Species lifetime distribution for simple models of ecologies

Interpretation of empirical results based on a taxa's lifetime distribution shows apparently conflicting results. Species' lifetime is reported to be exponentially distributed, whereas higher order taxa, such as families or genera, follow a broader distribution, compatible with power law decay. We show that both these evidences are consistent with a simple evolutionary model that does not require specific assumptions on species interaction. The model provides a zero-order description of the dynamics of ecological communities and its species lifetime distribution can be computed exactly. Different behaviors are found: an initial $t^{-3/2}$ power law, emerging from a random walk type of dynamics, which crosses over to a steeper $t^{-2}$ branching process-like regime and finally is cutoff by an exponential decay which becomes weaker and weaker as the total population increases. Sampling effects can also be taken into account and shown to be relevant: if species in the fossil record were sampled according to the Fisher log-series distribution, lifetime should be distributed according to a $t^{-1}$ power law. Such variability of behaviors in a simple model, combined with the scarcity of data available, cast serious doubts on the possibility to validate theories of evolution on the basis of species lifetime data.Comment: 19 pages, 2 figure

Measuring Online Social Bubbles

Social media have quickly become a prevalent channel to access information, spread ideas, and influence opinions. However, it has been suggested that social and algorithmic filtering may cause exposure to less diverse points of view, and even foster polarization and misinformation. Here we explore and validate this hypothesis quantitatively for the first time, at the collective and individual levels, by mining three massive datasets of web traffic, search logs, and Twitter posts. Our analysis shows that collectively, people access information from a significantly narrower spectrum of sources through social media and email, compared to search. The significance of this finding for individual exposure is revealed by investigating the relationship between the diversity of information sources experienced by users at the collective and individual level. There is a strong correlation between collective and individual diversity, supporting the notion that when we use social media we find ourselves inside "social bubbles". Our results could lead to a deeper understanding of how technology biases our exposure to new information

An exactly solvable model for a beta-hairpin with random interactions

I investigate a disordered version of a simplified model of protein folding, with binary degrees of freedom, applied to an ideal beta-hairpin structure. Disorder is introduced by assuming that the contact energies are independent and identically distributed random variables. The equilibrium free-energy of the model is studied, performing the exact calculation of its quenched value and proving the self-averaging feature.Comment: 9 page

Wireless ATM layouts for chain networks

In this paper we consider the problem of constructing ATM layouts for wireless networks in which mobile users can move along a chain of base stations. We first show that deciding the existence of a layout with maximum hop count h, load l and channel distance d is NP-complete for every fixed value of d greater or equal to 1. We then provide optimal layout constructions for the case d less than or equal to 2. Finally, optimal layout constructions are obtained also for any d within the class of the so-called canonic layouts, that so far have always been shown to be the optimal ones

Modeling urban street patterns

Urban streets patterns form planar networks whose empirical properties cannot be accounted for by simple models such as regular grids or Voronoi tesselations. Striking statistical regularities across different cities have been recently empirically found, suggesting that a general and details-independent mechanism may be in action. We propose a simple model based on a local optimization process combined with ideas previously proposed in studies of leaf pattern formation. The statistical properties of this model are in good agreement with the observed empirical patterns. Our results thus suggests that in the absence of a global design strategy, the evolution of many different transportation networks indeed follow a simple universal mechanism.Comment: 4 pages, 5 figures, final version published in PR

Observation of Fermi-Pasta-Ulam-Tsingou Recurrence and Its Exact Dynamics

One of the most controversial phenomena in nonlinear dynamics is the reappearance of initial conditions. Celebrated as the Fermi-Pasta-Ulam-Tsingou problem, the attempt to understand how these recurrences form during the complex evolution that leads to equilibrium has deeply influenced the entire development of nonlinear science. The enigma is rendered even more intriguing by the fact that integrable models predict recurrence as exact solutions, but the difficulties involved in upholding integrability for a sufficiently long dynamic has not allowed a quantitative experimental validation. In natural processes, coupling with the environment rapidly leads to thermalization, and finding nonlinear multimodal systems presenting multiple returns is a long-standing open challenge. Here, we report the observation of more than three Fermi-Pasta-Ulam-Tsingou recurrences for nonlinear optical spatial waves and demonstrate the control of the recurrent behavior through the phase and amplitude of the initial field. The recurrence period and phase shift are found to be in remarkable agreement with the exact recurrent solution of the nonlinear Schrödinger equation, while the recurrent behavior disappears as integrability is lost. These results identify the origin of the recurrence in the integrability of the underlying dynamics and allow us to achieve one of the basic aspirations of nonlinear dynamics: the reconstruction, after several return cycles, of the exact initial condition of the system, ultimately proving that the complex evolution can be accurately predicted in experimental conditions

Business model configuration and dynamics for technology commercialization in mature markets.

Purpose The food industry is a well-established and complex industry. New entrants attempting to penetrate it via the commercialization of a new technological innovation could face high uncertainty and constraints. The capability to innovate through collaboration and to identify suitable strategies and innovative business models (BMs) can be particularly important for bringing a technological innovation to this market. However, although the potential for these capabilities has been advocated, we still lack a complete understanding of how new ventures could support the technology commercialization process via the development of BMs. The paper aims to discuss these issues. Design/methodology/approach To address this gap, this paper builds a conceptual framework that knits together the different bodies of extant literature (i.e. entrepreneurship, strategy and innovation) to analyze the BM innovation processes associated with the exploitation of emerging technologies; determines the suitability of the framework using data from the exploratory case study of IT IS 3D – a firm which has started to exploit 3D printing in the food industry; and improves the initial conceptual framework with the findings that emerged in the case study. Findings From this analysis it emerged that: companies could use more than one BM at a time; hence, BM innovation processes could co-exist and be run in parallel; the facing of high uncertainty might lead firms to choose a closed and/or a familiar BM, while explorative strategies could be pursued with open BMs; significant changes in strategies during the technology commercialization process are not necessarily reflected in a radical change in the BM; and firms could deliberately adopt interim strategies and BMs as means to identify the more suitable ones to reach the market. Originality/value This case study illustrates how firms could innovate the processes of their BM development to face the uncertainties linked with the entry into a mature and highly conservative industry (food)

The dynamical evolution of protoplanetary disks and planets in dense star clusters

Most stars are born in dense stellar environments where the formation and early evolution of planetary systems may be significantly perturbed by encounters with neighbouring stars. To investigate on the fate of circumstellar gas disks and planets around young stars dense stellar environments, we numerically evolve star-disk-planet systems. We use the $N$-body codes NBODY6++GPU and SnIPES for the dynamical evolution of the stellar population, and the SPH-based code GaSPH for the dynamical evolution of protoplanetary disks. The secular evolution of a planetary system in a cluster differs from that of a field star. Most stellar encounters are tidal, adiabatic and nearly-parabolic. The parameters that characterize the impact of an encounter include the orientation of the protoplanetary disk and planet relative to the orbit of the encountering star, and the orbital phase and the semi-major axis of the planet. We investigate this dependence for close encounters ($r_p/a\leq 100$, where $r_p$ is the periastron distance of the encountering star and $a$ is the semi-major axis of the planet). We also investigate distant perturbers ($r_p/a\gg 100$), which have a moderate effect on the dynamical evolution of the planet and the protoplanetary disk. We find that the evolution of protoplanetary disks in star clusters differs significantly from that of isolated systems. When interpreting the outcome of the planet formation process, it is thus important to consider their birth environments.Comment: 14 Pages, 11 Figures, Accepted for pubblication on MNRAS on 13 September 202

Characterizing and modeling the dynamics of online popularity

Online popularity has enormous impact on opinions, culture, policy, and profits. We provide a quantitative, large scale, temporal analysis of the dynamics of online content popularity in two massive model systems, the Wikipedia and an entire country's Web space. We find that the dynamics of popularity are characterized by bursts, displaying characteristic features of critical systems such as fat-tailed distributions of magnitude and inter-event time. We propose a minimal model combining the classic preferential popularity increase mechanism with the occurrence of random popularity shifts due to exogenous factors. The model recovers the critical features observed in the empirical analysis of the systems analyzed here, highlighting the key factors needed in the description of popularity dynamics.Comment: 5 pages, 4 figures. Modeling part detailed. Final version published in Physical Review Letter