A Multidimensional Analysis Approach Toward Sea Cliff Erosion Forecasting by Maria Krivova, Michael J. Olsen, Ben A. Leshchinsky

“…Erosion is episodic and varies both spatially and temporarily; hence, forecasting erosion patterns to identify vulnerable infrastructure is immensely challenging. …”
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Exploring the Early Neolithic in the Arabian Gulf: A newly discovered 8,400-year-old stone-built architecture on Ghagha Island, United Arab Emirates. by Kevin Lidour, Noura Al Hameli, Rémy Crassard, Fabian D'Silva, Ahmed Al Haj

“…The site of GHG0088, with its two successive main phases of occupation, provides crucial data for re-evaluating our understanding of the Early Neolithic period (c. 6600-5400 cal. …”
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Mapping the Evolution of Corporate Social Responsibility Research (2015–2024): A Bibliometric Analysis Based on Scopus by Cristyano Cristyano, Suryadi Suryadi, Riyanto Riyanto

“…The objective is to map the intellectual evolution of CSR scholarship by identifying key thematic shifts, dominant theoretical frameworks, and methodological patterns. Using VOSviewer as the primary visualization tool, the study explores research networks, keyword co-occurrences, and temporal transitions in CSR literature over the past decade. …”
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Automated violence monitoring system for real-time fistfight detection using deep learning-based temporal action localization by Baolong Qi, Baoyuan Wu, Bailing Sun

“…The proposed framework leverages both Context-Aware Encoded Transformer (CAET) for modeling interactions between individuals and their environment and Spatial–Temporal Graph Convolutional Networks (ST-GCN) for capturing intra-person and inter-person dynamics from skeletal data. …”
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Tourist Destination Recommendations Using Deep Learning by Amarita Ritthipakdee, Chartchai Leenawong

“…The model employs Neural Collaborative Filtering (NCF), utilizing deep neural networks to capture complex, non-linear patterns between users and destinations, surpassing the limitations of traditional matrix factorization methods. …”
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Optimizing Supply Chain Resilience Using Advanced Analytics and Computational Intelligence Techniques by Jie Xu, Lixing Bo

“…The system’s effectiveness is evaluated through extensive experimentation and case studies, focusing on metrics such as forecasting accuracy, cost reduction, and resource utilization. …”
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Novel Differentially Expressed LncRNAs Regulate Artemisinin Biosynthesis in <i>Artemisia annua</i> by Tingyu Ma, Tianyuan Zhang, Jingyuan Song, Xiaofeng Shen, Li Xiang, Yuhua Shi

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Architecture-Aware Augmentation: A Hybrid Deep Learning and Machine Learning Approach for Enhanced Parkinson’s Disease Detection by Madjda Khedimi, Tao Zhang, Hanine Merzougui, Xin Zhao, Yanzhang Geng, Khamsa Djaroudib, Pascal Lorenz

“…We compare the accuracy of Vision Transformer (ViT) with K-Nearest Neighbors (KNN), Convolutional Neural Networks (CNN) with Support Vector Machines (SVM), and Residual Neural Networks (ResNet-50) with Logistic Regression, evaluating their performance on both augmented and non-augmented data. …”
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A selective CutMix approach improves generalizability of deep learning-based grading and risk assessment of prostate cancer by Sushant Patkar, Stephanie Harmon, Isabell Sesterhenn, Rosina Lis, Maria Merino, Denise Young, G. Thomas Brown, Kimberly M. Greenfield, John D. McGeeney, Sally Elsamanoudi, Shyh-Han Tan, Cara Schafer, Jiji Jiang, Gyorgy Petrovics, Albert Dobi, Francisco J. Rentas, Peter A. Pinto, Gregory T. Chesnut, Peter Choyke, Baris Turkbey, Joel T. Moncur

“…For cancer grading, a Gleason pattern detector was trained on tiles using a ResNet50 convolutional neural network and a selective CutMix training strategy involving a mixture of real and artificial examples. …”
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Environmental impacts shape the density-size relationship of benthic macroinvertebrates in Amazonian streams (Serra dos Carajás, Pará, Brazil) by Maria Eduarda Cabral Liberal, Camila Pinto Leão, Jaqueline Silva de Oliveira, Francisco Valente-Neto, Bruno Spacek Godoy

“…These changes suggest a simplification of trophic networks and decreased energy transfer efficiency. …”
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Temporal Dynamics in Short Text Classification: Enhancing Semantic Understanding Through Time-Aware Model by Khaled Abdalgader, Atheer A. Matroud, Ghaleb Al-Doboni

“…The model employs a hybrid architecture combining Convolutional Neural Networks (CNNs) and Bidirectional Long Short-Term Memory (BiLSTM) networks, enriched with attention mechanisms to capture both local and global dependencies. …”
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Application of Artificial Intelligence Techniques for the Estimation of Basal Insulin in Patients with Type I Diabetes by Guillermo Edinson Guzman Gómez, Luis Eduardo Burbano Agredo, Veline Martínez, Oscar Fernando Bedoya Leiva

“…We used neural networks (NNs), Bayesian networks (BNs), support vector machines (SVMs), and random forests (RF). …”
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Lightweight ECG signal classification via linear law-based feature extraction by Péter Pósfay, Marcell T Kurbucz, Péter Kovács, Antal Jakovác

“…We evaluate the method on two PhysioNet datasets, TwoLeadECG and variable projection networks (VPNet). …”
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A deep reinforcement learning approach for wind speed forecasting by Shahab S. Band, Ting Jia Lin, Sultan Noman Qasem, Rasoul Ameri, Danyal Shahmirzadi, Muhammad Shamrooz Aslam, Hao-Ting Pai, Ely Salwana, Amir Mosavi

“…The performance of the proposed EWT-DRL is evaluated against deep learning models, including LSTM, CNN-LSTM, CNN-GRU, and their coupling with EWT. …”
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Insights into hepatic angiomyolipoma: A case report highlighting scannographic findings by Fatima Zohra EL Yaagoubi, MD, Said Adnor, MD, Adam Hajjine, MD, Soukaina Wakrim

“…Postcontrast enhancement demonstrated a heterogeneous pattern with arterial-phase vascular structures (branches of the hepatic artery) and venous-phase elements (branches of the portal vein network). …”
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IRGL-RRI: interpretable graph representation learning for plant RNA–RNA interaction discovery by Qingquan Liao, Xuchong Liu, Wei Zhao, Yu Tong, Fangzheng Xu, Xinxin Liu, Yifan Chen

“…Furthermore, an RRI modeling approach combining Kolmogorov-Arnold Networks (KAN) and multi-scale fusion is proposed to deeply resolve the complex dynamic interaction mechanisms of RRIs and improve model interpretability. …”
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FetalMovNet: A Novel Deep Learning Model Based on Attention Mechanism for Fetal Movement Classification in US by Musa Turkan, Emre Dandil, Furkan Erturk Urfali, Mehmet Korkmaz

“…The model integrates convolutional neural networks (CNN) for feature extraction and an attention mechanism to capture spatio-temporal patterns, significantly improving classification performance of fetal movements. …”
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Intercomparison of Surface Currents Obtained Using SCHISM and the HF Radar Data in Galveston Bay and Sabine Lake, Texas by Cletus O. Ogbodo, Rosa M. Fitzgerald, Christopher Fuller, Jungwoo Lee, Roberto Perea, Javier Polanco-Gonzalez

“…One-month HF radar data, in April 2023, were extracted from the two newly installed HF radar networks comprising two and three HF radar stations at Sabine Lake and Galveston Bay, respectively. …”
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Data Governance Navigation for Advanced Operations in Healthcare Excellence by Vahideh Zarea Gavgani, Aniseh Pourrasmi

“…Therefore, in a wide treatment network with numerous electronic files, better coordination and coherence have been created, and while speeding up treatment processes, conditions will be provided for an advanced and more effective health control operation. …”
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Deep Learning Architectures for Single-Label and Multi-Label Surgical Tool Classification in Minimally Invasive Surgeries by Hisham ElMoaqet, Hamzeh Qaddoura, Mutaz Ryalat, Natheer Almtireen, Tamer Abdulbaki Alshirbaji, Nour Aldeen Jalal, Thomas Neumuth, Knut Moeller

“…Nonetheless, our results demonstrated that the proposed CNN-SE-FFM-BiLSTM multi-label model achieved competitive performance to state-of-the-art methods with excellent performance in detecting tools with complex usage patterns and in minority classes. Future work should focus on optimizing models for real-time applications, and broadening dataset evaluations to improve performance in diverse surgical environments. …”
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