19,461 research outputs found
In the Garden of Branching Processes
The current paper surveys and develops numerical methods for Markovian multitype branching processes in continuous time. Particular attention is paid to the calculation of means, variances, extinction probabilities, and marginal distributions in the presence of a Poisson stream of immigrant particles. The Poisson process assumption allows for temporally complex patterns of immigration and facilitates application of marked Poisson processes and Campbell’s formulas. The methods and formulas derived are applied to four models: two population genetics models, a model for vaccination against an infectious disease in a community of households, and a model for the growth of resistant HIV virus in patients undergoing drug therap
Epidemics in partially overlapped multiplex networks
Many real networks exhibit a layered structure in which links in each layer
reflect the function of nodes on different environments. These multiple types
of links are usually represented by a multiplex network in which each layer has
a different topology. In real-world networks, however, not all nodes are
present on every layer. To generate a more realistic scenario, we use a
generalized multiplex network and assume that only a fraction of the nodes
are shared by the layers. We develop a theoretical framework for a branching
process to describe the spread of an epidemic on these partially overlapped
multiplex networks. This allows us to obtain the fraction of infected
individuals as a function of the effective probability that the disease will be
transmitted . We also theoretically determine the dependence of the epidemic
threshold on the fraction of shared nodes in a system composed of two
layers. We find that in the limit of the threshold is dominated by
the layer with the smaller isolated threshold. Although a system of two
completely isolated networks is nearly indistinguishable from a system of two
networks that share just a few nodes, we find that the presence of these few
shared nodes causes the epidemic threshold of the isolated network with the
lower propagating capacity to change discontinuously and to acquire the
threshold of the other network.Comment: 13 pages, 4 figure
Hadronic decay of the gravitino in the early universe and its implications to inflation
We discuss the effects of the gravitino on the big-bang nucleosynthesis
(BBN), paying particular attention to the hadronic decay mode of the gravitino.
We will see that the hadronic decay of the gravitino significantly affect the
BBN and, for the case where the hadronic branching ratio is sizable, very
stringent upper bound on the reheating temperature after inflation is obtained.Comment: 6 pages, 2 Postscript figures, Talk given at PASCOS'04 (Boston, MA,
August 16 -- 22 (2004
Search for Interstellar Water in the Translucent Molecular Cloud toward HD 154368
We report an upper limit of 9 x 10^{12} cm-2 on the column density of water
in the translucent cloud along the line of sight toward HD 154368. This result
is based upon a search for the C-X band of water near 1240 \AA carried out
using the Goddard High Resolution Spectrograph of the Hubble Space Telescope.
Our observational limit on the water abundance together with detailed chemical
models of translucent clouds and previous measurements of OH along the line of
sight constrain the branching ratio in the dissociative recombination of H_3O+
to form water. We find at the level that no more than 30% of
dissociative recombinations of H_3O+ can lead to H_2O. The observed spectrum
also yielded high-resolution observations of the Mg II doublet at 1239.9 \AA
and 1240.4 \AA, allowing the velocity structure of the dominant ionization
state of magnesium to be studied along the line of sight. The Mg II spectrum is
consistent with GHRS observations at lower spectral resolution that were
obtained previously but allow an additional velocity component to be
identified.Comment: Accepted by ApJ, uses aasp
Flora robotica -- An Architectural System Combining Living Natural Plants and Distributed Robots
Key to our project flora robotica is the idea of creating a bio-hybrid system
of tightly coupled natural plants and distributed robots to grow architectural
artifacts and spaces. Our motivation with this ground research project is to
lay a principled foundation towards the design and implementation of living
architectural systems that provide functionalities beyond those of orthodox
building practice, such as self-repair, material accumulation and
self-organization. Plants and robots work together to create a living organism
that is inhabited by human beings. User-defined design objectives help to steer
the directional growth of the plants, but also the system's interactions with
its inhabitants determine locations where growth is prohibited or desired
(e.g., partitions, windows, occupiable space). We report our plant species
selection process and aspects of living architecture. A leitmotif of our
project is the rich concept of braiding: braids are produced by robots from
continuous material and serve as both scaffolds and initial architectural
artifacts before plants take over and grow the desired architecture. We use
light and hormones as attraction stimuli and far-red light as repelling
stimulus to influence the plants. Applied sensors range from simple proximity
sensing to detect the presence of plants to sophisticated sensing technology,
such as electrophysiology and measurements of sap flow. We conclude by
discussing our anticipated final demonstrator that integrates key features of
flora robotica, such as the continuous growth process of architectural
artifacts and self-repair of living architecture.Comment: 16 pages, 12 figure
Critical dynamics of the k-core pruning process
We present the theory of the k-core pruning process (progressive removal of
nodes with degree less than k) in uncorrelated random networks. We derive exact
equations describing this process and the evolution of the network structure,
and solve them numerically and, in the critical regime of the process,
analytically. We show that the pruning process exhibits three different
behaviors depending on whether the mean degree of the initial network is
above, equal to, or below the threshold _c corresponding to the emergence of
the giant k-core. We find that above the threshold the network relaxes
exponentially to the k-core. The system manifests the phenomenon known as
"critical slowing down", as the relaxation time diverges when tends to
_c. At the threshold, the dynamics become critical characterized by a
power-law relaxation (1/t^2). Below the threshold, a long-lasting transient
process (a "plateau" stage) occurs. This transient process ends with a collapse
in which the entire network disappears completely. The duration of the process
diverges when tends to _c. We show that the critical dynamics of the
pruning are determined by branching processes of spreading damage. Clusters of
nodes of degree exactly k are the evolving substrate for these branching
processes. Our theory completely describes this branching cascade of damage in
uncorrelated networks by providing the time dependent distribution function of
branching. These theoretical results are supported by our simulations of the
-core pruning in Erdos-Renyi graphs.Comment: 12 pages, 10 figure
Implicit learning of recursive context-free grammars
Context-free grammars are fundamental for the description of linguistic syntax. However, most artificial grammar learning
experiments have explored learning of simpler finite-state grammars, while studies exploring context-free grammars have
not assessed awareness and implicitness. This paper explores the implicit learning of context-free grammars employing
features of hierarchical organization, recursive embedding and long-distance dependencies. The grammars also featured
the distinction between left- and right-branching structures, as well as between centre- and tail-embedding, both
distinctions found in natural languages. People acquired unconscious knowledge of relations between grammatical classes
even for dependencies over long distances, in ways that went beyond learning simpler relations (e.g. n-grams) between
individual words. The structural distinctions drawn from linguistics also proved important as performance was greater for
tail-embedding than centre-embedding structures. The results suggest the plausibility of implicit learning of complex
context-free structures, which model some features of natural languages. They support the relevance of artificial grammar
learning for probing mechanisms of language learning and challenge existing theories and computational models of
implicit learning
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