Construction and demolition waste material library based on vision systems dataZenodo by Maria Teresa Calcagni, Giovanni Salerno, Gloria Cosoli, Giuseppe Pandarese, Gian Marco Revel

“…The data obtained were standardised and organised in a format compatible with the main statistical analysis and machine learning tools to facilitate their integration into predictive models and decision-making processes. The article describes in detail the library structure, data collection protocols, and practical applications in the fields of waste management and sustainable construction. …”
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C2 pars interarticularis length on the side of high-riding vertebral artery with implications for pars screw insertion by Tomasz Klepinowski, Miszela Kałachurska, Michał Chylewski, Natalia Żyłka, Dominik Taterra, Kajetan Łątka, Bartłomiej Pala, Wojciech Poncyljusz, Leszek Sagan

“…Sample size was estimated with pwr package and C2PIL was measured. Cut-off value and predictive statistics of C2PIL for HRVA were computed with cutpointr package. …”
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AUTOMATIC CONSTRUCTION METHODS OF ABSTRACTS ON THE BASIS OF THE TEXTS FREQUENCY ANALYSIS by F. I. Tretyakov, L. V. Serebryanaya

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An Intelligent Method for C++ Test Case Synthesis Based on a Q-Learning Agent by Serhii Semenov, Oleksii Kolomiitsev, Mykhailo Hulevych, Patryk Mazurek, Olena Chernyk

“…An explicit synthesis algorithm constructs new test cases by selecting API calls from a learned policy encoded in a Q-table. …”
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A Novel Fault Diagnosis of Induction Motor by Using Various Soft Computation Techniques: BESO-RDFA by Kapu V. Sri Ram Prasad, K. Dhananjay Rao, Guruvulu Naidu Ponnada, Umit Cali, Taha Selim Ustun

“…The established hybrid forecast scheme signifies the combined execution of Bald-Eagle- Search-Optimization (BESO) and Random-Decision-Forest-Algorithm (RDFA), called as BESO-RDFA prediction scheme. …”
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Graph convolution network for fraud detection in bitcoin transactions by Ahmad Asiri, K. Somasundaram

“…We have run different algorithms for predicting illicit transactions like Logistic Regression, Long Short Term Memory, Support Vector Machine, Random Forest, and a variation of Graph Neural Networks, which is called Graph Convolution Network (GCN). …”
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Detection of Transformer Faults: AI-Supported Machine Learning Application in Sweep Frequency Response Analysis by Hakan Çuhadaroğlu, Yılmaz Uyaroğlu

“…Among them, the Gradient Boost Classifier showed the best performance in classifying faults. This algorithm accurately predicted the health status of transformers by learning from large datasets. …”
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Land cover change mitigated 20 % of the total increased evapotranspiration in tropical Lancang-Mekong River Basin during 2001–2019 by Houbing Chen, Yaoliang Chen, Lamin R. Mansaray, Longwei Li, Shusen Wang

“…Study focus: Accurately assessing evapotranspiration (ET) change derived from land cover changes (LCCs) is challenging in tropical regions due to the large bias in existing ET products and the difficulty in improving the ET al.gorithm for tropical ecosystems. This study quantified the LCCs-driven ET in the TLMRB from 2001 to 2019 by using scenario simulations based on an improved MOD16 algorithm. …”
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Coastal Urban Ecological Security Pattern Identification Integrating Land Subsidence Factors: A Deep Learning-Based Case Study of Zhuhai City by Yuan Shaoxiong, Gong Qinghua, Ye Yuyao, Wang Jun, Hao Yinlei, Zhang Yaze, Liu Bowen

“…Results showed that the MLP model achieved an average prediction accuracy of 84.5% with an F1-score of 0.844, demonstrating the feasibility of deep learning approaches in ESP construction. …”
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External phantom-based validation of a deep-learning network trained for upscaling of digital low count PET data by Anja Braune, René Hosch, David Kersting, Juliane Müller, Frank Hofheinz, Ken Herrmann, Felix Nensa, Jörg Kotzerke, Robert Seifert

“…Conclusions Phantom-based validation of AI-based algorithms allows for a detailed assessment of the performance, limitations, and generalizability of deep-learning based algorithms for PET image enhancement. …”
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Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers by Wentong Li, Yiyi Zhang, Chuanhong Li, Mingyang Jiang, Dong Wang, Luomeng Chao, Luomeng Chao, Luomeng Chao, Yuxia Yang

“…Immune analysis revealed that this molecular chaperone axis modulates neuroinflammation by suppressing naive B cell differentiation (61% reduction) and activating Tregs (55.53% increase). …”
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Differing Effects of Alcohol Use on Epigenetic and Brain Age in Adult Children of Parents with Alcohol Use Disorder by Jamie L. Scholl, Kami Pearson, Kelene A. Fercho, Austin J. Van Asselt, Noah A. Kallsen, Erik. A. Ehli, Kari N. Potter, Kathleen A. Brown-Rice, Gina L. Forster, Lee A. Baugh

“…We examined structural brain differences and applied machine learning algorithms to predict biological brain and DNA methylation ages to investigate differences and determine any accelerated aging between these groups. …”
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Extended homogeneous field correction method based on oblique projection in OPM-MEG by Fulong Wang, Fuzhi Cao, Yujie Ma, Ruochen Zhao, Ruonan Wang, Nan An, Min Xiang, Dawei Wang, Xiaolin Ning

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Investigating factors influencing quality of life in thyroid eye disease: insight from machine learning approaches by Haiyang Zhang, Shuo Wu, Lehan Yang, Chengjing Fan, Huifang Chen, Hui Wang, Tianyi Zhu, Yinwei Li, Jing Sun, Xuefei Song, Huifang Zhou, Terry J Smith, Xianqun Fan

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Exploring high entropy alloys: A review on thermodynamic design and computational modeling strategies for advanced materials applications by Peter Ifeolu Odetola, Bukola Joseph Babalola, Ayodeji Ebenezer Afolabi, Ufoma Silas Anamu, Emmanuel Olorundaisi, Mutombo Christian Umba, Thabang Phahlane, Olusoji Oluremi Ayodele, Peter Apata Olubambi

“…By dissecting the foundational ''four core effects'' intrinsic to HEAs—high entropy, sluggish diffusion, severe lattice distortion, and cocktail effect—we illuminate the path towards predictable and tailored material properties. Central to the present discourse is the application of valence electron concentration (VEC) and cutting-edge strategies, including the CALculation of PHAse Diagrams (CALPHAD) method, first-principles approach, and machine-learning algorithms, which collectively empower the prediction and understanding of HEA behavior. …”
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Hyperspectral Inversion of Soil Cu Content in Agricultural Land Based on Continuous Wavelet Transform and Stacking Ensemble Learning by Kai Yang, Fan Wu, Hongxu Guo, Dongbin Chen, Yirong Deng, Zaoquan Huang, Cunliang Han, Zhiliang Chen, Rongbo Xiao, Pengcheng Chen

“…Therefore, the rapid and accurate prediction of heavy metal content in agricultural soil is crucial for environmental protection and soil remediation. …”
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Research on short-term power load forecasting based on deep reinforcement learning with multiple intelligences by Tianyun Luo, Dunlin Zhu, Jinming Liu, Sheng Yang, Jinglong He, Yuan Fu

“…Therefore, to realize accurate and efficient prediction of short-term power loads, a short-term power load prediction method based on multi-intelligence deep reinforcement learning is proposed to address the complex nonlinear characteristics of load data. …”
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Recommendations for All-Round Newborns and Infants Hearing Screening in Russian Federation by S. S. Chibisova, G. S. Tufatulin, L. S. Namazova-Baranova, I. V. Koroleva, E. R. Tsygankova, T. G. Markova, N. N. Volodin, G. A. Tavartkiladze

“…The prevalence rate of these factors in Russian population according to the literature and official statistics was studied. Evaluation of predictive significance of risk factors was based on retrospective data in the cohort of 393 children born in 2012 (280 with hearing loss, 113 healthy) examined in National Research Centre for Audiology and Hearing Rehabilitation at the age of 0–4 years. …”
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Modelling and Optimisation of Hysteresis and Sensitivity of Multicomponent Flexible Sensing Materials by Kai Chen, Qiang Gao, Yijin Ouyang, Jianyong Lei, Shuge Li, Songxiying He, Guotian He

“…Finally, the optimal solution of the prediction model is obtained using the multi-objective RIME (MORIME) algorithm. …”
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Binary Particle Swarm Optimization with Manta Ray Foraging Learning Strategies for High-Dimensional Feature Selection by Jianhua Liu, Yuxiang Chen, Shanglong Li

“…The results demonstrate that the proposed BPSO-MRFL algorithm achieves enhanced classification accuracy and feature reduction compared to traditional feature selection methods. …”
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