The European Physical Journal E最新文献

Understanding the values and origin of fundamental physical constants, one of the grandest challenges in modern science, has been discussed in particle physics, astronomy and cosmology. More recently, it was realized that fundamental constants have a biofriendly window set by life processes involving motion and flow. This window is related to intrinsic fluid properties such as energy and length scales in condensed matter set by fundamental constants. Here, we discuss important extrinsic factors governing the viscosity of complex fluids operating in life processes due to collective effects. We show that both extrinsic and intrinsic factors affecting viscosity need to be taken into account when estimating the biofriendly range of fundamental constants from life processes, and our discussion provides a straightforward recipe for doing this. Remarkably, the viscosity of a complex fluid such as blood with significant extrinsic effects is not far from the intrinsic viscosity calculated using the fundamental constants only, and we discuss the reason for this in terms of dynamics of contact points between cells.

Intelligent decisions in response to external informative input can allow organisms to achieve their biological goals while spending very little of their own resources. In this paper, we develop and study a minimal model for a navigational task, performed by an otherwise completely motorless particle that possesses the ability of hitchhiking in a bath of active Brownian particles (ABPs). Hitchhiking refers to identifying and attaching to suitable surrounding bath particles. Using a reinforcement learning algorithm, such an agent, which we refer to as intelligent hitchhiking particle (IHP), is enabled to persistently navigate in the desired direction. This relatively simple IHP can also anticipate and react to characteristic motion patterns of their hosts, which we exemplify for a bath of chiral ABPs (cABPs). To demonstrate that the persistent motion of the IHP will outperform that of the bath particles in view of long-time ballistic motion, we calculate the mean-squared displacement and discuss its dependence on the density and persistence time of the bath ABPs by means of an analytic model.

Illustration of an intelligent hitchhiking particle (IHP) in a bath of active Brownian particles (ABPs). The IHP fulfills a navigational task by holding on to an ABP only if its orientation points upwards, enabling persistent motion.

Scaling arguments are presented for end-to-wall reaction and end-to-end reactions of grafted chains for non-self-avoiding and self-avoiding chains with and without hydrodynamic interaction. The most realistic minimal model for the experiments of Kim and Lee (J Phys Chem Lett 12:4576, 2021. https://doi.org/10.1021/acs.jpclett.1c00962) is a chain tethered to a plane, the chain having excluded volume and hydrodynamic interaction with end-to-end reactions. From our scaling argument, such a chain obeys a law of mass action where the macroscopic reaction rate is proportional to the microscopic reaction rate multiplied by the probability that the chain ends are close together. More precisely, this means for long chains there is no diffusion controlled limit. In addition, a polymer attached to a plane where the end reacts with the entire plane, end-to-wall reactions, was also investigated. For sufficiently long polymers, this system is always diffusion controlled, even with excluded volume and hydrodynamic interaction. We test the scaling arguments for the simplest case of a non-self-avoiding chains obeying Rouse dynamics. The numerical results agree with the scaling analysis for both end-to-wall and end-to-end reactions of the grafted chain. In particular, our numerical simulations support the end-to-end reaction of a tethered non-self-avoiding is the marginal case in the scaling sense.

The idea of linear Diophantine fuzzy sets (LDFs) is a novel tool for analysis, soft computing, and optimization. Recently, the concept of a linear Diophantine fuzzy graph has been proposed in 2022. The aim of this research is to extend topological numbers to LDFSs. A real value assigned to a particular graph is known as a topological graph theoretic parameter. We extend the bound of the crisp graph toward the linear Diophantine fuzzy graph (LDFG), including the edge and vertex deletion operations via LDFG theoretic parameters. We also investigate the interesting bound of the LDFGs via LDFG theoretic parameters. Finally, for decision-making problems, we developed an algorithm by exploiting the relationship between LDFG theoretic parameters and LDFSs. Based on the established approach, we discussed a numerical example of an application of a medical diagnosis using the linear Diophantine fuzzy Sombor graph parameter and the first, fifth, and sixth versions of the linear Diophantine fuzzy Sombor graph parameters.

A way to the extension of fuzzy topological numbers.

We propose a simple numerical model for the motion of microswimmers based on the immersed boundary method. The swimmer, either pusher or puller, is represented by a distribution of point forces corresponding to the body and the flagellum. We study in particular the minimal model consisting of only three beads (two for the body and one for the flagellum) connected by rigid, inextensible links. When the beads are collinear, standard straight swimming is realized and, in the absence of propulsion, we demonstrate that the model recovers Jeffery’s equation for a thin rod. Conversely, by imposing an angle between body and flagellum the swimmer moves on circular orbits. We discuss how two swimmers, in collinear or non-collinear geometry, scatter upon encounter. Finally, we explore the dynamics of a large number of swimmers reacting to one another only via hydrodynamic interactions, and exemplify their complex collective dynamics in both straight and circular swimmers.

The pointlike curvature constraint (PCC) model and the disk detachment angle (DDA) model for the deformation-mediated interaction of conical integral protein inclusions in biomembranes are compared in the small deformation regime. Given the radius of membrane proteins, which is comparable to the membrane thickness, it is not obvious which of the two models should be considered the most adequate. For two proteins in a tensionless membranes, the PCC and DDA models coincide at the leading-order (sim r^{-4}) in their separation but differ at the next order. Yet, for distances larger than twice the proteins diameter, the difference is less than (10%). Like the DDA model, the PCC model includes all multibody interactions in a non-approximate way. The asymptotic (sim r^{-4}) many-body energy of triangular and square protein clusters is exactly the same in both models. Pentagonal clusters, however, behave differently; they have a vanishing energy in the PCC model, while they have a non-vanishing weaker (sim r^{-6}) asymptotic power law in the DDA model. We quantify the importance of multibody interactions in small polygonal clusters of three, four and five inclusions with identical or opposite curvatures in tensionless or tense membranes. We find that the pairwise approximation is almost always very poor. At short separation, the three-body interaction is not sufficient to account for the full many-body interaction. This is confirmed by equilibrium Monte Carlo simulations of up to ten inclusions.