Macroscopic consequences of demographic noise in non-equilibrium dynamical systems

For systems that are in equilibrium, fluctuations can be understood through interactions with external heat reservoirs. For this reason these fluctuations are known as thermal noise, and they usually become vanishingly small in the thermodynamic limit. However, many systems comprising interacting constituents studied by physicists in recent years are both far from equilibrium, and sufficiently small so that they must be considered finite. The finite number of constituents gives rise to an inherent demographic noise in the system, a source of fluctuations that is always present in the stochastic dynamics. This thesis investigates the role of stochastic fluctuations in the macroscopically observable dynamical behaviour of non-equilibrium, finite systems. To facilitate such a study, we construct microscopic models using an individual based modelling approach, allowing the explicit form of the demographic noise to be identified. In many physical systems and theoretical models, absorbing states are a defining feature. Once a system enters one, it cannot leave. We study the dynamics of a system with two symmetric absorbing states, finding that the amplitude of the multiplicative noise can induce a transition between two universal modes of domain coarsening as the system evolves to one of the absorbing states. In biological and ecological systems, cycles are a ubiquitously observed phenomenon, but are di cult to predict analytically from stochastic models. We examine a potential mechanism for cycling behaviour due to the flow of probability currents, induced by the athermal nature of the demographic noise, in a single patch population comprising two competing species. We find that such a current by itself cannot generate macroscopic cycles, but when combined with deterministic dynamics which constrain the system to a closed circular manifold, gives rise to global quasicycles in the population densities. Finally, we examine a spatially extended system comprising many such patch populations, exploring the emergence of synchronisation between the different cycles. By a stability analysis of the global synchronised state, we probe the relationship between the synchronicity of the metapopulation and the magnitude of the coupling between patches due to species migration. In all cases, we conclude that the nature of the demographic noise can play a pivotal role in the macroscopically observed dynamical behaviour of the system

Modeling adaptive dynamics in microbial populations with applications to the evolution of cellular resource allocation trade-offs

Adaptive evolution is the process by which natural selection, acting on variation within a population, promotes the survival of individuals that are more successful at reproducing and contributing to future generations. Evolutionary processes in microbes occur at the intersection of population genetics, natural selection, and underlying mechanistic constraints, to give rise to the repertoire of adaptation observed in nature. Understanding microbial adaptive evolution is of critical importance for human health for example, through the emergence of pathogenicity and antibiotic resistance. Moreover, the stability and function of natural and artificial ecosystems is contingent on the evolving interactions between microbes, and between microbes and the environment. We present a modelling framework, based on the theory of adaptive dynamics, to investigate how cellular resource allocation trade-offs affect the adaptation process. We used resource-consumer theory, which explicitly models the interactions between cells and their environment, together with matrix models of structured populations, to implement phenotype-determined cellular strategies of resource allocation between mutually exclusive processes. We then analyse the outcome of competitions between different phenotypes across environmental and competitive conditions. We applied our methods to the evolution of strategies (phenotypes) for resource allocation between two competing cellular process in microbial populations growing in chemostat-like environments. We calculated the adaptively stable strategies for several models and showed how state-structured population models can be mapped to simpler chemostat models on invariant manifolds. We then extended our analysis to the case where a limiting nutrient may be utilized using two alternative metabolic pathways. We described how the total population fitness of a metabolic strategy can be constructed from the individual decisions of its constituent members. We developed numerical methods to simulate and analyse general models of adaptive dynamics using principles from graph theory and discrete Markov processes. The methods were used to explore the evolution of nutrient use strategies for microbial populations growing on two and three substitutable nutrients. We highlight the importance of the ancestral phenotype in channelling the adaptation process, which, together with the choice of the mutational kernel, influences the adaptively stable strategies and modes of co-existence. In a related finding, we show how some phenotypes are adaptively stable only in the presence of a competitor lineage that modifies the environment in a manner that permits another phenotype to invade. Our methods also reveal instances where historical contingency and chance have an important effect on determining the stable nutrient use strategies. Finally, we demonstrate the existence of adaptively stable periodic solutions whereby, under some conditions, phenotype successions are cyclical. Our work builds on the foundation of adaptive dynamics theory to provide a general framework for analysing models of microbial adaptation. We focused on understanding the implications of underlying constraints and cellular resource allocation trade-offs in the context of adaptive evolution

Proceedings of the 2nd Conference on Production Systems and Logistics (CPSL 2021)

Proceedings of the CPSL 202

Distributed and Lightweight Meta-heuristic Optimization method for Complex Problems

The world is becoming more prominent and more complex every day. The resources are limited and efficiently use them is one of the most requirement. Finding an Efficient and optimal solution in complex problems needs to practical methods. During the last decades, several optimization approaches have been presented that they can apply to different optimization problems, and they can achieve different performance on various problems. Different parameters can have a significant effect on the results, such as the type of search spaces. Between the main categories of optimization methods (deterministic and stochastic methods), stochastic optimization methods work more efficient on big complex problems than deterministic methods. But in highly complex problems, stochastic optimization methods also have some issues, such as execution time, convergence to local optimum, incompatible with distributed systems, and dependence on the type of search spaces. Therefore this thesis presents a distributed and lightweight metaheuristic optimization method (MICGA) for complex problems focusing on four main tracks. 1) The primary goal is to improve the execution time by MICGA. 2) The proposed method increases the stability and reliability of the results by using the multi-population strategy in the second track. 3) MICGA is compatible with distributed systems. 4) Finally, MICGA is applied to the different type of optimization problems with other kinds of search spaces (continuous, discrete and order based optimization problems). MICGA has been compared with other efficient optimization approaches. The results show the proposed work has been achieved enough improvement on the main issues of the stochastic methods that are mentioned before.Maailmasta on päivä päivältä tulossa yhä monimutkaisempi. Resurssit ovat rajalliset, ja siksi niiden tehokas käyttö on erittäin tärkeää. Tehokkaan ja optimaalisen ratkaisun löytäminen monimutkaisiin ongelmiin vaatii tehokkaita käytännön menetelmiä. Viime vuosikymmenien aikana on ehdotettu useita optimointimenetelmiä, joilla jokaisella on vahvuutensa ja heikkoutensa suorituskyvyn ja tarkkuuden suhteen erityyppisten ongelmien ratkaisemisessa. Parametreilla, kuten hakuavaruuden tyypillä, voi olla merkittävä vaikutus tuloksiin. Optimointimenetelmien pääryhmistä (deterministiset ja stokastiset menetelmät) stokastinen optimointi toimii suurissa monimutkaisissa ongelmissa tehokkaammin kuin deterministinen optimointi. Erittäin monimutkaisissa ongelmissa stokastisilla optimointimenetelmillä on kuitenkin myös joitain ongelmia, kuten korkeat suoritusajat, päätyminen paikallisiin optimipisteisiin, yhteensopimattomuus hajautetun toteutuksen kanssa ja riippuvuus hakuavaruuden tyypistä. Tämä opinnäytetyö esittelee hajautetun ja kevyen metaheuristisen optimointimenetelmän (MICGA) monimutkaisille ongelmille keskittyen neljään päätavoitteeseen: 1) Ensisijaisena tavoitteena on pienentää suoritusaikaa MICGA:n avulla. 2) Lisäksi ehdotettu menetelmä lisää tulosten vakautta ja luotettavuutta käyttämällä monipopulaatiostrategiaa. 3) MICGA tukee hajautettua toteutusta. 4) Lopuksi MICGA-menetelmää sovelletaan erilaisiin optimointiongelmiin, jotka edustavat erityyppisiä hakuavaruuksia (jatkuvat, diskreetit ja järjestykseen perustuvat optimointiongelmat). Työssä MICGA-menetelmää verrataan muihin tehokkaisiin optimointimenetelmiin. Tulokset osoittavat, että ehdotetulla menetelmällä saavutetaan selkeitä parannuksia yllä mainittuihin stokastisten menetelmien pääongelmiin liittyen

Formaciones imaginarias del diseñador gráfico en el discurso del campo académico.

En este trabajo se describe un proyecto de tesis doctoral en el que se analiza el discurso sobre el diseñador gráfico. Se parte del supuesto de que existe una tricotomía de su perfil: 1) el campo profesional, 2) el campo educativo y, 3) el campo académico. Proponemos que dicha tricotomía permite la identificación de imaginarios sobre el tema, y no solo eso, sino que también aporta elementos que conforman la identidad (Bauman, 2002) de un diseñador gráfico. La pregunta de investigación es ¿Cuál es la identidad discursiva del diseñador gráfico en el campo académico? La investigación descrita es de tipo cualitativo y deductivo; para la construcción la identidad discursiva (Van Dijk, T; 2008) del diseñador gráfico, se toman en cuenta diversas publicaciones: principalmente investigaciones y breves artículos difundidos en comunidades/foros de reflexión y debate en torno a la temática, además de memorias de congresos y libros. En apoyo al desarrollo del proyecto se ha diseñado un Laboratorio de Intervención en el Diseño, cuyos objetivos son impulsar el desarrollo social y cultural de los diseñadores gráficos por medio de la investigación, educación continua, producción y vinculación. En un primer acercamiento a las formaciones imaginarias (Pêcheux, 1978) sobre la identidad del diseñador gráfico se centran en el grado de erudición para la ejecución de su trabajo, en la cultura que demuestran y en la autonomía con la que producen