Exploratory Analysis of Highly Heterogeneous Document Collections

We present an effective multifaceted system for exploratory analysis of highly heterogeneous document collections. Our system is based on intelligently tagging individual documents in a purely automated fashion and exploiting these tags in a powerful faceted browsing framework. Tagging strategies employed include both unsupervised and supervised approaches based on machine learning and natural language processing. As one of our key tagging strategies, we introduce the KERA algorithm (Keyword Extraction for Reports and Articles). KERA extracts topic-representative terms from individual documents in a purely unsupervised fashion and is revealed to be significantly more effective than state-of-the-art methods. Finally, we evaluate our system in its ability to help users locate documents pertaining to military critical technologies buried deep in a large heterogeneous sea of information.Comment: 9 pages; KDD 2013: 19th ACM SIGKDD Conference on Knowledge Discovery and Data Minin

Measurement of correlations between low-frequency vibrational modes and particle rearrangements in quasi-two-dimensional colloidal glasses

We investigate correlations between low-frequency vibrational modes and rearrangements in two-dimensional colloidal glasses composed of thermosensitive microgel particles which readily permit variation of sample packing fraction. At each packing fraction, the particle displacement covariance matrix is measured and used to extract the vibrational spectrum of the "shadow" colloidal glass (i.e., the particle network with the same geometry and interactions as the sample colloid but absent damping). Rearrangements are induced by successive, small reductions in packing fraction. The experimental results suggest that low-frequency quasi-localized phonon modes in colloidal glasses, i.e., modes that present low energy barriers for system rearrangements, are spatially correlated with rearrangements in this thermal system

One-year mortality after hospital admission as an indicator of palliative care need: A retrospective cohort study

Background. Globally there is increasing awareness of the need for end-of-life care and palliative care in hospitalised patients who are in their final year of life. Limited data are available on palliative care requirements in low- and middle-income countries, hindering the design and implementation of effective policies and health services for these patients.Objectives. To determine the proportion of patients who die within 1 year of their date of admission to public hospitals in South Africa (SA), as a proxy for palliative care need in SA.Methods. This was a retrospective cohort study using record linkage of admission and mortality data. The setting was 46 acute-care public hospitals in Western Cape Province, SA.Results. Of 10 761 patients (median (interquartile range (IQR)) age 44 (31 - 60) years) admitted to the 46 hospitals over a 2-week period in March 2012, 1 570 (14.6%) died within 1 year, the majority within the first 3 months. Mortality rose steeply with age. The median (IQR) age of death was 57.5 (45 - 70) years. A greater proportion of patients admitted to medical beds died within 1 year (21.3%) compared with those admitted to surgical beds (7.7%).Conclusions. Despite a median age <60 years at admission, a substantial percentage of patients admitted to public sector hospitals in SA are in the final year of their lives. This finding should be seen in the context of SA’s high communicable and non-communicable disease burden and resource-limited public health system, and highlights the need for policy development, planning and implementation of end-of-life and palliative care strategies for hospitals and patients.

The Search for Intergalactic Hydrogen Clouds in Voids

I present the results of a search for intergalactic hydrogen clouds in voids. Clouds are detected by their HI LyA absorption lines in the HST spectra of low-redshift AGN. The parameter with which the environments of clouds are characterized is the tidal field, which places a lower limit on the cloud mass-density which is dynamically stable against disruption. Galaxy redshift catalogs are used to sum the tidal fields along the lines of sight, sorting clouds according to tidal field upper, or lower limits. The analytical methodology employed is designed to detect gas clouds whose expansion following reionization is restrained by dark matter perturbations. End-products are the cloud equivalent width distribution functions (EWDF) of catalogs formed by sorting clouds according to various tidal field upper, or lower limits. Cumulative EWDFs are steep in voids (S ~ -1.5 \pm 0.2), but flatter in high tidal field zones (S ~ -0.5 \pm 0.1). Most probable cloud Doppler parameters are ~30 km/s in voids and ~60 km/s in proximity to galaxies. In voids, the cumulative line density at low EW (~ 15 mA) is ~ 500 per unit redshift. The void filling factor is found to be 0.87 <= f_v <= 0.94. The void EWDF is remarkably uniform over this volume, with a possible tendency for more massive clouds to be in void centers. The size and nature of the void cloud population suggested by this study is completely unanticipated by the results of published 3-D simulations, which predict that most clouds are in filamentary structures around galaxy concentrations, and that very few observable absorbers would lie in voids. Strategies for modeling this population are briefly discussed.Comment: 21 pages, 19 figures, apjemulate style, to appear in ApJ vol. 57

Characterization of uncertainties in atmospheric trace gas inversions using hierarchical Bayesian methods

We present a hierarchical Bayesian method for atmospheric trace gas inversions. This method is used to estimate emissions of trace gases as well as "hyper-parameters" that characterize the probability density functions (PDFs) of the a priori emissions and model-measurement covariances. By exploring the space of "uncertainties in uncertainties", we show that the hierarchical method results in a more complete estimation of emissions and their uncertainties than traditional Bayesian inversions, which rely heavily on expert judgment. We present an analysis that shows the effect of including hyper-parameters, which are themselves informed by the data, and show that this method can serve to reduce the effect of errors in assumptions made about the a priori emissions and model-measurement uncertainties. We then apply this method to the estimation of sulfur hexafluoride (SF6) emissions over 2012 for the regions surrounding four Advanced Global Atmospheric Gases Experiment (AGAGE) stations. We find that improper accounting of model representation uncertainties, in particular, can lead to the derivation of emissions and associated uncertainties that are unrealistic and show that those derived using the hierarchical method are likely to be more representative of the true uncertainties in the system. We demonstrate through this SF6 case study that this method is less sensitive to outliers in the data and to subjective assumptions about a priori emissions and model-measurement uncertainties than traditional methods

Effect of reconstruction methods and x-ray tube current-time product on nodule detection in an anthropomorphic thorax phantom : a crossed-modality JAFROC observer study

Purpose: To evaluate nodule detection in an anthropomorphic chest phantom in computed tomography (CT) images reconstructed with adaptive iterative dose reduction 3D (AIDR3D) and filtered back projection (FBP) over a range of tube current-time product (mAs). Methods: Two phantoms were used in this study: (i) an anthropomorphic chest phantom was loaded with spherical simulated nodules of 5, 8, 10 and 12mm in diameter and +100, -630 and -800 Hounsfied Units electron density; this would generate CT images for the observer study; (ii) a whole-body dosimetry verification phantom was used to ultimately estimate effective dose and risk according to the model of the BEIR VII committee. Both phantoms were scanned over a mAs range (10, 20, 30, and 40) while all other acquisition parameters remained constant. Images were reconstructed with both AIDR3D and FBP. 34 normal cases (no nodules) and 34 abnormal cases (containing 1-3 nodules, mean 1.35±0.54) cases were chosen for the observer study. Eleven observers evaluated images from all tube current-time product and reconstruction methods under the free-response paradigm. A crossed-modality jackknife alternative free-response operating characteristic (JAFROC) analysis method was developed for data analysis, averaging data over the two factors influencing nodule detection in this study: mAs and image reconstruction (AIDR3D or FBP). A Bonferroni correction was applied and the threshold for declaring significance was set at 0.025 to maintain the overall probability of Type I error at α = 0.05. Contrast-to-noise (CNR) was also measured for all nodules and evaluated by a linear least squares analysis. Results: For random-reader fixed-case crossed-modality JAFROC analysis there was no significant difference in nodule detection between AIDR3D and FBP when data was averaged over mAs (F(1,10) = 0.08, p = 0.789). However, when data was averaged over reconstruction methods, a significant difference was seen between multiple pairs of mAs settings (F(3,30) = 15.96, p&lt;0.001). Measurements of effective dose and effective risk showed the expected linear dependence on mAs. Nodule CNR was statistically higher for simulated nodules on images reconstructed with AIDR3D (p&lt;0.001). Conclusion: No significant difference in nodule detection performance was demonstrated between images reconstructed with FBP and AIDR3D. Tube current-time product was found to influence nodule detection, though further work is required for dose optimisation

Beyond the Refugee Crisis how the UK news media represent asylum seekers across national boundaries

Migration is one of the most pressing, divisive issues in global politics today, and media play a crucial role in how communities understand and respond. This study examines how UK newspapers (n = 974) and popular news websites (n = 1044) reported on asylum seekers throughout 2017. It contributes to previous literature in two important ways. First, by examining the ‘new normal’ of daily news coverage in the wake of the 2015 ‘refugee crisis’ in Europe. Second, by looking at how asylum seekers from different regions are represented. The content analysis finds significant variations in how asylum seekers are reported, including terminology use and topics they are associated with. The paper also identifies important commonalities in how all asylum seekers are represented - most notably, the dominance of political elites as sources across all media content. It argues that Entman’s ‘cascade network model’ can help to explain this, with elites in one country able to influence transnational reports