Systems of oscillators whose internal phases and spatial dynamics are coupled, swarmalators, present diverse collective behaviors which in some cases lead to explosive synchronization in a finite population as a function of the coupling parameter between internal phases. Near the synchronization transition, the phase energy of the particles is represented by the XY model, and they undergo a transition which can be of the first order or the second depending on the distribution of natural frequencies of their internal dynamics. The first-order transition is obtained after an intermediate state (static wings phase wave state) from which the nodes, in cascade over time, achieve complete phase synchronization at a precise value of the coupling constant. For a particular case of natural frequencies distribution, a new phenomenon, the rotational splintered phase wave state, is observed and leads progressively to synchronization through clusters switching alternatively from one to two and for which the frequency decreases as the phase coupling increases.

We study the synchronization of two coupled idealized economies. In the present work, we consider a recently developed economic system that shows a richness of dynamical behavior. By means of the Lyapunov exponents, we analyze that there is overly complex behavior in the transitions in the dynamics of an isolated economy, oscillating between chaotic attractors and limit cycles. Then, for two coupled economies, we analyze the synchronization states for the space of all control parameters as a function of the network coupling parameter. Interestingly, we have evidenced that there is a broad region of fully synchronized states and as we increase the coupling, some phenomena such as a smooth and intermittent loss in synchronization emerge. In the same way, we observe phase synchronization for one of the control parameters. Ultimately, in order to confirm this loss of synchronization, we inspect the stability of synchronized states through the master stability function method for some control parameters. Here, we corroborate what was previously observed, the unexpected vast range of control parameter values of instability corresponding to desynchronization.

The maintenance of species diversity is a central focus in ecology. It is not rare to observe more species than the number of limiting resources, especially in plankton communities. However, such high species diversity is hard to achieve in theory under the competitive exclusion principles, known as the plankton paradox. Previous studies often focus on the coexistence of predefined species and ignore the fact that species can evolve. We model multi-resource competitions using evolutionary games, where the number of species fluctuates under extinction and the appearance of new species. The interspecific and intraspecific competitions are captured by a dynamical payoff matrix, which has a size of the number of species. The competition strength (payoff entries) is obtained from comparing the capability of species in consuming resources, which can change over time. This allows for the robust coexistence of a large number of species, providing a possible solution to the plankton paradox.

The dynamics of competing opinions in social network plays an important role in society, with many applications in diverse social contexts such as consensus, election, morality, and so on. Here, we study a model of interacting agents connected in networks in order to analyze their decision stochastic process. We consider a first-neighbor interaction between agents in a one-dimensional network with the shape of ring topology. Moreover, some agents are also connected to a hub, or master node, who has preferential choice or bias. Such connections are quenched. As the main results, we observed a continuous nonequilibrium phase transition to an absorbing state as a function of control parameters. By using the finite-size scaling method we analyzed the static and dynamic critical exponents to show that this model probably cannot match any universality class already known.

Budget Impact Analyses require a set of essential information on health technology innovation, including expected rates of adoption. There is an absence of studies investigating trends, magnitude of budgetary effects and determinants of diffusion rates for health technology innovations worldwide during the last decades. The present study proposes a pilot assessment on main determinants influencing diffusion rates of pharmaceutical innovations within the Brazilian Unified National Health System (SUS). Data from the Brazilian Health Informatics Department (DATASUS) was gathered to establish the main determinants of diffusion rates of health technology innovations in Brazil, specifically referring to pharmaceutical innovations incorporated in the Brazilian Program for Specialized Pharmaceutical Services (CEAF) at SUS. Information was retrieved on DATASUS relating to patients who had used one of the medicines incorporated into CEAF at least three years prior to the beginning of the study (2015) for treatment of each health condition available. Thus, data from patients adopting 10 different medicines were analyzed in the study. Results from the zero-one inflated beta model showed a higher influence on diffusion rates of pharmaceutical innovations due to: number of pharmaceutical competitors for treatment of the same disease available at CEAF (negative); medicine used in combination with other medication (positive); and innovative medicine within the SUS (positive). Further research on diffusion rates of health technology innovations is required, including wider scope of diseases and medications, potential confusion factors and other variables that may influence rates of adoption in different health systems.