Unexpected feedback enhances episodic memory: Exploring signed and unsigned reward prediction errors with EEG by Yun Chen, Chunyu Zhao, Rong Liu, Qi Li

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Machine learning prediction of interfacial bond strength of FRP bars with different surface characteristics to concrete by Lingyu Tian, Luchen Wang, Guijun Xian

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Rapid prediction of beef colour evolution and myoglobin forms using near-infrared spectroscopy (NIRS) by Wenyang Jia, Nigel Scollan, Anastasios Koidis

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Evaluating the feasibility of using crystalline patterns induced by PBF-LB to predict strength enhancing orientations by José David Pérez-Ruiz, Luis Norberto López de Lacalle, Wilmer Velilla-Díaz, Jaime A. Mesa, Gaizka Gómez, Heriberto Maury, Gorka Urbikain, Haizea Gonzalez

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Data-driven electrochemical behavior prediction for refractory high-entropy alloys by global and focused learning by Xinpeng Zhao, Haiyou Huang, Yanjing Su, Lijie Qiao, Yu Yan

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iPSC-hepatocyte organoids as a novel platform to predict AAV gene therapy efficacy by Estelle Berreur, Giacomo Lazzaroni, Cyrill Roth, Marco Zihlmann, Martina Stirn, Ramona Matheis, Rebecca Xicluna, Ekaterina Breous-Nystrom, Adrian B. Roth

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Predicting Training Transfer of Oxygen Therapy During COVID-19: Theory of Planned Behavior Application by Hatam Faraji Dehsorkhi, Mostafa Azizi Shamami, Ali Asghar Hayat, Javad Rokni

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Comparative analysis prediction of prostate and testicular cancer mortality using machine learning: accuracy study by Aurélio Gomes de Albuquerque Neto, David Medeiros Nery, João Paulo Araújo Braz, Carla Ferreira do Nascimento, Tiago Almeida de Oliveira, Brígida Gabriele Albuquerque Barra, Leonardo Thiago Duarte Barreto Nobre, Diego Bonfada, Janine Karla França da Silva Braz

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EchoPT: A Pretrained Transformer Architecture That Predicts 2D In-Air Sonar Images for Mobile Robotics by Jan Steckel, Wouter Jansen, Nico Huebel

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Combined application of life cycle assessment and neural network model for modeling energy and environmental emissions in sugar beet production by Imane Mehdi, Abdelhalim Chmarkhi, Mohammed Ammari, Laïla Ben Allal

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Self-reported motoric cognitive risk syndrome predicts long-term mortality in older adults by Yiwen Xing, Li Zhang, Pan Liu, Yiming Pan, Zhe Tang, Lina Ma

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Analysis and prediction of storability and storage quality of pear fruit based on clustering and time series analysis by ZHOU Hui-juan, YE Zheng-wen, LI Rong-hua, WANG Xiao-qing, LUO Jun

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Predicting Interplanetary Shock Occurrence for Solar Cycle 25: Opportunities and Challenges in Space Weather Research by Denny M. Oliveira, Robert C. Allen, Livia R. Alves, Séan P. Blake, Brett A. Carter, Dibyendu Chakrabarty, Giulia D’Angelo, Kevin Delano, Ezequiel Echer, Cristian P. Ferradas, Matt G. Finley, Bea Gallardo‐Lacourt, Dan Gershman, Jesper W. Gjerloev, John Bosco Habarulema, Michael D. Hartinger, Rajkumar Hajra, Hisashi Hayakawa, Liisa Juusola, Karl M. Laundal, Robert J. Leamon, Michael Madelaire, Miguel Martínez‐Ledesma, Scott M. McIntosh, Yoshizumi Miyoshi, Mark B. Moldwin, Emmanuel Nahayo, Dibyendu Nandy, Bhosale Nilam, Katariina Nykyri, William R. Paterson, Mirko Piersanti, Ermanno Pietropaolo, Craig J. Rodger, Trunali Shah, Andy W. Smith, Nandita Srivastava, Bruce T. Tsurutani, S. Tulasi Ram, Lisa A. Upton, Bhaskara Veenadhari, Sergio Vidal‐Luengo, Ari Viljanen, Sarah K. Vines, Vipin K. Yadav, Jeng‐Hwa Yee, James W. Weygand, Eftyhia Zesta

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Integrating traditional and non-traditional model risk frameworks in credit scoring by Hendrik A. du Toit, Willem D. Schutte, Helgard Raubenheimer

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Environmental Data Analytics for Smart Cities: A Machine Learning and Statistical Approach by Ali Suliman AlSalehy, Mike Bailey

“…This work enhances understanding of CO dynamics in complex urban–industrial areas, providing accurate predictive models (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mi>R</mi><mn>2</mn></msup><mo>></mo><mn>0.95</mn></mrow></semantics></math></inline-formula>) and highlighting the importance of local sources and temporal patterns for improving air quality forecasts.…”
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Noncoding variants and sulcal patterns in congenital heart disease: Machine learning to predict functional impact by Enrique Mondragon-Estrada, Jane W. Newburger, Steven R. DePalma, Martina Brueckner, John Cleveland, Wendy K. Chung, Bruce D. Gelb, Elizabeth Goldmuntz, Donald J. Hagler, Jr., Hao Huang, Patrick McQuillen, Thomas A. Miller, Ashok Panigrahy, George A. Porter, Jr., Amy E. Roberts, Caitlin K. Rollins, Mark W. Russell, Martin Tristani-Firouzi, P. Ellen Grant, Kiho Im, Sarah U. Morton

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HELQ upregulates PARP1 to drive platinum resistance and predict therapeutic response in ovarian cancer by Shuran Tan, Fang Zhu, Yi Li, Xinxin Wen, Siyu Yang, Zexi Liao, Xuerui Duan, Di Xiao, Yu Zhang

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Filter for Traffic Congestion Prediction: Leveraging Traffic Control Signal Actions for Dynamic State Estimation by Younus Hasan Taher, Jit Singh Mandeep, Mohammad Tariqul Islam, Omer Tareq Abdulhae, Ahmed Thair Shakir, Md. Shabiul Islam, Mohamed S. Soliman

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Correlation Between Depression-Associated Genes and Cancer Types: Predicting Cancer Based on Mutation Frequencies by Fernando Patricio Carranco-Avila, Clayanela Zambrano-Caicedo, Jonathan Javier Loor-Duque, Ariana Deyaneira Jimenez-Narvaez, Ivan Galo Reyes-Chacon, Paulina Vizcaino, Isidro Rafael Amaro Martin, Manuel Eugenio Morocho-Cayamcela

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Triglyceride-Glucose Index Predicts Major Adverse Cardiovascular and Cerebrovascular Events in Non-Diabetic Individuals by Cangtuo Li, Qi Qi, Wansong Li, Xuechao Zhang, Lei Li, Jie Deng, Quanle Han, Shouling Wu, Kangbo Li

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