1,867 research outputs found
The Old Farm-House On The Hill : Song And Refrain
https://digitalcommons.library.umaine.edu/mmb-vp/2297/thumbnail.jp
Low prevalence, quasi-stationarity and power-law distribution in a model of spreading
Understanding how contagions (information, infections, etc) are spread on
complex networks is important both from practical as well as theoretical point
of view. Considerable work has been done in this regard in the past decade or
so. However, most models are limited in their scope and as a result only
capture general features of spreading phenomena. Here, we propose and study a
model of spreading which takes into account the strength or quality of
contagions as well as the local (probabilistic) dynamics occurring at various
nodes. Transmission occurs only after the quality-based fitness of the
contagion has been evaluated by the local agent. The model exhibits
quality-dependent exponential time scales at early times leading to a slowly
evolving quasi-stationary state. Low prevalence is seen for a wide range of
contagion quality for arbitrary large networks. We also investigate the
activity of nodes and find a power-law distribution with a robust exponent
independent of network topology. Our results are consistent with recent
empirical observations.Comment: 7 pages, 8 figures. (Submitted
Lateral Separation of Macromolecules and Polyelectrolytes in Microlithographic Arrays
A new approach to separation of a variety of microscopic and mesoscopic
objects in dilute solution is presented. The approach takes advantage of unique
properties of a specially designed separation device (sieve), which can be
readily built using already developed microlithographic techniques. Due to the
broken reflection symmetry in its design, the direction of motion of an object
in the sieve varies as a function of its self-diffusion constant, causing
separation transverse to its direction of motion. This gives the device some
significant and unique advantages over existing fractionation methods based on
centrifugation and electrophoresis.Comment: 4 pages with 3 eps figures, needs RevTeX 3.0 and epsf, also available
in postscript form http://cmtw.harvard.edu/~deniz
A new method for tracking of motor skill learning through practical application of Fitts’ law
This article is made available through the Brunel Open Access Publishing Fund.A novel upper limb motor skill measure, task productivity rate (TPR) was developed integrating speed and spatial error, delivered by a practical motor skill rehabilitation task (MSRT). This prototype task involved placement of 5 short pegs horizontally on a spatially configured rail array. The stability of TPR was tested on 18 healthy right-handed adults (10 women, 8 men, median age 29 years) in a prospective single-session quantitative within-subjects study design. Manipulations of movement rate 10% faster and slower relative to normative states did not significantly affect TPR, F(1.387, 25.009) = 2.465, p = .121. A significant linear association between completion time and error was highest during the normative state condition (Pearson's r = .455, p < .05). Findings provided evidence that improvements in TPR over time reflected motor learning with possible changes in coregulation behavior underlying practice under different conditions. These findings extend Fitts’ law theory to tracking of practical motor skill using a dexterity task, which could have potential clinical applications in rehabilitation
Separatrix splitting at a Hamiltonian bifurcation
We discuss the splitting of a separatrix in a generic unfolding of a
degenerate equilibrium in a Hamiltonian system with two degrees of freedom. We
assume that the unperturbed fixed point has two purely imaginary eigenvalues
and a double zero one. It is well known that an one-parametric unfolding of the
corresponding Hamiltonian can be described by an integrable normal form. The
normal form has a normally elliptic invariant manifold of dimension two. On
this manifold, the truncated normal form has a separatrix loop. This loop
shrinks to a point when the unfolding parameter vanishes. Unlike the normal
form, in the original system the stable and unstable trajectories of the
equilibrium do not coincide in general. The splitting of this loop is
exponentially small compared to the small parameter. This phenomenon implies
non-existence of single-round homoclinic orbits and divergence of series in the
normal form theory. We derive an asymptotic expression for the separatrix
splitting. We also discuss relations with behaviour of analytic continuation of
the system in a complex neighbourhood of the equilibrium
Collective Decision Dynamics in the Presence of External Drivers
We develop a sequence of models describing information transmission and
decision dynamics for a network of individual agents subject to multiple
sources of influence. Our general framework is set in the context of an
impending natural disaster, where individuals, represented by nodes on the
network, must decide whether or not to evacuate. Sources of influence include a
one-to-many externally driven global broadcast as well as pairwise
interactions, across links in the network, in which agents transmit either
continuous opinions or binary actions. We consider both uniform and variable
threshold rules on the individual opinion as baseline models for
decision-making. Our results indicate that 1) social networks lead to
clustering and cohesive action among individuals, 2) binary information
introduces high temporal variability and stagnation, and 3) information
transmission over the network can either facilitate or hinder action adoption,
depending on the influence of the global broadcast relative to the social
network. Our framework highlights the essential role of local interactions
between agents in predicting collective behavior of the population as a whole.Comment: 14 pages, 7 figure
A IMPOSSIBILIDADE DE SE MORRER NO (A)MAR: ECOS DE UM MAR MORTO
A partir da obra Mar morto, de Jorge Amado, buscaremos o enfoque de dois elementos recorrentes: amor e morte. Elementos estes tĂŁo presentes na vida de Guma, dos marĂtimos, do cais. Seguiremos a análise guiados pelo estudo da narrativa presente em Agamben, Morin e Blanchot, buscando tecer contextos entre eles, o amor, a morte e a Literatura, conduzidos como o leme nas mĂŁos experientes de Guma Ă procura dos mistĂ©rios do mar e de Iemanjá. Iremos, com ele, em busca do desconhecido narrativo.
 
Influence of the Dufour effect on convection in binary gas mixtures
Linear and nonlinear properties of convection in binary fluid layers heated
from below are investigated, in particular for gas parameters. A Galerkin
approximation for realistic boundary conditions that describes stationary and
oscillatory convection in the form of straight parallel rolls is used to
determine the influence of the Dufour effect on the bifurcation behaviour of
convective flow intensity, vertical heat current, and concentration mixing. The
Dufour--induced changes in the bifurcation topology and the existence regimes
of stationary and traveling wave convection are elucidated. To check the
validity of the Galerkin results we compare with finite--difference numerical
simulations of the full hydrodynamical field equations. Furthermore, we report
on the scaling behaviour of linear properties of the stationary instability.Comment: 14 pages and 10 figures as uuencoded Postscript file (using uufiles
#Bieber + #Blast = #BieberBlast: Early Prediction of Popular Hashtag Compounds
Compounding of natural language units is a very common phenomena. In this
paper, we show, for the first time, that Twitter hashtags which, could be
considered as correlates of such linguistic units, undergo compounding. We
identify reasons for this compounding and propose a prediction model that can
identify with 77.07% accuracy if a pair of hashtags compounding in the near
future (i.e., 2 months after compounding) shall become popular. At longer times
T = 6, 10 months the accuracies are 77.52% and 79.13% respectively. This
technique has strong implications to trending hashtag recommendation since
newly formed hashtag compounds can be recommended early, even before the
compounding has taken place. Further, humans can predict compounds with an
overall accuracy of only 48.7% (treated as baseline). Notably, while humans can
discriminate the relatively easier cases, the automatic framework is successful
in classifying the relatively harder cases.Comment: 14 pages, 4 figures, 9 tables, published in CSCW (Computer-Supported
Cooperative Work and Social Computing) 2016. in Proceedings of 19th ACM
conference on Computer-Supported Cooperative Work and Social Computing (CSCW
2016
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