Acousto-Electric Conversion Fiber Networks via Regional Activation of Schwann Cell-Derived Exosomes for Neurogenic Bone Regeneration by Weiwei Yi, Xiaoyu Han, Fan Wang, Qiuyu Tang, Huzhe Liu, Bo Liao, Jieliang Shen, Juan Wang, Wenguo Cui, Dingqun Bai

“…The incorporation of the piezoelectric polymer glycine imparts superior piezoelectric characteristics to the fiber network, while the conjugated π-electron motion within the conductive graphene network enhances internal electron transfer efficiency, thereby facilitating electrical conductivity. …”
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Surgical Management of Thumb Carpometacarpal Osteoarthritis: A Systematic Review, Network Meta-analysis, and Longitudinal Analysis of Surgical Complications by Annora Ai-Wei Kumar, BBioMedSc, Matthew Lawson-Smith, MBBCh BAO

“…Bayesian network meta-analyses were conducted, and longitudinal analysis of complication severity was performed using the Kruskal-Wallis H test. …”
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Integrating network pharmacology and experimental validation to reveal the anti-growth mechanism of panaxadiol against glioblastoma via calcium signaling by Guobin Qiu, Zhiyong Wu, Dunhui Yang, Luqiu Zhou

“…Further, In our study, we employed the MOCDE and CytoHubba plugins within the Cytoscape framework to identify seven hub genes, including GRIA2, GRIN1, GRIN2B, GRM1, GRM5, HTR1A, and HTR2A, and validated their binding capabilities with Panaxadiol through molecular docking. Furthermore, we conducted experiments in vitro and in vivo experiments, which encompassed CCK-8, colony formation, flow cytometry apoptosis, intracellular calcium ion measurement, and xenograft tumor experiments utilizing nude mice, to validate the function of Panaxadiol in suppressing the growth of GBM via the modulation of calcium ion levels. …”
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Comparative effectiveness of non-pharmacological therapies for postoperative cognitive dysfunction: Protocol for a systematic review and network meta-analysis. by Kexin Wu, Qiongnan Bao, Jun Huang, Shanshan Sun, Yaqin Li, Xinyue Zhang, Manze Xia, Zhenghong Chen, Jin Yao, Wanqi Zhong, Zihan Yin, Fanrong Liang

“…Two reviewers will independently conduct study selection and data extraction. The primary outcome will be the changes in the overall cognitive function before and after the intervention. …”
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SR-YOLO: Spatial-to-Depth Enhanced Multi-Scale Attention Network for Small Target Detection in UAV Aerial Imagery by Shasha Zhao, He Chen, Di Zhang, Yiyao Tao, Xiangnan Feng, Dengyin Zhang

“…Finally, the model’s detection performance for small targets is improved by utilizing the Normalized Wasserstein Distance loss function to optimize the Complete Intersection over Union loss function. …”
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α-Lipoic acid mitigates age-related macular degeneration via ferroptosis: integrative multi-omics and network pharmacology by Yaqiong Zhang, Yaqiong Zhang, Yuanyuan Chen, Chenglin Sun, Fang Li, Yin Shen, Yin Shen

“…Core genes were identified through interaction network construction, functional enrichment analysis, and machine learning-based screening. …”
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The efficacy of platelet-rich plasma preparation protocols in the treatment of osteoarthritis: a network meta-analysis of randomized controlled trials by Dongsheng Yu, Jiani Zhao, Kun Zhao

“…Clinical outcomes were compared using a frequentist network meta-analysis, and treatment options were ranked using the P-Score. …”
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Enhancing functional motor outcomes in chronic stroke: A systematic review of the growing role of non-invasive brain stimulation. by Mirjam Bonanno, Maria Grazia Maggio, Angelo Quartarone, Giovanni Morone, Alessandro Marco De Nunzio, David Militi, Carmela Casella, Svonko Galasso, Rocco Salvatore Calabrò

“…<h4>Introduction</h4>Non-invasive brain stimulation (NIBS) promotes functional recovery by enhancing neuroplasticity and reorganizing brain networks. …”
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Finite-time distributed optimization formation control of networked robots with time-varying reference signals under directed graphs by Weicheng Zhao, Qian Chen, Li Ding

“…Abstract In this paper, we propose a novel finite-time optimization formation control framework for networked robots, which integrates a finite-time optimal estimator (FOE) with a finite-time local controller (FLC). …”
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Integrative Single-Cell Analysis of Cardiomyopathy Identifies Differences in Cell Stemness and Transcriptional Regulatory Networks among Fibroblast Subpopulations by Wenyang Nie, Zhijie Zhao, Yuhang Liu, Youcao Wang, Jingwen Zhang, Ying Hu, Yang Liu, Yong Wang, Zhen Wang

“…Therefore, in this study, we conducted comprehensive single-cell analysis of cardiac fibroblasts in cardiomyopathy to explore differences in cellular plasticity and transcriptional regulatory networks among fibroblast subpopulations, with the aim of providing as many useful references as possible for the diagnosis, prognosis, and treatment of cardiomyopathy. …”
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A High-Efficient Method for Synthesizing Multiple Antenna Array Radiation Patterns Simultaneously Based on Convolutional Neural Network by Shiyuan Zhang, Chuan Shi, Ming Bai

“…Boundary functions are designed to reshape the important characteristics of target radiation patterns and transform them into a two-channel mask matrix, allowing for the simultaneous input of multiple target radiation patterns into the neural network without sacrificing computational efficiency. …”
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Authorisation inconsistency in IoT third‐party integration by Jiongyi Chen, Fenghao Xu, Shuaike Dong, Wei Sun, Kehuan Zhang

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Research on Performance Predictive Model and Parameter Optimization of Pneumatic Drum Seed Metering Device Based on Backpropagation Neural Network by Yilong Pan, Yaxin Yu, Junwei Zhou, Wenbing Qin, Qiang Wang, Yinghao Wang

“…The method applies a backpropagation neural network (BPNN) to establish a predictive model and multi-objective particle swarm optimization (MOPSO) to search for the optimal solution. …”
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Index-Based Neural Network Framework for Truss Structural Analysis via a Mechanics-Informed Augmented Lagrangian Approach by Hyeonju Ha, Sudeok Shon, Seungjae Lee

“…The IBNN framework approximates member forces and nodal displacements using separate neural networks and incorporates structural equations derived from the force method as mechanics-informed constraints within the loss function. …”
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Research on energy management strategies for high-power diesel-electric hybrid tractors based on double deep Q-network by Yiwei Wu, Yifan Zhao, Changkai Wen, Junjiang Zhang, Xianghai Yan

“…With engine power as the agent’s control action, drive motor power and battery SOC as state variables, and tractor equivalent fuel consumption and battery SOC as the reward function, an energy management strategy based on deep reinforcement learning was designed using the double deep Q-network (DDQN) algorithm. …”
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Engine Mass Flow Estimation through Neural Network Modeling in Semi-Transient Conditions: A New Calibration Approach by T. Savioli, M. Pampanini, G. Visani, L. Esposito, C. A. Rinaldini

“…A model that estimates air mass flow is created by adopting either a tree ensemble model or an artificial neural network trained on a small dataset, which was previously acquired at the test bench using a random calibration of the volumetric efficiency map. …”
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BiEHFFNet: A Water Body Detection Network for SAR Images Based on Bi-Encoder and Hybrid Feature Fusion by Bin Han, Xin Huang, Feng Xue

“…To address this issue, a bi-encoder and hybrid feature fuse network (BiEHFFNet) is proposed for achieving accurate water body detection. …”
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Social Relations and Interpersonal Dialogue among Couples: A Study in the City of Yazd Based on the Grounded Theory by Lida Hatefi rad, Mehraban Parsamehr, Ali Ruhani

“…It assumes distinct roles and functions and addresses a range of human needs. Central to family life and functioning are the relationships among family members. …”
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Application of artificial neural networks for predicting soil settlement in geotechnical applications with plastic waste reinforcement above buried pipes by Sinan A. Al-Haddad, Hala Adnan Abbas, Luttfi A. Al-Haddad, Mustafa I. Al-Karkhi

“…This paper investigates the impact of recycled plastic bottle utilization on soil settlement above buried pipes under static loads and employs a two-hidden-layer artificial neural network (ANN) model to accurately predict settlement values. …”
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LWSARDet: A Lightweight SAR Small Ship Target Detection Network Based on a Position–Morphology Matching Mechanism by Yuliang Zhao, Yang Du, Qiutong Wang, Changhe Li, Yan Miao, Tengfei Wang, Xiangyu Song

“…Specifically, based on the YOLOv5 framework, a dual strategy for the lightweight network is adopted as follows: On the one hand, to address the limited nonlinear representation ability of the original network, a global channel attention mechanism is embedded and a feature extraction module, GCCR-GhostNet, is constructed, which can effectively enhance the network’s feature extraction capability and high-frequency noise suppression, while reducing computational cost. …”
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