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Recolector de Ciencia Abierta, RECOLECTA
Doctoral thesis . 2023
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Collective behavior of biological aggregates

Authors: González Albaladejo, Rafael;

Collective behavior of biological aggregates

Abstract

El comportamiento de los sistemas vivos puede mostrar fenómenos emergentes que no están presentes en sus componentes individuales. Los sistemas vivos están alejados del equilibrio, pueden carecer de leyes de conservación y es todo un reto emplear herramientas de la física estadística y la termodinámica. Experimentos y observaciones cuantitativas producen una gran cantidad de datos que permiten diseñar modelos que expliquen aspectos importantes del comporamiento de estos sistemas. Esta tesis se centra en dos temas, el comportamiento colectivo de los enjambres de insectos voladores como los mosquitos y el comportamiento colectivo de las biopelículas bacterianas. Los estudios previos de enjambres de insectos se han centrado en su formación como una transición orden-desorden, lo que no explica muchos aspectos tanto cualitativos como cuantitativos. En esta tesis estudiamos el modelo de Vicsek confinado por un potencial armónico. Usando herramientas de sistemas dinámicos y de mecánica estadística hemos descubierto una nueva transición de fase caracterizada por caos libre de escalas, que presenta leyes de potencias y tiene rasgos cualitativos compatibles con las observaciones y experimentos de laboratorio de enjambres de dípteros. Por otro lado, las biopelículas bacterianas plantean un reto teórico, pues se debe modelar elementos a diferentes escalas espaciales y temporales. Presentamos un modelo híbrido basado en una arquitectura de fronteras inmersas con un metabolismo de presupuesto de balance energético. El modelo captura las diferencias geométricas entre bacterias, generando patrones diversos según su forma y competencia entre bacterias de distintos tipos. Permite estudiar la resistencia de biopelículas a antibióticos y el diseño de cócteles para erradicarlos.

The behavior of living systems can exhibit emergent phenomena that are not present in their individual components. Living systems are far from equilibrium, may lack conservation laws and using tools from statistical physics and thermodynamics is challenging. However, quantitative observations and experiments yield a wealth of data that allow to design models capturing important aspects of the behavior of these systems. This thesis focuses on two topics, the collective behavior of midge swarms and the collective behavior of bacterial biofilms. Prior studies of insect swarms have focused on their formation as an ordering phase transition, which fails to capture many qualitative and quantitative features. In this thesis we study the Vicsek model confined by a harmonic potential. By using dynamical systems and statistical mechanics tools, we have discovered a novel phase transition characterized by scale free chaos, which exhibits power laws and present qualitative features compatible with observations of swarms of male midges in nature and in the laboratory. On the second topic, bacterial biofilms pose a challenge to theorists, who must model elements on different spatial and temporal scales. We present a hybrid model based on an architecture of immersed boundaries with a dynamic energy budget metabolism. The model captures geometric differences between bacteria, being able to reproduce varied patterns depending on their shapes and competence phenomena between different types. We can study antibiotic resistance in biofilms and test cocktails to eradicate them.

Country
Spain
Related Organizations
Keywords

Biomathematics, Dynamical phase transitions, Mathematical model, Scale free chaos, Matemáticas, Vicsek model, Biología y Biomedicina

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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