Asymptotic enumeration of correlation-immune boolean functions

A boolean function of $n$ boolean variables is {correlation-immune} of order $k$ if the function value is uncorrelated with the values of any $k$ of the arguments. Such functions are of considerable interest due to their cryptographic properties, and are also related to the orthogonal arrays of statistics and the balanced hypercube colourings of combinatorics. The {weight} of a boolean function is the number of argument values that produce a function value of 1. If this is exactly half the argument values, that is, $2^{n-1}$ values, a correlation-immune function is called {resilient}. An asymptotic estimate of the number $N(n,k)$ of $n$-variable correlation-immune boolean functions of order $k$ was obtained in 1992 by Denisov for constant $k$. Denisov repudiated that estimate in 2000, but we will show that the repudiation was a mistake. The main contribution of this paper is an asymptotic estimate of $N(n,k)$ which holds if $k$ increases with $n$ within generous limits and specialises to functions with a given weight, including the resilient functions. In the case of $k=1$, our estimates are valid for all weights.Comment: 18 page

A Search for H2O Megamasers in High-z Type-2 AGNs

We report a search for H2O megamasers in 274 SDSS type-2 AGNs (0.3 < z < 0.83), half of which can be classified as type-2 QSOs from their [OIII] 5007 luminosity, using the Robert C. Byrd Green Bank Telescope (GBT) and the Effelsberg 100-m radio telescope. Apart from the detection of the extremely luminous water vapor megamaser SDSS J080430.99+360718.1, already reported by Barvainis & Antonucci (2005), we do not find any additional line emission. This high rate of non-detections is compared to the water maser luminosity function created from the 78 water maser galaxies known to date and its extrapolation towards the higher luminosities of "gigamasers" that we would have been able to detect given the sensitivity of our survey. The properties of the known water masers are summarized and discussed with respect to the nature of high-z type-2 AGNs and megamasers in general. In the appendix, we list 173 additional objects (mainly radio galaxies, but also QSOs and galaxies) that were observed with the GBT, the Effelsberg 100-m radio telescope, or Arecibo Observatory without leading to the detection of water maser emission.Comment: 28 pages, 3 figures. Accepted for publication in the Astrophysical Journa

Population structure and cultural geography of a folktale in Europe.

Despite a burgeoning science of cultural evolution, relatively little work has focused on the population structure of human cultural variation. By contrast, studies in human population genetics use a suite of tools to quantify and analyse spatial and temporal patterns of genetic variation within and between populations. Human genetic diversity can be explained largely as a result of migration and drift giving rise to gradual genetic clines, together with some discontinuities arising from geographical and cultural barriers to gene flow. Here, we adapt theory and methods from population genetics to quantify the influence of geography and ethnolinguistic boundaries on the distribution of 700 variants of a folktale in 31 European ethnolinguistic populations. We find that geographical distance and ethnolinguistic affiliation exert significant independent effects on folktale diversity and that variation between populations supports a clustering concordant with European geography. This pattern of geographical clines and clusters parallels the pattern of human genetic diversity in Europe, although the effects of geographical distance and ethnolinguistic boundaries are stronger for folktales than genes. Our findings highlight the importance of geography and population boundaries in models of human cultural variation and point to key similarities and differences between evolutionary processes operating on human genes and culture

An Iterative Genetic and Dynamical Modelling Approach Identifies Novel Features of the Gene Regulatory Network Underlying Melanocyte Development

The mechanisms generating stably differentiated cell-types from multipotent precursors are key to understanding normal development and have implications for treatment of cancer and the therapeutic use of stem cells. Pigment cells are a major derivative of neural crest stem cells and a key model cell-type for our understanding of the genetics of cell differentiation. Several factors driving melanocyte fate specification have been identified, including the transcription factor and master regulator of melanocyte development, Mitf, and Wnt signalling and the multipotency and fate specification factor, Sox10, which drive mitf expression. While these factors together drive multipotent neural crest cells to become specified melanoblasts, the mechanisms stabilising melanocyte differentiation remain unclear. Furthermore, there is controversy over whether Sox10 has an ongoing role in melanocyte differentiation. Here we use zebrafish to explore in vivo the gene regulatory network (GRN) underlying melanocyte specification and differentiation. We use an iterative process of mathematical modelling and experimental observation to explore methodically the core melanocyte GRN we have defined. We show that Sox10 is not required for ongoing differentiation and expression is downregulated in differentiating cells, in response to Mitfa and Hdac1. Unexpectedly, we find that Sox10 represses Mitf-dependent expression of melanocyte differentiation genes. Our systems biology approach allowed us to predict two novel features of the melanocyte GRN, which we then validate experimentally. Specifically, we show that maintenance of mitfa expression is Mitfa-dependent, and identify Sox9b as providing an Mitfa-independent input to melanocyte differentiation. Our data supports our previous suggestion that Sox10 only functions transiently in regulation of mitfa and cannot be responsible for long-term maintenance of mitfa expression; indeed, Sox10 is likely to slow melanocyte differentiation in the zebrafish embryo. More generally, this novel approach to understanding melanocyte differentiation provides a basis for systematic modelling of differentiation in this and other cell-types

CLICS² An Improved Database of Cross-Linguistic Colexifications : Assembling Lexical Data with the Help of Cross-Linguistic Data Formats

International audienceThe Database of Cross-Linguistic Colexifications (CLICS), has established a computer-assisted framework for the interactive representation of cross-linguistic colexification patterns. In its current form, it has proven to be a useful tool for various kinds of investigation into cross-linguistic semantic associations , ranging from studies on semantic change, patterns of conceptualization, and linguistic pale-ontology. But CLICS has also been criticized for obvious shortcomings, ranging from the underlying dataset, which still contains many errors, up to the limits of cross-linguistic colexification studies in general. Building on recent standardization efforts reflected in the Cross-Linguistic Data Formats initiative (CLDF) and novel approaches for fast, efficient, and reliable data aggregation, we have created a new database for cross-linguistic colexifications, which not only supersedes the original CLICS database in terms of coverage but also offers a much more principled procedure for the creation, curation and aggregation of datasets. The paper presents the new database and discusses its major features

Sequence comparison in computational historical linguistics

With increasing amounts of digitally available data from all over the world, manual annotation of cognates in multi-lingual word lists becomes more and more time-consuming in historical linguistics. Using available software packages to pre-process the data prior to manual analysis can drastically speed-up the process of cognate detection. Furthermore, it allows us to get a quick overview on data which have not yet been intensively studied by experts. LingPy is a Python library which provides a large arsenal of routines for sequence comparison in historical linguistics. With LingPy, linguists can not only automatically search for cognates in lexical data, but they can also align the automatically identified words, and output them in various forms, which aim at facilitating manual inspection. In this tutorial, we will briefly introduce the basic concepts behind the algorithms employed by LingPy and then illustrate in concrete workflows how automatic sequence comparison can be applied to multi-lingual word lists. The goal is to provide the readers with all information they need to (1) carry out cognate detection and alignment analyses in LingPy, (2) select the appropriate algorithms for the appropriate task, (3) evaluate how well automatic cognate detection algorithms perform compared to experts, and (4) export their data into various formats useful for additional analyses or data sharing. While basic knowledge of the Python language is useful for all analyses, our tutorial is structured in such a way that scholars with basic knowledge of computing can follow through all steps as well.This research was supported by the European Research Council Starting Grant ‘Computer-Assisted Language Comparison’ (Grant CALC 715618, J.M.L., T.T.) and the Australian Research Council’s Centre of Excellence for the Dynamics of Language (Australian National University, Grant CE140100041, S.J.G.). As part of the GlottoBank project (http://glottobank.org), this work was further supported by the Department of Linguistic and Cultural Evolution of the Max Planck Institute for the Science of Human History (Jena) and the Royal Society of New Zealand (Marsden Fund, Grant 13-UOA-121)

Sequence comparison in computational historical linguistics

With increasing amounts of digitally available data from all over the world, manual annotation of cognates in multi-lingual word lists becomes more and more time-consuming in historical linguistics. Using available software packages to pre-process the data prior to manual analysis can drastically speed-up the process of cognate detection. Furthermore, it allows us to get a quick overview on data which have not yet been intensively studied by experts. LingPy is a Python library which provides a large arsenal of routines for sequence comparison in historical linguistics. With LingPy, linguists can not only automatically search for cognates in lexical data, but they can also align the automatically identified words, and output them in various forms, which aim at facilitating manual inspection. In this tutorial, we will briefly introduce the basic concepts behind the algorithms employed by LingPy and then illustrate in concrete workflows how automatic sequence comparison can be applied to multi-lingual word lists. The goal is to provide the readers with all information they need to (1) carry out cognate detection and alignment analyses in LingPy, (2) select the appropriate algorithms for the appropriate task, (3) evaluate how well automatic cognate detection algorithms perform compared to experts, and (4) export their data into various formats useful for additional analyses or data sharing. While basic knowledge of the Python language is useful for all analyses, our tutorial is structured in such a way that scholars with basic knowledge of computing can follow through all steps as well

Distinct Streptococcus pneumoniae cause invasive disease in Papua New Guinea

Streptococcus pneumoniae is a key contributor to childhood morbidity and mortality in Papua New Guinea (PNG). For the first time, whole genome sequencing of 174 isolates has enabled detailed characterisation of diverse S. pneumoniae causing invasive disease in young children in PNG, 1989-2014. This study captures the baseline S. pneumoniae population prior to the introduction of 13-valent pneumococcal conjugate vaccine (PCV13) into the national childhood immunisation programme in 2014. Relationships amongst lineages, serotypes and antimicrobial resistance traits were characterised, and the population was viewed in the context of a global collection of isolates. The analyses highlighted adiverse S. pneumoniae population associated with invasive disease in PNG, with 45 unique Global Pneumococcal Sequence Clusters (GPSCs) observed amongst the 174 isolates reflecting multiple lineages observed in PNG that have not been identified in other geographic locations. The majority of isolates were from children with meningitis, of which 52% (n=72) expressed non-PCV13 serotypes. Over a third of isolates were predicted to be resistant to at least one antimicrobial. PCV13 serotype isolates had 10.1 times the odds of being multidrug-resistant (MDR) compared to non-vaccine serotype isolates, and no isolates with GPSCs unique to PNG were MDR. Serotype 2 was the most commonly identified serotype; we identified a highly clonal cluster of serotype 2 isolates unique to PNG, and a distinct second cluster indicative of long-distance transmission. Ongoing surveillance, including whole-genome sequencing, is needed to ascertain the impact of the national PCV13 programme upon the S. pneumoniae population, including serotype replacement and antimicrobial resistance traits. © 2022 The Authors