Computer Vision Aided Beamforming Fused With Limited Feedback by T. Xiang, J. Gu, Y. Wang, Y. Gao, X. Zhang

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Uncertainty Quantification of Geophysical and Hydrologic Parameters Estimated From Borehole Nuclear Magnetic Resonance Data by Burke J. Minsley, Stephanie N. Phillips, Stephanie R. James

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Adjoint‐Based Marker‐In‐Cell Data Assimilation for Constraining Thermal and Flow Processes From Lagrangian Particle Records by Atsushi Nakao, Tatsu Kuwatani, Shin‐ichi Ito, Hiromichi Nagao

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Attention-Aided Outdoor Localization in Commercial 5G NR Systems by Guoda Tian, Dino Pjanic, Xuesong Cai, Bo Bernhardsson, Fredrik Tufvesson

“…The integration of high-precision cellular localization and machine learning (ML) is considered a cornerstone technique in future cellular navigation systems, offering unparalleled accuracy and functionality. …”
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Why is it problematic for technicians to say they teach in higher education? by Tim Savage, Kelly Vere

“…The authors call upon the sector to formally acknowledge this valuable element of HE and to integrate it not just into the language but into the formal functions, structures, systems and strategies to create a unified space in which academic and technical educators integrate and collaborate to develop curricula and deliver pedagogies that enhance student learning and advance knowledge. …”
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The Transformative Potential of Inquiry: Engaging With and Navigating Complex “Worlds” by Carolin Kreber

“… I propose a model of the scholarship of teaching and learning that builds on and at the same time extends previous work. …”
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Can education heal? Staff and students exploring reparative pedagogies in the context of institutional harms in higher education by Havva Görkem Altunbas, Xiaoyan Guo, Yuncong Liu, Helen Knowler, Tor Wright

“…Reckoning with historic and contemporary harms in educational contexts is under-theorised in learning development literature. Situating our analysis within what ​Zembylas (2015)​ and others have called the ‘affective turn’, we follow ​Sriprakash’s (2023)​ theorising of the reparative functions of education exploring the ways that reparative pedagogies can be harnessed, particularly by those higher education institutions that have acknowledged histories and legacies of harm. …”
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Neuromorphic Wireless Split Computing With Multi-Level Spikes by Dengyu Wu, Jiechen Chen, Bipin Rajendran, H. Vincent Poor, Osvaldo Simeone

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Rapid Bayesian Imaging of Large‐Scale Transient Electromagnetic Data Using Probabilistic Neural Networks by Jian Chen, Stefano Galli, Alessandro Signora, Nicole Anna Lidia Sullivan, Bo Zhang, Gianluca Fiandaca

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Getting the Best Out of Both Worlds: Algorithms for Hierarchical Inference at the Edge by Vishnu Narayanan Moothedath, Jaya Prakash Champati, James Gross

“…We thus propose an online meta-learning framework that the ED can use to predict the correctness of the S-ML inference. …”
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Teachers’ perceived social-emotional competence as a vital mechanism of adult SEL by Rebecca J. Collie, Fabiola M. Sáez-Delgado, Helena Granziera

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Automatic Differentiation‐Based Full Waveform Inversion With Flexible Workflows by Feng Liu, Haipeng Li, Guangyuan Zou, Junlun Li

“…In addition, ADFWI is integrated with deep learning for implicit model reparameterization via neural networks, which not only introduces learned regularization but also allows rapid estimation of uncertainty through dropout. …”
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Factors influencing the consumers’ purchase intentions toward Organic food by Nimra Nasir

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Organizational Factors, Teachers’ Professional Development and Teaching Practices: Findings From Female Elementary School Teachers by Naveed R. Khan, Sana Zaidi, Najmunnisa Khan

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The representation of mature students in governing bodies of a Portuguese university by José Pedro Amorim, Felismina Viterbo

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One‐Fit‐All Transformer for Multimodal Geophysical Inversion: Method and Application by Yiran Jiang, Jianwei Ma, Jieyuan Ning, Jiaqi Li, Han Wu, Tiezhao Bao

“…Abstract The increasing variety of geophysical data sets enhances inversion constraints but also poses significant challenges for conventional methods in terms of precision and efficiency due to factors like non‐linearity and limited observation coverage. While deep learning has the potential to address these challenges, issues such as data representation and domain transformation limit the development of universally applicable deep learning‐based inversion methods across various geophysical scenarios. …”
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Social-emotional standards for secondary students in the United States: A systematic review and synthesis by Christi Bergin, Nicole Brass, Lindsay Brockmeier, Alice Hung, Riley Rohler

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Data-Driven Energy Efficiency Modeling in Large-Scale Networks: An Expert Knowledge and ML-Based Approach by David Lopez-Perez, Antonio De Domenico, Nicola Piovesan, Merouane Debbah

“…This paper introduces the simulated reality of communication networks (SRCON) framework, a novel, data-driven modeling paradigm that harnesses live network data and employs a blend of machine learning (ML)- and expert-based models. These mix of models accurately characterizes the functioning of network components, and predicts network energy efficiency and user equipment (UE) quality of service for any energy carrier shutdown configuration in a specific network. …”
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Explainable AI for Enhancing Efficiency of DL-Based Channel Estimation by Abdul Karim Gizzini, Yahia Medjahdi, Ali J. Ghandour, Laurent Clavier

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Multi‐Annual Inventorying of Retrogressive Thaw Slumps Using Domain Adaptation by Yiling Lin, Xie Hu, Haoyu Lu, Fujun Niu, Gengnian Liu, Lingcao Huang, Shanghang Zhang, Jifu Liu, Yunhuai Liu

“…We introduced the Tversky loss and the automatic adjustment of weights for multiple loss functions to suppress false positives and to improve the generalization of TADA. …”
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