Exploring fecal microbiota signatures associated with immune response and antibiotic impact in NSCLC: insights from metagenomic and machine learning approaches by Wenjie Han, Wenjie Han, Yuhang Zhou, Yuhang Zhou, Yiwen Wang, Yiwen Wang, Xiaolin Liu, Tao Sun, Tao Sun, Junnan Xu, Junnan Xu, Junnan Xu

“…To address this challenge, we performed a comprehensive integration of publicly available global metagenomic datasets. …”
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On the problem of the korenization and ukrainization of state authorities in the 1920s–1930s (based on the materials of the North Caucasus) by E. V. Tufanov

“…The North Caucasus region was an integral part of a large Soviet state and all the processes that took place in the country were reflected in the South of the country. …”
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Analysis of Bridge Health Detection Based on Data Fusion by Ying Chen, Jiuhong Zhang, Yanfeng Li, Jialong Li

“…A rough neural network algorithm integrating the rough set and neural network was applied to data fusion of the database, with the attribute-reduction function of the rough set used to reduce the input dimension of the neural network. …”
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Evaluation of Microwave Radiometer Sea Ice Concentration Products over the Baltic Sea by Marko Mäkynen, Stefan Kern, Rasmus Tonboe

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Standard characteristics of functional state of the rectal obturator muscles obtained from neurophysiological examination by O. Yu. Fomenko, Yu. A. Shelygin, A. Yu. Titov, S. V. Belousova

“…Integral values of mean and maximal BEA amplitude  for the rectal obturator muscles at rest, for voluntary contraction,  during straining, and with increased intra-abdominal pressure were calculated.Results. …”
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Cascade Machine Learning Approach Applied to Short-Term Medium Horizon Demand Forecasting by Bruno Brentan, Ariele Zanfei, Martin Oberascher, Robert Sitzenfrei, Joaquin Izquierdo, Andrea Menapace

“…The LSTM model estimates, utilizing a univariate approach, the hourly forecasting of water demand for the entire available dataset and the minimum night flow. The algorithm considers various time series sizes for each DMA and predicts the water demand values for each hour throughout the week. …”
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Emerging Diagnostic Approaches for Musculoskeletal Disorders: Advances in Imaging, Biomarkers, and Clinical Assessment by Rahul Kumar, Kiran Marla, Kyle Sporn, Phani Paladugu, Akshay Khanna, Chirag Gowda, Alex Ngo, Ethan Waisberg, Ram Jagadeesan, Alireza Tavakkoli

“…Artificial intelligence and machine learning algorithms now automate image interpretation, predict clinical outcomes, and enhance clinical decision support, complementing conventional clinical evaluations. …”
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Deterministic and fractional-order modeling of measles dynamics with harmonic mean incidence rate and quarantine impact by Rehan Khan, Ioan-Lucian Popa, Emad A. A. Ismail, Fuad A. Awwad, Umar Ishtiaq

“…Parameters are estimated using a genetic algorithm based on cumulative monthly case data for measles in Indonesia. …”
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CrySPAI: A New Crystal Structure Prediction Software Based on Artificial Intelligence by Zongguo Wang, Ziyi Chen, Yang Yuan, Yangang Wang

“…The software consists of three key modules, an evolutionary optimization algorithm (EOA) that searches for all possible crystal structure configurations, density functional theory (DFT) that provides the accurate energy values for these structures, and a deep neural network (DNN) that learns the relationship between crystal structures and their corresponding energies. …”
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Real‐Time Energy Management System for a Hybrid Renewable Microgrid System by Christian Ndeke Bipongo, Marco Adonis, Ali Almaktoof

“…The battery state of charge (SOC) was maintained between the fixed values (20% and 100%) as stated by the algorithm.…”
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Assessment of salt tolerance in peas using machine learning and multi-sensor data by Zehao Liu, Qiyan Jiang, Yishan Ji, Rong Liu, Hongquan Liu, Xiuxiu Ya, Zhenxing Liu, Zhirui Wang, Xiuliang Jin, Tao Yang

“…Using this information, aboveground biomass (AGB) and Soil Plant Analyses Development (SPAD) values were estimated under both growth conditions using four machine learning algorithms: CatBoost, Light Gradient Boosting Machine (LightGBM), support vector machines (SVM), and random forest regression (RF). …”
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Estimation of gas hydrate and free gas saturation using the rock physics model based on constrained least squares and trust region method in the Shenhu Area, South China Sea by Dajiang Meng, Dajiang Meng, Ruwei Zhang, Ruwei Zhang, Yuan Gu, Yuan Gu, Baojin Zhang, Baojin Zhang, Yunqian Lu, Yunqian Lu, Jiangnan Lin, Jiangnan Lin, Lijie Wang, Lijie Wang

“…Additionally, the application results indicate that the trust region algorithm demonstrates favorable global convergence.…”
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Improved Phase Diversity Wavefront Sensing with a Deep Learning-Driven Hybrid Optimization Approach by Yangchen Wang, Ming Wen, Hongcai Ma

“…However, conventional optimization-based PDWS methods often suffer from high computational costs and sensitivity to initial values. To address these challenges, this paper proposes a hybrid PDWS method that integrates deep learning with nonlinear optimization to improve efficiency and accuracy. …”
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Research on fault line selection technology of distribution network based on EMD and WVD by Jin Zhang, Dezhi Chen, Siman Han

“…Amplitude and energy values are combined to define correctness weights. …”
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Enhancing Visitor Forecasting with Target-Concatenated Autoencoder and Ensemble Learning by Ray-I Chang, Chih-Yung Tsai, Yu-Wei Chang

“…Preceding forecasting algorithms primarily focused on time series analysis, often overlooking influential factors such as economic conditions. …”
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Digital Twin and Data-Driven Remaining Useful Life Prediction of Gearbox by Quanbo Lu, Mei Li, Xiaojuan Huang

“…To further improve prediction accuracy, the paper employs the Central Particle Swarm Optimization algorithm to merge both theoretical and actual RUL values. …”
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CNN-GRU Battery SOC Estimation Method Fused with Attention Mechanism for Electric Multiple Units by WANG Shenghui, TIAN Qin, LIU Lihao, FENG Enlai, YU Tianjian

“…To precisely estimate the SOC of small-sample battery cycling data, this paper transforms the continuous regression model into a classification problem, discretizes the battery SOC ranges, and converts the final prediction result into discrete SOC values. The experimental results show that compared with the CNN-GRU algorithm, the proposed approach improves three key metrics — root mean square error, mean absolute error, and mean relative error by 18.90%, 17.92% and 19.78%, respectively, demonstrating impressive prediction accuracy and stability.…”
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Leveraging Graph Neural Networks for IoT Attack Detection by Mevlüt Uysal, Erdal Özdoğan, Onur Ceran

“…To address this challenge, researchers propose a novel hybrid approach combining Graph Neural Networks and XGBoost algorithm for robust intrusion detection in IoT ecosystems. …”
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N-Bipolar Soft Expert Sets and Their Applications in Robust Multi-Attribute Group Decision-Making by Sagvan Y. Musa, Amlak I. Alajlan, Baravan A. Asaad, Zanyar A. Ameen

“…Existing MAGDM approaches often lack the ability to simultaneously integrate positive and negative assessments, especially in nuanced, multi-valued evaluation spaces. …”
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METHOD OF QUALIFICATION ESTIMATION AND OPTIMIZATION OF PROFESSIONAL TEAMS OF PROGRAMMERS by A. A. Prihozhy, A. M. Zhdanouski

“…The qualification of a group of programmers is evaluated taking into account the requirements for a particular project, which integrates three components: the average qualification of programmers included in the group; the qualification of the group with respect to the best representatives for each of the technologies; threshold values of the levels of programmer qualification and group qualification for each of the technologies, as well as threshold values of the integrated qualification, reflecting the specifics of the given project. …”
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