The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population

We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology

Modelling Evolution in Structured Populations Involving Multiplayer Interactions

We consider models of evolution in structured populations involving multiplayer games. Whilst also discussing other models, we focus on the modelling framework developed by Broom and Rychtář (J Theor Biol 302:70–80, 2012) onwards. This includes key progress so far, the main gaps and limitations, the relationship and synergies with other models and a discussion of the direction of future work. In this regard as well as discussing existing work, there is some new research on the applicability and robustness of current models with respect to using them to model real populations. This is an important potential advance, as previously all of the work has been entirely theoretical. In particular, the most complex models will have many parameters, and we concentrate on considering simpler versions with a small number of parameters which still possess the key features which would make them applicable. We find that these models are generally robust, in particular issues that can arise related to small payoff changes at critical values and removal of pivotal vertices would have similar effects on other modelling system including evolutionary graph theory. These often occur where it can be argued that there is a lack of robustness in the real system that the model faithfully picks up, and so is not a problematic feature

Network topology and movement cost, not updating mechanism, determine the evolution of cooperation in mobile structured populations

Evolutionary models are used to study the self-organisation of collective action, often incorporating population structure due to its ubiquitous presence and long-known impact on emerging phenomena. We investigate the evolution of multiplayer cooperation in mobile structured populations, where individuals move strategically on networks and interact with those they meet in groups of variable size. We find that the evolution of multiplayer cooperation primarily depends on the network topology and movement cost while using different stochastic update rules seldom influences evolutionary outcomes. Cooperation robustly co-evolves with movement on complete networks and structure has a partially detrimental effect on it. These findings contrast an established principle from evolutionary graph theory that cooperation can only emerge under some update rules and if the average degree is lower than the reward-to-cost ratio and the network far from complete. We find that group-dependent movement erases the locality of interactions, suppresses the impact of evolutionary structural viscosity on the fitness of individuals, and leads to assortative behaviour that is much more powerful than viscosity in promoting cooperation. We analyse the differences remaining between update rules through a comparison of evolutionary outcomes and fixation probabilities

Models and measures of animal aggregation and dispersal

The dispersal of individuals within an animal population will depend upon local properties intrinsic to the environment that differentiate superior from inferior regions as well as properties of the population. Competing concerns can either draw conspecifics together in aggregation, such as collective defence against predators, or promote dispersal that minimizes local densities, for instance to reduce competition for food. In this paper we consider a range of models of non-independent movement. We include established models, such as the ideal free distribution, but also develop novel models, such as the wheel. We also develop several ways to combine different models to create a flexible model of addressing a variety of dispersal mechanisms. We further devise novel measures of movement coordination and show how to generate a population movement that achieves appropriate values of the measure specified. We find the value of these measures for each of the core models described, as well as discuss their use, and potential limitations, in discerning the underlying movement mechanisms. The movement framework that we develop is both of interest as a stand-alone process to explore movement, but also able to generate a variety of movement patterns that can be embedded into wider evolutionary models where movement is not the only consideration

Рентгенологическое исследование как альтернативный метод визуализации изменений в легких при инфекции, вызванной Covid-19

Introduction. Despite the existence of generally accepted diagnostic protocols, when a new coronavirus infection is suspected, in some cases, it is increasingly difficult to detect changes in the lung tissue in a timely manner due to the heavy workload of the main method of radiation diagnostics – computed tomography. Purpose of the study. To determine the effectiveness of the appointment of an X-ray examination as first-line metgod, as well as to carry out a comparative analysis of the use of radiation diagnostics methods – computed tomography and radiography in relation to the diagnostic sensitivity to changes in lung tissue when a person is infected with the SARS-COV-2 virus.Materials and methods. 150 patients (63.0 ± 8.4 years) with confirmed coronavirus infection were examined. Each of the participants underwent X-ray examination and computed tomography of the chest organs. The percentage of subjects studied for each of the degrees of severity of lung damage was determined to identify the proportion of involvement of lung tissue in the pathological process in the bulk of the examined individuals.Results. Of the 150 patients, changes in the lung tissue during chest X-ray were detected in 97 (65%), respectively, in 53 (35%), pathological changes in the lungs were not visualized. When examining patients by computed tomography, changes in the lungs were detected in 143 patients (95%), X-ray morphological changes were not detected in 7 subjects (5%). When detecting the volume of lung damage, it turned out that the majority of the subjects – 86 people (57%) – had the degree of damage CT-2. The degree of CT-1 and CT-3 was determined in 26 (17%) and 25 (17%) patients, respectively. CT-4 was observed in 6 patients (4%), and in 5% of cases, CT was not able to detect pathological changes in the lung tissue, the degree of CT-0 was established.Conclusion. In the assessment of viral lung damage, radiography takes a significant place, but in 35% of cases, radiographic examination failed to identify the existing pathological changes. CT of the chest organs confirms its value as the “gold standard” in the study of pulmonary pathology in coronavirus infection, but if it is impossible to perform it, radiography is recommended.Введение. Несмотря на наличие общепринятых протоколов диагностики, при подозрении на наличие новой коронавирусной инфекции, в ряде случаев все чаще отмечаются трудности своевременного выявления изменений в легочной ткани ввиду большой загруженности основного метода лучевой диагностики – компьютерной томографии.Цель исследования. Определить эффективность назначения рентгенологического обследования, а также провести сравнительный анализ применения методов лучевой диагностики – компьютерной томографии и рентгенографии в отношении чувствительности к изменению легочной ткани при инфицировании человека вирусом sars-cov-2.Материалы и методы. Было обследовано 150 пациентов (63,0 + 8,4 лет) с подтвержденной коронавирусной инфекцией. Каждому из участников было проведено рентгенологическое обследование и компьютерная томография. Также определен процент исследуемых по каждому из степеней тяжести поражения для выявления процентного соотношения объема вовлечения легких в патологический процесс у основной массы обследуемых лиц.Результаты. Из 150 пациентов изменения легочной ткани посредством проведения рентгена были обнаружены у 97 исследуемых (65%), соответственно у 53 человек (35%) патологические преобразования в легких не визуализировались. При обследовании больных методом компьютерной томографии изменения в легких были выявлены у 143 пациентов (95%), морфологических изменений не было обнаружено у 7 обследуемых (5 %). При выявлении объема поражения легких выяснилось, что основной массе обследуемых - 86 человек (57%) была установлена степень поражения КТ-2.  Степень КТ-1 и КТ-3 определили у 26 (17%) и 25 (17%) пациентов соответственно. КТ-4 наблюдалась у 6 больных (4%), и в 5% случаев КТ не удалось определить патологических изменений в легочной системе, была установлена степень КТ-0.Заключение. В оценке вирусного поражения легких рентгенография занимает существенное место, но в 35% случаев рентгену не удалось идентифицировать патологические изменения. КТ является «золотым стандартом» при исследовании легочной патологии, однако при невозможности проведения компьютерной томографии допускается проведение рентгенографии

The Evolution of Cooperation in a Mobile Population on Random Networks: Network Topology Matters Only for Low-Degree Networks

We consider a finite structured population of mobile individuals that strategically explore a network using a Markov movement model and interact with each other via a public goods game. We extend the model of Erovenko et al. (Proc R Soc A: Math Phys Eng Sci 475(2230):20190399, 2019) from complete, circle, and star graphs to various random networks to further investigate the effect of network topology on the evolution of cooperation. We discover that the network topology affects the outcomes of the evolutionary process only for networks of small average degree. Once the degree becomes sufficiently high, the outcomes match those for the complete graph. The actual value of the degree when this happens is much smaller than that of the complete graph, and the threshold value depends on other network characteristics