A transformer based generative chemical language AI model for structural elucidation of organic compounds by Xiaofeng Tan

“…This approach demonstrates the potential of transformer based generative AI to accelerate traditional scientific problem-solving processes. The model's ability to iterate quickly based on new data highlights its potential for rapid advancements in structural elucidation.…”
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Machine learning and deep learning in medicine and neuroimaging by Iván Sánchez Fernández, Jurriaan M. Peters

“…Machine learning is the subfield of artificial intelligence in which computers have the ability to learn and iteratively improve their performance without being explicitly programmed. …”
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A Framework to Calibrate Ecosystem Demography Models Within Earth System Models Using Parallel Surrogate Global Optimization by Yanyan Cheng, Wei Xia, Matteo Detto, Christine A. Shoemaker

“…Ecosystem demographic (ED) models can explicitly represent vegetation dynamics and are a key component of next‐generation Earth System Models (ESMs). …”
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Advanced Temporal Convolutional Network Framework for Intrusion Detection in Electric Vehicle Charging Stations by Ikram Benfarhat, Vik Tor Goh, Chun Lim Siow, It Ee Lee, Muhammad Sheraz, Eng Eng Ngu, Teong Chee Chuah

“…The proposed Temporal Convolutional Network (TCN)-based Intrusion Detection System (IDS) architecture integrates four key innovations: multi-receptive fields, a gating mechanism, iterative dilation, and a self-attention mechanism combined with a Squeeze-and-Excitation (SE) block to recalibrate feature responses by explicitly modeling interactions between different channels. …”
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TMTS: A Physics-Based Turbulence Mitigation Network Guided by Turbulence Signatures for Satellite Video by Jie Yin, Tao Sun, Xiao Zhang, Guorong Zhang, Xue Wan, Jianjun He

“…By bridging turbulence physics with deep learning, our approach provides both performance enhancements and interpretable restoration mechanisms, offering a viable solution for operational satellite video processing under atmospheric disturbances.…”
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Understanding the effectiveness and underlying mechanisms of lifestyle modification interventions in adults with learning disabilities: a mixed-methods systematic review by Dikshyanta Rana, Sophie Westrop, Nishant Jaiswal, Evi Germeni, Arlene McGarty, Louisa Ells, Phillippa Lally, Michael McEwan, Craig Melville, Leanne Harris, Olivia Wu

“…After this was finalised through iterative discussions between two researchers, the remaining studies were uploaded, and the coding framework was applied. …”
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Characterizing Breast Tumor Heterogeneity Through IVIM-DWI Parameters and Signal Decay Analysis by Si-Wa Chan, Chun-An Lin, Yen-Chieh Ouyang, Guan-Yuan Chen, Chein-I Chang, Chin-Yao Lin, Chih-Chiang Hung, Chih-Yean Lum, Kuo-Chung Wang, Ming-Cheng Liu

“…The methodology involved several steps: acquisition of multi-b-value IVIM-DWI images, image pre-processing, including correction for motion and intensity inhomogeneity, treating the multi-b-value data as hyperspectral image stacks, applying hyperspectral techniques like band expansion, and evaluating three tumor detection methods: kernel-based constrained energy minimization (KCEM), iterative KCEM (I-KCEM), and deep neural networks (DNNs). …”
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