1,720,972 research outputs found
Impossibility results on stability of phylogenetic consensus methods
Full text linkWe answer two questions raised by Bryant, Francis, and Steel in their work on consensus methods in phylogenetics. Consensus methods apply to every practical instance where it is desired to aggregate a set of given phylogenetic trees (say, gene evolution trees) into a resulting, “consensus” tree (say, a species tree). Various stability criteria have been explored in this context, seeking to model desirable consistency properties of consensus methods as the experimental data are updated (e.g., more taxa, or more trees, are mapped). However, such stability conditions can be incompatible with some basic regularity properties that are widely accepted to be essential in any meaningful consensus method. Here, we prove that such an incompatibility does arise in the case of extension stability on binary trees and in the case of associative stability. Our methods combine general theoretical considerations with the use of computer programs tailored to the given stability requirements. [Associative stability; consensus; extension stability; phylogeny.
Stationary distributions via decomposition of stochastic reaction networks
No full textWe examine reaction networks (CRNs) through their associated continuous-time Markov processes. Studying the dynamics of such networks is in general hard, both analytically and by simulation. In particular, stationary distributions of stochastic reaction networks are only known in some cases. We analyze class properties of the underlying continuous-time Markov chain of CRNs under the operation of join and examine conditions such that the form of the stationary distributions of a CRN is derived from the parts of the decomposed CRNs. The conditions can be easily checked in examples and allow recursive application. The theory developed enables sequential decomposition of the Markov processes and calculations of stationary distributions. Since the class of processes expressible through such networks is big and only few assumptions are made, the principle also applies to other stochastic models. We give examples of interest from CRN theory to highlight the decomposition.</p
Stationary distributions and condensation in autocatalytic CRN
Full text linkWe investigate a broad family of non weakly reversible stochastically modeled
reaction networks (CRN), by looking at their steady-state distributions. Most
known results on stationary distributions assume weak reversibility and zero
deficiency. We first give explicitly product-form steady-state distributions
for a class of non weakly reversible autocatalytic CRN of arbitrary deficiency.
Examples of interest in statistical mechanics (inclusion process), life
sciences and robotics (collective decision making in ant and robot swarms) are
provided. The product-form nature of the steady-state then enables the study of
condensation in particle systems that are generalizations of the inclusion
process.Comment: 25 pages. Some typos corrected, shortened some part
Stationary distributions and condensation in autocatalytic reaction networks
Full text linkWe investigate a broad family of stochastically modeled reaction networks by looking at their stationary distributions. Most known results on stationary distributions assume weak reversibility and zero deficiency. We first explicitly give product-form stationary distributions for a class of mostly non-weakly-reversible autocatalytic reaction networks of arbitrary deficiency. We provide examples of interest in statistical mechanics (inclusion process), life sciences, and robotics (collective decision making in ant and robot swarms). The product-form nature of the stationary distribution then enables the study of condensation in particle systems that are generalizations of the inclusion process
Fast reactions with non-interacting species in stochastic reaction networks
Full text linkWe consider stochastic reaction networks modeled by continuous-time Markov
chains. Such reaction networks often contain many reactions, potentially
occurring at different time scales, and have unknown parameters (kinetic rates,
total amounts). This makes their analysis complex. We examine stochastic
reaction networks with non-interacting species that often appear in examples of
interest (e.g. in the two-substrate Michaelis Menten mechanism).
Non-interacting species typically appear as intermediate (or transient)
chemical complexes that are depleted at a fast rate. We embed the Markov
process of the reaction network into a one-parameter family under a two
time-scale approach, such that molecules of non-interacting species are
degraded fast. We derive simplified reaction networks where the non-interacting
species are eliminated and that approximate the scaled Markov process in the
limit as the parameter becomes small. Then, we derive sufficient conditions for
such reductions based on the reaction network structure for both homogeneous
and time-varying stochastic settings, and study examples and properties of the
reduction
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Asymptotic analysis for stationary distributions of multiscaled reaction networks
Full text linkWe study stationary distributions in the context of stochastic reaction networks. In particular, we are interested in complex balanced reaction networks and the reduction of such networks by assuming that a set of species (called non-interacting species) are degraded fast (and therefore essentially absent from the network), implying that some reaction rates are large relative to others. Technically, we assume that these reaction rates are scaled by a common parameter N and let . The limiting stationary distribution as is compared with the stationary distribution of the reduced reaction network obtained by elimination of the non-interacting species. In general, the limiting stationary distribution could differ from the stationary distribution of the reduced reaction network. We identify various sufficient conditions under which these two distributions are the same, including when the reaction network is detailed balanced and when the set of non-interacting species consists of intermediate species. In the latter case, the limiting stationary distribution essentially retains the form of the complex balanced distribution. This finding is particularly surprising given that the reduced reaction network could be non-weakly reversible and might exhibit unconventional kinetics
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