A Bayesian Inference Analysis of the X-ray Cluster Luminosity-Temperature Relation

We present a Bayesian inference analysis of the Markevitch (1998) and Allen & Fabian (1998) cooling flow corrected X-ray cluster temperature catalogs that constrains the slope and the evolution of the empirical X-ray cluster luminosity-temperature (L-T) relation. We find that for the luminosity range 10^44.5 erg s^-1 < L_bol < 10^46.5 erg s^-1 and the redshift range z < 0.5, L_bol is proportional to T^2.80(+0.15/-0.15)(1+z)^(0.91-1.12q_0)(+0.54/-1.22). We also determine the L-T relation that one should use when fitting the Press- Schechter mass function to X-ray cluster luminosity catalogs such as the Einstein Medium Sensitivity Survey (EMSS) and the Southern Serendipitous High- Redshift Archival ROSAT Catalog (Southern SHARC), for which cooling flow corrected luminosities are not determined and a universal X-ray cluster temperature of T = 6 keV is assumed. In this case, L_bol is proportional to T^2.65(+0.23/-0.20)(1+z)^(0.42-1.26q_0)(+0.75/-0.83) for the same luminosity and redshift ranges.Comment: Accepted to The Astrophysical Journal, 20 pages, LaTe

Connecting disability equality to citizenship education

This thesis argues that the invisibility of disabled people in the Citizenship curriculum is no longer tenable. In analogue to race and sex discrimination, I use legal case analyses, together with empirically framed case studies within an international perspective, to systematically explore different aspects of citizenship. Citizenship elements range from ‘legal’, ‘constitutional context’, ‘political participation’, ‘human rights’, ‘community’, ‘socio-economic’ to ‘identity and belonging’. Through a mash up methodology of running voices of disabled people themselves over various themes of citizenship, the contributions, barriers and achievements of disabled people are embedded in the analysis. This includes often apparently conflicting or contradictory voices and cross cultural discussions. Disabled people’s experiences are constitutive of, not additional to, citizenship values. The work confirms that a paradigm shift is taking place in our understanding of disability, which profoundly challenges traditional models of citizenship and leads to uncertainties in professional practice. I propose a three-pillar model of inclusive citizenship, underpinned by the social model of disability, a socio-legal framework of rights-based anti-discrimination, and recognition of struggle as a political manifestation of contested ideologies. Each pillar is associated with concomitant shifts not only in individual but also in institutional behaviour, which extends to a critical examination of the law, the role of the state, social and institutional practices. The extent to which curriculum development on Citizenship, policy ideas, resources and practices are inclusive of and accessible to disabled people, and how programmes of study at key stages 3 and 4 reference disabled citizens, is critically discussed. This leads to an outline of practice with potential that connects disability equality to Citizenship education

The Redshift of GRB 970508

GRB 970508 is the second gamma-ray burst (GRB) for which an optical afterglow has been detected. It is the first GRB for which a distance scale has been determined: absorption and emission features in spectra of the optical afterglow place GRB 970508 at a redshift of z >= 0.835 (Metzger et al. 1997a, 1997b). The lack of a Lyman-alpha forest in these spectra further constrains this redshift to be less than approximately 2.3. I show that the spectrum of the optical afterglow of GRB 970508, once corrected for Galactic absorption, is inconsistent with the relativistic blast-wave model unless a second, redshifted source of extinction is introduced. This second source of extinction may be the yet unobserved host galaxy. I determine its redshift to be z = 1.09^{+0.14}_{-0.41}, which is consistent with the observed redshift of z = 0.835. Redshifts greater than z = 1.40 are ruled out at the 3 sigma confidence level.Comment: Accepted to The Astrophysical Journal (Letters), 10 pages, LaTe

GRB 970228 Revisited: Evidence for a Supernova in the Light Curve and La te Spectral Energy Distribution of the Afterglow

At the time of its discovery, the optical and X-ray afterglow of GRB 970228 appeared to be a ringing endorsement of the previously untried relativistic fireball model of gamma-ray burst (GRB) afterglows, but now that nearly a dozen optical afterglows to GRBs have been observed, the wavering light curve and reddening spectrum of this afterglow make it perhaps the most difficult of the observed afterglows to reconcile with the fireball model. In this Letter, we argue that this afterglow's unusual temporal and spectral properties can be attributed to a supernova that overtook the light curve nearly two weeks after the GRB. This is the strongest case yet for a GRB/supernova connection. It strengthens the case that a supernova also dominated the late afterglow of GRB 980326, and the case that GRB 980425 is related to SN 1998bw.Comment: Accepted to The Astrophysical Journal (Letters), 14 pages, LaTe

Bridging languages through images with deep partial canonical correlation analysis

We present a deep neural network that leverages images to improve bilingual text embeddings. Relying on bilingual image tags and descriptions, our approach conditions text embedding induction on the shared visual information for both languages, producing highly correlated bilingual embeddings. In particular, we propose a novel model based on Partial Canonical Correlation Analysis (PCCA). While the original PCCA finds linear projections of two views in order to maximize their canonical correlation conditioned on a shared third variable, we introduce a non-linear Deep PCCA (DPCCA) model, and develop a new stochastic iterative algorithm for its optimization. We evaluate PCCA and DPCCA on multilingual word similarity and cross-lingual image description retrieval. Our models outperform a large variety of previous methods, despite not having access to any visual signal during test time inference. Our code and data are available at: https://github.com/rotmanguy/DPCCA

Towards zero-shot language modeling

Can we construct a neural language model which is inductively biased towards learning human language? Motivated by this question, we aim at constructing an informative prior for held-out languages on the task of character-level, open-vocabulary language modeling. We obtain this prior as the posterior over network weights conditioned on the data from a sample of training languages, which is approximated through Laplace’s method. Based on a large and diverse sample of languages, the use of our prior outperforms baseline models with an uninformative prior in both zero-shot and few-shot settings, showing that the prior is imbued with universal linguistic knowledge. Moreover, we harness broad language-specific information available for most languages of the world, i.e., features from typological databases, as distant supervision for held-out languages. We explore several language modeling conditioning techniques, including concatenation and meta-networks for parameter generation. They appear beneficial in the few-shot setting, but ineffective in the zero-shot setting. Since the paucity of even plain digital text affects the majority of the world’s languages, we hope that these insights will broaden the scope of applications for language technology

Do we really need fully unsupervised cross-lingual embeddings?

Recent efforts in cross-lingual word embedding (CLWE) learning have predominantly focused on fully unsupervised approaches that project monolingual embeddings into a shared cross-lingual space without any cross-lingual signal. The lack of any supervision makes such approaches conceptually attractive. Yet, their only core difference from (weakly) supervised projection-based CLWE methods is in the way they obtain a seed dictionary used to initialize an iterative self-learning procedure. The fully unsupervised methods have arguably become more robust, and their primary use case is CLWE induction for pairs of resource-poor and distant languages. In this paper, we question the ability of even the most robust unsupervised CLWE approaches to induce meaningful CLWEs in these more challenging settings. A series of bilingual lexicon induction (BLI) experiments with 15 diverse languages (210 language pairs) show that fully unsupervised CLWE methods still fail for a large number of language pairs (e.g., they yield zero BLI performance for 87/210 pairs). Even when they succeed, they never surpass the performance of weakly supervised methods (seeded with 500-1,000 translation pairs) using the same self-learning procedure in any BLI setup, and the gaps are often substantial. These findings call for revisiting the main motivations behind fully unsupervised CLWE methods

Design and Fabrication of Three-Dimensional Scaffolds for Tissue Engineering of Human Heart Valves

We developed a new fabrication technique for 3-dimensional scaffolds for tissue engineering of human heart valve tissue. A human aortic homograft was scanned with an X-ray computer tomograph. The data derived from the X-ray computed tomogram were processed by a computer-aided design program to reconstruct a human heart valve 3-dimensionally. Based on this stereolithographic model, a silicone valve model resembling a human aortic valve was generated. By taking advantage of the thermoplastic properties of polyglycolic acid as scaffold material, we molded a 3-dimensional scaffold for tissue engineering of human heart valves. The valve scaffold showed a deviation of only +/- 3-4% in height, length and inner diameter compared with the homograft. The newly developed technique allows fabricating custom-made, patient-specific polymeric cardiovascular scaffolds for tissue engineering without requiring any suture materials. Copyright (c) 2008 S. Karger AG, Base