Comparison of conventional and radiomics-based analysis of myocardial infarction using multimodal non-linear optical microscopy by Gabriel Giardina, Laszlo Papp, Arno Krause, James Marchant, Nestor Pallares-Lupon, Kanchan Kulkarni, Clemens P. Spielvogel, David Haberl, Xu Li, Wolfgang Drexler, Richard D. Walton, Angelika Unterhuber, Marco Andreana

“…This study represents a significant step towards integrating quantitative image analysis in therapeutic interventions.…”
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ViViT-Prob: A Radar Echo Extrapolation Model Based on Video Vision Transformer and Spatiotemporal Sparse Attention by Yunan Qiu, Bingjian Lu, Wenrui Xiong, Zhenyu Lu, Le Sun, Yingjie Cui

“…Finally, a parallel output decoder generates all time step predictions simultaneously, then maps back to the prediction space through a deconvolution module to reconstruct high-resolution images. …”
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Predicting Sugarcane Yield Through Temporal Analysis of Satellite Imagery During the Growth Phase by Julio Cezar Souza Vasconcelos, Caio Simplicio Arantes, Eduardo Antonio Speranza, João Francisco Gonçalves Antunes, Luiz Antonio Falaguasta Barbosa, Geraldo Magela de Almeida Cançado

“…Overall, the results of this study represent an initial step toward developing more robust models for predicting sugarcane yield. …”
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A COSMIC-2-Based Global Mean TEC Model and Its Application to Calibrating IRI-2020 Global Ionospheric Maps by Yuxiao Lei, Weitang Wang, Yibin Yao, Liang Zhang

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Formation of the pediatric electroretinogram database parameters for the development of doctor’s decisionmaking algorithm by A. E. Zhdanov, A. Yu. Dolganov, V. N. Kazaykin, V. I. Borisov, V. O. Ponomarev, L. G. Dorosinsky, A. V. Lizunov, E. Luchian, X. Bao

“…To transfer clinical practice to patients the establishment of standardized protocols is an important step. It is important for monitoring successful molecular therapy in retinal degeneration. …”
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Accelerometry-Based Digital Gait Characteristics for Classification of Parkinson's Disease: What Counts? by Rana Zia Ur Rehman, Christopher Buckley, Maria Encarna Mico-Amigo, Cameron Kirk, Michael Dunne-Willows, Claudia Mazza, Jian Qing Shi, Lisa Alcock, Lynn Rochester, Silvia Del Din

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Zero-BertXGB: An Empirical Technique for Abstract Classification in Systematic Reviews by Mohammad Shariful Islam, Mohammad Abu Tareq Rony, Md Rasel Hossain, Samah Alshathri, Walid El-Shafai

“…Abstract classification in systematic reviews (SRs) is a crucial step in evidence synthesis but is often time-consuming and labour-intensive. …”
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Metal commodity futures price forecasting based on a hybrid secondary decomposition error-corrected model by Yuetong Zhang, Ying Peng, Yuping Song

“…Finally, two predicted sequences are reconstructed to obtain the final one-step result, and based on the result of the one-step prediction, the two-step prediction is made using the sliding prediction method. …”
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Enhancing assertiveness of South Asian children in Hong Kong: an online intervention† by Yau Yu Chan, Zheng Liang Sun

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Safe Switching Model-Free Value Iteration for General Nonlinear Systems by Timotei Lala

“…To guarantee safety during runtime operation, the systems maximum one-step transition is estimated. Then, the switching control signal is designed to select the MFVI controller only in the region of the state space both covered by the collected transitions during the exploration phase and with the distance to the unsafe set greater than the computed maximum one-step transition. …”
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Attention-Based Convolutional Aggregation: An Efficient Model for Off-Gas Profile Forecasting and Dynamic Pre-Control of BOF Steelmaking by Tian-yi Xie, Jun-guo Zhang, Lan-jie Li, Fei Zhang, Shuai Liu, Han-jie Guo

“…First, a data pre-processing method was proposed based on the characteristics of the off-gas curves, where there are many samples, but each sample contains limited time-steps. It is termed the mixed-batch approach. The importance of the time series’ channels and time-steps were also analyzed by models with attention mechanism. …”
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Improving Sharpness-Aware Minimization Using Label Smoothing and Adaptive Adversarial Cross-Entropy Loss by Tanapat Ratchatorn, Masayuki Tanaka

“…Recent advances in learning algorithms have identified loss surface sharpness as an effective metric for reducing the generalization gap. …”
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A hybrid long short-term memory with generalized additive model and post-hoc explainable artificial intelligence with causal inference for air pollutants prediction in Kimberley, S... by Israel Edem Agbehadji, Ibidun Christiana Obagbuwa

“…The model was evaluated with the mean squared error (MSE), root mean squared error (RMSE) and mean absolute error (MAE) for different time-steps. The proposed referred to as long short-term memory generalized additive model based post-hoc eXplainable Artificial Intelligence (LSTM-GAM_xAI) model with a 10-day time-step and 5-day time-step for multiple pollutants prediction guaranteed least MSE. …”
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Entre tâche et activité : analyse des échanges langagiers d’élèves de cycle 3 lors de l’utilisation d’un outil de correction orthographique by Prisca Fenoglio, Catherine Brissaud

“…Based on these results, we discuss the learning processes fostered by the « twoutils » and make some proposals in order to improve their efficiency for all students.…”
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Evaluation of Artificial Intelligence Effectiveness in Detection of Lumbosacral Spine Degenerative Diseases by N. В. Nudnov, A. V. Korobov, А. А. Skachkov, T. V. Kulneva, V. V. Sherstoboev, L. А. Titova, A. S. Rusakov, V. V. Tumko, R. S. Sarbaev, N. А. Uspenskaya, E. А. Andrienko, M. Е. Ivannikov

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CoReaAgents: A Collaboration and Reasoning Framework Based on LLM-Powered Agents for Complex Reasoning Tasks by Zhonghe Han, Jiaxin Wang, Xiaolu Yan, Zhiying Jiang, Yuanben Zhang, Siye Liu, Qihang Gong, Chenwei Song

“…Nevertheless, existing studies still suffer from missing steps, deviated task execution and incorrect tool selection. …”
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A Review of Task Multi-criteria Prioritization Methods by PAN Zheping, ZOU Gui, ZHAO Jun, CHENG Weizheng

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Optimizing Geospatial Data for ML/CV Applications: A Python-Based Approach to Streamlining Map Processing by Removing Irrelevant Areas by David Kasperek, Michal Podpora

“…Massive image datasets are often required for the proper functioning of Machine Learning (ML) and Computer Vision (CV) applications. …”
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Local-Global and Multi-Scale (LG-MS) Mixer Architecture for Long-Term Time Series Forecasting by Zhennan Peng, Boyong Gao, Ziqi Xia, Jie Liu

“…Although deep learning models dominate time series forecasting, they still struggle with long-sequence processing due to the challenges of extracting dynamic fluctuations and pattern features as input length increases. …”
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Self-Denoising of BOTDA Using Deep Convolutional Neural Networks by Di Qi, Chun-Kit Chan, Xun Guan

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