We present a novel mathematical model of two adversarial forces in the vicinity of a non-combatant population in order to explore the impact of each force pursuing specific decision-making strategies. Each force has the opportunity to draw support by enabling the decision-making initiative of the population, in tension with maintaining tactical and organisational effectiveness over their adversary. Each dynamic model component of force, population and decision-making, is defined by the archetypal Lanchester, Lotka-Volterra and Kuramoto-Sakaguchi models, with feedback between each component adding heterogeneity. Developing a scheme where cultural factors determine decision-making strategies for each force, this work highlights the parametric and topological factors that influence favourable results in a non-linear system where physical outcomes are highly dependent on the non-physical and cognitive nature of each force's intended strategy.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0281169 | PLOS |
J Am Med Inform Assoc
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Institute of Data Science, National University of Singapore, 117602, Singapore.
Objectives: This study introduces Smart Imitator (SI), a 2-phase reinforcement learning (RL) solution enhancing personalized treatment policies in healthcare, addressing challenges from imperfect clinician data and complex environments.
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Department of Research, Norwegian Institute of Public Health, Oslo, Norway.
Introduction: Somalia is continuing to recover from three decades of underdevelopment, political instability, civil unrest, and protracted humanitarian crises. However, Somalia has one of the lowest maternal health indicators in the world. For instance, the maternal mortality ratio is 621 per 100,000 live births.
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School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China.
Stock trend prediction is a significant challenge due to the inherent uncertainty and complexity of stock market time series. In this study, we introduce an innovative dual-branch network model designed to effectively address this challenge. The first branch constructs recurrence plots (RPs) to capture the nonlinear relationships between time points from historical closing price sequences and computes the corresponding recurrence quantifification analysis measures.
View Article and Find Full Text PDFAm J Ther
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Faculty of Medicine, "Transilvania" University, Brasov, Romania; and.
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View Article and Find Full Text PDFCancer Nurs
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Author Affiliations: Department Research, Hospital Germans Trias i Pujol, Universitat Autonòma de Barcelona; and NURECARE Research Group, Institut d'Investigació i Hospital Germans Trias i Pujol (IGTP), Ctra de Can Ruti, Camí de les Escoles (Dr Huertas-Zurriaga); Department Research, Institut Català Oncologia-Hospital Germans Trias i Pujol; Universitat Autonòma de Barcelona; GRIN Group, IDIBELL, Institute of Biomedical Research; and NURECARE Research Group, IGTP, Ctra de Can Ruti, Camí de les Escoles (Dr Cabrera-Jaime); Tecnocampus University and NURECARE Research Group, IGTP, Ctra de Can Ruti, Camí de les Escoles (Dr Navarri); Oncology Department, Hereditarian Cancer Program, Institut Català Oncologia-Hospital Germans Trias i Pujol, B-ARGO (Badalona Applied Research Group in Oncology), IGTP (Health Research Institute Germans Trias i Pujol), Universitat Autònoma de Barcelona (Dr Teruel-Garcia); and Nursing Research Group in Vulnerability and Health (GRIVIS); and Nursing Department, Faculty of Medicine, Universitat Autònoma de Barcelona (Dr Leyva-Moral), Badalona, Spain.
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