Neural Network Parameterization of Subgrid‐Scale Physics From a Realistic Geography Global Storm‐Resolving Simulation by Oliver Watt‐Meyer, Noah D. Brenowitz, Spencer K. Clark, Brian Henn, Anna Kwa, Jeremy McGibbon, W. Andre Perkins, Lucas Harris, Christopher S. Bretherton

“…Online, we achieve stable 35‐day simulations, with metrics of skill such as the time‐mean pattern of near‐surface temperature and precipitation comparable or slightly better than a baseline simulation with conventional physical parameterizations. …”
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Spatiotemporal Analysis of Human Mobility in Greater Tokyo Area Using Hourly 500 m Mobile Spatial Statistics from 2019 to 2021 by Thanakrit Yoongsomporn, Alvin Christopher Galang Varquez, Sunkyung Choi, Makoto Okumura, Shinya Hanaoka, Manabu Kanda

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An interpretable approach for trustworthy intrusion detection systems against evasion samples by Ngoc Tai Nguyen, Hien Do Hoang, The Duy Phan, Van-Hau Pham

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AI-driven biomarker discovery: enhancing precision in cancer diagnosis and prognosis by Esther Ugo Alum

“…The use of AI in biomarker discovery improves precision medicine by uncovering biomarker signatures that are essential for early detection and treatment of diseases within vast and diverse datasets. Deep learning and machine learning diagnostics are two examples of AI technologies that are changing the way biomarkers are made by finding patterns in large datasets and making new technologies that make it possible to deliver accurate and effective therapies. …”
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Electricity Demand Prediction by a Transformer-Based Model by Ahmed Mohammed Mahmood, Musaddak Maher Abdul Zahra, Waleed Hamed, Bashar S. Bashar, Alaa Hussein Abdulaal, Taif Alawsi, Ali Hussein Adhab

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Long-Term Neonatal EEG Modeling with DSP and ML for Grading Hypoxic–Ischemic Encephalopathy Injury by Leah Twomey, Sergi Gomez, Emanuel Popovici, Andriy Temko

“…The results of this study show that the proposed representation and workflow increase the potential for background grading of EEG signals, increasing the accuracy of grading background patterns that are most relevant for therapeutic intervention, across large windows of time.…”
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AP-GRIP evaluation framework for data-driven train delay prediction models: systematic literature review by Tiong Kah Yong, Zhenliang Ma, Carl-William Palmqvist

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Mental Health Issues and 24-Hour Movement Guidelines–Based Intervention Strategies for University Students With High-Risk Social Network Addiction: Cross-Sectional Study Using a Ma... by Lin Luo, Junfeng Yuan, Chen Xu, Huilin Xu, Haojie Tan, Yinhao Shi, Haiping Zhang, Haijun Xi

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Dysregulated neural coding in the vagus nerve during long sepsis by Joshua J. Strohl, Tomás S. Huerta, Sergio Robbiati, Patricio T. Huerta

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Artificial Intelligence in Primary Malignant Bone Tumor Imaging: A Narrative Review by Platon S. Papageorgiou, Rafail Christodoulou, Panagiotis Korfiatis, Dimitra P. Papagelopoulos, Olympia Papakonstantinou, Nancy Pham, Amanda Woodward, Panayiotis J. Papagelopoulos

“…Notably, convolutional neural networks have demonstrated exceptional capabilities in pattern recognition, significantly improving tumor detection, segmentation, and differentiation. …”
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Devanagari Character Recognition: A Comprehensive Literature Review by Sandhya Arora, Latesh Malik, Sonakshi Goyal, Debotosh Bhattacharjee, Mita Nasipuri, Ondrej Krejcar

“…Advances introduced structural and statistical techniques, improving accuracy by analyzing geometric properties and patterns. The advent of machine learning, particularly deep learning, revolutionized HDCR with convolutional neural networks (CNNs) and recurrent neural networks (RNNs), significantly enhancing performance. …”
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Leveraging multi-modal feature learning for predictions of antibody viscosity by Krishna D. B. Anapindi, Kai Liu, Willie Wang, Yao Yu, Yan He, Edward J. Hsieh, Ying Huang, Daniela Tomazela

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SwinDenoising: A Local and Global Feature Fusion Algorithm for Infrared Image Denoising by Wenhao Wu, Xiaoqing Dong, Ruihao Li, Hongcai Chen, Lianglun Cheng

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Multi-user frequency selective beam steering by reconfigurable intelligent surfaces in the Ka-band by Lukas Mueller, Alexander Wolff, Steffen Klingel, Janis Krieger, Lars Franke, Ralf Stemler, Marco Rahm

“…For such targeted multi-frequency beam steering, we implemented a customized neural network-based machine learning architecture specifically designed to optimize the bias voltage patterns of the RIS. …”
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Multimodal Deep Learning Model for Cylindrical Grasp Prediction Using Surface Electromyography and Contextual Data During Reaching by Raquel Lázaro, Margarita Vergara, Antonio Morales, Ramón A. Mollineda

“…In this context, the identification of patterns and prediction of hand grasp types is crucial, with cylindrical grasp being one of the most common and functional. …”
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Transcriptomic profiling of burn patients reveals key lactylation-related genes and their molecular mechanisms by Yang Li, Jizhong Ma, Yeping Wang, Weibin Zhan, Qian Wang

“…Clustering analysis based on these four molecules divided burn patients into two subgroups, each exhibiting distinct gene expression patterns and pathway enrichments.ConclusionThis study provides insights into the molecular alterations in burn patients, especially regarding lactylation. …”
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Regional Low Flow Hydrology: Model Development and Evaluation by Vinícius B. P. Chagas, Pedro L. B. Chaffe, Günter Blöschl

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Distinguishing Dyslexia, Attention Deficit, and Learning Disorders: Insights from AI and Eye Movements by Alae Eddine El Hmimdi, Zoï Kapoula

“…These findings suggest that specific terminology, such as “dyslexia”, may capture unique eye movement patterns, underscoring the importance of eye movement analysis as a diagnostic tool for understanding the complexity of these conditions. …”
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Dual‐Transformer Deep Learning Framework for Seasonal Forecasting of Great Lakes Water Levels by Yi Chen, Pengfei Xue

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A Comprehensive Multidimensional Analysis of Mental Health Challenges in the Digital Age by Fakhroddin Noorbehbahani, Hooman Hoghooghi Esfahani, Soroush Bajoghli

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