Human V4 size predicts crowding distance by Jan W. Kurzawski, Brenda S. Qiu, Najib J. Majaj, Noah C. Benson, Denis G. Pelli, Jonathan Winawer

“…We conclude that the size of V4 predicts the spacing limit of visual perception.…”
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Prediction of the Reference Evapotranspiration Using a Chaotic Approach by Wei-guang Wang, Shan Zou, Zhao-hui Luo, Wei Zhang, Dan Chen, Jun Kong

“…The correlation dimension method was employed to investigate the chaotic behavior of the reference evapotranspiration series. …”
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PREDICTION OF MEAT PRODUCT QUALITY BY THE MATHEMATICAL PROGRAMMING METHODS by A. B. Lisitsyn, M. A. Nikitina, A. N. Zakharov, E. B. Sus, V. V. Nasonova, L. I. Lebedeva

“…Meat processing is accompanied by the complex physico-chemical, biochemical and mechanical processes. To predict the behavior of meat raw material during the technological processing, a complex of physico-technological and structural-mechanical indicators, which objectively reflects its quality, is used. …”
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Digital Twin-Driven Design of an Ice Prediction Model by Andrea Serino, Alberto Dagna, Eugenio Brusa, Cristiana Delprete

“…The characteristics of the icing phenomena are first defined, then their effects on aircraft behavior during operation are evaluated. This allows us to develop a highly parametric predictive model of the actual icing conditions experienced by the aircraft during a given flight mission. …”
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Junction temperature prediction Model Development with Co-simulation by Mustafa Ozden, Gokhan Ozkan, S M Imrat Rahman, Elutunji Buraimoh, Laxman Timilsina, Behnaz Papari, Christopher S. Edrington

“…This study examines the thermal behavior and junction temperature of MOSFET modules under varying operating conditions using ANSYS/Fluent software, with simulations managed through Python/Jupyter Notebook. …”
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Erasable hippocampal neural signatures predict memory discrimination by Nathaniel R. Kinsky, Daniel J. Orlin, Evan A. Ruesch, Brian Kim, Siria Coello, Kamran Diba, Steve Ramirez

“…Anisomycin also arrests learning-related remapping and blocks coordinated activity predictive of memory-related freezing behavior, effects that are likewise absent in untreated mice that exhibit poor memory expression. …”
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Predictive Modeling of Textile Heat Sinks for Enhanced Thermal Management in Space and Military Applications by Michal Frydrysiak, Piotr Kosobudzki

“…The aim of this research is to create a numerical model of a THS that not only simulates the thermal behavior of knitted fabrics, which are used to construct a THS, but also serves as a predictive tool for the heat flow coming from different devices, thus increasing thermal management safety. …”
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Development and Evaluation of Neural Network Architectures for Model Predictive Control of Building Thermal Systems by Jevgenijs Telicko, Andris Krumins, Agris Nikitenko

“…To address this challenge, model predictive control based on artificial neural networks can be employed. …”
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Dust impact on photovoltaic modules: Global data, predictive models, emphasis on chemical composition by Hussam Almukhtar, Tek Tjing Lie, Wisam Al-Shohani

“…Incorporating 690 global datasets and leveraging Artificial Neural Networks (ANN) and Multiple Linear Regression (MLR) in MATLAB, the study integrates key dust chemical components (Si, Fe, Ca, Al) and weight to predict the PV optical properties. This approach enhances models’ predictive accuracy across diverse environmental settings, which in turn enables more accurate forecasting of PV power output and thermal behavior under varying dust conditions, as these optical properties govern the module equations. …”
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Multifractal based topological characterization of perovskite crystal and predictive analysis on its physical properties by K. Yogalakshmi, D. Easwaramoorthy

“…In this paper, the topological indices are derived from the M-polynomial for CaTiO3 perovskite crystal structure depends on reverse degree using the edge partitioning technique and the behavior of this crystal structure is presented as numerically derived equations and topological descriptors. …”
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Tube-Based Robust Model Predictive Control for Autonomous Vehicle with Complex Road Scenarios by Yang Chen, Youping Sun, Junming Li, Jiangmei He, Chengwei He

“…More specifically, the proposed approach improves the representation of vehicle dynamic behavior by introducing a unified vehicle–tire modeling framework. …”
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Predicting Upcoming Events Occurring in the Space Surrounding the Hand by Maria L. Rangel, Lidiane Souza, Erika C. Rodrigues, José M. Oliveira, Michelle F. Miranda, Antonio Galves, Claudia D. Vargas

“…Predicting upcoming sensorimotor events means creating forward estimates of the body and the surrounding world. …”
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Economic-mathematical model for predicting financial market dynamics by Artur R. Musin

“…The main study purpose is developing a predictive economic-mathematical model that allows combining both approaches. …”
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Generalized Predictive Control for a Single-Phase, Three-Level Voltage Source Inverter by Diego Naunay, Paul Ayala, Josue Andino, Wilmar Martinez, Diego Arcos-Aviles

“…In contrast, generalized predictive control (GPC), part of CCS–MPC, offers significant advantages. …”
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Machine Learning-Based Prediction of No-Show Telemedicine Encounters by C. Mahony Reategui-Rivera, Wanting Cui, Stefan Escobar-Agreda, Leonardo Rojas-Mezarina, Joseph Finkelstein

“…Aim: This study aimed to evaluate the performance of machine learning (ML) models in predicting patient no-shows for telemedicine appointments within Peruvian health system and identify key predictors of nonattendance. …”
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Neural ODE-Based Dynamic Modeling and Predictive Control for Power Regulation in Distribution Networks by Libin Wen, Jinji Xi, Hong Hu, Li Xiong, Guangling Lu, Tannan Xiao

“…The NODE model demonstrates high accuracy in predicting the dynamic behavior in a DN against a detailed simulator, with maximum relative errors below 0.35% for active power. …”
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Predictive models for the surface roughness and subsurface damage depth of semiconductor materials in precision grinding by Shang Gao, Haoxiang Wang, Han Huang, Zhigang Dong, Renke Kang

“…Surface roughness and subsurface damage depth (SDD) are crucial indicators for evaluating the surface quality of these materials after grinding. Existing prediction models lack general applicability and do not accurately account for the complex material behavior under grinding conditions. …”
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On the interpretability of the SVM model for predicting infant mortality in Bangladesh by Md Abu Sayeed, Azizur Rahman, Atikur Rahman, Rumana Rois

“…Abstract Background Although machine learning (ML) models are well-liked for their outperformance in prediction, greatly avoided due to the lack of intuition and explanation of their predictions. …”
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Predictive Validity of the Patient Health Questionnaire‐9 for Depression in Poststroke Patients: A Systematic Review and Meta‐Analysis by Junya Chen, Mei Chan Chong, Hmwe Nant Thin Thin, Fen Xu, Xiao Dong, Xiaoxian Yang, Ruan Jia Yin, Huimin Hong

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Influenza and pneumococcal vaccine hesitancy in the elderly population: results from two representative surveys in Germany by Dorothee Heinemeier, Philipp Schmid, Sarah Eitze, Cornelia Betsch, Vaccination60+ study group

“…Multiple logistic regressions were conducted to identify the relevant determinants of vaccination behavior. Results Results show unique patterns in the psychological antecedents: while confidence, the belief in the effectiveness of vaccination and calculation, the need for information, complacency, the lack of risk perception and constraints, and perceived practical barriers to vaccination predicted influenza vaccination behavior, only complacency predicted pneumococcal vaccination behavior. …”
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