Exploratory GABAa-informed control network modulates hyperarousal brain dynamics in chronic insomnia by Liyong Yu, Liang Gong, Xiaoqin Chen, Yuqi He, Rong Li, Xiaojuan Hong, Qi Zhang, Siyi Yu

“…This study demonstrates that hyperarousal in chronic insomnia is characterized by more frequent and unpredictable transitions between brain states compared to healthy controls, as revealed by hidden Markov modeling of resting-state functional MRI data. By conducting an exploratory integration of DTI-based structural connectivity and regional GABAa receptor distribution within a network control theory framework, we find that chronic insomnia is associated with a flattened energy landscape reflecting hyperarousal, indicating that less energy is required for the brain to transition between states. …”
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IEDSFAN: information enhancement and dynamic-static fusion attention network for traffic flow forecasting by Lianfei Yu, Ziling Wang, Wenxi Yang, Zhijian Qu, Chongguang Ren

“…To this end, we propose a novel information enhancement and dynamic-static fusion attention network (IEDSFAN). …”
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Discrete Dynamic Berth Allocation Optimization in Container Terminal Based on Deep Q-Network by Peng Wang, Jie Li, Xiaohua Cao

“…A novel deep Q-network (DQN)-based model is proposed, leveraging a custom state space, rule-based actions, and an optimized reward function to dynamically allocate berths and schedule vessel arrivals. …”
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A Special Points and Neural Network-Based Dynamic Multi-Objective Optimization Algorithm by Sanyi Li, Wenjie Hou, Peng Liu, Weichao Yue, Qian Wang

“…This paper introduces a special points and neural network- based dynamic multi-objective optimization algorithm (SPNN-DMOA) for solving dynamic multi-objective optimization problems (DMOPs) with an irregularly changing pareto set. …”
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DGAT: a dynamic graph attention neural network framework for EEG emotion recognition by Shihang Ding, Kaixuan Wang, Wenhao Jiang, Cong Xu, Hongjian Bo, Lin Ma, Haifeng Li

“…However, current graph neural network models rely on predefined fixed adjacency matrices during training, which imposes certain limitations on the model's adaptability and feature expressiveness.MethodsIn this study, we propose a novel EEG emotion recognition framework known as the Dynamic Graph Attention Network (DGAT). …”
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Generative Adversarial Network-Based Lightweight High-Dynamic-Range Image Reconstruction Model by Gustavo de Souza Ferreti, Thuanne Paixão, Ana Beatriz Alvarez

“…In this context, this paper presents a lightweight architecture for reconstructing HDR images from three Low-Dynamic-Range inputs. The proposed model is based on Generative Adversarial Networks and replaces traditional convolutions with depthwise separable convolutions, reducing the number of parameters while maintaining high visual quality and minimizing luminance artifacts. …”
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Coupled Dynamic Model of Resource Diffusion and Epidemic Spreading in Time-Varying Multiplex Networks by Ping Huang, Xiao-Long Chen, Ming Tang, Shi-Min Cai

“…However, the social relationships of individuals are time-varying, which affects such coupled dynamics. For that, we propose a coupled resource-epidemic (RNR-SIS) dynamic model (coupled model for short) on a time-varying multiplex network to synchronously simulate the resource diffusion and epidemic spreading in dynamic social networks. …”
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User-cooperative dynamic resource allocation for backscatter-aided wireless-powered MEC network by Huaiwen He, Chenghao Zhou, Feng Huang, Hong Shen, Yihong Yang, Shangsong Liang, Xinyuan Jin

“…However, there is little research on the integration of user cooperation in WPMEC scenarios within volatile network environments. In this paper, we propose a dynamic task offloading algorithm for a Backscatter-assisted WPMEC system, which involves two (MDs) and a Hybrid Access Point (HAP) with user cooperation. …”
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Unpacking the dynamics: The influence of M&A networks on e-innovation in African Listed Firms by Suleman Bawa, Xie Yongping, Ibn W. Benin, Inuusah Mahama, Abdulaziz S. Almudaihesh

“…Multiple regression models are used to test hypotheses regarding the structural characteristics of MA networks and their impact on e-innovation, with robustness tests conducted to ensure reliability. …”
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Numerical heat transfer analysis considering thermal contact conductance between rough reciprocating sliding surfaces by Yuwei Liu, Jiasong Yang, Zhiqiang Guo, Yanpeng Yuan, Weizheng Zhang, Sichuang Wanyan

“…Furthermore, a prediction model is developed based on the BP neural networks. The results indicate that the heat flow distribution coefficient and surface contact temperature increase with rising motion frequency or interface thermal contact conductance and eventually reach a steady state. …”
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Temporal representation learning enhanced dynamic adversarial graph convolutional network for traffic flow prediction by Linlong Chen, Linbiao Chen, Hongyan Wang, Jian Zhao

“…To address this issue, this paper proposes a temporal representation learning enhanced dynamic adversarial graph convolutional network (TRL-DAG). …”
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Precipitation-driven hydrological characteristics of Bei hot spring: Insights from dynamic variations of natural tracers (water discharge, water temperature, and electrical conduct... by Yongli Guo, Fuxiang Chi, Qiong Xiao, Matej Blatnik

“…Study focus: The primary objectives of this research are to analyze geothermal water characteristics of Bei hot spring, simulate the dynamic process of water discharge (Q), groundwater temperature (Tw), and electrical conductivity (EC) during the precipitation event, and build the hydrogeological genetic model for the Bei hot spring. …”
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Burstiness of Interference Pikes in Wireless Networks by Mahin K. Atiq, Udo Schilcher, Xhemal Pengili, Martin Haenggi, Christian Bettstetter

“…The temporal dynamics of interference in wireless networks affects their performance but has only been studied for some cases. …”
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Biobased Thermoset Sandwiched Composites Enabled by Dynamic Covalent Chemistry for Electrical Insulation, EMI Shielding, and Thermal Management by Xiao‐Li Zhao, Ling‐Yu Li, Yi‐Dong Li, Jian‐Bing Zeng

“…Here, we relied on the dynamic covalent chemistry to propose an innovative interface‐welding strategy to fabricate a sandwiched thermoset (covalent adaptable network)/carbon nanotubes/boron nitride (CAN/CNTs/BN) composite. …”
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ANN-based analysis of thin film Maxwell fluid dynamics with electro-osmotic and nonlinear thermal effects by Irfan Saif Ud Din, Imran Siddique, Zohaib Zahid, Muhammad Nadeem, S. Islam

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A Spatio-Temporal Tensor Graph Neural Network-Based Method for Node-Link Prediction in Port Networks by Zhixin Xia, Zhangqi Zheng, Feiyang Wei, Yongshan Liu, Lu Yu

“…The updated spatial features and temporal edge embedding vectors are then weighted for feature fusion to predict the security of port network links. Finally, this paper conducts experiments on seven publicly available dynamic graph datasets, and the results show that the prediction accuracy of the spatio-temporal tensor graph neural network model is better than the baseline models, such as GC-LSTM, HTGN, and GAT, in general.…”
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Influence of Dynamic Properties of Nonlinear Over-Voltage Limiter on Over-Voltage Limitation in Distribution Networks by A. N. Bokhan, V. V. Krotenok, S. N. Prokhorenko

“…It is necessary to take into account dynamic properties of the nonlinear over-voltage limiter in order to ensure authentic simulation of  over-voltage in the network A dynamic model of  the non-linear over-voltage limiter which takes a time lag constant   τ  into account during transition of the nonlinear over-voltage limiter into conducting state has been developed in the paper.…”
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Improving neural network training using dynamic learning rate schedule for PINNs and image classification by Veerababu Dharanalakota, Ashwin Arvind Raikar, Prasanta Kumar Ghosh

“…Experiments are conducted on problems related to physics-informed neural networks (PINNs) and image classification using multilayer perceptrons and convolutional neural networks, respectively. …”
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MSDG: Multi-Scale Dynamic Graph Neural Network for Industrial Time Series Anomaly Detection by Zhilei Zhao, Zhao Xiao, Jie Tao

“…Therefore, this paper constructs a multi-scale dynamic graph neural network (MSDG) for anomaly detection in industrial sensor data. …”
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Enhancing Trajectory Tracking in Humanoid Robots Using Neural Network-Based Dynamic Gain Control by Darwin Trujillo, Luis A. Morales, Danilo Chávez, María Trujillo, David F. Pozo-Espín

“…This paper presents the development and evaluation of a dynamic gain controller utilizing neural networks to enhance trajectory tracking performance in the NAO humanoid robot. …”
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