Growing Graphs with Hyperedge Replacement Graph Grammars

Discovering the underlying structures present in large real world graphs is a fundamental scientific problem. In this paper we show that a graph's clique tree can be used to extract a hyperedge replacement grammar. If we store an ordering from the extraction process, the extracted graph grammar is guaranteed to generate an isomorphic copy of the original graph. Or, a stochastic application of the graph grammar rules can be used to quickly create random graphs. In experiments on large real world networks, we show that random graphs, generated from extracted graph grammars, exhibit a wide range of properties that are very similar to the original graphs. In addition to graph properties like degree or eigenvector centrality, what a graph "looks like" ultimately depends on small details in local graph substructures that are difficult to define at a global level. We show that our generative graph model is able to preserve these local substructures when generating new graphs and performs well on new and difficult tests of model robustness.Comment: 18 pages, 19 figures, accepted to CIKM 2016 in Indianapolis, I

Serum anti-Müllerian hormone concentrations before and after treatment of an ovarian granulosa cell tumour in a cat

Case summary A 15-year-old female cat was presented for investigation of progressive behavioural changes, polyuria, polydipsia and periuria. An ovarian granulosa cell tumour was identified and the cat underwent therapeutic ovariohysterectomy (OHE). The cat’s clinical signs resolved, but 6 months later it was diagnosed as having an anaplastic astrocytoma and was euthanased. Serum anti-Müllerian hormone (AMH) concentration prior to OHE was increased vs a control group of entire and neutered female cats. Following OHE, serum AMH concentration decreased to <1% of the original value. Relevance and novel information Serum AMH measurement may represent a novel diagnostic and monitoring tool for functional ovarian neoplasms in cats

The meta book and size-dependent properties of written language

Evidence is given for a systematic text-length dependence of the power-law index gamma of a single book. The estimated gamma values are consistent with a monotonic decrease from 2 to 1 with increasing length of a text. A direct connection to an extended Heap's law is explored. The infinite book limit is, as a consequence, proposed to be given by gamma = 1 instead of the value gamma=2 expected if the Zipf's law was ubiquitously applicable. In addition we explore the idea that the systematic text-length dependence can be described by a meta book concept, which is an abstract representation reflecting the word-frequency structure of a text. According to this concept the word-frequency distribution of a text, with a certain length written by a single author, has the same characteristics as a text of the same length pulled out from an imaginary complete infinite corpus written by the same author.Comment: 7 pages, 6 figures, 1 tabl

Rare regions of the susceptible-infected-susceptible model on Barabási-Albert networks

I extend a previous work to susceptible-infected-susceptible (SIS) models on weighted Barabási-Albert scale-free networks. Numerical evidence is provided that phases with slow, power-law dynamics emerge as the consequence of quenched disorder and tree topologies studied previously with the contact process. I compare simulation results with spectral analysis of the networks and show that the quenched mean-field (QMF) approximation provides a reliable, relatively fast method to explore activity clustering. This suggests that QMF can be used for describing rare-region effects due to network inhomogeneities. Finite-size study of the QMF shows the expected disappearance of the epidemic threshold λc in the thermodynamic limit and an inverse participation ratio ∼0.25, meaning localization in case of disassortative weight scheme. Contrarily, for the multiplicative weights and the unweighted trees, this value vanishes in the thermodynamic limit, suggesting only weak rare-region effects in agreement with the dynamical simulations. Strong corrections to the mean-field behavior in case of disassortative weights explains the concave shape of the order parameter ρ(λ) at the transition point. Application of this method to other models may reveal interesting rare-region effects, Griffiths phases as the consequence of quenched topological heterogeneities

Lidar technology measurements and technology: Report of panel

Lidar is ready to make an important contribution to tropospheric chemistry research with a variety of spaceborne measurements that complement the measurements from passive instruments. Lidar can now be considered for near-term and far-term space missions dealing with a number of scientifically important issues in tropospheric chemistry. The evolution in the lidar missions from space are addressed and details of these missions are given. The laser availability for space missions based upon the technical data is assessed

Fitting Ranked English and Spanish Letter Frequency Distribution in U.S. and Mexican Presidential Speeches

The limited range in its abscissa of ranked letter frequency distributions causes multiple functions to fit the observed distribution reasonably well. In order to critically compare various functions, we apply the statistical model selections on ten functions, using the texts of U.S. and Mexican presidential speeches in the last 1-2 centuries. Dispite minor switching of ranking order of certain letters during the temporal evolution for both datasets, the letter usage is generally stable. The best fitting function, judged by either least-square-error or by AIC/BIC model selection, is the Cocho/Beta function. We also use a novel method to discover clusters of letters by their observed-over-expected frequency ratios.Comment: 7 figure

Effects of rapid prey evolution on predator-prey cycles

We study the qualitative properties of population cycles in a predator-prey system where genetic variability allows contemporary rapid evolution of the prey. Previous numerical studies have found that prey evolution in response to changing predation risk can have major quantitative and qualitative effects on predator-prey cycles, including: (i) large increases in cycle period, (ii) changes in phase relations (so that predator and prey are cycling exactly out of phase, rather than the classical quarter-period phase lag), and (iii) "cryptic" cycles in which total prey density remains nearly constant while predator density and prey traits cycle. Here we focus on a chemostat model motivated by our experimental system [Fussmann et al. 2000,Yoshida et al. 2003] with algae (prey) and rotifers (predators), in which the prey exhibit rapid evolution in their level of defense against predation. We show that the effects of rapid prey evolution are robust and general, and furthermore that they occur in a specific but biologically relevant region of parameter space: when traits that greatly reduce predation risk are relatively cheap (in terms of reductions in other fitness components), when there is coexistence between the two prey types and the predator, and when the interaction between predators and undefended prey alone would produce cycles. Because defense has been shown to be inexpensive, even cost-free, in a number of systems [Andersson and Levin 1999, Gagneux et al. 2006,Yoshida et al. 2004], our discoveries may well be reproduced in other model systems, and in nature. Finally, some of our key results are extended to a general model in which functional forms for the predation rate and prey birth rate are not specified.Comment: 35 pages, 8 figure

Machine Learning in Automated Text Categorization

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual definition of a classifier by domain experts) are a very good effectiveness, considerable savings in terms of expert manpower, and straightforward portability to different domains. This survey discusses the main approaches to text categorization that fall within the machine learning paradigm. We will discuss in detail issues pertaining to three different problems, namely document representation, classifier construction, and classifier evaluation.Comment: Accepted for publication on ACM Computing Survey

On the width of the equatorial deep jets

The equatorial deep jets (EDJ) are a striking feature of the equatorial ocean circulation. In the Atlantic Ocean, the EDJ are associated with a vertical scale of between 300 and 700 m, a time scale of roughly 4.5 years and upward energy propagation to the surface. It has been found that the meridional width of the EDJ is roughly 1.5 times larger than expected based on their vertical scale. Here we use a shallow water model for a high order baroclinic vertical normal mode to argue that mixing of momentum along isopycnals can explain the enhanced width. A lateral eddy viscosity of 300 m2 s−1 10 is found to be sufficient to account for the width implied by observations

Framework Report: The AIDS Accountability Workplace Scorecard, September 2011

The aim of the AIDS Accountability Workplace Scorecard is to improve HIV and AIDS workplace programmes in the countries and sectors most affected by the disease, and improve the health of employees, their families and communities. Through this initiative we will: / 1. Provide tools for HIV and AIDS workplace programme monitoring and evaluation AAI has developed scorecard tools for small, medium and large workplaces, which can be used to assess a global, regional or national HIV and AIDS programme or interventions at a specific workplace site. The scorecards can serve as both internal monitoring and evaluation tools and as assessments to present to stakeholders within and outside the organization. / 2. Publish annual Rankings of HIV and AIDS Workplace Programmes Scorecard users who wish to receive a ranking analysis and recommendations for how to improve their programmes can submit their scorecards to AAI. AAI ‘s ranking analysis will allow users to compare their performance with others and over time also measure their own progress. Respondents will be encouraged to publish their ranking in AAI’s yearly Ranking Reports. / 3. Share good practice The knowledge and good practices generated through the published rankings will be used to stimulate improved HIV and AIDS Workplace Programmes worldwide. Large networks of companies, trade union confederations, and national and international organizations can use the scorecard as a common framework for monitoring and evaluation of workplace programmes