In this paper, we derive a four-mode model for the Kolmogorov flow by employing Galerkin truncation and the Craya-Herring basis for the decomposition of velocity field. After this, we perform a bifurcation analysis of the model. Though our low-dimensional model has fewer modes than past models, it captures the essential features of the primary bifurcation of the Kolmogorov flow. For example, it reproduces the critical Reynolds number for the supercritical pitchfork bifurcation and the flow structures of past works. We also demonstrate energy transfers from intermediate scales to large scales. We perform direct numerical simulations of the Kolmogorov flow and show that our model predictions match the numerical simulations very well.Following the idea that dissipation in turbulence at high Reynolds number is dominated by singular events in space-time and described by solutions of the inviscid Euler equations, we draw the conclusion that in such flows, scaling laws should depend only on quantities appearing in the Euler equations. This excludes viscosity or a turbulent length as scaling parameters and constrains drastically possible analytical pictures of this limit. We focus on the drag law deduced by Newton for a projectile moving quickly in a fluid at rest. Inspired by this Newton’s drag force law (proportional to the square of the speed of the moving object in the limit of large Reynolds numbers), which is well verified in experiments when the location of the detachment of the boundary layer is defined, we propose an explicit relationship between the Reynolds stress in the turbulent wake and quantities depending on the velocity field (averaged in time but depending on space). This model takes the form of an integrodifferential equation for the velocity which is eventually solved for a Poiseuille flow in a circular pipe.Detrended fluctuation analysis (DFA) is widely used to characterize long-range power-law correlations in complex signals. However, it has restrictions when nonstationarity is not limited only to slow variations in the mean value. To improve the characterization of inhomogeneous datasets, we have proposed the extended DFA (EDFA), which is a modification of the conventional method that evaluates an additional scaling exponent to take into account the features of time-varying nonstationary behavior. Based on EDFA, here, we analyze rat electroencephalograms to identify specific changes in the slow-wave dynamics of brain electrical activity associated with two different conditions, such as the opening of the blood-brain barrier and sleep, which are both characterized by the activation of the brain drainage function. find more We show that these conditions cause a similar reduction in the scaling exponents of EDFA. Such a similarity may represent an informative marker of fluid homeostasis of the central nervous system.We analyze the 2019 Chilean social unrest episode, consisting of a sequence of events, through the lens of an epidemic-like model that considers global contagious dynamics. We adjust the parameters to the Chilean social unrest aggregated public data available from the Undersecretary of Human Rights and observe that the number of violent events follows a well-defined pattern already observed in various public disorder episodes in other countries since the 1960s. Although the epidemic-like models display a single event that reaches a peak followed by an exponential decay, we add standard perturbation schemes that may produce a rich temporal behavior as observed in the 2019 Chilean social turmoil. Although we only have access to aggregated data, we are still able to fit it to our model quite well, providing interesting insights on social unrest dynamics.The key to the survival of a species lies in understanding its evolution in an ever-changing environment. We report a theoretical model that integrates frequency-dependent selection, mutation, and asexual reproduction for understanding the biological evolution of a host species in the presence of parasites. We study the host-parasite coevolution in a one-dimensional genotypic space by considering a dynamic and heterogeneous environment modeled using a fitness landscape. It is observed that the presence of parasites facilitates a faster evolution of the host population toward its fitness maximum. We also find that the time required to reach the maximum fitness (optimization time) decreases with increased infection from the parasites. However, the overall fitness of the host population declines due to the parasitic infection. In the limit where parasites are considered to evolve much faster than the hosts, the optimization time reduces even further. Our findings indicate that parasites can play a crucial role in the survival of its host in a rapidly changing environment.The development of 2D and 3D structures on the nanoscale containing viral nanoparticles (VNPs) as interesting nanobuilding blocks has come into focus for a bottom-up approach as an alternative to the top-down approach in nanobiotechnology. Our research has focused on the plant Tomato Bushy Stunt Virus (TBSV). In a previous study, we reported the impact of the pH value on the 2D assembly of viral monolayers. Here, we extend these studies into the third dimension by using specific interactions between the layers in combination with selective side chains on the viral capsid. The virus bilayer structure is prepared by an alternating deposition of His-tagged TBSV (4D6H-TBSV, first layer), Ni-NTA nanogold (second layer) complexes and 4D6H-TBSV, respectively, and 6D-TBSV (6xaspartic acid TBSV) as the third layer, i.e., the second layer of VNPs. The formed layer structures were imaged by using scanning force and scanning electron microscopy. The data show that a virus bilayer structure was successfully built up by means of the interaction between Ni-NTA nanogold and histidine. By comparing 4D6H- with 6D-TBSV in the third layer, the importance of these specific interactions is shown. This work paves the way for 3D nanodevices based on VNPs.Protein-coated polymer-based microparticles are attractive supports for cell delivery, but the interplay between microparticle properties, protein coating, and cell response is poorly understood. The interest in alternative microparticle formulations increases the need for a better understanding of how functional protein coatings form on different microparticles. In this work, microparticle formulations based on biodegradable polymers [poly (lactic-co-glycolic acid) (PLGA) and the triblock copolymer PLGA-poloxamer-PLGA] were prepared via an emulsion-based process. To explore the impact that the use of a surfactant has on the properties of the microparticles, the emulsion was stabilized by using either a surfactant, poly(vinyl alcohol), or an organic solvent, propylene glycol. Four different types of microparticles were prepared through combinations of the two types of polymers and the two types of stabilizers. The coating of microparticles with proteins/polypeptides such as fibronectin and poly-d-lysine has been demonstrated before and is an integral step for their application as microcarriers, e.