THE BIBLE, OPEN AND DISTANCE EDUCATION AND LEARNING, AND SPIRITUALITY: POSSIBILITIES IN A POST-SECULAR TIME by C. Lombaard

“…These problems are in some respects compounded in Open and Distance Education and Learning institutions such as the University of South Africa, where direct contact with students and, hence, spiritual formation (undertaken either implicitly or explicitly) is limited and media-ted. …”
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Learning-based pattern-data-driven forecast approach for predicting future well responses by Yeongju Kim, Baehyun Min, Alexander Sun, Bo Ren, Hoonyoung Jeong

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Making Good Decisions: Television and Young Children’s Learning, A Parent Tip Sheet by David C. Diehl, Stephanie C. Toelle

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Development of mobile augmented reality-based geometry learning games to facilitate spatial reasoning by Arif Sapta Mandala, Lathiful Anwar, Cholis Sa'dijah, Hutkemri Zulnaidi

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Rainfall forecasts, learning subsidies and conservation agriculture adoption: Experimental evidence from Zambia by Hambulo Ngoma, Esau Simutowe, João Vasco Silva, Isaiah Nyagumbo, Kelvin Kalala, Mukwemba Habeenzu, Christian Thierfelder

“…We use incentivized economic field experiments in Zambia to test, ex-ante, whether providing rainfall forecasts and a time-bound learning subsidy can help increase the adoption of conservation agriculture. …”
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Detecting respiratory diseases using machine learning-based pattern recognition on spirometry data by Ahmed I. Taloba, R.T. Matoog

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Impact of Climate Change and Air Pollution Forecasting Using Machine Learning Techniques in Bishkek by Erkin Isaev, Boobek Ajikeev, Urmatbek Shamyrkanov, Kenjebek-uulu Kalnur, Karimov Maisalbek, Roy C. Sidle

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Learning to Be a Father: How Do We Do It? Isn't there a Manual Somewhere? by Garett D. Evans, Kate Fogarty

“… Learning to be a good father is not for wimps. It takes time, energy, interest, and responsibility. …”
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Poor hypotheses and research waste in biology: learning from a theory crisis in psychology by Shinichi Nakagawa, David W. Armitage, Tom Froese, Yefeng Yang, Malgorzata Lagisz

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Advancing Coherent Power Grid Partitioning: A Review Embracing Machine and Deep Learning by Mohamed Massaoudi, Maymouna Ez Eddin, Ali Ghrayeb, Haitham Abu-Rub, Shady S. Refaat

“…Subsequently, state-of-the-art research that envisions the use of clustering-based machine learning and deep learning-based solutions for PGP is presented. …”
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The Relationship Between Consumption Power and GDP Growth in China and Machine Learning Prediction Analysis by Hu Runsong

“…The paper examines the use of machine learning for predicting consumption capacity by integrating various economic models, including Support Vector Regression (SVR) and Long Short-Term Memory Network (LSTM). …”
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A cooperative jamming decision-making method based on multi-agent reinforcement learning by Bingchen Cai, Haoran Li, Naimin Zhang, Mingyu Cao, Han Yu

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Real world federated learning with a knowledge distilled transformer for cardiac CT imaging by Malte Tölle, Philipp Garthe, Clemens Scherer, Jan Moritz Seliger, Andreas Leha, Nina Krüger, Stefan Simm, Simon Martin, Sebastian Eble, Halvar Kelm, Moritz Bednorz, Florian André, Peter Bannas, Gerhard Diller, Norbert Frey, Stefan Groß, Anja Hennemuth, Lars Kaderali, Alexander Meyer, Eike Nagel, Stefan Orwat, Moritz Seiffert, Tim Friede, Tim Seidler, Sandy Engelhardt

“…Abstract Federated learning is a renowned technique for utilizing decentralized data while preserving privacy. …”
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Multi-label classification with deep learning techniques applied to the B-Scan images of GPR by El Karakhi, Soukayna, Reineix, Alain, Guiffaut, Christophe

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Machine Learning in the Management of Patients Undergoing Catheter Ablation for Atrial Fibrillation: Scoping Review by Aijing Luo, Wei Chen, Hongtao Zhu, Wenzhao Xie, Xi Chen, Zhenjiang Liu, Zirui Xin

“…In terms of model type, deep learning, represented by convolutional neural networks, was most frequently applied (14/23, 61%). …”
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Deep Reinforcement Learning-Based Anti-Jamming Approach for Fast Frequency Hopping Systems by Sixi Cheng, Xiang Ling, Lidong Zhu

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Contrastive-learning of language embedding and biological features for cross modality encoding and effector prediction by Yue Peng, Junze Wu, Yi Sun, Yuanxing Zhang, Qiyao Wang, Shuai Shao

“…Here, we introduce a model named Contrastive-learning of Language Embedding and Biological Features (CLEF) leveraging contrastive learning to integrate PLM representations with supplementary biological features. …”
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Retraction: Post COVID green intellectual capital management with the mediation of organizational learning capability by Frontiers Editorial Office

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Correction: Enhanced wave overtopping simulation at vertical breakwaters using machine learning algorithms. by PLOS One Staff

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Sentiment analysis of the Hamas-Israel war on YouTube comments using deep learning by Ashagrew Liyih, Shegaw Anagaw, Minichel Yibeyin, Yitayal Tehone

Subjects: “…Deep learning approach…”
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