Skew Logistic Distribution Applied as Activation Function in Artificial Neural Networks by Eder Silva Dos Santos, Altemir da Silva Braga, Ana Beatriz Alvarez, Thuanne Paixao

Subjects: “…Activation function…”
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Research into Robust Federated Learning Methods Driven by Heterogeneity Awareness by Junhui Song, Zhangqi Zheng, Afei Li, Zhixin Xia, Yongshan Liu

Subjects: “…federated learning…”
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Shifted Hexpo activation function: An improved vanishing gradient mitigation activation function for disease classification by Joseph Otoo, Suleman Nasiru, Irene Dekomwine Angbing

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KCNJ2 Facilitates Clear Cell Renal Cell Carcinoma Progression and Glucose Metabolism by Qiyue Zhao, Zhengshu Wei, Guanglin Yang, Liwei Wei, Hao Chen, Zelin Cui, Naikai Liao, Min Qin, Jiwen Cheng

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Methyltransferase-like 3 is a target for the diagnose and therapy of clear cell renal carcinoma by Dongqiong Xiao, Xiaojuan Su

“…Patients diagnosed with clear cell renal carcinoma (ccRCC) frequently exhibit metastatic disease, which complicates treatment strategies, underscoring the urgent need for mechanistic insights and early diagnostic biomarkers. …”
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Assessment of Patient-Reported Outcomes in the Use of Clear Aligners Compared to Conventional Fixed Braces by Kakarla Subbaraju, Jashan Deep Goyal, Vijeta Patri, Pragyna Panigrahi, Mahishi G. Suthar, Praveen Kumar Varma, Afreen Kauser

“…Introduction: This study aims to compare patient-reported outcomes (PROs) between clear aligners and conventional fixed braces. Orthodontic treatments not only focus on functional outcomes but also patient satisfaction, comfort, and aesthetics. …”
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Synergistic application of molecular docking and machine learning for improved binding pose by Li Yaqi, Lin Hongrui, Yang He, Yuan Yannan, Zou Rongfeng, Zhou Gengmo, Zheng Linfeng, Zheng Hang

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Learning High-Dimensional Chaos Based on an Echo State Network with Homotopy Transformation by Shikun Wang, Fengjie Geng, Yuting Li, Hongjie Liu

“…Based on an echo state network (ESN), we introduce homotopy transformation in topological theory to learn high-dimensional chaos. On the premise of maintaining the basic topological properties, our model can obtain the key features of chaos for learning through the continuous transformation between different activation functions, achieving an optimal balance between nonlinearity and linearity to enhance the generalization capability of the model. …”
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Prediction of Corroded Pipeline Failure Pressure Based on Empirical Knowledge and Machine Learning by Hongbo Liu, Xiangzhao Meng

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Ensemble learning techniques reveals multidimensional EEG feature alterations in pediatric schizophrenia by Ying Mao, Ying Mao, Fang Wang, Shan Wang, Zhaowei Wang, Gang Li, Xuchen Qi, Xuchen Qi, Yu Sun, Yu Sun

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The dual-edged potential of AI autonomously defining loss functions by Abbas Ghori

Subjects: “…AI-defined loss functions…”
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The role of the body in learning and development of the Child by Manuela Valentini, Marta Vizzini, Monica Minucci

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Environmental adaptations in metagenomes revealed by deep learning by Johanna C. Winder, Simon Poulton, Taoyang Wu, Thomas Mock, Cock van Oosterhout

Subjects: “…Deep learning…”
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GEOGEBRA DALAM PEMBELAJARAN FUNGSI KUADRAT DAN PENGARUHNYA TERHADAP MOTIVASI DAN HASIL BELAJAR SISWA by Riska Ermilia, Laila Fitriana, Vitri Riyanti

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ACTION: Augmentation and computation toolbox for brain network analysis with functional MRI by Yuqi Fang, Junhao Zhang, Linmin Wang, Qianqian Wang, Mingxia Liu

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Enhancing Indian summer monsoon prediction: Deep learning approach for skillful long-lead forecasts of rainfall by Kalpesh R. Patil, Takeshi Doi, J.V. Ratnam, Swadhin K. Behera

“…We attempted to address this issue using a deep learning model based on convolutional neural networks (CNN). …”
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Comparative Analysis of Gradient Descent Learning Algorithms in Artificial Neural Networks for Forecasting Indonesian Rice Prices by Rica Ramadana, Agus Perdana Windarto, Dedi Suhendro

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Segmentation Studies on Al‐Si‐Mg Metallographic Images Using Various Different Deep Learning Algorithms and Loss Functions by Abeyram M. Nithin, Murukessan Perumal, M. J. Davidson, M. Srinivas, C. S. P. Rao, Katika Harikrishna, Jayant Jagtap, Abhijit Bhowmik, A. Johnson Santhosh

“…Other deep learning algorithms, such as Segnet, Resnet, and FCN, were compared with the Unet approach that was suggested. …”
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Physics-Informed Deep Learning for Three Dimensional Black Holes by Emad Yaraie, Hossein Ghaffarnejad, Mohammad Farsam

Subjects: “…machine learning, deep learning, black holes, three dimensions, btz…”
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Artificial Intelligence and Objective‐Function Methods Can Identify Bankfull River Channel Extents by Jonathan Garber, Karen Thompson, Matthew J. Burns, Joshphar Kunapo, Geordie Z. Zhang, Kathryn Russell

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