Educação e tecnologia: o telefone celular como recurso de aprendizagem by Márcia Gorett Ribeiro Grossi, Letícia Carvalho Belchior Emerick Fernandes

“…Among digital technologies of information and communication (TDICs) currently available in the educational process, the mobile phone stands out with its various functions such as photographic and video cameras, message service, bluetooth, notepad and internet access. …”
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Simulating the dynamics of NV− formation in diamond in the presence of carbon self-interstitials by Guangzhao Chen, Joseph C. A. Prentice, Jason M. Smith

“…Abstract This study utilises linear-scaling density functional theory (DFT) and develops a new machine-learning potential for carbon and nitrogen (GAP-CN), based on the carbon potential (GAP20), to investigate the interaction between carbon self-interstitials and nitrogen-vacancy (NV) centres in diamond, focusing on their excited states and diffusion behaviour. …”
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Research on Reactive Power Optimization Strategy under the Intelligent Improvement Model of the Distribution Network by Menglin Yu

“…In order to improve the reactive power optimization effect of the distribution network, this paper combines the multiagent deep reinforcement learning algorithm to analyze the reactive power optimization strategy of the distribution network and constructs an intelligent optimization model. …”
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Intégrer les Tice à une approche cognitive de la grammaire du discours by Muriel Barbazan

“…In the light of results from psycholinguistics and cognitive psychology concerning learning models and verbal production processes, this article follows up two objectives. …”
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L’accompagnement des élèves par le tutorat entre pairs by Sylvain Connac

“…The act of learning is an individual activity facilitated by the relationship. …”
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The acceptability, feasibility, and usability of a virtual reality pain education and rehabilitation program for Veterans: a mixed-methods study by Amelia K. Mardon, Amelia K. Mardon, Amelia K. Mardon, Dianne Wilson, Hayley B. Leake, Hayley B. Leake, Daniel Harvie, Andre Andrade, K. Jane Chalmers, K. Jane Chalmers, Aaron Bowes, G. Lorimer Moseley, G. Lorimer Moseley

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Biomarkers in glioblastoma and degenerative CNS diseases: defining new advances in clinical usefulness and therapeutic molecular target by Fan Bu, Jifa Zhong, Ruiqian Guan

“…BackgroundDiscovering biomarkers is central to the research and treatment of degenerative central nervous system (CNS) diseases, playing a crucial role in early diagnosis, disease monitoring, and the development of new treatments, particularly for challenging conditions like degenerative CNS diseases and glioblastoma (GBM).MethodsThis study analyzed gene expression data from a public database, employing differential expression analyses and Gene Co-expression Network Analysis (WGCNA) to identify gene modules associated with degenerative CNS diseases and GBM. Machine learning methods, including Random Forest, Least Absolute Shrinkage and Selection Operator (LASSO), and Support Vector Machine - Recursive Feature Elimination (SVM-RFE), were used for case-control differentiation, complemented by functional enrichment analysis and external validation of key genes.ResultsNinety-five commonly altered genes related to degenerative CNS diseases and GBM were identified, with RELN and GSTO2 emerging as significant through machine learning screening. …”
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Medium-Term Hourly Electricity Tariff Forecasting Using Ensemble Models by Matrenin P.V., Arestova A.Yu., Antonenkov D.V.

“…This work aims to study the potential for medium-term forecasting of retail electricity tariff rates and develop a predictive machine learning model. Hourly data on the retail market tariffs of the Novosibirsk region (Siberia) for four years were collected, several machine learning models were applied, and an analysis of the input parameters for forecasting was carried out. …”
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Basal ganglia deep brain stimulation restores cognitive flexibility and exploration-exploitation balance disrupted by NMDA-R antagonism by Nir Asch, Noa Rahamim, Anna Morozov, Uri Werner-Reiss, Zvi Israel, Rony Paz, Hagai Bergman

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Self-utility distance as a computational approach to understanding self-concept clarity by Josué García-Arch, Christoph W. Korn, Lluís Fuentemilla

“…Abstract Self-concept stability and cohesion are crucial for psychological functioning and well-being, yet the mechanisms that underpin this fundamental aspect of human cognition remain underexplored. …”
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Substantial Heritability Underlies Fairness Norm Adaptation Capability and its Neural Basis by Yuening Jin, Dang Zheng, Ruolei Gu, Qingchen Fan, Martin Dietz, Changshuo Wang, Xinying Li, Jie Chen, Yuanyuan Hu, Yuan Zhou

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Phygitalization of educational technologies in Russia: directions, examples, problems by Andrey I. Kapterev

“…The phygitalization of educational technologies at universities has the potential to increase the subjectivity of vocational education by providing students with individual learning trajectories and a much more exciting learning experience.…”
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TRANSFORMATION OF HIGHER EDUCATION IN MODERN CONDITIONS by I.V. Boyko, O.P. Bukhanchenko, V.M. Havryliev, V.V. Bondarenko

“…At the same time, it should be noted that students are most often concerned with the following problems: poor or no Internet 30.2% of respondents; complex emotional state and psychological problems of higher education applicants 25.9; absence or lack of gadgets for learning 12.1%; a higher education student does not accept distance learning 10% of respondents; 9.2% of respondents noted that they were able to join distance learning partially or only for a certain period. …”
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Linear regressive weighted Gaussian kernel liquid neural network for brain tumor disease prediction using time series data by Firoz Khan, Sardar Irfanullah Amanullah, Shitharth Selvarajan

“…Advanced techniques, including medical imaging and machine learning, are widely used for early diagnosis. However, conventional machine learning and deep learning detection models face challenges in achieving high accuracy in brain tumor disease prediction while minimizing time complexity. …”
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PEDAGOGICAL FRAMEWORKS OF EDUCATION POLICY FOR SUSTAINABLE DEVELOPMENT OF THE EURASIAN SPACE by Zh. O. Zhilbayev, L. V. Moiseeva, M. V. Barsanova

“…These conditions are related to the basic principles proposed by the International Commission on Education that reflect target educational tendencies of the 21st century: “learning to know, learning to do, learning to live together, and learning to be”. …”
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CHIRP-Seq: FOXP2 transcriptional targets in zebra finch brain include numerous speech and language-related genes by Gregory L. Gedman, Todd H. Kimball, Lee L. Atkinson, Daniella Factor, Gabriela Vojtova, Madza Farias-Virgens, Timothy F. Wright, Stephanie A. White

“…Gene ontology analyses revealed enrichment for human speech- and language-related functions in males only, consistent with the sexual dimorphism of song learning in this species. …”
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Investigating and improving student understanding of the basics of quantum computing by Peter Hu, Yangqiuting Li, Chandralekha Singh

“…The inquiry-based learning sequences in the tutorial provide scaffolding support to help students develop a functional understanding. …”
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Weighted Hybrid Random Forest Model for Significant Feature prediction in Alzheimer’s Disease Stages by M. Rohini, D. Surendran

“…Abstract In recent studies, several machine learning and deep learning prediction models have been proposed for the early detection and classification of various stages of Alzheimer’s Disease (AD). …”
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Perception of medical students at public universities in Uganda on their education environment: a cross-sectional study by David Jolly Muganzi, Timothy Mwanje Kintu, Racheal Mukisa Nakandi, Linda Atulinda, Immaculate Kaducu Atim, Francis Mwaka, Blair Kizza, Joseph Ngonzi

“…Abstract Background The healthcare workforce is one of the six core components of a well-functioning and sufficient health system. The WHO highlights that improving education and training of the health workforce is critical to improving health systems. …”
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A self-conformation-aware pre-training framework for molecular property prediction with substructure interpretability by Jianbo Qiao, Junru Jin, Ding Wang, Saisai Teng, Junyu Zhang, Xuetong Yang, Yuhang Liu, Yu Wang, Lizhen Cui, Quan Zou, Ran Su, Leyi Wei

“…Notably, we develop a multitask pretraining framework, which incorporates four supervised and unsupervised tasks: molecular fingerprint prediction, functional group prediction using chemical prior information, 2D atomic distance prediction, and 3D bond angle prediction, covering aspects from molecular structures to functions. …”
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