Reinforced liquid state machines—new training strategies for spiking neural networks based on reinforcements by Dominik Krenzer, Martin Bogdan, Martin Bogdan, Martin Bogdan

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Estimation of mass loss under wear test of nanoclay-epoxy nanocomposite using response surface methodology and artificial neural networks by Manjunath Shettar, Ashwini Bhat, Nagaraj N. Katagi

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Application of Machine Learning for Target Selection and Acid Treatment Design by I. I. Mannanov, M. A. Varfolomeev, G. R. Ganieva, A. R. Gimaeva, R. R. Giniyatullin

“…The problem of predicting the reaction kinetics of acid systems by processing an array of laboratory data using machine learning methods, specifically linear regression and random forest methods, was discussed. …”
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Machine Learning Decision Support for Macronutrients in Neonatal Parenteral Nutrition by Setareh Derakhshandara, Valentina Franzoni, Daniele Mezzetti, Valentina Poggioni

“…Determining the appropriate amount and composition of parenteral nutrition bag for each infant is a complex and individualized process. …”
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Deep Learning for Spectroscopic X‐ray Nano‐Imaging Denoising by Tianyu Fu, Kai Zhang, Qingxi Yuan, Jizhou Li, Piero Pianetta, Yijin Liu

“…To address this issue, a deep learning‐based algorithm is developed for suppressing the image noise, grounded in self‐supervised learning principles. …”
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Determinants Factors in Predicting Life Expectancy Using Machine Learning by B. Kouame Amos, I. V. Smirnov

“…Therefore, various machine learning models have been developed to predict life expectancy.   …”
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The Impact of Digital Devices on Children’s Health: A Systematic Literature Review by Valentina Presta, Alessandro Guarnieri, Fabiana Laurenti, Salvatore Mazzei, Maria Luisa Arcari, Prisco Mirandola, Marco Vitale, Michael Yong Hwa Chia, Giancarlo Condello, Giuliana Gobbi

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Predicting metabolite response to dietary intervention using deep learning by Tong Wang, Hannah D. Holscher, Sergei Maslov, Frank B. Hu, Scott T. Weiss, Yang-Yu Liu

“…Deep learning methods dedicated to such tasks are still lacking. …”
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The Role of the Visual Versus Verbal Modality in Learning Novel Verbs by Maria Luisa Lorusso, Laura Pigazzini, Laura Zampini, Michele Burigo, Martina Caccia, Anna Milani, Massimo Molteni

“…Thus, response modality could be either explicit or implicit, and either congruent or incongruent with respect to learning modality. Methods: In Experiment 1, 100 children from grade 1 to 5 were asked to explain the meaning of verbs introduced via verbal or visual instances. …”
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Detection of microplastics stress on rice seedling by visible/near-infrared hyperspectral imaging and synchrotron radiation Fourier transform infrared microspectroscopy by Chaojie Wei, Hongxin Xie, Hongxin Xie, Hongxin Xie, Wei Wang, Yu-Feng Li, Yu-Feng Li, Yu-Feng Li, Xiaorong Wang, Ziwei Song, Fajun Chen

“…Meanwhile, SR-FTIR spectroscopy was used to investigate compositional changes in both leaf lamina and veins, and two-dimensional correlation spectroscopy (2DCOS) was employed to reveal the sequential interactions among molecular components.DiscussionIn conclusion, the combination of spectral technology and deep learning to capture the physiological and biochemical reactions of leaves could provide a rapid and interpretable method for detecting rice seedlings under MPs stress. …”
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Computed tomography-based radiomics predicts prognostic and treatment-related levels of immune infiltration in the immune microenvironment of clear cell renal cell carcinoma by Shiyan Song, Wenfei Ge, Xiaochen Qi, Xiangyu Che, Qifei Wang, Guangzhen Wu

“…Therefore, the CT-based ML achieved good predictive results in predicting immune infiltration in ccRCC, with the ExtraTrees machine learning algorithm being optimal. …”
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Prediction of drought-flood prone zones in inland mountainous regions under climate change with assessment and enhancement strategies for disaster resilience in high-standard farml... by Yongheng Shen, Qingxia Guo, Zhenghao Liu, Yanli Shen, Yikun Jia, Yuehan Wei

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Plant photosynthesis in basil (C3) and maize (C4) under different light conditions as basis of an AI-based model for PAM fluorescence/gas-exchange correlation by Isabell Pappert, Stefan Klir, Luca Jokic, Celine Ühlein, Khanh Tran Quoc, Ralf Kaldenhoff

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Zero-Shot Remote Sensing Scene Classification Based on Automatic Knowledge Graph and Dual-Branch Semantic Correlation Supervision by Chao Wang, Jiajun Yang, Tanvir Ahmed, Yang Zhao, Tong Zhang, Bing Sun, Tao Xie, Jie Wang, Tianyu Chen

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Association between composite dietary antioxidant index and cognitive function impairment in the elderly: evidence from NHANES 2011–2014 by Yingying Qian, Qiang Liu, Tianlang Li

“…ObjectiveAntioxidant-rich diets are posited as protective factors against cognitive function impairment. The Composite Dietary Antioxidant Index (CDAI) serves as a pivotal measure of antioxidant intake, yet its relationship with cognitive function impairment has been sparsely investigated. …”
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OpenForest: a data catalog for machine learning in forest monitoring by Arthur Ouaknine, Teja Kattenborn, Etienne Laliberté, David Rolnick

“…We hope to encourage collaborations among scientists, fostering the sharing and exploration of diverse datasets through the application of machine learning methods for large-scale forest monitoring. …”
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Irrigated rice-field mapping in Brazil using phenological stage information and optical and microwave remote sensing by Andre Dalla Bernardina Garcia, MD Samiul Islam, Victor Hugo Rohden Prudente, Ieda Del’Arco Sanches, Irene Cheng

“…Irrigated rice-field mapping methodologies have been rapidly evolving as a result of advanced remote sensing (RS) technology. However, current methods rely on extensive time-series data and a wide range of multi-spectral bands. …”
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An improved deep learning approach for automated detection of multiclass eye diseases by Feudjio Ghislain, Saha Tchinda Beaudelaire, Romain Atangana, Tchiotsop Daniel

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Scene classification-assisted deep learning for crack detection in asphalt pavements by Hiromu Tanaka, Kazuma Shibano, Tetsuya Suzuki

“…Traditional visual inspection methods face challenges due to subjective judgment, shortage of qualified engineers, and budget constraints. …”
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Imitation-Reinforcement Learning Penetration Strategy for Hypersonic Vehicle in Gliding Phase by Lei Xu, Yingzi Guan, Jialun Pu, Changzhu Wei

“…To enhance the penetration capability of hypersonic vehicles in the gliding phase, an intelligent maneuvering penetration strategy combining imitation learning and reinforcement learning is proposed. Firstly, a reinforcement learning penetration model for hypersonic vehicles is established based on the Markov Decision Process (MDP), with the design of state, action spaces, and composite reward function based on Zero-Effort Miss (ZEM). …”
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