Interpretable correlator Transformer for image-like quantum matter data by Abhinav Suresh, Henning Schlömer, Baran Hashemi, Annabelle Bohrdt

“…Next to these traditional applications, machine learning (ML) methods have also been demonstrated to be versatile tools in the analysis of image-like data of quantum phases of matter, e.g. given snapshots of many-body wave functions obtained in ultracold atom experiments. …”
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Identification of anoikis-related genes in heart failure: bioinformatics and experimental validation by Lina Zhang, Jianjun Gu, Yan Jiang, Juan Xue, Ye Zhu

“…GEO2R was used to screen for differentially expressed genes (DEGs), then by overlapping DEGs with ARGs, differentially expressed ARGs (DEARGs) were screened. The biological functions of the DEARGs were determined using DAVID. …”
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From fixing to connecting—developing mutual empathy guided through movement as a novel path for the discovery of better outcomes in autism by Anat Baniel, Eilat Almagor, Neil Sharp, Ohad Kolumbus, Martha R. Herbert, Martha R. Herbert

“…This article presents the theoretical foundation of two well established movement-based methods that represent a fundamental departure from most current interventions and are applied globally with children and adults experiencing diverse motoric, cognitive, and social challenges as well as with high functioning individuals: the Feldenkrais method and Anat Baniel Method® NeuroMovement®. …”
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Fostering the Teachers Rediness for Using the Informational Educational Environment in Higher Scool by N. V. Lomovtseva, E. V. Tchubarkova, A. A. Karasik

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Efficient Multiple Imputation for Diverse Data in Python and R: MIDASpy and rMIDAS by Ranjit Lall, Thomas Robinson

“… This paper introduces software packages for efficiently imputing missing data using deep learning methods in Python (MIDASpy) and R (rMIDAS). …”
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An outlook on structural biology after AlphaFold: tools, limits and perspectives by Serena Rosignoli, Maddalena Pacelli, Francesca Manganiello, Alessandro Paiardini

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A Study on the Application of Explainable AI on Ensemble Models for Predictive Analysis of Chronic Kidney Disease by K. M. Tawsik Jawad, Anusha Verma, Fathi Amsaad, Lamia Ashraf

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Human Complexity vs. Machine Linearity: Tug-of-War Between Two Realities Coexisting in Precarious Balance by Paolo Barile, Clara Bassano, Paolo Piciocchi

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Modern challenges of higher legal education by Inessa Shagenovna Galstyan, Irina Nikolaevna Klyukovskaya, Ruslan Kurmanovich Melekayev, Irina Nikolaevna Ter-Avanesova, Yevgeny Yurievich Cherkashin

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Detection of Welding Defects Tracked by YOLOv4 Algorithm by Yunxia Chen, Yan Wu

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A Multi-Scale Unsupervised Feature Extraction Network with Structured Layer-Wise Decomposition by Yusuf Şevki Günaydın, Baha Şen

“…Recent developments in deep learning have underscored prizing effective feature extraction in scenarios with limited or unlabeled data. …”
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A variable metric proximal stochastic gradient method: An application to classification problems by Pasquale Cascarano, Giorgia Franchini, Erich Kobler, Federica Porta, Andrea Sebastiani

“…Due to the continued success of machine learning and deep learning in particular, supervised classification problems are ubiquitous in numerous scientific fields. …”
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Application of Feedforward Artificial Neural Networks to Predict the Hydraulic State of a Water Distribution Network by Leandro Evangelista, Débora Móller, Bruno Brentan, Gustavo Meirelles

“…These parameters were chosen because they are frequently used in objective functions, minimizing energy consumption and leakage volume, as well in operational restrictions. …”
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Developmental coordination disorder questionnaire – translation and adaptation into Danish by Marta Topor, Anne Husted Henriksen, Rasmus Ahmt Rohde, Anna Bugge, Emma Bundgård Fals, Ida Jacobsen, Keenie Andersen, Jacob Wienecke

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Smart Solutions for Mega-Cities: Utilizing Long Short-Term Memory and Multi-Head Attention in Parking Prediction by Hasan Kemik, Tugba Dalyan, Murat Aydogan

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Advancements and future directions of artificial intelligence in tumor imaging: A comprehensive review of techniques and applications by Jinglei Xue, Jing Yu, Qianqian Mao, Xiaochun Gu

“…Techniques such as AI, machine learning (ML), neural networks (NNs), and deep learning (DL) enhance the accuracy and efficiency of tumor recognition. …”
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Empowering voice assistants with TinyML for user-centric innovations and real-world applications by Sireesha Chittepu, Sheshikala Martha, Debajyoty Banik

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Well Production Forecasting in Volve Field Using Kolmogorov–Arnold Networks by Xingyu Lu, Jing Cao, Jian Zou

“…However, traditional methods often struggle to capture the complex dynamics of reservoirs, and existing machine learning models rely on large parameter sets, resulting in high computational costs and limited scalability. …”
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The integration of psychological education and moral dilemmas from a value perspective by XiaoFen Jia, WenQing Wu

“…Moreover, optimization functions pertinent to deep learning are examined, alongside their practical implications for enhancing educational practices. …”
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Cognition from genes to ecology: individual differences incognition and its potential role in a social network by Brian H. Smith

“…Abstract There have now been many reports of intra-colony differences in how individuals learn on a variety of conditioning tasks in both honey bees and bumble bees. …”
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