Do pensamento computacional desplugado ao plugado no processo de aprendizagem da matemática / Computational thinking unplugged to plugged in the mathematic learning process by Ingrid Santella, Adriana Aparecida de Lima Terçariol, Elisangela Aparecida Bulla Ikeshoji

“…. /// This article is an excerpt from the dissertation entitled «Computational thinking in the mathematics learning process in the final years of elementary school», linked to the Master Program in Management and Educational Practices (PROGEPE) at Nove de Julho University, in particular, to the Research and intervention line learning methodology and teaching pratices (LIMAPE). …”
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Overview of Computational Toxicology Methods Applied in Drug and Green Chemical Discovery by Jose I. Bueso-Bordils, Gerardo M. Antón-Fos, Rafael Martín-Algarra, Pedro A. Alemán-López

“…Currently, there are numerous commercially available and free web-based programs for toxicity prediction, which can be used to construct various predictive models. …”
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Unveiling the role of IL7R in metabolism-associated fatty liver disease leading to hepatocellular carcinoma through transcriptomic and machine learning approaches by Priyadharshini Annadurai, Arnold Emerson Isaac

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Microcontroller Unit-Based Gesture Recognition System by Jakub Grabarczyk, Agnieszka Lazarowska

“…This article describes the design, construction, and programming of a microcontroller-based system, which uses hand gestures with machine learning algorithms to control an unmanned aerial vehicle (UAV). …”
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The Contribution of Linguistic Distance to L3 Learning Motivation: A Cross-L2 Comparison of University English as a Foreign Language Learners by Xuan Wang, Yilin Zhu

“…In this study, we respond to calls for more research on the motivation to learn a third language (L3), especially regarding how this motivation is influenced by linguistic distance in various second language (L2) contexts. …”
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Designing an overview Theory of Change for a multi-component support community for people affected by rare dementia by Mary Pat Sullivan, Paul M. Camic, Emma Harding, Joshua Stott, Gill Windle, Ian Davies-Abbott, Sebastian J. Crutch

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Machine Learning Modeling for Building Energy Performance Prediction Based on Simulation Data: A Systematic Review of the Processes, Performances, and Correlation of Process-Relate... by Damla Kömürcü, Ecem Edis

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Arduino-Based Mobile Robotics for Fostering Computational Thinking Development: An Empirical Study with Elementary School Students Using Problem-Based Learning Across Europe by Rolando Barradas, José Alberto Lencastre, Salviano Pinto Soares, António Valente

“…The eBooks serve as a guide to the construction and programming of a small Arduino-based robot. …”
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Identification of cellular senescence-associated genes for predicting the diagnosis, prognosis and immunotherapy response in lung adenocarcinoma via a 113-combination machine learn... by Ting Ge, Guixin He, Qian Cui, Shuangcui Wang, Zekun Wang, Yingying Xie, Yuanyuan Tian, Juyue Zhou, Jianchun Yu, Jinmin Hu, Wentao Li

“…Subsequently, we developed a novel machine learning framework that incorporated 12 machine learning algorithms and their 113 combinations to construct a LUAD CS-related signature (LUAD-CSRS), which were assessed in both training and validation cohorts. …”
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SOME PROBLEMS OF THE ORGANIZATION OF NETWORK INTERUNIVERSITY INTERACTION by E. K. GITMAN, M. B. GITMAN, V. Yu. STOLBOV, A. P. CHUGUNOV

“…Solutions are based on network education program being developed in module and competence form and individual education program constructed with the preference to student wishes. …”
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M3S-GRPred: a novel ensemble learning approach for the interpretable prediction of glucocorticoid receptor antagonists using a multi-step stacking strategy by Nalini Schaduangrat, Hathaichanok Chuntakaruk, Thanyada Rungrotmongkol, Pakpoom Mookdarsanit, Watshara Shoombuatong

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Integrated machine learning identifies disulfidptosis-related and ferroptosis-related genes to evaluate survival prognosis and treatment efficacy in kidney renal clear cell carcino... by Yuan Xiang, Zijian Zhou, Tong Mu, Shunyao Zhang, Lei Xie, Yajie Zhou, Wenxiong Zhang, Liuxiang Fu

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Predicting student achievement through peer network analysis for timely personalization via generative AI by Ivica Pesovski, Petar Jolakoski, Vladimir Trajkovik, Zuzana Kubincova, Michael A. Herzog

“…The neutral group was given the option to request specific learning materials and self-assessment quizzes on demand to address their individual learning needs. …”
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Analyzing the compressive performance of lightweight foamcrete and parameter interdependencies using machine intelligence strategies by Wang Guoyuan, Fan Wenbo, Shi Qingbin, Luo Yingqi

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Modalités de collaboration entre étudiants et constitution d'une communauté dans une activité à distance by Charlotte Dejean-Thircuir

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Research on Curriculum System for Academic Doctoral Training in Teacher Education: A Case Study of Michigan State University by ZHAO Ying, LIU Yanren

“…To achieve this goal, the program constructed a high-quality "4+1" modular curriculum system. …”
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從工具示能性與關係行動主體之觀點 探討偏鄉教育系統賦能策略之研究 Investigating the Construction of Empowerment Action Models in Remote Educational Systems Through the Lenses of Tool Affordance and Relational Age... by 陳佩英 Peiying Chen, 洪琴雯 Chin-Wen Hung

“…This was the practical and creative value of tools and the key cognition for the team’s continuous professional learning. Continuous Inquiry Cycles Were an Effective Way to Construct Rural Education System Empowerment Due to the Complex and Rapidly Changing Nature of Rural Education Systems Learning from feedback in practice and ongoing discussion was particularly important. …”
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Research on Reservoir Identification of Gas Hydrates with Well Logging Data Based on Machine Learning in Marine Areas: A Case Study from IODP Expedition 311 by Xudong Hu, Wangfeng Leng, Kun Xiao, Guo Song, Yiming Wei, Changchun Zou

“…This study explores the logging identification method of marine GHRs based on machine learning (ML) according to the logging data of the International Ocean Drilling Program (IODP) Expedition 311. …”
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Pretreatment CT-Based Machine Learning Radiomics Model Predicts Response in Inoperable Stage III NSCLC Treated with Concurrent Radiochemotherapy Plus PD-1 Inhibitors by Ya Li Bachelor, Min Zhang Bachelor, Yong Hu MM, Bo Du Bachelor, Youlong Mo Bachelor, Tianchu He MM, Mingdan Zhao Bachelor, Benlan Li Bachelor, Ji Xia Bachelor, Zhongjun Huang Bachelor, Fangyang Lu MD, Zhen Huang Bachelor, Bing Lu MD, Jie Peng MD

“…Results Based on the performance of radiomics models constructed by various machine learning algorithms in the prospective validation set, the LR with the highest AUC value (AUC: 90.00%) was finally selected, which also performed well in the independent test set (AUC: 84.96%). …”
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MRI-based deep learning and radiomics for predicting the efficacy of PD-1 inhibitor combined with induction chemotherapy in advanced nasopharyngeal carcinoma: A prospective cohort... by Yiru Wang, Fuli Chen, Zhechen Ouyang, Siyi He, Xinling Qin, Xian Liang, Weimei Huang, Rensheng Wang, Kai Hu

“…Aim: To establish and evaluate a model for predicting the efficacy of programmed death-1 (PD-1) inhibitor combined with GP (gemcitabine and cisplatin) induction chemotherapy based on deep learning features (DLFs) and radiomic features. …”
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