CrossInteractions · Models with cross interactions between partial dynamical processes aiming to understand significant or abrupt dynamic changes.

Models with cross interactions between partial dynamical processes aiming to understand significant or abrupt dynamic changes.

The purpose of the "CrossInteractions" project is to study and understand crucial events in nonlinear dynamical systems, with a special emphasis on bifurcations that often signal abrupt and significant shifts in system behavior. By modeling such transitions, the research aims to enhance predictive capabilities, inform state-of-the-art strategies, and establish best practices in fields such as population biology, neurology, and epidemiology. The motivation for this study stems from the urgent need to decipher and control complex systems where small changes can lead to significant effects on behavior. Such transitions are frequently observed in ecosystems affected by disturbances, neural networks governing brain activity, and the spread of infectious diseases. This study seeks to explain these shifts using bifurcation theory, thereby providing both theoretical frameworks and practical decision-making tools. In population biology, the study examines the dynamic interplay of prey-predator systems in fragmented habitats, focusing on how interagent interactions affect the stability, persistence, and biodiversity of species within ecosystems. Understanding chaotic and periodic patterns in these systems is crucial for conservation and ecosystem management. The neurological component of the study analyzes how modular neuronal subsystems influence synchronization dynamics and conflicts in neural activity. These transitions often arise from synchronization events, which play a critical role in motor control, learning, and perception. Using bifurcation theory, the research investigates the mechanics underlying transient behaviors, particularly their implications for disorders such as focal epilepsy. This includes studying high-frequency oscillations (HFOs) and phase synchronization in interconnected neuronal networks, offering insights into novel biomarkers for epilepsy and other synchronization-related neurological disorders. The findings aim to advance neuroscience and provide new approaches to managing neurological diseases, ultimately improving clinical outcomes. The epidemiological aspect of the project focuses on how seasonal variations, vaccination strategies, and other external factors influence the progression of infectious disease epidemics. The results will directly inform public health decision-making, enhancing preparedness and mitigation strategies for future outbreaks. By exploring the interaction between epidemic cycles and seasonality, this research provides actionable insights into managing diseases such as COVID-19. The "CrossInteractions" project bridges mathematical biology, social sciences, and public health to ensure both social relevance and theoretical rigor. By promoting multidisciplinary collaboration and making mathematical tools accessible, the project highlights their applicability in real-world scenarios. Its emphasis on open research, sustainability, and international cooperation underscores the goal of maximizing societal impact. The expected outputs of "CrossInteractions" include the development of theoretical knowledge, predictive models, and sustainable solutions for environmental policy, healthcare, and public policy. These contributions are anticipated to have a far-reaching impact, aiding in biodiversity conservation, improving neurological health, and guiding epidemic control strategies. By addressing fundamental socioeconomic and ecological challenges, the project is both academically significant and practically relevant.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз