Code mixing practices in Indonesian language learning by class VII teachers of Junior High School 45 of Surabaya by Sri Utami, Devito Andharu

“…It focuses on identifying the types, forms, causes, functions, and impacts of code mixing in classroom activities. …”
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VTA projections to M1 are essential for reorganization of layer 2-3 network dynamics underlying motor learning by Amir Ghanayim, Hadas Benisty, Avigail Cohen Rimon, Sivan Schwartz, Sally Dabdoob, Shira Lifshitz, Ronen Talmon, Jackie Schiller

“…Using dexterity task, calcium imaging, chemogenetic inhibiting, and geometric data analysis, we demonstrate VTA-dependent reorganization of M1 layer 2-3 during motor learning. While average activity and average functional connectivity of layer 2-3 network remain stable during learning, activity kinetics, correlational configuration of functional connectivity, and average connectivity strength of layer 2-3 neurons gradually transform towards an expert configuration. …”
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How to Measure the State of Flow in Learning? Testing of the Study-Related Flow Inventory on a Sample of Russian Students by Alina E. Ivanova, Ilya S. Denisov

“…Validation was conducted on a sample of about 600 individuals who, at the time of the survey, were in the process of learning. Confirmatory factor analysis was used to gather evidence of construct validity; the functioning of the scale for different groups of survey participants was also investigated; in addition, the item response theory was applied to assess the reliability of the scale, to assess the quality of individual scale items, and to investigate the functioning of individual categories. …”
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The Interpretative Effects of Normalization Techniques on Complex Regression Modeling: An Application to Real Estate Values Using Machine Learning by Debora Anelli, Pierluigi Morano, Francesco Tajani, Maria Rosaria Guarini

“…The performance of machine learning models depends on several factors, including data normalization, which can significantly improve its accuracy. …”
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Structural Damage Detection in the Wooden Bridge Using the Fourier Decomposition, Time Series Modeling and Machine Learning Methods by Younes Nouri, Farzad Shahabian, Hashem Shariatmadar, Alireza Entezami

“…This method encompasses the Fourier decomposition method that decompose the response of the bridge into a sequence of Fourier Intrinsic Band Functions (FIBF). These functions comprise the responses of the structure that contain inherent information of structure as well as noise from the vibrations. …”
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Machine Learning Enabled High‐Throughput Screening of 2D Ultrawide Bandgap Semiconductors for Flexible Resistive Materials by Chi Chen, Hao Wang, Houzhao Wan, Dan Sun

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Nitrogen addition enhances soil carbon and nutrient dynamics in Chinese croplands: a machine learning and nationwide synthesis by Yu Li, Yuan Li

“…This AI-derived dataset enables automated mapping of soil carbon and nutrient functions, capturing substantial spatial heterogeneity under varying environmental conditions. …”
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A Deep Learning-Based System for Automatic License Plate Recognition Using YOLOv12 and PaddleOCR by Bianca Buleu, Raul Robu, Ioan Filip

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Optimizing Kernel Extreme Learning Machine based on a Enhanced Adaptive Whale Optimization Algorithm for classification task. by ZeSheng Lin

“…EAWOA demonstrates superior optimization accuracy compared to WOA across 21 test functions, with a notable edge on certain functions. …”
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Enhancing user experience in e-learning systems: A new user-centric RESTful web services approach by Belkacem Mostefai, Tarek Boutefara, Nabila Bousbia, Amar Balla, Sahraoui Dhelim, Abderrahmane Hammia

“…The development of e-learning platforms often focuses on designing system requirements rather than users’ functional requirements, which negatively impacts user behavior, interaction, and the overall e-learning experience. …”
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TetraRNA, a tetra-class machine learning model for deciphering the coding potential derivation of RNA world by Hanrui Bai, Jie Wang, Xiaoke Jiang, Zhen Guo, Wenjing Yang, Zitian Yang, Jing Li, Changning Liu

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Unveiling the role of coagulation-related genes in acute myeloid leukemia prognosis and immune microenvironment through machine learning by Liyun Ji, Yanxia Yang, Siyue Ma

“…We further identified differentially expressed genes (DEGs) between groups and conducted functional enrichment analyses. Additionally, a prognostic model was constructed using machine learning techniques, and its prognostic ability was validated. …”
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Investigating combined hypoxia and stemness indices for prognostic transcripts in gastric cancer: Machine learning and network analysis approaches by Sharareh Mahmoudian-Hamedani, Maryam Lotfi-Shahreza, Parvaneh Nikpour

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Amelioration of Chronic Ethanol Administration‐Induced Learning and Memory Impairments by High‐Intensity Interval Training (HIIT) and Ritalin by Sara Shirazpour, Farahnaz Taheri, Gholamreza Sepehri, Mahla Zangiabadizadeh, Mostafa Zangiabadi, Najmeh Sadat Hosseini, Sara Sheikhi, Azadeh Shahrokhi Raeini, Sara Sheibani Tezerji

“…ABSTRACT Objectives The current study aimed to investigate the impacts of 8‐week high‐intensity interval training (HIIT) and Ritalin (RIT), alone and in combination, on cognitive functions and hippocampal oxidative parameters following chronic ethanol consumption in male rats. …”
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Bra.Di.P.O. and P.I.G.R.O.: Innovative Devices for Motor Learning Programs by Guido Belforte, Gabriella Eula, Silvia Sirolli, Paolo Bois, Elisabetta Geda, Federico D'Agata, Franco Cauda, Sergio Duca, Marina Zettin, Roberta Virgilio, Giuliano Geminiani, Katiuscia Sacco

“…(brain discovery pneumatic orthosis) is an MR-compatible device, designed to improve fMRI (functional magnetic resonance imaging) analysis. The two devices are presented together because both are involved in the study of new robotic treatments of patients affected by ictus or brain stroke or in some motor learning experimental investigations carried out on healthy subjects.…”
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Sustainable Material Cutting Optimization Using Deep Q-Networks: A Reinforcement Learning Approach for Resource Efficiency by Chen Linxuan

“…In my own study using KTH-TIPS dataset for model training, I have achieved promising experimental outcomes, decreasing loss functions and stabilizing total rewards, which demonstrates the model’s ability to progressively decrease prediction errors in stages and reach the best cutting patterns.…”
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Using machine learning methods to investigate the role of volatile organic compounds in non-alcoholic fatty liver disease by Chih-Hao Shen, Ruei-Hao Huang, Yaw-Kuen Li, Ta-Wei Chu, Ta-Wei Chu, Dee Pei, Dee Pei

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Real-World Robot Control Based on Contrastive Deep Active Inference With Demonstrations by Kentaro Fujii, Takuya Isomura, Shingo Murata

“…Despite significant advances in robotics and deep learning, the ability of robots to perceive and act remain far below that of humans. …”
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From bench to bedside via bytes: Multi-omic immunoprofiling and integration using machine learning and network approaches by Hanxi Xiao, Aaron Rosen, Prabal Chhibbar, Lenny Moise, Jishnu Das

“…These profiles capture different aspects of core regulatory and functional processes at different scales of resolution from molecular and cellular to organismal. …”
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Convolutional neural network (CNN) configuration using a learning automaton model for neonatal brain image segmentation. by Iran Sarafraz, Hamed Agahi, Azar Mahmoodzadeh

“…., size, length, and width of the filter in each layer along with the type of pooling functions with a reinforcement learning approach and an LA model are determined. …”
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