IRAS and ground-based observations of star formation regions in the Magellanic clouds

The Infrared Astronomy Satellite (IRAS) detected several hundred individual regions of star formation in the Large and Small Magellanic Clouds. Nearly two dozen of the brightest such sources were searched for from the ground at 10 microns; most of these were located and measured at wavelengths from 0.6 to 20 microns. Three principle results emerge from this study: First, the IRAS data show that star formation is considerably less active in the SMC than in the LMC, relative either to mass, luminosity, or H I content. The reduced activity in the SMC is consistent with the smaller amount of molecular material inferred from CO observations. Second, the sizes of the objects range from less than a few arcsecs (objects which look like extremely compact HII regions, with little or no extended radio, optical, or infrared emission) to some tens of arcsecs across (giant HII regions, of which the largest and brightest is 30 Doradus). Third, there are no obvious differences in the characteristics of the central portions of the LMC and SMC sources; all look like Galactic H II regions of similar luminosity

On mining complex sequential data by means of FCA and pattern structures

Nowadays data sets are available in very complex and heterogeneous ways. Mining of such data collections is essential to support many real-world applications ranging from healthcare to marketing. In this work, we focus on the analysis of "complex" sequential data by means of interesting sequential patterns. We approach the problem using the elegant mathematical framework of Formal Concept Analysis (FCA) and its extension based on "pattern structures". Pattern structures are used for mining complex data (such as sequences or graphs) and are based on a subsumption operation, which in our case is defined with respect to the partial order on sequences. We show how pattern structures along with projections (i.e., a data reduction of sequential structures), are able to enumerate more meaningful patterns and increase the computing efficiency of the approach. Finally, we show the applicability of the presented method for discovering and analyzing interesting patient patterns from a French healthcare data set on cancer. The quantitative and qualitative results (with annotations and analysis from a physician) are reported in this use case which is the main motivation for this work. Keywords: data mining; formal concept analysis; pattern structures; projections; sequences; sequential data.Comment: An accepted publication in International Journal of General Systems. The paper is created in the wake of the conference on Concept Lattice and their Applications (CLA'2013). 27 pages, 9 figures, 3 table

Bolometric luminosities and infrared properties of carbon stars in the Magellanic Clouds and the Galaxy

Broad band J, H, K photometry and narrow band CO and H_2O indices have been obtained for 89 luminous red stars in the Large Magellanic Cloud (LMC) and 21 in the Small Magellanic Cloud (SMC), chosen largely from the sample of Blanco, McCarthy, and Blanco. Most are known to be carbon stars, and their infrared properties are compared with new observations of 33 galactic carbon stars. The bolometric luminosity distributions of an unbiased sample of Magellanic Cloud carbon stars are compared with those predicted from evolutionary calculations by Renzini and Voli for double shell burning stars undergoing He shell flashes. The observed and theoretical distributions disagree markedly: nearly all the observed stars have lower luminosities than even the faintest theoretical carbon star. In addition, we find many fewer than expected high luminosity stars with initial mass greater than 3 M_⊙. Possible explanations for this include a steep initial mass function for intermediate mass stars, a star formation rate significantly higher in the past than at present, or a neglected physical effect, such as underestimation of the importance of mass loss. Nevertheless, it appears that the hypothesis that He shell flashes lead to a dredge-up of carbon into the envelope, which results in a carbon star, can be maintained, if dredging occurs after fewer shell flashes than are predicted by presently available stellar evolutionary calculations. The colors and indices of the late M giants in the LMC field are similar to those of late M giants in the Galaxy. The narrow band infrared data are interpreted qualitatively in terms of the effects of molecular band absorption, which also strongly influences the infrared broad band colors of carbon stars. The small differences in the color-color relationships of the SMC and LMC samples are consistent with the differences in heavy metal abundance between the LMC, SMC, and Galaxy

Trends in P2Y12 Receptor Inhibitor Use and Adherence After Percutaneous Coronary Intervention, 2008-2016

Post-angioplasty, patient adherence to recommended antiplatelet therapy decreased when newer, more expensive drugs were introduced. From 2008-2016, as the use of newer agents increased, the proportion of patients not filling any antiplatelet prescription within 30 days of discharge increased from 6.4% to 19.1%. In the subsequent 12 months, the newer drugs were associated with higher patient costs and lower adherence to recommended therapy

Ultra-High-Resolution Optical Coherence Tomographic Findings in Commotio Retinae

Commotio retinae is a self-limited opacification of the retina secondary to direct blunt ocular trauma. Histologic studies of monkeys and humans relate this clinical observation to damaged photoreceptor outer segments and receptor cell bodies.[superscript 1 - 3] Reports using time-domain optical coherence tomography (OCT) and spectral-domain OCT support the involvement of the photoreceptor layer, but these techniques lack the resolution necessary to confirm results of histologic analysis.[superscript 4 - 6] Prototype high-speed ultra–high-resolution OCT (hs-UHR-OCT) images demonstrate these anatomical changes in a patient with acute commotio retinae.National Institutes of Health (U.S.) (Contract Number RO1-EY11289-23)National Institutes of Health (U.S.) (Contract Number R01-EY13178-07)United States. Air Force Office of Scientific Research (Grant Number FA9550-07-1-0101)United States. Air Force Office of Scientific Research (Grant Number FA9550-07-1-0014

Size Ranges of Magnetic Domain States in Tetrataenite

Paleomagnetic studies of meteorites provide unique constraints on the evolution of magnetic fields in the early solar system. These studies rely on the identification of magnetic minerals that can retain stable magnetizations over ≳4.5 billion years (Ga). The ferromagnetic mineral tetrataenite (γ''-Fe0.5Ni0.5) is found in iron, stony-iron and chondrite meteorite groups. Nanoscale intergrowths of tetrataenite have been shown to carry records of paleomagnetic fields, although the effect of magnetostatic interactions on their magnetic remanence acquisition remains to be fully understood. Tetrataenite can also occur as isolated, non-interacting, nanoscale grains in many meteorite groups, although the paleomagnetic potential of these grains is particularly poorly understood. Here, we aim to improve our understanding of tetrataenite magnetization to refine our knowledge of existing paleomagnetic analyses and broaden the spectrum of meteorite groups that can be used for future paleomagnetic studies. We present the results of analytical calculations and micromagnetic modeling of isolated tetrataenite grains with various geometries. We find that tetrataenite forms a stable single domain state at grain lengths between 6 and ∼160 nm dependent on its elongation. It also possesses a magnetization resistant to viscous remagnetization over the lifetime of the solar system at 293 K. At larger grain sizes, tetrataenite's lowest energy state is a lamellar two-domain state, stable at Ga-scale timescales. Unlike many other magnetic minerals, tetrataenite does not form a single-vortex domain state due to its large uniaxial anisotropy. Our results show that single domain and two-domain tetrataenite grains carry an extremely stable magnetization and therefore are promising for paleomagnetic studies

A FCA-based analysis of sequential care trajectories

International audienceThis paper presents a research work in the domains of sequential pattern mining and formal concept analysis. Using a combined method, we show how concept lattices and interestingness measures such as stability can improve the task of discovering knowledge in symbolic sequential data. We give example of a real medical application to illustrate how this approach can be useful to discover patterns of trajectories of care in a french medico-economical database

MIRAO: a mid-IR adaptive optics system design for TMT

We present a design of a thermal-infrared optimized adaptive optics system for the TMT 30-meter telescope. The approach makes use of an adaptive secondary but during an initial implementation contains a more conventional ambient-temperature optical relay and deformable mirror. The conventional optical relay is used without sacrificing the thermal background by using multiple off-axis laser guide stars to avoid a warm dichroic in the common path. Three laser guide stars, equally spaced 75" off axis, and a "conventional" 30×30 deformable mirror provide a Strehl > 0.9 at wavelengths longer than 10 microns and the LGS beams can be passed to the LGS wavefront sensors with pickoff mirrors while a one-arcminute field is passed unvignetted to the science instrument and NGS WFSs. The overall design is relatively simple with a wavefront correction similar to existing high-order systems (e.g. 30×30) but still provides competitive performance over the higher-order TMT NIR AO design at wavelengths as short as 3 microns due to its reduced thermal emissivity. We present our figures of merit and design considerations within the context of the science drivers for high-spectral resolution NIR/MIR spectroscopy at 5-28 microns on a 30-meter ground-based telescope

Vers une mesure de similarité pour les séquences complexes

National audienceComputing the similarity between sequences is a very important challenge for many different data mining tasks. There is a plethora of similarity measures for sequences in the literature, most of them being designed for sequences of items. In this work, we study the problem of measuring the similarity ratio between sequences of itemsets. We present new combinatorial results for efficiently counting distinct and common subsequences. These theoretical results are the cornerstone for an effective dynamic programming approach to deal with this problem.Le calcul de similarité entre les séquences est d'une extrême importance dans de nombreuses approches d'explorations de données. Il existe une multitude de mesures de similarités de séquences dans la littérature. Or, la plupart de ces mesures sont conçues pour des séquences simples, dites séquences d'items. Dans ce travail, nous étudions d'un point de vue purement combinatoire le problème de similarité entre des séquences complexes (i.e., des séquences d'ensembles ou itemsets). Nous présentons de nouveaux résultats afin de compter efficacement toutes les sous-séquences communes à deux séquences. Ces résultats théoriques sont la base d'une mesure de similarité calculée efficacement grâce à une approche de programmation dynamique

On Measuring Similarity for Sequences of Itemsets

Computing the similarity between sequences is a very important challenge for many different data mining tasks. There is a plethora of similarity measures for sequences in the literature, most of them being designed for sequences of items. In this work, we study the problem of measuring the similarity between sequences of itemsets. We present new combinatorial results for efficiently counting distinct and common subsequences. These theoretical results are the cornerstone of an effective dynamic programming approach to deal with this problem. Experiments on healthcare trajectories and synthetic datasets, show that our measure of similarity produces competitive scores and indicates that our method is relevant for large scale sequential data analysis.Le calcul de similarité entre les séquences est d'une extrême importance dans de nombreuses approches d'explorations de données. Il existe une multitude de mesures de similarités de séquences dans la littérature. La plupart de ces mesures sont conçues pour des séquences simples, dites séquences d'items. Dans ce travail, nous étudions le problème de similarité entre des séquences complexes (i.e., des séquences d'ensembles ou itemsets) d'un point de vue purement combinatoire. Nous présentons de nouveaux résultats afin de compter efficacement toutes les sous-séquences communes à deux séquences. Ces résultats théoriques sont la base d'une mesure de similarité calculée efficacement grâce à une approche de programmation dynamique. Des expériences réalisées et présentées sur des soins de santé et sur des jeux de données synthétiques, montrent que notre mesure de similarité produit des résultats intéressants et probants. Cette série d'expériences indique que notre mesure de similarité est pertinente pour les applications impliquant l'analyse de données séquentielle