International Journal of Modern Physics C

The problem of determining total distance ascended during a mountain bike trip is addressed. Altitude measurements are obtained from GPS receivers utilizing both GPS-based and barometric altitude data, with data averaging used to reduce fluctuations. The estimation process is sensitive to the degree of averaging, and is related to the well-known question of determining coastline length. Barometric-based measurements prove more reliable, due to their insensitivity to GPS altitude fluctuations.

We solve numerically in the complex plane all the differential equations involved in Hartle's perturbation method for computing general-relativistic polytropic models of rotating neutron stars. We give emphasis on computing quantities describing the geometry of models in rapid rotation. Compared to numerical results obtained by certain sophisticated iterative methods, we verify appreciable improvement of our results vs to those given by the classical Hartle's perturbative scheme.

The comprehension of the innate immune system of cell populations is not only of interest to understand systems in vivo but also in vitro, for example, in the control of the release of viral particles for the production of vaccines. In this report I introduce a model, based on dynamical networks, that simulates the cell signaling responsible for this innate immune response and its effect on the infection spread and virus production. The central motivation is to represent a cell population that is constantly mixed in a bio-reactor where there is a cell-to-cell signaling of cytokines (which are proteins responsible for the activation of the antiviral response inside the cell). Such signaling allows the definition of clusters of linked immune cells. Additionally, depending on the density of links, it is possible to identify critical threshold parameters associated to a percolation phase transition. I show that the control of this antiviral response is equivalent to a percolation process.

The electronic structure and linear optical properties of luminescent material EuKNaTaO₅ are investigated by employing full-potential linear augmented plane wave method. Our results show highly localized Eu4f states which pinned in the energy range below the unoccupied Ta5d states and over the occupied O 2p states. The optical spectra are analyzed and interpreted in terms of the electronic structure. It is found that Eu ions absorb the major parts of the incident energy below 3.3 eV. This is in accordance with the experimental result that EuKNaTaO₅ phosphor is efficient under the excitation of 535 nm (2.3 eV) visible part of the spectrum. The linear optical properties are found to be anisotropic.

Many cellular automaton models (CA models) have been applied to analyze traffic flow. When analyzing multilane traffic flow, it is important how we define lane-changing rules. However, conventional models have used simple lane-changing rules that are dependent only on the distance from neighboring vehicles. We propose a new lane-changing rule considering velocity differences with neighboring vehicles; in addition, we embed the rules into a variant of the Nagel–Schreckenberg (NaSch) model, called the S-NFS model, by considering an open boundary condition. Using numerical simulations, we clarify the basic characteristics resulting from different assumptions with respect to lane changing.

The standard Penna ageing model with sexual reproduction is enlarged by adding additional bit-strings for love: Marriage happens only if the male love strings are sufficiently different from the female ones. We simulate at what level of required difference the population dies out.

Network navigation is one of the main problems in large communication networks. We propose a new routing strategy in which some smart nodes in networks deliver messages to next hops on the paths towards destinations according to Yan's algorithm while the other nodes just deliver messages randomly. We test our routing strategy in a large scale-free network. Simulations show that the average delivery time decreases with increase of number of smart nodes, while the maximal network capacity increases with number of smart nodes in the network. Moreover our strategy is much more efficient when employed with target selection than with random selection of the smart nodes.

Previous works have pointed out that one of the reasons for the formation of traffic congestion is instability in traffic flow. In this study, we investigate theoretically how the characteristics of individual drivers influence the instability of traffic flow. The discussions are based on the optimal velocity model, which has three parameters related to individual driver characteristics. We specify the mappings between the model parameters and driver characteristics in this study. With linear stability analysis, we obtain a condition for when instability occurs and a constraint about how the model parameters influence the unstable traffic flow. Meanwhile, we also determine how the region of unstable flow densities depends on these parameters. Additionally, the Langevin approach theoretically validates that under the constraint, the macroscopic characteristics of the unstable traffic flow becomes a mixture of free flows and congestions. All of these results imply that both overly aggressive and overly conservative drivers are capable of triggering traffic congestion.