Convolutional Neural Networks—Long Short-Term Memory—Attention: A Novel Model for Wear State Prediction Based on Oil Monitoring Data by Ying Du, Hui Wei, Tao Shao, Shishuai Chen, Jianlei Wang, Chunguo Zhou, Yanchao Zhang

“…To address this, a CNN–LSTM–Attention network is specially constructed for predicting wear state, which hierarchically integrates convolutional neural networks (CNNs) for spatial feature extraction, long short-term memory (LSTM) networks for temporal dynamics modeling, and self-attention mechanisms for adaptive feature refinement. …”
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Machine learning-assisted analysis of serum metabolomics and network pharmacology reveals the effective compound from herbal formula against alcoholic liver injury by Jiamu Ma, Peng Wei, Xiao Xu, Ruijuan Dong, Xixi Deng, Feng Zhang, Mengyu Sun, Mingxia Li, Wei Liu, Jianling Yao, Yu Cao, Letian Ying, Yuqing Yang, Yongqi Yang, Xiaopeng Wu, Gaimei She

“…In order to accurately identify the direct acting target as well as the most effective compound, the relationship between the compounds and their targets was investigated using a feature-based prediction model conducted by AdaBoost. The binding mode of the effective compound and the direct-acting target was verified by molecular docking, dynamics simulations, and western blotting. …”
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From unipotency to pluripotency: deciphering protein networks and signaling pathways in the generation of embryonic stem-like cells from murine spermatogonial stem cells by Nima Ghasemi, Hossein Azizi, Ali Qorbanee, Thomas Skutella

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Temporal and Modality Awareness-Based Lightweight Residual Network With Attention Mechanism for Human Activity Recognition Using a Lower-Limb Exoskeleton Robot by Chang-Sik Son, Won-Seok Kang

“…To address these issues, this study proposes a lightweight residual network for recognizing diverse locomotion activities across varying terrains using multimodal sensing data. …”
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Mitotherapy attenuates sepsis-induced brain injury in rats subjected to cecal ligation and puncture: Role of SIRT-1/PGC-1α network by Behnaz Mokhtari, Alireza Alihemmati, Soleyman Bafadam, Solmaz Boraghi, Reza Badalzadeh, Ata Mahmoodpoor

“…Repetitive injections provided greater therapeutic benefits than a single injection.Conclusion: Mitotherapy mitigated sepsis-induced brain injury by improving mitochondrial function, biogenesis, and dynamics within the SIRT-1/PGC-1α network and concurrently suppressing inflammation. …”
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Real-Time Adaptive Traffic Flow Prediction Based on a GE-GRU-KNN Model by Xiangyu YI, Hongmei ZHOU, Shaopeng ZHONG

“…The method enables the model to effectively characterise the dynamic correlation of traffic flow. An experiment using traffic flow data from 22 detectors on California freeways is conducted. …”
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Pharmacological mechanisms of probenecid for SARS-CoV-2 and RSV co-infection: findings of system pharmacology, molecular docking, molecular dynamics simulation, and structure–activ... by Junbin Hong, Zhendong Guo, XiaoMei Huang, Peng Wu, Xinying Chen, Xiaoyi Liu, Jinghua Yang, Yanni Lai

“…To further validate these findings, we conducted molecular docking, MD simulations, electrostatic potential mapping, and SAR analysis to explore the binding interactions between probenecid and the identified core targets.ResultsWe identified 141 targets that overlapped with the co-infection and probenecid, and used these shared targets to construct a protein-protein interaction (PPI) network. …”
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Parameter estimation for networked SIR models with stochastic perturbations using JEKF: a study using COVID-19 daily data from Indian states by Prince Achankunju, Saroj Kumar Dash

“…This sophisticated estimation algorithm iteratively predicts and refines the state based on current estimates, combining model predictions with observed data to enhance accuracy, making it effective for estimating critical parameters in dynamic systems. Finally, we visually illustrate our algorithms through experiments conducted on a small-world Watts-Strogatz graph and a simple tree network. …”
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Machine vision approach for monitoring and quantifying fish school migration by Feng Lin, Jicheng Zhu, Aiju You, Lei Hua

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Investigating the role and mechanisms of bisphenol compounds in premature ovarian insufficiency using computational biology and bioinformatics by Deshui Kong, Yufei Nie, Haojie He, Hongyan Guo

“…Using bioinformatics tools, we identified potential target genes related to both bisphenols and POI, and conducted functional enrichment analysis. Further, we calculated differentially expressed genes for POI, extracted core networks, and explored immune function and screened core genes. …”
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CNN-based vane-type vortex generator modelling by Koldo Portal-Porras, Unai Fernandez-Gamiz, Ekaitz Zulueta, Roberto Garcia-Fernandez, Xabier Uralde-Guinea

“…In order to obtain data for training the network, 20 different CFD simulations were conducted, considering the same inflow conditions but different vane heights and angles of attack of the VGs. …”
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Identification and validation of susceptibility modules and hub genes of adrenocortical carcinoma through WGCNA and machine learning by Yaoming Yang, Xinbao Wang, Liuqing Wu, Shihua Zhao, Ran Chen, Guoyong Yu

“…In this study, we applied Weighted Gene Co-Expression Network Analysis (WGCNA) to identify gene co-expression modules associated with ACC progression. …”
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Integrating artificial neural networks, multi-objective metaheuristic optimization, and multi-criteria decision-making for improving MXene-based ionanofluids applicable in PV/T sol... by Tao Hai, Ali Basem, As’ad Alizadeh, Kamal Sharma, Dheyaa J. jasim, Husam Rajab, Abdelkader Mabrouk, Lioua Kolsi, Wajdi Rajhi, Hamid Maleki, Narinderjit Singh Sawaran Singh

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Application of Neural Network Models for Analyzing the Impact of Flight Speed and Angle of Attack on Flow Parameter Non-Uniformity in a Turbofan Engine Inlet Duct by Adam Kozakiewicz, Maciej Adamczyk, Rafał Kieszek

“…In the second phase of the study, an artificial neural network (ANN) utilizing a Feed-Forward architecture was implemented to predict pressure distributions for intermediate flight conditions. …”
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Adaptive Nonlinear Proportional–Integral–Derivative Control of a Continuous Stirred Tank Reactor Process Using a Radial Basis Function Neural Network by Joo-Yeon Lee, Gang-Gyoo Jin, Gun-Baek So

“…The network’s ability to approximate nonlinear functions and its online learning capabilities are leveraged by effectively integrating an NPID control scheme with a radial basis function neural network (RBFNN). …”
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Quand les associations expérimentent : les dynamiques relationnelles locales à l’épreuve des appels à projets. Le cas du PIC La Locomotive by Nina Aubry, Aurélien Martineau, Emmanuel Bioteau

“…The article examines the effects of project calls on associations and the local relational dynamics in which they operate. It explores the concrete translation of injunctions to networking and multi-partnership collaboration. …”
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Physics-informed machine learning for building performance simulation-A review of a nascent field by Zixin Jiang, Xuezheng Wang, Han Li, Tianzhen Hong, Fengqi You, Ján Drgoňa, Draguna Vrabie, Bing Dong

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Skeleton Photoperiod Enhances Photosynthetic Yield in Celery via Circadian-Regulated Metabolic Coordination by Hengmin Lv, Chen Chen, Jian Luo, Mengting Xiao, Aisheng Xiong, Xilin Hou, Xiong You

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The evolutionary adaptation of wood‐decay macrofungi to host gymnosperms differs from that to host angiosperms by Xuetong Zhang, Yuran Dong, Yuying Li, Xiuping Wu, Siyu Chen, Mingyuan Wang, Yao Li, Zhiwei Ge, Min Zhang, Lingfeng Mao

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Integration of phytochemical profiling and computational approaches to evaluate the neuroprotective potential of Nardostachys jatamansi in Alzheimer's disease by Abdul Jalil Shah, Mohammad Younis Dar, Mohd Adnan, Tanmaykumar Varma, Dhairiya Agarwal, Prabha Garg, Reyaz Hassan Mir, Rampratap Meena, Mubashir Hussain Masoodi

“…To investigate the molecular targets and therapeutic potential of N. jatamansi for Alzheimer's disease (AD), we used Gas Chromatography-Mass Spectrometry (GC-MS), ADMET analysis, network pharmacology, differential gene expression analysis, molecular docking, and molecular dynamics (MD) simulations. …”
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