance simulation of L-shaped heat pipe and air coupled cooling process for ternary lithium battery module by Shengshi Wang, Tianshi Zhang, Qing Gao, Zhiwu Han, Haizhen Huang, Jingyu Yao

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Design and Fabrication of Cylindrical Fiber Backplanes with 2T1C Pixel Circuits for Truly Wearable Woven Displays by Jiseong Lee, Soyoon Park, Seong Uk Kong, Jiwoo Park, Daehyun Kim, Kyung Cheol Choi

“…The study utilizes a direct patterning method with metal masks on cylindrical fiber substrates, which facilitates the formation of low‐temperature TFTs with high mobility (≈10 cm2 V−1 s−1) and stable electrical properties. …”
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Multi-risk-scenarios flexibility evaluation model of regional power grid considering economic efficiency of dispatching measures by ZHOU Qihang, GUAN Lin, XIAN Weihong, XUAN Peizheng, CHENG Lanfen, LI Zixi

“…Because of the integration of large amount of new energy sources, the power flow variation and voltage volatility in regional power system increase and it escalates the risk of equipment overload. …”
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Optical Flow Magnification and Cosine Similarity Feature Fusion Network for Micro-Expression Recognition by Heyou Chang, Jiazheng Yang, Kai Huang, Wei Xu, Jian Zhang, Hao Zheng

“…Recent advances in deep learning have significantly advanced micro-expression recognition, yet most existing methods process the entire facial region holistically, struggling to capture subtle variations in facial action units, which limits recognition performance. …”
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