Modelling the flow of discourse in a corpus of written academic English

Discourse studies attempt to describe how context affects text, and how text progresses from one sentence to the next. Systemic Functional Linguistics (SFL) offers a model of language to describe how information flow varies according to context and co-text through the Textual metafunction, especially using the functions of Participant Identification and Tracking, Theme and Information Structure. These systems were evaluated by assembling a corpus of academic texts and assessing their information flow. Results of the analysis of the three grammatical systems in the Textual Metafunction demonstrate significant patterns, or unmarked choices, where the participant, thematic and information systems combine to powerful effect. Where the systems are not aligned, there is a recognisable effect on the flow of information

Frequency-domain waveform approximants capturing Doppler shifts

Gravitational wave astrophysics has only just begun, and as current detectors are upgraded and new detectors are built, many new, albeit faint, features in the signals will become accessible. One such feature is the presence of time-dependent Doppler shifts, generated by the acceleration of the center of mass of the gravitational-wave emitting system. We here develop a generic method that takes a frequency-domain, gravitational-wave model devoid of Doppler shifts and introduces modifications that incorporate them. Building upon a perturbative expansion that assumes the Doppler-shift velocity is small relative to the speed of light, the method consists of the inclusion of a single term in the Fourier phase and two terms in the Fourier amplitude. We validate the method through matches between waveforms with a Doppler shift in the time domain and waveforms constructed with our method for two toy problems: constant accelerations induced by a distant third body and Gaussian accelerations that resemble a kick profile. We find mismatches below $\sim\!10^{-6}$ for all of the astrophysically relevant cases considered, and improve further at smaller velocities. The work presented here will allow for the use of future detectors to extract new, faint features in the signal from the noise.Comment: 11 pages, 5 figures, submitted to Phys. Rev.

Information-theoretic bounds and phase transitions in clustering, sparse PCA, and submatrix localization

We study the problem of detecting a structured, low-rank signal matrix corrupted with additive Gaussian noise. This includes clustering in a Gaussian mixture model, sparse PCA, and submatrix localization. Each of these problems is conjectured to exhibit a sharp information-theoretic threshold, below which the signal is too weak for any algorithm to detect. We derive upper and lower bounds on these thresholds by applying the first and second moment methods to the likelihood ratio between these "planted models" and null models where the signal matrix is zero. Our bounds differ by at most a factor of root two when the rank is large (in the clustering and submatrix localization problems, when the number of clusters or blocks is large) or the signal matrix is very sparse. Moreover, our upper bounds show that for each of these problems there is a significant regime where reliable detection is information- theoretically possible but where known algorithms such as PCA fail completely, since the spectrum of the observed matrix is uninformative. This regime is analogous to the conjectured 'hard but detectable' regime for community detection in sparse graphs.Comment: For sparse PCA and submatrix localization, we determine the information-theoretic threshold exactly in the limit where the number of blocks is large or the signal matrix is very sparse based on a conditional second moment method, closing the factor of root two gap in the first versio

Developing an assessed reading portfolio to improve reading habits and raise test results

For over 10 years, preparatory students at Khalifa University, UAE, have been encouraged to improve their reading and language learning skills through the use of an assessed reading portfolio. This paper briefly outlines the rationale behind this type of assessment and the design features of the portfolio, before detailing some of the many adaptations that it has experienced over the years, paying particular attention to recent developments involving the use of technology. Through an evaluation of the portfolio, using authentic scores for the portfolio and comparing them to IELTS reading test scores, it emerges that students who do well on the portfolio are more likely to make gains in their reading scores than those who do not perform well in their reading portfolio assessment

RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language.

Programs for Bayesian inference of phylogeny currently implement a unique and fixed suite of models. Consequently, users of these software packages are simultaneously forced to use a number of programs for a given study, while also lacking the freedom to explore models that have not been implemented by the developers of those programs. We developed a new open-source software package, RevBayes, to address these problems. RevBayes is entirely based on probabilistic graphical models, a powerful generic framework for specifying and analyzing statistical models. Phylogenetic-graphical models can be specified interactively in RevBayes, piece by piece, using a new succinct and intuitive language called Rev. Rev is similar to the R language and the BUGS model-specification language, and should be easy to learn for most users. The strength of RevBayes is the simplicity with which one can design, specify, and implement new and complex models. Fortunately, this tremendous flexibility does not come at the cost of slower computation; as we demonstrate, RevBayes outperforms competing software for several standard analyses. Compared with other programs, RevBayes has fewer black-box elements. Users need to explicitly specify each part of the model and analysis. Although this explicitness may initially be unfamiliar, we are convinced that this transparency will improve understanding of phylogenetic models in our field. Moreover, it will motivate the search for improvements to existing methods by brazenly exposing the model choices that we make to critical scrutiny. RevBayes is freely available at http://www.RevBayes.com [Bayesian inference; Graphical models; MCMC; statistical phylogenetics.]

A Case of Extrapulmonary Tuberculosis Two-Ways

Tuberculosis (TB) is a widespread epidemic. The World HealthOrganization estimated 10.4 million cases of tuberculosis in 2016,with 490,000 new cases of multi-drug resistant (MDR) TB.1 Theprimary presentation of TB is pulmonary. However, in the UnitedStates in 2014, 21% of TB cases were extrapulmonary with the mostcommon sites in descending order of incidence being TB lymphadenitis(38.2%), pleural (16.3%), bone and/or joint (10.4%), peritoneal(5.7%), genitourinary (5%), meningeal (4.5%), and laryngeal (0.2%).