Modeling Evolution in Theory and Practice

This paper uses a number of examples of diverse types and functions of models in evolutionary biology to argue that the demarcation between theory and practice, or "theory model" and "data model." is often difficult to make. It is shown how both mathematical and laboratory models function as plausibility arguments, existence proofs, and refutations in the investigation of questions about the pattern and process of evolutionary history. I consider the consequences of this for the semantic approach to theories and theory confirmation. The paper attempts to reconcile the insights of both critics and advocates of the semantic approach to theories

Australian Marine Research in Progress: Great Barrier Reef Region 1988-1989

The Great Barrier Reef Marine Park Authority, with the assistance of the CSIRO Information Services Unit, has produced this update of the computer-based information system on Australian Marine Research in Progress (AMRIP) for the Great Barrier Reef Region only

Leo: Lagrange Elementary Optimization

Global optimization problems are frequently solved using the practical and efficient method of evolutionary sophistication. But as the original problem becomes more complex, so does its efficacy and expandability. Thus, the purpose of this research is to introduce the Lagrange Elementary Optimization (Leo) as an evolutionary method, which is self-adaptive inspired by the remarkable accuracy of vaccinations using the albumin quotient of human blood. They develop intelligent agents using their fitness function value after gene crossing. These genes direct the search agents during both exploration and exploitation. The main objective of the Leo algorithm is presented in this paper along with the inspiration and motivation for the concept. To demonstrate its precision, the proposed algorithm is validated against a variety of test functions, including 19 traditional benchmark functions and the CECC06 2019 test functions. The results of Leo for 19 classic benchmark test functions are evaluated against DA, PSO, and GA separately, and then two other recent algorithms such as FDO and LPB are also included in the evaluation. In addition, the Leo is tested by ten functions on CECC06 2019 with DA, WOA, SSA, FDO, LPB, and FOX algorithms distinctly. The cumulative outcomes demonstrate Leo's capacity to increase the starting population and move toward the global optimum. Different standard measurements are used to verify and prove the stability of Leo in both the exploration and exploitation phases. Moreover, Statistical analysis supports the findings results of the proposed research. Finally, novel applications in the real world are introduced to demonstrate the practicality of Leo.Comment: 28 page

Modeling Evolution in Theory and Practice

This paper uses a number of examples of diverse types and functions of models in evolutionary biology to argue that the demarcation between theory and practice, or "theory model" and "data model." is often difficult to make. It is shown how both mathematical and laboratory models function as plausibility arguments, existence proofs, and refutations in the investigation of questions about the pattern and process of evolutionary history. I consider the consequences of this for the semantic approach to theories and theory confirmation. The paper attempts to reconcile the insights of both critics and advocates of the semantic approach to theories

Modeling Evolution in Theory and Practice

This paper uses a number of examples of diverse types and functions of models in evolutionary biology to argue that the demarcation between theory and practice, or "theory model" and "data model." is often difficult to make. It is shown how both mathematical and laboratory models function as plausibility arguments, existence proofs, and refutations in the investigation of questions about the pattern and process of evolutionary history. I consider the consequences of this for the semantic approach to theories and theory confirmation. The paper attempts to reconcile the insights of both critics and advocates of the semantic approach to theories

Integration of parasite genetic information in malaria transmission modelling

Mathematical models of malaria transmission are increasingly used to quantify the impact of malaria control efforts and to assist in the development and costing of future initiatives such as the WHO Global Technical Strategy for Malaria 2016-2030. These models have highlighted both the progress made so far, but also how continued investment is needed to reach the milestones required. However, the increase in global malaria cases reported in 2018 suggests that new tools may be required to continue the gains made and to address the growing risk of antimalarial resistance threatening to reverse the recent declines in malaria burden. The proliferation of genetic sequencing and the publication of the Plasmodium falciparum reference genome in 2002 has facilitated a greater understanding of the genetic determinants of resistance and molecular tools are subsequently poised to become a routine tool for malaria control. Consequently, integrating parasite genetic information into established models of malaria transmission models can contribute to both our understanding of the drivers and optimum policies for addressing resistance and detailing the potential of molecular tools within malaria control. Plasmodium falciparum is known to have evolved several times in response to first line antimalarials. However, recent evidence has shown evolution to rapid diagnostic tests. The WHO has consequently issued guidance advising national malaria control programmes to conduct surveillance for pfhrp2/3 deletions. The timing of this policy recommendation and my previous work modelling pfhrp2 deletions necessitated a timely extension of our previous model to evaluate the implications of seasonality in malaria transmission on estimates of the prevalence of pfhrp2/3 deletions. Recent studies have suggested that malaria genotyping could be a useful tool for epidemiological surveillance. By developing an extended version of an established model of malaria transmission, which now models individual mosquitoes affording the full parasite life cycle to be represented, I characterise the potential utility of malaria genomics for inferring changes in transmission intensity. I conclude that although molecular tools could enable accurate estimation of malaria prevalence, greater attention needs to be placed on the chosen sampling scheme, recording patient metadata and developing the statistical toolkit for analysing polyclonal infected individuals. In 2015, health ministers in the Greater Mekong Subregion (GMS) adopted the WHO strategy for malaria elimination in the GMS 2016-2030. The strategy was developed to accelerate elimination in South-East Asia, which is currently the best approach to address the growing threat of artemisinin resistance and the emergence of multidrug resistant parasite lineages. In response, I demonstrate how the therapeutic lifespan of the five currently recommended artemisinin combination therapies can be prolonged by reducing antimalarial overprescription by ensuring that all suspected malaria fevers are tested before administering antimalarials. I conclude by comparing different cycling and mixing strategies before reviewing how each strategy can be improved to slow the spread of antimalarial resistance. Elimination in the GMS is undoubtedly an effective mechanism for preventing the spread of artemisinin resistance to Africa. However, if efforts to eliminate by 2030 have failed it will be imperative to understand the mechanisms with which resistance may continue to spread. To this extent, the capability of resistant strains to invade susceptible populations is evaluated using data from standard membrane feeding assays. Findings are incorporated in the transmission model to quantify the transmission advantage of artemisinin resistance at the population level.Open Acces

Patrons de diversité génétique brassés par la migration et la recombinaison

This thesis presents two different models to study how recombination and migration shuffle genetic diversity. In the first model, recombination is the only evolutionary force. At time 0, each individual has her unique chromosome painted in a distinct color. By the blending effect of recombination, the genomes of the descending individuals look like mosaics of colors, each color representing the genetic material inherited from a different ancestral individual. Each segment of the same color is called an identical-by-descent (IBD) segment. We have been able to characterize the sizes and positions of the segments that are IBD to a given locus in the chromosome of a randomly sampled individual in the population. The second model is devoted to the study of the effects of geographic structure, migration, mutation and recombination in the genetic composition of a metapopulation. The metapopulation is modelled as a graph where vertices correspond to subpopulations and edges are associated to migration rates. The idea behind this project is to study speciation: when two subpopulations accumulate enough genetic differences they may become separate species. We have been able to characterize the distribution of the genetic distances between subpopulations in a low mutation - low migration regime, depending on the geographic structure, and to show that some geographic configurations can promote speciation.Cette thèse présente deux modèles différents pour étudier comment la recombinaison et la migration permettent de brasser la diversité génétique. Dans le premier modèle, au temps 0, chaque individu a son chromosome peint d’une couleur différente. Par l’effet de la recombinaison, les génomes des descendants sont des mosaïques de couleurs, où chaque couleur représente le matériel génétique hérité d’un des ancêtres. Chaque segment d’une même couleur correspond à un segment identique par descendance (IBD en anglais). Nous avons caractérisé la distribution des blocks IBD dans le chromosome d’un individu échantillonné au hasard dans la population. Le deuxième modèle permet d’étudier l’effet de la structure géographique, la migration, la mutation et la recombinaison sur la composition génétique d’une métapopulation. La métapopulation est représentée par un graphe où chaque sommet représente une sous-population et chaque arrête est associée à un taux de migration. Le but est d’étudier la speciation: quand deux sous-populations accumulent assez de différences génétiques, elles peuvent former deux espèces séparées. Nous avons caractérisé la distribution des distances génétiques entre les sous-populations dans un régime de mutation et migration rares, en fonction de la structure géographique. Nous avons montré que certaines structures géographiques peuvent favoriser la speciation

Adaptive evolution in static and dynamic environments

This thesis provides a framework for describing a canonical evolutionary system. Populations of individuals are envisaged as traversing a search space structured by genetic and developmental operators under the influence of selection. Selection acts on individuals' phenotypic expressions, guiding the population over an evaluation landscape, which describes an idealised evaluation surface over the phenotypic space. The corresponding valuation landscape describes evaluations over the genotypic space and may be transformed by within generation adaptive (learning) or maladaptive (fault induction) local search. Populations subjected to particular genetic and selection operators are claimed to evolve towards a region of the valuation landscape with a characteristic local ruggedness, as given by the runtime operator correlation coefficient. This corresponds to the view of evolution discovering an evolutionarily stable population, or quasi-species, held in a state of dynamic equilibrium by the operator set and evaluation function. This is demonstrated by genetic algorithm experiments using the NK landscapes and a novel, evolvable evaluation function, The Tower of Babel. In fluctuating environments of varying temporal ruggedness, different operator sets are correspondingly more or less adapted. Quantitative genetics analyses of populations in sinusoidally fluctuating conditions are shown to describe certain well known electronic filters. This observation suggests the notion of Evolutionary Signal Processing. Genetic algorithm experiments in which a population tracks a sinusoidally fluctuating optimum support this view. Using a self-adaptive mutation rate, it is possible to tune the evolutionary filter to the environmental frequency. For a time varying frequency, the mutation rate reacts accordingly. With local search, the valuation landscape is transformed through temporal smoothing. By coevolving modifier genes for individual learning and the rate at which the benefits may be directly transmitted to the next generation, the relative adaptedness of individual learning and cultural inheritance according to the rate of environmental change is demonstrated

Virginia Commonwealth University Graduate Bulletin

Graduate bulletin for Virginia Commonwealth University includes information on academic regulations, degree requirements, course offerings, faculty, academic calendar, and tuition and expenses for graduate programs