Biomarkers of Suicidal Ideation in Depression: Insights From VMHC Analysis and Machine Learning by Wang X, Liu F, Hu X, Zhang Q, Guan X, Wu J, Long X, Lu Z

“…VMHC values were calculated to assess interhemispheric functional connectivity. Brain regions with significant differences between the groups were identified. …”
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EFL Learners’ Perceptions About Language Learning and Culture When Using Telecollaboration by Natalia Ramírez-Lizcano, María Alejandra Cabrera-Tovar

“…The findings show students’ understanding of the nature of language situated within functional and humanistic perspectives. Furthermore, participants alluded to the importance of language learning as a means to understand the scope of culture and cultural identity.…”
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Learning to Write and Writing to Write: Composition Instruction from Habit Formation to Cognition by Amin Kebieche

“…Indeed, the shift was from a focus on syntactic maturity and grammatical accuracy at the sentence level, to a focus on the different rhetorical functions at the discourse level. …”
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Envisioning Answers: Unleashing Deep Learning for Visual Question Answering in Artistic Images by Erfan Zolghadriha, Kazim Fouladi-Ghaleh, Pouya Ardehkhani

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Crossing the Valley of Death in Spinal Cord Injury: Learning from Successful Translators by Vieri Failli, Stephen M. Strittmatter, Martin E. Schwab, Aileen J. Anderson, Angela Ruban, Hassan Al-Ali, Armin Curt, Adrien Cohen, Jane T.C. Hsieh

“…This article reflects the translational journey of five SCI scientists who have encountered similar and different scenarios while striving to launch or complete a clinical trial. Learning from these experiences has identified lessons learned and gaps, particularly with respect to funding and support for SCI translation.…”
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Identification of biomarkers and target drugs for melanoma: a topological and deep learning approach by Xiwei Cui, Xiwei Cui, Jipeng Song, Qingfeng Li, Jieyi Ren

“…Additionally, deep learning models were implemented to predict drug-target interactions, leveraging molecular features derived from network analyses.ResultsSignificant topological divergences emerged between nevi and melanoma networks, with dominant functional modules transitioning from cell cycle regulation in benign lesions to DNA repair and cell migration pathways in malignant tumors. …”
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Development of Machine Learning Atomistic Potential for Molecular Simulation of Hematite–Water Interfaces by Mozhdeh Shiranirad, Niall J. English

“…Utilizing neural networks augmented with a pool-based active learning sampling method, a potential energy surface (PES) is developed for the accurate modeling of interfaces of hematite iron oxide and water, fitting the much more expensive density functional theory (DFT). …”
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The Importance of Being Uncertain―or What I Learned From Writing History With Rumors by Sebastian Jobs

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Escape Rooms for Learning: A Case Study of a Collaborative, Interdisciplinary Project by Holly Surbaugh, Melissa Jones

“…This case study documents a two-year, multiphase project piloting two approaches to using escape rooms for learning. During the first phase (“Escape Room as an Assignment”), instruction librarians embedded with two classes to develop functional inputs for the second phase (“Escape Room as a Classroom/Lab”), which entailed using a library escape room to teach information literacy. …”
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Warning on every puff: Learning from Canada's innovative tobacco control strategy by Elakeya Udhaya, Snehasish Tripathy, Ankita Mathur, Vini Mehta, Luca Fiorillo

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The Neural Correlates and Behavioral Impact of Peripheral Noise Electrical Stimulation on Motor Learning by Li-Wei Chou, Man-Wai Kou, Hui-Min Lee, Felipe Fregni, Vincent Chen, Chung-Lan Kao

“…While research has demonstrated that peripheral electrical stimulation with noise waveform improves motor performance and functions, the effects of noise electrical stimulation on motor learning remain unknown. …”
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Unified pre- and postsynaptic long-term plasticity enables reliable and flexible learning by Rui Ponte Costa, Robert C Froemke, P Jesper Sjöström, Mark CW van Rossum

“…Although it is well known that long-term synaptic plasticity can be expressed both pre- and postsynaptically, the functional consequences of this arrangement have remained elusive. …”
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Adaptive Particle Swarm Optimization with Landscape Learning for Global Optimization and Feature Selection by Khalil Abbal, Mohammed El-Amrani, Oussama Aoun, Youssef Benadada

“…Our approach involves adaptively updating the cognitive and acceleration factors based on the estimation of the ruggedness factor using a machine learning-based method and a deterministic way. We tested them on global optimization functions and the feature selection problem. …”
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Optimal estimates of trace distance between bosonic Gaussian states and applications to learning by Lennart Bittel, Francesco Anna Mele, Antonio Anna Mele, Salvatore Tirone, Ludovico Lami

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An Oil Painters Recognition Method Based on Cluster Multiple Kernel Learning Algorithm by Zhifang Liao, Le Gao, Tian Zhou, Xiaoping Fan, Yan Zhang, Jinsong Wu

“…This paper proposes a cluster multiple kernel learning algorithm, which extracts oil painting features from three aspects: color, texture, and spatial layout, and generates multiple candidate kernels with different kernel functions. …”
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Learning from Traditional House Architecture During the Covid-19 Pandemic Process by Emriye Kazaz

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Effects of described demonstrator ability on brain and behavior when learning from others by Ida Selbing, Nina Becker, Yafeng Pan, Björn Lindström, Andreas Olsson

“…Forty-five participants performed an observational learning task while undergoing functional magnetic resonance imaging (fMRI). …”
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Conceptual images and learning obstacles in exponentiation and logarithms: A hermeneutic phenomenological analysis by Yuvita Andriani Kusumadewi, Riki Andriatna

“…The concept of exponentials and logarithms is one of the essential concepts in mathematics as part of transcendent functions. However, students' understanding of these two concepts has yet to be fully mastered, so there are still errors in solving problems related to these two concepts. …”
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Enhancing Global Optimization through the Integration of Multiverse Optimizer with Opposition-Based Learning by Vu Hong Son Pham, Nghiep Trinh Nguyen Dang, Van Nam Nguyen

“…The effectiveness of iMVO is assessed through a series of tests involving both classical and IEEE CEC 2021 benchmark functions, demonstrating competitive performance against established algorithms. …”
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Network Analysis on the Symmetric Coordination in a Reinforcement-Learning-Based Minority Game by Chunqiang Shao, Wenjia Rao, Wangfang Xu, Longbao Wei

“…By constructing the correlation networks among agents, we carry out a structural, functional, and temporal analysis of the emergent symmetric coordination. …”
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