474,369 research outputs found
Growth-Driven Percolations: The Dynamics of Community Formation in Neuronal Systems
The quintessential property of neuronal systems is their intensive patterns
of selective synaptic connections. The current work describes a physics-based
approach to neuronal shape modeling and synthesis and its consideration for the
simulation of neuronal development and the formation of neuronal communities.
Starting from images of real neurons, geometrical measurements are obtained and
used to construct probabilistic models which can be subsequently sampled in
order to produce morphologically realistic neuronal cells. Such cells are
progressively grown while monitoring their connections along time, which are
analysed in terms of percolation concepts. However, unlike traditional
percolation, the critical point is verified along the growth stages, not the
density of cells, which remains constant throughout the neuronal growth
dynamics. It is shown, through simulations, that growing beta cells tend to
reach percolation sooner than the alpha counterparts with the same diameter.
Also, the percolation becomes more abrupt for higher densities of cells, being
markedly sharper for the beta cells.Comment: 8 pages, 10 figure
Concentric Characterization and Classification of Complex Network Nodes: Theory and Application to Institutional Collaboration
Differently from theoretical scale-free networks, most of real networks
present multi-scale behavior with nodes structured in different types of
functional groups and communities. While the majority of approaches for
classification of nodes in a complex network has relied on local measurements
of the topology/connectivity around each node, valuable information about node
functionality can be obtained by Concentric (or Hierarchical) Measurements. In
this paper we explore the possibility of using a set of Concentric Measurements
and agglomerative clustering methods in order to obtain a set of functional
groups of nodes. Concentric clustering coefficient and convergence ratio are
chosen as segregation parameters for the analysis of a institutional
collaboration network including various known communities (departments of the
University of S\~ao Paulo). A dendogram is obtained and the results are
analyzed and discussed. Among the interesting obtained findings, we emphasize
the scale-free nature of the obtained network, as well as the identification of
different patterns of authorship emerging from different areas (e.g. human and
exact sciences). Another interesting result concerns the relatively uniform
distribution of hubs along the concentric levels, contrariwise to the
non-uniform pattern found in theoretical scale free networks such as the BA
model.Comment: 15 pages, 13 figure
Behavior of physical observables in the vicinity of the QCD critical end point
Using the SU(3) Nambu-Jona-Lasinio (NJL) model, we study the chiral phase
transition at finite and . Special attention is given to the QCD
critical end point (CEP): the study of physical quantities, as the pressure,
the entropy, the baryon number susceptibility and the specific heat near the
CEP, will provide complementary information concerning the order of the phase
transition. We also analyze the information provided by the study of the
critical exponents around the CEP.Comment: Talk given at Quark Confinement and the Hadron Spectrum VII, Ponta
Delgada, Azores, Portugal, 2-7 Sep 200
Quantum Applications In Political Science
Undergraduate Research ScholarshipThis paper will show the current state of quantum computation and its application as a political science research method. It will look at contemporary empirical literature to assess the current state of the method in both political science and computer science. Then, by assessing the state of quantum computation, this paper will make predictions concerning quantum computation as a research tool and also assess its capability as a catalyst for international diplomacy and discourse. Quantum computation is an emerging technology with increasing scientific attention. This paper will use IBM’s quantum computer, accessed through the cloud, to model and execute quantum algorithms that show the utility for political science research. Furthermore, through the base mathematics of common quantum algorithms, this paper will show how these algorithms can be expanded. This paper finds that quantum computation is a valuable tool with remarkable potential. However, quantum computing has its limitations and currently resides in an important juncture that will decide whether technology involving it will be resigned as a niche theoretical tool or be continued to be developed into a mainstream technology.No embargoAcademic Major: World Politic
On the Potential of the Excluded Volume and Auto-Correlation as Neuromorphometric Descriptors
This work investigates at what degree two neuromorphometric measurements,
namely the autocorrelation and the excluded volume of a neuronal cell can
influence the characterization and classification of such a type of cells.
While the autocorrelation function presents good potential for quantifying the
dendrite-dendrite connectivity of cells in mosaic tilings, the excluded volume,
i.e. the amount of the surround space which is geometrically not accessible to
an axon or dendrite, provides a complementary characterization of the cell
connectivity. The potential of such approaches is illustrated with respect to
real neuronal cells.Comment: 15 pages, 6 figure
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