Explore the Mechanism of Astragalus mongholicus Bunge against Nonalcoholic Fatty Liver Disease Based on Network Pharmacology and Experimental Verification by Lili Fu, Zhongming Wu, Yanjun Chu, Wenbin Chen, Ling Gao, Shumin Mu, Jiajun Zhao

“…Finally, molecular docking and experiments were used to verify the results of network pharmacological prediction. Results. Network pharmacology predicted that quercetin may be the main active component in AMB, and the TNF and MAPK signaling pathways may be the key targets of AMB against NAFLD. …”
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Optimized Naive-Bayes and Decision Tree Approaches for fMRI Smoking Cessation Classification by Amirhessam Tahmassebi, Amir H. Gandomi, Mieke H. J. Schulte, Anna E. Goudriaan, Simon Y. Foo, Anke Meyer-Baese

“…This paper aims at developing new theory-driven biomarkers by implementing and evaluating novel techniques from resting-state scans that can be used in relapse prediction for nicotine-dependent patients and future treatment efficacy. …”
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Semantic communication aware reinforcement learning for communication fault-tolerant UAV collaborative control by ZHANG Yang, GU Hongyu, FENG Bohao, WANG Ran

“…This information was then used autonomously to predict the future flight paths of the leading UAV. …”
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Pharmacist-led medication reviews: A scoping review of systematic reviews. by Miriam Craske, Wendy Hardeman, Nicholas Steel, Michael James Twigg

“…Other lower-quality reviews reported evidence supporting intervention effectiveness for some clinical outcomes (odds ratio: achieving diabetes control = 3.11 95% prediction intervals (PI), 1.48-6.52, achieving blood pressure target = 2.73, 95% PI, 1.05-7.083.50).…”
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Priestia flexa as a Novel Urinary Tract Pathogen in Daloa, Côte d’Ivoire: Insights From Genomic Sequencing by Dého Aristide Gbégbé, Okran Beyosse Christophe Kacou, N’goran Parfait N’zi, Djédoux Maxime Angaman

“…No virulence or resistance genes were predicted in the genomes of strains 21LM07 and 21LM1136. …”
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Investigation of Heat and Mass Transfer in the Process of Fuel Preparation from Biomass Particles with High Moisture by A. V. Mitrofanov, O. B. Kolibaba, R. N. Gabitov, D. A. Dolinin, S. V. Vasilevich

“…In addition, the drying stage is extremely energy-consuming, so reliable prediction of its kinetics largely determines the efficiency of the entire technological process. …”
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Design and implementation of an intelligent sports management system (ISMS) using wireless sensor networks by ZhiGuo Zhu

“…Among these industries, the sports sector is experiencing significant transformation, which needs support in accurately monitoring athlete predicting and performance injuries arising due to traditional methods’ limitations. …”
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Spatial transcriptome reveals histology-correlated immune signature learnt by deep learning attention mechanism on H&E-stained images for ovarian cancer prognosis by Chun Wai Ng, Kwong-Kwok Wong, Barrett C. Lawson, Sammy Ferri-Borgogno, Samuel C. Mok

“…Abstract Background The ability to predict the prognosis of patients with ovarian cancer can greatly improve disease management. …”
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Bayesian deep learning applied to diabetic retinopathy with uncertainty quantification by Masoud Muhammed Hassan, Halbast Rashid Ismail

“…In the case of Diabetic Retinopathy (DR), DL models have shown high efficacy in tasks such as classification, segmentation, detection, and prediction. However, DL model's opacity and complexity lead to errors in decision-making, particularly in complex cases, making it necessary to estimate the model's uncertainty in predictions. …”
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Strength Investigation of the Silt-Based Cemented Paste Backfill Using Lab Experiments and Deep Neural Network by Chongchun Xiao, Xinmin Wang, Qiusong Chen, Feng Bin, Yihan Wang, Wei Wei

“…Deep neural network (DNN) was employed to predict the UCS of CPB from its influencing variables, namely, the proportion of OPC, CG, CFA, and YS, the solids content, and the curing time. …”
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Prestack Inversion Identification of Dolomite Reservoirs in the Fourth Member of the Sinian Dengying Formation in Moxi Area, Sichuan Basin, SW China by Yong Wu, Xuxu Wang, Lu Zhou, Chongyang Han, Lianjin Zhang, Xuemei Lan, Peng Lu

“…The dolomite reservoir of the fourth member of Dengying Formation in Moxi area of Sichuan Basin is thin, is fast in lateral variation, and has P-impedance difference from the surrounding rock; it is difficult to identify and predict the dolomite reservoir and fluid properties by conventional poststack seismic inversion. …”
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Multi-Physical Intelligent Analysis of the Thermal-Structural-Optical Coupling for Mirror Based on Surrogate Model by Wenxiong Li, Junli Shen, Zhenyu Lu, Shudong Men, Qingwen Wu

“…Compared with traditional methods, the hybrid network has the smallest symmetric mean absolute percentage error (SMAPE) of 2.674% on the same test set, which indicates that the hybrid network obtains a higher prediction accuracy of the surrogate model. Finally, through the thermal structure-optical coupling analysis of a mirror of an optical system, it is shown that the high precision mirror TSO-MCA based on the surrogate model is 3 orders of magnitude faster than the traditional finite element analysis in terms of computation time, indicating that the surrogate model is more efficient and convenient.…”
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Analysis of Waves in the Oman Sea Using Numerical Software and Field Data by Homayun Kalantari, Kamran Lari, Afshin Mohseni Arasteh, Masoud Torabi Azad

“…Accurate prediction of wave parameters is of great significance for marine and coastal operations. …”
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Screening tools for work-related musculoskeletal symptoms among workers: A rapid review of the literature by Esteban Portilla-Rojas, Laura Daniela Puche-Varón, Daniela Rivera-Guevara, Sebastián Rebolledo-Del Toro, Francisco Palencia-Sánchez

“…Inclusion criteria were: 1) screening tools for musculoskeletal disorders, 2) studies presenting analytical results such as proportion descriptions, sensitivity, specificity, positive predictive value and negative predictive value, and 3) articles focusing on the working population. …”
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Effect of Receiver Holes on Flow and Heat Transfer Characteristics in A Radial Pre-swirl System: A LES Study by D. Wang, C. Song, C. Qiu, W. Wang, Y. Xu, P. I. Mihailovich

“…In addition, a mathematical model was developed to predict the relative total pressure and temperature inside the co-rotating cavity. …”
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Terminalia catappa Extract Palliates Redox Imbalance and Inflammation in Diabetic Rats by Upregulating Nrf-2 Gene by Franklyn Nonso Iheagwam, Gaber El-Saber Batiha, Olubanke Olujoke Ogunlana, Shalom Nwodo Chinedu

“…Molecular docking and prediction of major TCA phytoconstituents’ biological activity related to T2DM-induced oxidative stress were evaluated in silico. …”
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Yindanxinnaotong, a Chinese compound medicine, synergistically attenuatesatherosclerosis progress by Long Cheng, Guo-feng Pan, Xiao-dong Zhang, Jian-lu Wang, Wan-dan Wang, Jian-yong Zhang, Hui Wang, Ri-xin Liang, Xiao-bo Sun

“…We initiallyperformed a computational prediction based on a network pharmacology simulation,which clued YD exerted synergistically anti-atherosclerosis properties by vascularendothelium protection, lipid-lowering, anti-inflammation and anti-oxidation. …”
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Optimizing Lightweight Recurrent Networks for Solar Forecasting in TinyML: Modified Metaheuristics and Legal Implications by Gradimirka Popovic , Zaklina Spalevic , Luka Jovanovic , Miodrag Zivkovic , Lazar Stosic , Nebojsa Bacanin 

“…Therefore, the accurate prediction of solar power production is vital for efficient grid management and energy trading. …”
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Unified constitutive modeling for hot tensile behavior of TC4 alloy with and without diffusion bonding joint by Zhongman Cai, Yong Li, Yanqiang Xu, Jiarui Chen, Xiaoxing Li, Guanglu Ma, Dongsheng Li

“…The constitutive model has been further applied to the finite element method (FEM), and the prediction ability of the deformation behavior and the fracture of the model for hot deformation processes have been verified. …”
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Intelligent information systems for power grid fault analysis by computer communication technology by Ronglong Xu, Jing Zhang

“…Moreover, the system exhibits strong robustness in complex scenarios, with an average fault prediction error rate of just 1.1% across multiple simulations. …”
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