From rapid place learning to behavioral performance: a key role for the intermediate hippocampus. by Tobias Bast, Iain A Wilson, Menno P Witter, Richard G M Morris

“…We found that the intermediate hippocampus is necessary and largely sufficient for behavioral performance based on rapid place learning. In contrast, a residual septal pole of the hippocampus, although displaying intact electrophysiological indices of rapid information encoding (LTP, precise place-related firing, and rapid remapping), failed to sustain watermaze performance based on rapid place learning. …”
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Multi-agent based DRL with federated learning for data transmission in mobile sensor networks by M. Senthamilselvi, C. Ranjeeth Kumar

“…Different from most of its competitors, the proposed results frame the routing problem as a reinforcement learning problem with several agents. To optimize more complicated cost functions, such as the time it takes for bags to be delivered and the amount of energy used in a baggage handling system, it is possible to model every router as a deep neural network. …”
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Structuring of the disciplines «Engineering ecology» and «Safety of the Life» as a means of improving the quality of their learning by V. M. Mikhailov

“…This is due to the fact that our internal cognitive process is built systemically and at the initial (unfinished) stage of learning is able to provide perception only of structurally represented patterns. …”
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Towards an Interactive and Participatory Risk Communication: Lessons Learned from COVID-19 in Indonesia by Gregoria A. Yudarwati, Ignatius A. Putranto, Ina N. Ratriyana, Philipus Parera

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A Study on The Role of Complementary Courses in Translation and Interpreting Programs in Gaining Learning Competence by Güldane Duygu Tümer

“…First, the concepts of ‘information literacy’ and ‘information fluency’, which constitute the conceptual and theoretical framework of the study are discussed in the context of learning competence and translation competence. Then, the definitions and functions of the specified courses in the curriculum are explained and evaluated in terms of information fluency as a learning competence and translation competence.…”
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Prediction of virus-host associations using protein language models and multiple instance learning. by Dan Liu, Francesca Young, Kieran D Lamb, David L Robertson, Ke Yuan

“…Furthermore, EvoMIL identifies important proteins in the prediction task, capturing key functions involved in virus-host specificity.…”
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Deep learning-based CAD system for Alzheimer’s diagnosis using deep downsized KPLS by Syrine Neffati, Kawther Mekki, Mohsen Machhout

“…It is linked with a gradual decline in various brain functions, such as memory. Many research efforts are now directed toward non-invasive procedures for early diagnosis because early detection greatly benefits the patient care and treatment outcome. …”
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Simulation game-based learning for cognitive apprenticeship development: a focus on processing speed by Patcharabhorn Sounthornwiboon, Khwanying Sriprasertpap, Prachyanun Nilsook

“…Future implications include expanding SGBL with AR/VR and multiplayer functions to enhance engagement and applicability.…”
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Optimizing Renewable Energy Systems Placement Through Advanced Deep Learning and Evolutionary Algorithms by Konstantinos Stergiou, Theodoros Karakasidis

“…This study introduces GREENIA, a novel artificial intelligence (AI)-powered framework for optimizing RES placement that holistically integrates machine learning (gated recurrent unit neural networks with swish activation functions and attention layers), evolutionary optimization algorithms (Jaya), and Shapley additive explanations (SHAPs). …”
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Decoding motor execution and motor imagery from EEG with deep learning and source localization by Sina Makhdoomi Kaviri, Ramana Vinjamuri

“…The use of noninvasive imaging techniques has become pivotal in understanding human brain functionality. While modalities like MEG and fMRI offer excellent spatial resolution, their limited temporal resolution, often measured in seconds, restricts their application in real-time brain activity monitoring. …”
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A Graduate Level Personalized Learning Environment in the Field of f-NIRS Signal Processing by Dominique Persano Adorno, Giuseppe Costantino Giaconia

“…The development of a personalized, student-centered learning environment that encourages teamwork and inquiry-based learning aligns with the contemporary push for interdisciplinary education in bioengineering fields. …”
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Development of an Augmented Reality-Integrated Student Worksheet (LKPD) to Enhance Mathematics Learning Outcomes by Sri Murni Hidayani, Arif Muchyidin, Arif Abdul Haqq

“…Future research should focus on improving AR functionality for broader accessibility. …”
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Predictive Modeling of Compressive Strength and Slump in High-Performance Concrete Utilizing Machine Learning by Yu Yang, Ye Chen, Peng Zhang, Weining Zhang

“…The research estimates the compressive strength and slump of the HPC by advanced machine learning regression frameworks such as ADAR, SVR, and three optimizers: GOA and CBOA. …”
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Machine Learning Approaches for Data-Driven Self-Diagnosis and Fault Detection in Spacecraft Systems by Enrico Crotti, Andrea Colagrossi

“…A high-fidelity functional engineering simulator is employed to generate realistic datasets from typical onboard signals, including sensor and actuator outputs. …”
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Deep Learning‐Based Ion Channel Kinetics Analysis for Automated Patch Clamp Recording by Shengjie Yang, Jiaqi Xue, Ziqi Li, Shiqing Zhang, Zhang Zhang, Zhifeng Huang, Ken Kin Lam Yung, King Wai Chiu Lai

“…The framework integrates machine learning for anomaly detection and deep learning for multi‐class classification. …”
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Neural correlates of sensorimotor adaptation: Thalamic contributions to learning from sensory prediction error by Shirin Mahdavi, Axel Lindner, Carsten Schmidt-Samoa, Anna-Lena Müsch, Peter Dechent, Melanie Wilke

“…While the previous literature has focused on cortical and cerebellar changes, the involvement of the thalamus has received less attention. This functional magnetic resonance imaging study aims to explore the neural substrates of learning from sensory prediction errors with an additional focus on the thalamus. …”
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Accelerating crystal structure search through active learning with neural networks for rapid relaxations by Stefaan S. P. Hessmann, Kristof T. Schütt, Niklas W. A. Gebauer, Michael Gastegger, Tamio Oguchi, Tomoki Yamashita

“…We present a method that efficiently uses active learning of neural network force fields for structure relaxation, minimizing the required number of steps in the process. …”
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Identifying effective immune biomarkers in alopecia areata diagnosis based on machine learning methods by Qingde Zhou, Lan Lan, Wei Wang, Xinchang Xu

“…Machine learning methods were then used to identify three hub genes as potential diagnostic markers for AA. …”
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Google Sites as a Tool for Chemistry: Exploring the 8E Learning Cycle Approach by Nani Arum Pratiwi, Muhammad Zamhari, Pandu Ridzaniyanto

“…These findings indicate that the developed Google Sites learning media functions as an effective alternative that is in line with the principles of student-centered learning and supports students in understandingthe fundamental laws of chemistry. …”
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Advancing Enzyme-Based Detoxification Prediction with ToxZyme: An Ensemble Machine Learning Approach by Kashif Iqbal Sahibzada, Shumaila Shahid, Mohsina Akhter, Muhammad Faisal, Reham A. Abd El Rahman, Muhammad Imran, Yangyong Lv, Dongqing Wei, Yuansen Hu

“…The aaccurate prediction of enzymes with environment detoxification functions is crucial, not only to achieve a better understanding of bioremediation strategies, but also to alleviate environmental pollution. …”
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