Hazel Blossoms : Reverie

https://digitalcommons.library.umaine.edu/mmb-ps/1556/thumbnail.jp

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 02iω0^2 i\omega 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

&nbsp; &nbsp;&nbsp; &nbsp;A partir da obra Mar morto, de Jorge Amado, buscaremos o enfoque de dois elementos recorrentes: amor e morte. Elementos estes tão presentes na vida de Guma, dos marítimos, 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 mãos experientes de Guma à procura dos mistérios do mar e de Iemanjá. Iremos, com ele, em busca do desconhecido narrativo. &nbsp

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