3,310 research outputs found
Slow nucleic acid unzipping kinetics from sequence-defined barriers
Recent experiments on unzipping of RNA helix-loop structures by force have
shown that about 40-base molecules can undergo kinetic transitions between two
well-defined `open' and `closed' states, on a timescale = 1 sec [Liphardt et
al., Science 297, 733-737 (2001)]. Using a simple dynamical model, we show that
these phenomena result from the slow kinetics of crossing large free energy
barriers which separate the open and closed conformations. The dependence of
barriers on sequence along the helix, and on the size of the loop(s) is
analyzed. Some DNAs and RNAs sequences that could show dynamics on different
time scales, or three(or more)-state unzipping, are proposed.Comment: 8 pages Revtex, including 4 figure
Adaptive Cluster Expansion for Inferring Boltzmann Machines with Noisy Data
We introduce a procedure to infer the interactions among a set of binary
variables, based on their sampled frequencies and pairwise correlations. The
algorithm builds the clusters of variables contributing most to the entropy of
the inferred Ising model, and rejects the small contributions due to the
sampling noise. Our procedure successfully recovers benchmark Ising models even
at criticality and in the low temperature phase, and is applied to
neurobiological data.Comment: Accepted for publication in Physical Review Letters (2011
Large Pseudo-Counts and -Norm Penalties Are Necessary for the Mean-Field Inference of Ising and Potts Models
Mean field (MF) approximation offers a simple, fast way to infer direct
interactions between elements in a network of correlated variables, a common,
computationally challenging problem with practical applications in fields
ranging from physics and biology to the social sciences. However, MF methods
achieve their best performance with strong regularization, well beyond Bayesian
expectations, an empirical fact that is poorly understood. In this work, we
study the influence of pseudo-count and -norm regularization schemes on
the quality of inferred Ising or Potts interaction networks from correlation
data within the MF approximation. We argue, based on the analysis of small
systems, that the optimal value of the regularization strength remains finite
even if the sampling noise tends to zero, in order to correct for systematic
biases introduced by the MF approximation. Our claim is corroborated by
extensive numerical studies of diverse model systems and by the analytical
study of the -component spin model, for large but finite . Additionally
we find that pseudo-count regularization is robust against sampling noise, and
often outperforms -norm regularization, particularly when the underlying
network of interactions is strongly heterogeneous. Much better performances are
generally obtained for the Ising model than for the Potts model, for which only
couplings incoming onto medium-frequency symbols are reliably inferred.Comment: 25 pages, 17 figure
Fandom from afar: identification, attachment, and consumption behaviors among United States based fans of English premier league soccer clubs.
The purpose of this study was to explore the antecedents to organizational identification among U.S.-based EPL fans and examine the relationship between these antecedents and various forms of sport consumption behavior. Specifically, this study examined the extent to which points of attachment explained variances in organizational identification and three types of sport consumption behavior – broadcast media consumption, social media consumption, and team-related merchandise purchases. Additionally, this study examined differences in points of attachment between fans of successful EPL organizations, known as the “Big Six” EPL clubs, and fans of unsuccessful EPL organizations. In contrast to most existing sport fan identification and attachment research, this study focused on distant fans, a group yet to receive significant attention in the sport management literature. This study utilized social identity theory as a conceptual foundation. Social identity theory is a socio-cognitive framework that explains the formation and behaviors of social groups. It provides the main theoretical foundation for research on organizational identification and team identification. Points of attachment represent an extension of team identification research that accounts for the potential of multiple factors to contribute toward one’s fan identification. Previous research suggests an understanding of fan identification and attachment is crucial to developing targeted marketing plans which positively influence sport consumption behaviors. To address the purpose of the study, a questionnaire was distributed to U.S.-based EPL fans through Facebook group pages organized around fan support and interactions for EPL clubs. The questionnaire contained items to assess respondent’s levels of organizational identification, attachment to various aspects of the organization, and consumption behaviors. Participant responses (n = 753) revealed attachment to fan community exhibited the strongest relationship with organizational identification and each type of sport consumption behavior. Attachment to venue also suggested positive relationships with organizational identification and sport consumption behaviors. Two new points of attachment created for this study, attachment to owner and attachment to organizational history/tradition, positively explained respondent’s frequency of merchandise purchases. Additional analysis revealed player and venue attachment held particular salience among U.S.-based fans of Big Six EPL organizations. Meanwhile, attachment to fan community, city/region, and owner displayed significantly higher ratings among U.S.-based fans of EPL organizations outside the Big Six. These results produce several theoretical and practical implications for researchers and practitioners. From a theoretical perspective, the results illuminate similarities and differences in identification and attachment among distant fan populations compared to local sport fans. Additionally, factor analyses supported a factor structure for items relating to the two new points of attachment created for this study. This sets a foundation for future researchers to utilize these points of attachment in a variety of new research contexts covering distant and local fan types. From a practical implication perspective, the results show the importance of placing the concept of fan community at the heart of marketing strategies for EPL organizations and their U.S.-based broadcast partner, NBC Sports. As information technology and high-speed internet access continue to eliminate boundaries between sport teams and fans from across the world, it will become increasingly crucial for sport organizations to understand their fan bases in distant markets. This study provides initial evidence of variables that demonstrate a significant, positive impact on organizational identification and sport consumption behaviors for a particular set of distant fans
Gender Stereotypes and Figurative Language Comprehension
The paper aims to show how and to what extent social and cultural cues influence figurative language understanding. In the first part of the paper, we argue that social-contextual knowledge is organized in “schemas” or stereotypes, which act as strong bias in speaker’s meaning comprehension. Research in Experimental Pragmatics has shown that age, gender, race and occupation stereotypes are important contextual sources of information to interpret others’ speech and provide an explanation of their behavior. In the second part of the paper, we focus on gender stereotypes and their influence on the comprehension of figurative language, to show how the social functions of figurative language are modulated by gender stereotypes. We provide then an explanation of gender stereotypical bias on figurative language in terms of possible outcomes in the social context
Exponentially hard problems are sometimes polynomial, a large deviation analysis of search algorithms for the random Satisfiability problem, and its application to stop-and-restart resolutions
A large deviation analysis of the solving complexity of random
3-Satisfiability instances slightly below threshold is presented. While finding
a solution for such instances demands an exponential effort with high
probability, we show that an exponentially small fraction of resolutions
require a computation scaling linearly in the size of the instance only. This
exponentially small probability of easy resolutions is analytically calculated,
and the corresponding exponent shown to be smaller (in absolute value) than the
growth exponent of the typical resolution time. Our study therefore gives some
theoretical basis to heuristic stop-and-restart solving procedures, and
suggests a natural cut-off (the size of the instance) for the restart.Comment: Revtex file, 4 figure
Solving satisfiability problems by fluctuations: The dynamics of stochastic local search algorithms
Stochastic local search algorithms are frequently used to numerically solve
hard combinatorial optimization or decision problems. We give numerical and
approximate analytical descriptions of the dynamics of such algorithms applied
to random satisfiability problems. We find two different dynamical regimes,
depending on the number of constraints per variable: For low constraintness,
the problems are solved efficiently, i.e. in linear time. For higher
constraintness, the solution times become exponential. We observe that the
dynamical behavior is characterized by a fast equilibration and fluctuations
around this equilibrium. If the algorithm runs long enough, an exponentially
rare fluctuation towards a solution appears.Comment: 21 pages, 18 figures, revised version, to app. in PRE (2003
The dynamics of proving uncolourability of large random graphs I. Symmetric Colouring Heuristic
We study the dynamics of a backtracking procedure capable of proving
uncolourability of graphs, and calculate its average running time T for sparse
random graphs, as a function of the average degree c and the number of vertices
N. The analysis is carried out by mapping the history of the search process
onto an out-of-equilibrium (multi-dimensional) surface growth problem. The
growth exponent of the average running time is quantitatively predicted, in
agreement with simulations.Comment: 5 figure
Relaxation and Metastability in the RandomWalkSAT search procedure
An analysis of the average properties of a local search resolution procedure
for the satisfaction of random Boolean constraints is presented. Depending on
the ratio alpha of constraints per variable, resolution takes a time T_res
growing linearly (T_res \sim tau(alpha) N, alpha < alpha_d) or exponentially
(T_res \sim exp(N zeta(alpha)), alpha > alpha_d) with the size N of the
instance. The relaxation time tau(alpha) in the linear phase is calculated
through a systematic expansion scheme based on a quantum formulation of the
evolution operator. For alpha > alpha_d, the system is trapped in some
metastable state, and resolution occurs from escape from this state through
crossing of a large barrier. An annealed calculation of the height zeta(alpha)
of this barrier is proposed. The polynomial/exponentiel cross-over alpha_d is
not related to the onset of clustering among solutions.Comment: 23 pages, 11 figures. A mistake in sec. IV.B has been correcte
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