4,330 research outputs found
Breaking the MBA delivery mould: A multi-group international MBA / practitioner virtual collaborative project
The marketing education project presented here brings together a major UK financial institution in the banking sector and a selection of its high value clients (B-to-B) via e-mail, telephone, video conferencing and other web-based technologies, with two geographically dispersed MBA classes in the UK and the US. Student groups were set up in virtual teams to target critical customer issues, analyzing gaps in the client-company interface. The two MBA courses included Customer Management & Quality Systems delivered at the University of Manchester, Manchester Business School (UK) and International Marketing, delivered at Missouri State University (US). The groups worked as a "think tank" collaborating to solve important customer service issues
Generating Robust and Efficient Networks Under Targeted Attacks
Much of our commerce and traveling depend on the efficient operation of large
scale networks. Some of those, such as electric power grids, transportation
systems, communication networks, and others, must maintain their efficiency
even after several failures, or malicious attacks. We outline a procedure that
modifies any given network to enhance its robustness, defined as the size of
its largest connected component after a succession of attacks, whilst keeping a
high efficiency, described in terms of the shortest paths among nodes. We also
show that this generated set of networks is very similar to networks optimized
for robustness in several aspects such as high assortativity and the presence
of an onion-like structure
A stronger topology for the Brownian web
We propose a metric space of coalescing pairs of paths on which we are able
to prove (more or less) directly convergence of objects such as the persistence
probability in the (one dimensional, nearest neighbor, symmetric) voter model
or the diffusively rescaled weight distribution in a silo model (as well as the
equivalent output distribution in a river basin model), interpreted in terms of
(dual) diffusively rescaled coalescing random walks, to corresponding objects
defined in terms of the Brownian web.Comment: 22 page
Is the Riemann zeta function in a short interval a 1-RSB spin glass ?
Fyodorov, Hiary & Keating established an intriguing connection between the
maxima of log-correlated processes and the ones of the Riemann zeta function on
a short interval of the critical line. In particular, they suggest that the
analogue of the free energy of the Riemann zeta function is identical to the
one of the Random Energy Model in spin glasses. In this paper, the connection
between spin glasses and the Riemann zeta function is explored further. We
study a random model of the Riemann zeta function and show that its two-overlap
distribution corresponds to the one of a one-step replica symmetry breaking
(1-RSB) spin glass. This provides evidence that the local maxima of the zeta
function are strongly clustered.Comment: 20 pages, 1 figure, Minor corrections, References update
Nature vs. Nurture: Dynamical Evolution in Disordered Ising Ferromagnets
We study the predictability of zero-temperature Glauber dynamics in various
models of disordered ferromagnets. This is analyzed using two independent
dynamical realizations with the same random initialization (called twins). We
derive, theoretically and numerically, trajectories for the evolution of the
normalized magnetization and twin overlap as the system size tends to infinity.
The systems we treat include mean-field ferromagnets with light-tailed and
heavy-tailed coupling distributions, as well as highly-disordered models with a
variety of other geometries. In the mean-field setting with light-tailed
couplings, the disorder averages out and the limiting trajectories of the
magnetization and twin overlap match those of the homogenous Curie--Weiss
model. On the other hand, when the coupling distribution has heavy tails, or
the geometry changes, the effect of the disorder persists in the thermodynamic
limit. Nonetheless, qualitatively all such random ferromagnets share a similar
time evolution for their twin overlap, wherein the two twins initially
decorrelate, before either partially or fully converging back together due to
the ferromagnetic drift.Comment: 16 pages, 7 figure
Nature versus Nurture in Complex and Not-So-Complex Systems
Understanding the dynamical behavior of many-particle systems both in and out
of equilibrium is a central issue in both statistical mechanics and complex
systems theory. One question involves "nature versus nurture": given a system
with a random initial state evolving through a well-defined stochastic
dynamics, how much of the information contained in the state at future times
depends on the initial condition ("nature") and how much on the dynamical
realization ("nurture")? We discuss this question and present both old and new
results for low-dimensional Ising spin systems.Comment: 7 page
Towards designing robust coupled networks
Natural and technological interdependent systems have been shown to be highly
vulnerable due to cascading failures and an abrupt collapse of global
connectivity under initial failure. Mitigating the risk by partial
disconnection endangers their functionality. Here we propose a systematic
strategy of selecting a minimum number of autonomous nodes that guarantee a
smooth transition in robustness. Our method which is based on betweenness is
tested on various examples including the famous 2003 electrical blackout of
Italy. We show that, with this strategy, the necessary number of autonomous
nodes can be reduced by a factor of five compared to a random choice. We also
find that the transition to abrupt collapse follows tricritical scaling
characterized by a set of exponents which is independent on the protection
strategy
Statistically validated networks in bipartite complex systems
Many complex systems present an intrinsic bipartite nature and are often
described and modeled in terms of networks [1-5]. Examples include movies and
actors [1, 2, 4], authors and scientific papers [6-9], email accounts and
emails [10], plants and animals that pollinate them [11, 12]. Bipartite
networks are often very heterogeneous in the number of relationships that the
elements of one set establish with the elements of the other set. When one
constructs a projected network with nodes from only one set, the system
heterogeneity makes it very difficult to identify preferential links between
the elements. Here we introduce an unsupervised method to statistically
validate each link of the projected network against a null hypothesis taking
into account the heterogeneity of the system. We apply our method to three
different systems, namely the set of clusters of orthologous genes (COG) in
completely sequenced genomes [13, 14], a set of daily returns of 500 US
financial stocks, and the set of world movies of the IMDb database [15]. In all
these systems, both different in size and level of heterogeneity, we find that
our method is able to detect network structures which are informative about the
system and are not simply expression of its heterogeneity. Specifically, our
method (i) identifies the preferential relationships between the elements, (ii)
naturally highlights the clustered structure of investigated systems, and (iii)
allows to classify links according to the type of statistically validated
relationships between the connected nodes.Comment: Main text: 13 pages, 3 figures, and 1 Table. Supplementary
information: 15 pages, 3 figures, and 2 Table
The role of asymmetric interactions on the effect of habitat destruction in mutualistic networks
Plant-pollinator mutualistic networks are asymmetric in their interactions:
specialist plants are pollinated by generalist animals, while generalist plants
are pollinated by a broad involving specialists and generalists. It has been
suggested that this asymmetric ---or disassortative--- assemblage could play an
important role in determining the equal susceptibility of specialist and
generalist plants under habitat destruction. At the core of the argument lies
the observation that specialist plants, otherwise candidates to extinction,
could cope with the disruption thanks to their interaction with generalist
pollinators. We present a theoretical framework that supports this thesis. We
analyze a dynamical model of a system of mutualistic plants and pollinators,
subject to the destruction of their habitat. We analyze and compare two
families of interaction topologies, ranging from highly assortative to highly
disassortative ones, as well as real pollination networks. We found that
several features observed in natural systems are predicted by the mathematical
model. First, there is a tendency to increase the asymmetry of the network as a
result of the extinctions. Second, an entropy measure of the differential
susceptibility to extinction of specialist and generalist species show that
they tend to balance when the network is disassortative. Finally, the
disappearance of links in the network, as a result of extinctions, shows that
specialist plants preserve more connections than the corresponding plants in an
assortative system, enabling them to resist the disruption.Comment: 14 pages, 7 figure
- …