3,875 research outputs found
Epidemic Spreading in Random Rectangular Networks
The use of network theory to model disease propagation on populations
introduces important elements of reality to the classical epidemiological
models. The use of random geometric graphs (RGG) is one of such network models
that allows for the consideration of spatial properties on disease propagation.
In certain real-world scenarios -like in the analysis of a disease propagating
through plants- the shape of the plots and fields where the host of the disease
is located may play a fundamental role on the propagation dynamics. Here we
consider a generalization of the RGG to account for the variation of the shape
of the plots/fields where the hosts of a disease are allocated. We consider a
disease propagation taking place on the nodes of a random rectangular graph
(RRG) and we consider a lower bound for the epidemic threshold of a
Susceptible-Infected-Susceptible (SIS) or Susceptible-Infected-Recovered (SIR)
model on these networks. Using extensive numerical simulations and based on our
analytical results we conclude that (ceteris paribus) the elongation of the
plot/field in which the nodes are distributed makes the network more resilient
to the propagation of a disease due to the fact that the epidemic threshold
increases with the elongation of the rectangle. These results agree with
accumulated empirical evidence and simulation results about the propagation of
diseases on plants in plots/fields of the same area and different shapes.Comment: Version 4, 13 pages, 6 figures, 44 ref
Evolvability: What Is It and How Do We Get It?
Biological organisms exhibit spectacular adaptation to their environments. However, another marvel of biology lurks behind the adaptive traits that organisms exhibit over the course of their lifespans: it is hypothesized that biological organisms also exhibit adaptation to the evolutionary process itself. That is, biological organisms are thought to possess traits that facilitate evolution. The term evolvability was coined to describe this type of adaptation. The question of evolvability has special practical relevance to computer science researchers engaged in longstanding efforts to harness evolution as an algorithm for automated design. It is hoped that a more nuanced understanding of biological evolution will translate to more powerful digital evolution techniques. This thesis presents a theoretical overview of evolvability, illustrated with examples from biology and evolutionary computing
Nonclassicality and criticality in symmetry-protected magnetic phases
Quantum and global discord in a spin-1 Heisenberg chain subject to single-ion
anisotropy (uniaxial field) are studied using exact diagonalisation and the
density matrix renormalisation group (DMRG). We find that these measures of
quantum nonclassicality are able to detect the quantum phase transitions
confining the symmetry protected Haldane phase and show critical scaling with
universal exponents. Moreover, in the case of thermal states, we find that
quantum discord can increase with increasing temperature.Comment: 7 pages, 6 figures, Close to published version. Includes a link to
data used for the figure
Years Out Of Academy Influences General And Job-Specific Fitness In Deputy Sheriff Incumbents
Only the strong survive: Relationships between lower-body strength and power with the 75-kg and 91-kg body drag
Fit for Duty, Fit for Life? An Analysis of the Health and Fitness of Deputy Sheriffs after Working in Custody
Exploring Evolved Multicellular Life Histories in a Open-Ended Digital Evolution System
Evolutionary transitions occur when previously-independent replicating
entities unite to form more complex individuals. Such transitions have
profoundly shaped natural evolutionary history and occur in two forms:
fraternal transitions involve lower-level entities that are kin (e.g.,
transitions to multicellularity or to eusocial colonies), while egalitarian
transitions involve unrelated individuals (e.g., the origins of mitochondria).
The necessary conditions and evolutionary mechanisms for these transitions to
arise continue to be fruitful targets of scientific interest. Here, we examine
a range of fraternal transitions in populations of open-ended self-replicating
computer programs. These digital cells were allowed to form and replicate kin
groups by selectively adjoining or expelling daughter cells. The capability to
recognize kin-group membership enabled preferential communication and
cooperation between cells. We repeatedly observed group-level traits that are
characteristic of a fraternal transition. These included reproductive division
of labor, resource sharing within kin groups, resource investment in offspring
groups, asymmetrical behaviors mediated by messaging, morphological patterning,
and adaptive apoptosis. We report eight case studies from replicates where
transitions occurred and explore the diverse range of adaptive evolved
multicellular strategies
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