Machine learning assisted design of Fe-Ni-Cr-Al based multi-principal elements alloys with ultra-high microhardness and unexpected wear resistance by Ling Qiao, Jingchuan Zhu, Junya Inoue

“…Generalized Regression Neural Network (GRNN) showed high accuracy to construct the composition-microhardness model and was used for microhardness prediction and composition optimization. …”
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Review of machine learning-assisted multi-property design of high-entropy alloys: phase structure, mechanical, tribological, corrosion, and hydrogen storage properties by Yunlong Li, Jialiang Tan, Cheng Qian, Xiaochao Liu, Rui Nie

“…It outlines the basic workflow, including data collection, data preprocessing, ML algorithm selection, hyperparameter optimization, model evaluation and model interpretability. …”
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Design and analysis of timing silent chain system based on hybrid electric passenger vehicles by YANG Zeyu, ZHU Kaihong, XIA Chunyu, SHI Pengli

“…Based on the actual working conditions and structural composition of a hybrid electric engine, the design calculation and simulation analysis were conducted of its timing silent chain system.MethodsThe structural layout, chain length, chain plate and sprocket of the timing silent chain system were designed and calculated, and a three-dimensional model was established. …”
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Simulation and Evaluation Hydrogen-rich Syngas Production from Palm Kernell Shell Through Gasification by Laksmi Dewi Kasmiarno, Arifatin Nurufazzah

“…Simulation outputs showed strong agreement with experimental data, validating the model’s accuracy. This study demonstrates the potential of PKS gasification for renewable energy generation and highlights the effectiveness of process simulation for system design and optimization prior to industrial implementation. …”
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Mental health effects of government transfer payments in urban China—An empirical study based on CFPS panel data by Jing Zeng, Yunting Chen, Yafeng Li

“…Methods: Based on panel data from the 2016 and 2018 China Family Panel Studies (CFPS) urban sample composition (N = 6645), the PSM-DID model was used to investigate the mental health effects of government transfer payments. …”
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Principles of creating a digital twin prototype for the process of alkylation of benzene with propylene based on a neural network by K. G. Kichatov, T. R. Prosochkina, I. S. Vorobyova

“…This model can be loaded into a microcontroller to allow for real-time determination of the economic efficiency of plant operation and automated optimization depending on the following factors: composition of incoming raw materials; the technological mode of the plant; the temperature mode of the process; and the pressure in the reactor.Conclusions. …”
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High Quality Power Supply Service Mode Considering Service Life of Mitigation Equipment Against Voltage Sag by Pei LI, Yongjun YU, Zhiquan MA, Chongkai CAI

“…Secondly, a HPSL service pricing optimization model is established with a comprehensive consideration of the cost and income composition of equipment manufacturers and users, and with the maximum net income of both parties as objective. …”
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PS-YOLO-seg: A Lightweight Instance Segmentation Method for Lithium Mineral Microscopic Images Based on Improved YOLOv12-seg by Zeyang Qiu, Xueyu Huang, Zhicheng Deng, Xiangyu Xu, Zhenzhong Qiu

“…Microscopic image automatic recognition is a core technology for mineral composition analysis and plays a crucial role in advancing the intelligent development of smart mining systems. …”
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Logging evaluation of shale oil in the second member of Funing Formation of Qintong Sag, Subei Basin by WANG Xin,HAN Jianqiang,ZAN Ling,LI Xiaolong,PENG Xingping

“…These include total organic carbon content, effective porosity, bedding fracture density, and mineral composition content. The model employs a variety of mathematical methodologies such as physical concept analysis, optimization, fitting, and both forward and backward numerical simulations. …”
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Intelligent prediction and oriented design of high-hardness high-entropy ceramics by Anzhe Wang, Jicheng Liu, Linwei Guo, Kejie Qu, Haishen Xie, Yawei Li, Bin Du

“…This achievement is attributed to three key innovations: the construction of the feature space based on the Pearson correlation coefficient and genetic algorithm, along with algorithm selection and optimization through hyperparameter tuning; the novel combination of reduced-dimensionality component compositions with atomic/precursor descriptors, achieving a model R2 value of up to 0.898; the optimization of constituent elements using genetic algorithm and principal component analysis, providing direct guidance for the design of high-hardness high-entropy ceramics. …”
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Host-specific effects of Eubacterium species on Rg3-mediated modulation of osteosarcopenia in a genetically diverse mouse population by Soyeon Hong, Bao Ngoc Nguyen, Huitae Min, Hye-Young Youn, Sowoon Choi, Emmanuel Hitayezu, Kwang-Hyun Cha, Young Tae Park, Choong-Gu Lee, GyHye Yoo, Myungsuk Kim

“…This study investigated the interplay between host genetics, gut microbiota, and musculoskeletal health in a mouse model of osteosarcopenia, exploring the therapeutic potential of gut microbiota modulation. …”
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Effect of material and spoke pattern on the strength and fatigue life of automotive wheels by Mostafizur Rahman, Md Shariful Islam, Md Arifuzzaman, Md Abdullah Al Bari

“…The results indicate that Mg AZ91D is the most suitable material, while the spoke design labeled model 3 achieved the lowest score of 28.17, making it the most optimized. …”
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Phase Stability and Solidification of 9Cr-ODS Alloys for Wire Additive Manufacturing: A Computational Approach by Sarah Najm Al-Challabi, Ali Samer Muhsan, Thar Mohammed Badri, Mohammad Shakir Nasif

“…Thermal property analysis indicates a liquidus temperature range of 1470.27°C to 1500.67°C and a solidus temperature range of 1387.91°C to 1462.38°C, with thermal conductivity varying between 23.05 W/m·K and 27.56 W/m·K. Phase composition studies using the Scheil model reveal that at 1480°C, the FCC_L12 phase comprises 65% of the solidified structure, decreasing to 55% at 1500°C and further reducing to 45% at 1550°C, where BCC_B2 becomes dominant at 55%. …”
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Comparative Analysis of Codon Usage Patterns in the Chloroplast Genomes of <i>Fagopyrum</i> Species by Qilin Liu, Shurui Li, Dinghong He, Jinyu Liu, Xiuzhi He, Chengruizhi Lin, Jinze Li, Zhixuan Huang, Linkai Huang, Gang Nie, Xinquan Zhang, Guangyan Feng

“…In chloroplast genomes, the optimization of CUB is critical for improving the efficacy of genetic engineering approaches. …”
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Computational intelligence investigations on evaluation of salicylic acid solubility in various solvents at different temperatures by Adel Alhowyan, Wael A. Mahdi, Ahmad J. Obaidullah

“…We employed four distinct models: cubist regression, gradient boosting (GB), extreme gradient boosting (XGB), and extra trees (ET) for correlation of drug solubility to pressure, temperature, and solvent composition. …”
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Application of diabatic extractive distillation schemes with preliminary separation of azeotropic components for separation of acetone-toluene-<i>n</i>-butanol mixture by P. S. Klauzner, D. G. Rudakov, E. A. Anokhina, A. V. Timoshenko

“…As a model for describing vapor-liquid equilibrium, the local composition Non-Random Two Liquid equation model was used. …”
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Discovery of ultra-high strength aluminum alloys with high damage tolerance via interpretable chain-based machine learning by Lei Jiang, Xinbiao Zhang, Wentao Zhoutai, Zhilin Han, Minghong Mao, Wenli Xue, Jianxin Xie

“…Firstly, by integrating a gradient boosting regression model linking alloy composition (AC) and solution-aging processes (SAP) to tensile mechanical properties (TMP), including ultimate tensile strength σb, yield strength σy, and elongation A, with an explicit quantitative relationship between TMP and fatigue strength (FS), expressed as FS = ασbA1/4, a multi-scale interpretable prediction model was constructed to AC + SAP → TMP → FS. …”
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Chemometrics to connect feedstock quality, process settings and calorific value of hydrochar through infrared spectra by Álvaro Amado-Fierro, Tim Offermans, Jeroen Jansen, Teresa A. Centeno, María A. Díez

“…The scores and loading plots point out the pivotal functional groups that distinguish the various hydrochars, while also unveiling the inherent similarities among them. A second model has been further devised to predict the HHV of hydrochar as a function of feedstock composition and HTC operation conditions, thus allowing process optimization. …”
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Dynamics of recurrent neural networks with piecewise linear activation function in the context-dependent decision-making task by Kononov, Roman Andreevich, Maslennikov, O.  V., Nekorkin, Vladimir Isaakovich

“…An ensemble of neural networks with piecewise linear activation functions was constructed. These models were optimized using the proximal policy optimization method. …”
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A Deep Learning-Based Solution to the Class Imbalance Problem in High-Resolution Land Cover Classification by Pengdi Chen, Yong Liu, Yuanrui Ren, Baoan Zhang, Yuan Zhao

“…Recent advancements in deep learning have opened new avenues for tackling the CI problem in this context, focusing on three key aspects: the semantic segmentation model, loss function design, and dataset composition. …”
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