The Organization and Control of an Evolving Interdependent Population

Starting with Darwin, biologists have asked how populations evolve from a low fitness state that is evolutionarily stable to a high fitness state that is not. Specifically of interest is the emergence of cooperation and multicellularity where the fitness of individuals often appears in conflict with that of the population. Theories of social evolution and evolutionary game theory have produced a number of fruitful results employing two-state two-body frameworks. In this study we depart from this tradition and instead consider a multi-player, multi-state evolutionary game, in which the fitness of an agent is determined by its relationship to an arbitrary number of other agents. We show that populations organize themselves in one of four distinct phases of interdependence depending on one parameter, selection strength. Some of these phases involve the formation of specialized large-scale structures. We then describe how the evolution of independence can be manipulated through various external perturbations.Comment: To download simulation code cf. article in Proceedings of the Royal Society, Interfac

The Simulation Model of a Sliding Contact

This paper deals with the brush slip ring contact modeling. Approaches the sliding contact problem with the synergy theory. The contact layer is considered using mechanical, electrical and thermal properties. The simulation model includes algorithms of: - generation of microscale contact surface, - approachment of two surfaces, - fritting and breakdown effects of oxide layer, - extracting clusters of conducting area, - calculating constriction resistance using fractal dimensionality, - generation of heat caused by electrical current and mechanical friction, - calculation of integral characteristics. The program implementing the model may be used to optimize the contact materials before time-consuming and expensive tests. Finally discusses the implemented model and its results, problems of verification and validation

Readiness of Quantum Optimization Machines for Industrial Applications

There have been multiple attempts to demonstrate that quantum annealing and, in particular, quantum annealing on quantum annealing machines, has the potential to outperform current classical optimization algorithms implemented on CMOS technologies. The benchmarking of these devices has been controversial. Initially, random spin-glass problems were used, however, these were quickly shown to be not well suited to detect any quantum speedup. Subsequently, benchmarking shifted to carefully crafted synthetic problems designed to highlight the quantum nature of the hardware while (often) ensuring that classical optimization techniques do not perform well on them. Even worse, to date a true sign of improved scaling with the number of problem variables remains elusive when compared to classical optimization techniques. Here, we analyze the readiness of quantum annealing machines for real-world application problems. These are typically not random and have an underlying structure that is hard to capture in synthetic benchmarks, thus posing unexpected challenges for optimization techniques, both classical and quantum alike. We present a comprehensive computational scaling analysis of fault diagnosis in digital circuits, considering architectures beyond D-wave quantum annealers. We find that the instances generated from real data in multiplier circuits are harder than other representative random spin-glass benchmarks with a comparable number of variables. Although our results show that transverse-field quantum annealing is outperformed by state-of-the-art classical optimization algorithms, these benchmark instances are hard and small in the size of the input, therefore representing the first industrial application ideally suited for testing near-term quantum annealers and other quantum algorithmic strategies for optimization problems.Comment: 22 pages, 12 figures. Content updated according to Phys. Rev. Applied versio

Nonlocal one-dimensional Fisher-Kolmogorov-Petrovskii-Piskunov equation with abnormal diffusion

Analytical solutions are constructed for the nonlocal space fractional Fisher-Kolmogorov-Petrovskii- Piskunov equation with abnormaldiffusion. Such solutions allow us to describe quasi-steady state patterns. Special attention is given to the role of fractional derivative. Fractional diffusion equations are useful for applications in which a cloud of particles spreads faster than predicted by the classical equation. The resulting solutions spread faster than the classical solutions and may exhibit asymmetry, depending on the fractional derivative used. Results of numerical simulations and properties of analytical solutions are presented. Influence of the fractional derivative on patterns ordered in space and time is discussed

Nuclear rocket engine

This article describes a solution to the problem of insufficient capacity of existing rocket engines for interplanetary missions. Development in the sphere was analyzed by comparing the examples of the rockets of 1970 and present time. Further development of the nuclear engine is discussed

Modeling the Role of Networks and Individual Differences in Inter-Group Violence

There is significant heterogeneity within and between populations in their propensity to engage in conflict. Most research has neglected the role of within-group effects in social networks in contributing to between-group violence and focused instead on the precursors and consequences of violence, or on the role of between-group ties. Here, we explore the role of individual variation and of network structure within a population in promoting and inhibiting group violence towards other populations. Motivated by ethnographic observations of collective behavior in a small-scale society, we describe a model with differentiated roles for individuals embedded within friendship networks. Using a simple model based on voting-like dynamics, we explore several strategies for influencing group-level behavior. When we consider changing population level attitude changes and introducing control nodes separately, we find that a particularly effective control strategy relies on exploiting network degree. We also suggest refinements to our model such as tracking fine-grained information spread dynamics that can lead to further enrichment in using evolutionary game theory models for sociological phenomena

The Structure of Negative Social Ties in Rural Village Networks

Negative (antagonistic) connections have been of longstanding theoretical importance for social structure. In a population of 24,696 adults interacting face to face within 176 isolated villages in western Honduras, we measured all connections that were present, amounting to 105,175 positive and 16,448 negative ties. Here, we show that negative and positive ties exhibit many of the same structural characteristics. We then develop a complete taxonomy of all 138 possible triads of two-type relationships. Consistent with balance theory, we find that antagonists of friends and friends of antagonists tend to be antagonists; but, in an important empirical refutation of balance theory, we find that antagonists of antagonists also tend to be antagonists, not friends. Finally, villages with comparable levels of animosity tend to be geographically proximate. Similar processes, involving social contact, give rise to both positive and negative social ties in rural villages, and negative ties play an important role in social structure

The glucose-lowering therapy structure in special groups of type 2 diabetes mellitus patients based on data from the Moscow region register

BACKGROUND: Data of real clinical practice in diabetes mellitus (DM) register allow to evaluate features and trends in structure of glucose-lowering therapy (GLT). AIM: Тo analyze of structure of GLT received by patients with type 2 diabetes mellitus (T2DM) in Moscow region for 2018 and to evaluate its dynamics over 15 years. METHODS: Analysis of GLT structure was carried out on basis of data from register of patients with DM in Moscow region, which is part of National register of diabetes mellitus in Russian Federation. In March 2018 it contained data on 211,792 T2DM patients of Moscow region. Structure of GLT administration was evaluated according T2DM duration, patient’s age and presence of cardiovascular diseases (CVD). Dynamics of GLT is analyzed from 2004 to 2018 yrs. RESULTS: In 2018 non-insulin glucose-lowering drugs (NIGD) prescription prevailed (78.3%), insulin therapy was prescribed in 18.5% of patients, 3.2% of patients did not receive drug therapy. Most commonly prescribed NIGD were metformin (69.3%) and sulfonylurea (51.3%). Older patients more often than younger did not use GLT at all and less frequently received insulin therapy and iDPP-4. Insulin therapy was prescribed twice as often in patients with CVD compared with patients without CVD (29.6% and 15.5%). NIGD monotherapy has been less commonly used in patients with CVD (67.3% and 81.2%). Glucagon-like peptide-1 receptor agonists (GLP-1 RA) were prescribed to patients with CVD GLP-1 RA – in 0.1% of cases, without CVD in 0.3% of cases, and sodium-glucose cotransporter 2 (SGLT2) inhibitors in 1.1% and 0.6%. correspondently. CONCLUSION: Metformin was most commonly prescribed drug in GLT structure for T2DM patients in the Moscow region in 2018 yr. Percentage of new drugs in the structure of GLT increased mainly due to iDPP-4, and secondly due to SGLT2 inhibitors. New classes of GLT were more often prescribed to patients of younger age, with diabetes duration up to 10 years, overweight or obese. Administration of NIGD with proven cardiovascular protection in presence of CVD is almost two times less than for those without CVD

Impact of Polymer Nanoparticles on DPPC Monolayer Properties

The application of surface rheology and Brewster angle microscopy on mixed monolayers of DPPC and polymeric nanoparticles (cationic and anionic) showed that the sign of the particle charge affects the dynamic properties of the monolayers less than the nanoparticles’ ability to aggregate. Under almost physiological conditions, the effect of nanoparticles on the elasticity of DPPC monolayer is insignificant. However, the particles prevent the surface tension from decreasing to extremely low values. This effect could affect the functionality of pulmonary surfactants