Learning Materials as FAIR Digital Objects: A Shared Methodology for Training in H2IOSC by Giulia Pedonese, Francesca Fontini, Roberta Ottaviani, Federico Boschetti, Alessia Spadi, Lucia Francalanci, Alessia Scognamiglio, Pietro Restaneo, Antonina Chaban, Jana Striova, Laura Benassi

“…After describing the teaching strategy (Section 2) and the application of the Skills4EOSC FAIR-by-Design methodology to pre-existing learning materials (Section 3), the paper describes the process of designing two platforms with functionalities consistent with the requirements of learning objects, taking as an example the CLARIN course Introduction to Language Data: Standards and Repositories translated and adapted in H2IOSC (Section 4).…”
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Learning compositional sequences with multiple time scales through a hierarchical network of spiking neurons. by Amadeus Maes, Mauricio Barahona, Claudia Clopath

“…Sequential behaviour is often compositional and organised across multiple time scales: a set of individual elements developing on short time scales (motifs) are combined to form longer functional sequences (syntax). Such organisation leads to a natural hierarchy that can be used advantageously for learning, since the motifs and the syntax can be acquired independently. …”
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Toward aitiopoietic cognition: bridging the evolutionary divide between biological and machine-learned causal systems by Tomas Veloz

“…We examine and compare autopoietic systems (biological organisms) and machine learning systems (MLSs) highlighting crucial differences in how causal reasoning emerges and operates. …”
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Competing with Media Richness: Cognitive and Psychological Endowment Effects as the Fundamentally Pervasive Perspective of Learning Performance by Sumiyana Sumiyana, Muhammad Adlin Saputra

“…The authors find that the cognitive and psychological endowments’ functional superiority dominates the learning achievement compared to the MR role types. …”
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Element-specific estimation of background mutation rates in whole cancer genomes through transfer learning by Farideh Bahari, Reza Ahangari Cohan, Hesam Montazeri

“…Existing methods rely on various genomic regions and features for BMR estimation but lack a model that integrates both intergenic intervals and functional genomic elements on a comprehensive set of genomic features. …”
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A Learning Probabilistic Boolean Network Model of a Smart Grid with Applications in System Maintenance by Pedro Juan Rivera Torres, Chen Chen, Jaime Macías-Aguayo, Sara Rodríguez González, Javier Prieto Tejedor, Orestes Llanes Santiago, Carlos Gershenson García, Samir Kanaan Izquierdo

“…This idea was tested in a Probabilistic Boolean Network model of the WSCC nine-bus system that incorporates Intelligent Power Routers on every bus. The model learned the equality and negation functions in the different experiments performed. …”
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High-throughput screening of CO2 cycloaddition MOF catalyst with an explainable machine learning model by Xuefeng Bai, Yi Li, Yabo Xie, Qiancheng Chen, Xin Zhang, Jian-Rong Li

“…The high porosity and tunable chemical functionality of metal-organic frameworks (MOFs) make it a promising catalyst design platform. …”
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Passive Anti-amyloid Beta Monoclonal Antibodies: Lessons Learned over Past 20 Years by Alexandra Wicker, Jahnavi Shriram, Boris Decourt, Marwan Noel Sabbagh

“…Abstract Alzheimer’s disease (AD) is a neurodegenerative disorder that significantly impairs cognitive and functional abilities, placing a substantial burden on both patients and caregivers. …”
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Human neural organoid microphysiological systems show the building blocks necessary for basic learning and memory by Dowlette-Mary Alam El Din, Leah Moenkemoeller, Alon Loeffler, Forough Habibollahi, Jack Schenkman, Amitav Mitra, Tjitse van der Molen, Lixuan Ding, Jason Laird, Maren Schenke, Erik C. Johnson, Brett J. Kagan, Thomas Hartung, Lena Smirnova

“…Neural organoids showed synapse formation, glutamatergic and GABAergic receptor expression, immediate early gene expression basally and evoked, functional connectivity, criticality, and synaptic plasticity in response to theta-burst stimulation. …”
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Machine learning‐driven design of dual‐band antennas using PGGAN and enhanced feature mapping by Lung‐Fai Tuen, Ching‐Lieh Li, Yu‐Jen Chi, Chien‐Ching Chiu, Po Hsiang Chen

“…Abstract This paper presents a systematic antenna design methodology that integrates machine learning, leveraging the progressive growth technique of Progressive Growing of GANs (PGGAN) to generate images of various dual‐band PIFA‐like antenna structures. …”
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An Improved Deep Learning Model for Online Tool Condition Monitoring Using Output Power Signals by Lang Dai, Tianyu Liu, Zhongyong Liu, Lisa Jackson, Paul Goodall, Changqing Shen, Lei Mao

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Machine learning and multi-omics analysis reveal key regulators of proneural–mesenchymal transition in glioblastoma by Can Xu, Jin Yang, Huan Xiong, Xiaoteng Cui, Yuhao Zhang, Mingjun Gao, Lei He, Qiuyue Fang, Changxi Han, Wei Liu, Yangyang Wang, Jin Zhang, Ying Yuan, Zhaomu Zeng, Ruxiang Xu

“…The Lasso, Cox, and Step machine learning algorithms were used to construct and screen the optimal risk assessment prognostic model. …”
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Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-Dimensional Tokens by Vittorio Erba, Emanuele Troiani, Luca Biggio, Antoine Maillard, Lenka Zdeborová

“…Statistical physics provides powerful tools to study the functioning of learning with neural networks and has played a recognized role in the development of modern machine learning. …”
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Deep Learning-Based Gain Estimation for Multi-User Software-Defined Radios in Aircraft Communications by Viraj K. Gajjar, Kurt L. Kosbar

“…It may be helpful to integrate multiple aircraft communication and navigation functions into a single software-defined radio (SDR) platform. …”
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Intelligent analysis of the quality of educational content on statistics of student performance in the learning management system "Scorina" by A. G. Savenko

“…A mathematical model of educational process of learning management system "Scorina", and approach to assessing the knowledge of students are presented.The implementation of functional diagram and the algorithm of the module for the intelligent analysis of the quality of educational content of learning management system "Scorina" is proposed. …”
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The Design of Effective ICT-Supported Learning Activities: Exemplary Models, Changing Requirements, and New Possibilities by Cameron Richards

“…To the extent that such approaches go beyond and transform traditional "transmission" models of teaching and formal lesson planning, this paper investigates the changing requirements and new possibilities represented by the challenge of integrating ICTs in education in a way which at the same time connects more effectively with both the specific contents of the curriculum and the various stages and elements of the learning process. Case studies from teacher education foundation courses provide an exemplary focus of inquiry in order to better link relevant new theories or models of learning with practice, to build upon related learner-centered strategies for integrating ICT resources and tools, and to incorporate interdependent functions of learning as information access, communication, and applied interactions. …”
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Validation of a Machine Learning Model for Certification Using Symbolic Regression and a Behaviour Envelope by Moritz Neumaier, Marcel Anselment, Stephan Rudolph

“…Aviation is highly regulated with a strong focus on safety. If machine learning models are to be used in aviation, their correctness must be proven as part of the certification process. …”
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A Short Review: Tribology in Machining to Understand Conventional and Latest Modeling Methods with Machine Learning by Seisuke Kano

“…Modern engineering materials often incorporate functional materials in metastable states, such as composites of dissimilar materials, rather than conventional stable-phase materials. …”
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Using the Trala application for learning to play the violin: A study of techniques, which affect listeners by Wei Liu

“…Mastering the violin depends on the possibility of achieving a higher dynamic accuracy of sounds, which requires high-quality learning approaches. The purpose of this paper is to explore the possibilities of using the Trala application to develop violin-playing skills, considering the techniques that influence listeners. …”
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Harnessing Deep Learning With AlexNet for Tomato Leaf Disease Detection in the Indian Himalayan Terrain by Ruchika Sharma, Sameena Naaz, Pankaj Vaidya

“…Agriculture is essential for living in the Indian Himalayan region (IHR), as it functions as the main occupation and source of income. …”
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