Machine Learning-Driven Prediction of Glass-Forming Ability in Fe-Based Bulk Metallic Glasses Using Thermophysical Features and Data Augmentation by Renato Dario Bashualdo Bobadilla, Marcello Baricco, Mauro Palumbo

“…In this study, we developed machine learning (ML) models to predict the critical casting diameter (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>D</mi><mrow><mi>m</mi><mi>a</mi><mi>x</mi></mrow></msub></semantics></math></inline-formula>) of Fe-based BMGs, enabling rapid assessment of glass-forming ability (GFA) using composition-based and calculated thermophysical features. …”
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Inverse design of a valley-Hall photonic topological insulator based on tandem residual neural networks by Bing-Jiang Wang, Le Zhang, Ben-Xin Wang, Dong-Ping Zhang, Ya-Guang Xie, Jin-Hui Cai

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Machine learning-based prediction of knee pain risk using lipid metabolism biomarkers: a prospective cohort study from CHARLS by Biao Guo, Yuan Li, Yuan Li, Weihang Peng, Yabin Liu, Fei He, Zhe Zhai

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Major Adverse Kidney Events in Hospitalized Older Patients With Acute Kidney Injury: Machine Learning–Based Model Development and Validation Study by Xiao-Qin Luo, Ning-Ya Zhang, Ying-Hao Deng, Hong-Shen Wang, Yi-Xin Kang, Shao-Bin Duan

“…ObjectiveThis study aimed to develop and validate a machine learning–based model to predict MAKE30 in hospitalized older patients with AKI. …”
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Genetic programming-based algorithms application in modeling the compressive strength of steel fiber-reinforced concrete exposed to elevated temperatures by Mohsin Ali, Li Chen, Qadir Bux Alias Imran Latif Qureshi, Deema Mohammed Alsekait, Adil Khan, Kiran Arif, Muhammad Luqman, Diaa Salama Abd Elminaam, Amir Hamza, Majid Khan

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Atrial fibrillation risk model based on LASSO and SVM algorithms and immune infiltration of key mitochondrial energy metabolism genes by Xunjie Yang, Weng Lan, Chunyi Lin, Chunyu Zhu, Zicong Ye, Zhishi Chen, Guian Zheng

“…Significant differences in immune cell composition were observed between the AF and control groups. …”
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Unraveling volatile metabolites in pigmented onion (Allium cepa L.) bulbs through HS-SPME/GC–MS-based metabolomics and machine learning by Kaiqi Cheng, Kaiqi Cheng, Jingzhe Xiao, Jingyuan He, Rongguang Yang, Jinjin Pei, Jinjin Pei, Wengang Jin, Wengang Jin, A. M. Abd El-Aty, A. M. Abd El-Aty

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Deep learning-based skin lesion analysis using hybrid ResUNet++ and modified AlexNet-Random Forest for enhanced segmentation and classification. by Saleem Mustafa, Arfan Jaffar, Muhammad Rashid, Sheeraz Akram, Sohail Masood Bhatti

“…This paper offers a cutting-edge hybrid deep learning approach of better segmentation and classification of skin lesions. …”
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Compressive strength prediction of fly ash/slag-based geopolymer concrete using EBA-optimised chemistry-informed interpretable deep learning model by Yang Yu, Iman Munadhil Abbas Al-Damad, Stephen Foster, Ali Akbar Nezhad, Ailar Hajimohammadi

“…This study develops a deep learning (DL) model based on convolutional neural networks (CNN) to predict the CS of FA/GGBS-based GPC. …”
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High entropy alloy property predictions using a transformer-based language model by Spyros Kamnis, Konstantinos Delibasis

“…Abstract This study introduces a language transformer-based machine learning model to predict key mechanical properties of high-entropy alloys (HEAs), addressing the challenges due to their complex, multi-principal element compositions and limited experimental data. …”
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A retrospective study on predicting clinically significant prostate cancer via a bi-parametric ultrasound-based deep learning radiomics model by Xiang Liu, Zhong-Xin Zhang, Bing Zheng, Min Xu, Xin-Yu Cao, Hai-Ming Huang

“…PurposeThis study aimed to establish and evaluate a model utilizing bi-parametric ultrasound-based deep learning radiomics (DLR) in conjunction with clinical factors to anticipate clinically significant prostate cancer (csPCa).MethodsWe retrospectively analyzed 232 participants from our institution who underwent both B-mode ultrasound and shear wave elastography (SWE) prior to prostate biopsy between June 2022 and December 2023. …”
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Unveiling geological complexity in the Serra Dourada Granite using self-organizing maps and hierarchical clustering: Insights for REE prospecting in the Goiás Tin Province, Brasíli... by Guilherme Ferreira da Silva, Marcos Vinícius Ferreira, Lucy Takehara Chemale, Igor Vasconcelos Santana, Nilson Francisquini Botelho

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Programmable friction control in 3D printed patterned multi-materials: a flexible design strategy by Xinle Yao, Yuxiong Guo, Mingyang Wang, Yaozhong Lu, Zhibin Lu, Xin Jia, Yu Gao, Xiaolong Wang

“…This study introduces an innovative manufacturing strategy for polymer-based self-lubricating composites, integrating additive manufacturing technology (digital light processing) with a machine learning (ML)-driven interactive system to predict and control tribological behaviour. …”
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Scientific and technical translation training in the conditions of electronic information and educational environment in the construction university by V. N. Smirnova

“…In the process of the study descriptive, comparative, categorical and statistical methods were used.Results. The article describes the modular organization of the electronic information and educational environment in a building university, which implies the inclusion of several interactive platforms in its composition with an indication of their capabilities in teaching scientific and technical translation. …”
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A Multi-Objective Optimization Design Method for High-Aspect-Ratio Wing Structures Based on Mind Evolution Algorithm Backpropagation Surrogate Model by Jin Nan, Junhua Zheng, Bochuan Jiang, Yuhang Li, Jiayun Chen, Xuanqing Fan

“…These results showcased the effectiveness of the proposed method and validated the feasibility of integrating intelligent optimization algorithms and machine learning in the field of aircraft design.…”
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Texture Aware Deep Feature Map Based Linear Weighted Medical Image Fusion by Vijayarajan Rajangam, Dheeraj Kandikattu, Utkarsh, Mukul Kumar, Alex Noel Joseph Raj

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Deep Learning-Based Detection of Honey Storage Areas in <i>Apis mellifera</i> Colonies for Predicting Physical Parameters of Honey via Linear Regression by Watit Khokthong, Panpakorn Kritangkoon, Chainarong Sinpoo, Phuwasit Takioawong, Patcharin Phokasem, Terd Disayathanoowat

“…Especially, electrical conductivity exhibited statistically significant correlations with dataset performance across different dataset splits (<i>p</i> < 0.05), suggesting some potential influence of chemical composition on model accuracy. Our findings demonstrate the viability of image-based honey classification as a reliable technique for monitoring beehive productivity. …”
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Identification of Key Genes Related to Intramuscular Fat Content of Psoas Major Muscle in Saba Pigs by Integrating Bioinformatics and Machine Learning Based on Transcriptome Data by Zixia Huang, Yongli Yang, Jinhua Lai, Qiang Chen, Xiaoyi Wang, Shuyan Wang, Mingli Li, Shaoxiong Lu

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The Effectiveness of Instruction Based on the Four-Component Instructional Design (4C-ID) Model on Meaningful Learning and Critical Thinking in Sixth-Grade Students of Ardabil by Nader Heidari Raziabad, Vahid Rahimzadeh, Ali Khaleghkhah

“…Method Considering that the purpose of this research was the effectiveness of instruction based on the four-component educational design model (4C-ID) on meaningful learning and critical thinking. …”
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ARK: Aggregation of Reads by K-Means for Estimation of Bacterial Community Composition. by David Koslicki, Saikat Chatterjee, Damon Shahrivar, Alan W Walker, Suzanna C Francis, Louise J Fraser, Mikko Vehkaperä, Yueheng Lan, Jukka Corander

“…<h4>Results</h4>There has been a recent surge of interest in using compressed sensing inspired and convex-optimization based methods to solve the estimation problem for bacterial community composition. …”
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