925 research outputs found
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 power law, emerging from a random walk type of
dynamics, which crosses over to a steeper 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 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 -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 (, where is the periastron distance of the encountering star and
is the semi-major axis of the planet). We also investigate distant perturbers
(), 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
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