Mid-infrared diagnostics of starburst galaxies: clumpy, dense structures in star-forming regions in the Antennae (NGC 4038/4039)

Recently, mid-infrared instruments have become available on several large ground-based telescopes, resulting in data sets with unprecedented spatial resolution at these long wavelengths. In this paper we examine 'ground-based-only' diagnostics, which can be used in the study of star-forming regions in starburst galaxies. By combining output from the stellar population synthesis code Starburst 99 with the photoionization code Mappings, we model stellar clusters and their surrounding interstellar medium, focusing on the evolution of emission lines in the N- and Q-band atmospheric windows (8-13 and 16.5-24.5 micron respectively) and those in the near-infrared. We address the detailed sensitivity of various emission line diagnostics to stellar population age, metallicity, nebular density, and ionization parameter. Using our model results, we analyze observations of two stellar clusters in the overlap region of the Antennae galaxies obtained with VLT Imager and Spectrometer for mid Infrared (VISIR). We find evidence for clumpy, high density, ionized gas. The two clusters are young (younger than 2.5 and 3 Myr respectively), the surrounding interstellar matter is dense (10^4 cm^-3 or larger) and can be characterized by a high ionization parameter (logU > -1.53). Detailed analysis of the mid-infrared spectral features shows that a (near-)homogeneous medium cannot account for the observations, and that complex structure on scales below the resolution limit, containing several young stellar clusters embedded in clumpy gas, is more likely.Comment: 24 pages, 16 figures (3 in color), accepted for publication in Ap

Iron abundances from optical Fe III absorption lines in B-type stellar spectra

The role of optical Fe III absorption lines in B-type stars as iron abundance diagnostics is considered. To date, ultraviolet Fe lines have been widely used in B-type stars, although line blending can severely hinder their diagnostic power. Using optical spectra, covering a wavelength range ~ 3560 - 9200 A, a sample of Galactic B-type main-sequence and supergiant stars of spectral types B0.5 to B7 are investigated. A comparison of the observed Fe III spectra of supergiants, and those predicted from the model atmosphere codes TLUSTY (plane-parallel, non-LTE), with spectra generated using SYNSPEC (LTE), and CMFGEN (spherical, non-LTE), reveal that non-LTE effects appear small. In addition, a sample of main-sequence and supergiant objects, observed with FEROS, reveal LTE abundance estimates consistent with the Galactic environment and previous optical studies. Based on the present study, we list a number of Fe III transitions which we recommend for estimating the iron abundance from early B-type stellar spectra.Comment: 3 figures and 8 tables. Table 3 is to be published online only (included here on last page). Accepted for publication in MNRA

Bayesian Parameter Estimation for Latent Markov Random Fields and Social Networks

Undirected graphical models are widely used in statistics, physics and machine vision. However Bayesian parameter estimation for undirected models is extremely challenging, since evaluation of the posterior typically involves the calculation of an intractable normalising constant. This problem has received much attention, but very little of this has focussed on the important practical case where the data consists of noisy or incomplete observations of the underlying hidden structure. This paper specifically addresses this problem, comparing two alternative methodologies. In the first of these approaches particle Markov chain Monte Carlo (Andrieu et al., 2010) is used to efficiently explore the parameter space, combined with the exchange algorithm (Murray et al., 2006) for avoiding the calculation of the intractable normalising constant (a proof showing that this combination targets the correct distribution in found in a supplementary appendix online). This approach is compared with approximate Bayesian computation (Pritchard et al., 1999). Applications to estimating the parameters of Ising models and exponential random graphs from noisy data are presented. Each algorithm used in the paper targets an approximation to the true posterior due to the use of MCMC to simulate from the latent graphical model, in lieu of being able to do this exactly in general. The supplementary appendix also describes the nature of the resulting approximation.Comment: 26 pages, 2 figures, accepted in Journal of Computational and Graphical Statistics (http://www.amstat.org/publications/jcgs.cfm

Analysis of factors influencing the ultrasonic fetal weight estimation

Objective: The aim of our study was the evaluation of sonographic fetal weight estimation taking into consideration 9 of the most important factors of influence on the precision of the estimation. Methods: We analyzed 820 singleton pregnancies from 22 to 42 weeks of gestational age. We evaluated 9 different factors that potentially influence the precision of sonographic weight estimation ( time interval between estimation and delivery, experts vs. less experienced investigator, fetal gender, gestational age, fetal weight, maternal BMI, amniotic fluid index, presentation of the fetus, location of the placenta). Finally, we compared the results of the fetal weight estimation of the fetuses with poor scanning conditions to those presenting good scanning conditions. Results: Of the 9 evaluated factors that may influence accuracy of fetal weight estimation, only a short interval between sonographic weight estimation and delivery (0-7 vs. 8-14 days) had a statistically significant impact. Conclusion: Of all known factors of influence, only a time interval of more than 7 days between estimation and delivery had a negative impact on the estimation

The Holistic Impact of Classroom Spaces on Learning in Specific Subjects

The Holistic Evidence and Design (HEAD) study of U.K. primary schools sought to isolate the impact of the physical design of classrooms on the learning progress of pupils aged from 5 to 11 years (U.S. kindergarten to fifth grade). One hundred fifty-three classrooms were assessed and links made to the learning of the 3,766 pupils in them. Through multilevel modeling, the role of physical design was isolated from the influences of the pupils’ characteristics. This article presents analyses for the three main subjects assessed, namely, reading, writing, and math. Variations in the importance of the physical design parameters are revealed for the learning of each subject. In addition to some common factors, such as lighting, a heavy salience for Individualization in relation to math becomes apparent and the importance emerges of Connection for reading and of Links to Nature for writing. Possible explanations are suggested. These results provide a stimulus for additional finesse in practice and for further investigation by researchers

Statistical Inference for Valued-Edge Networks: Generalized Exponential Random Graph Models

Across the sciences, the statistical analysis of networks is central to the production of knowledge on relational phenomena. Because of their ability to model the structural generation of networks, exponential random graph models are a ubiquitous means of analysis. However, they are limited by an inability to model networks with valued edges. We solve this problem by introducing a class of generalized exponential random graph models capable of modeling networks whose edges are valued, thus greatly expanding the scope of networks applied researchers can subject to statistical analysis

Designing electronic collaborative learning environments

Electronic collaborative learning environments for learning and working are in vogue. Designers design them according to their own constructivist interpretations of what collaborative learning is and what it should achieve. Educators employ them with different educational approaches and in diverse situations to achieve different ends. Students use them, sometimes very enthusiastically, but often in a perfunctory way. Finally, researchers study them and—as is usually the case when apples and oranges are compared—find no conclusive evidence as to whether or not they work, where they do or do not work, when they do or do not work and, most importantly, why, they do or do not work. This contribution presents an affordance framework for such collaborative learning environments; an interaction design procedure for designing, developing, and implementing them; and an educational affordance approach to the use of tasks in those environments. It also presents the results of three projects dealing with these three issues

A large scale survey reveals that chromosomal copy-number alterations significantly affect gene modules involved in cancer initiation and progression

Background Recent observations point towards the existence of a large number of neighborhoods composed of functionally-related gene modules that lie together in the genome. This local component in the distribution of the functionality across chromosomes is probably affecting the own chromosomal architecture by limiting the possibilities in which genes can be arranged and distributed across the genome. As a direct consequence of this fact it is therefore presumable that diseases such as cancer, harboring DNA copy number alterations (CNAs), will have a symptomatology strongly dependent on modules of functionally-related genes rather than on a unique "important" gene. Methods We carried out a systematic analysis of more than 140,000 observations of CNAs in cancers and searched by enrichments in gene functional modules associated to high frequencies of loss or gains. Results The analysis of CNAs in cancers clearly demonstrates the existence of a significant pattern of loss of gene modules functionally related to cancer initiation and progression along with the amplification of modules of genes related to unspecific defense against xenobiotics (probably chemotherapeutical agents). With the extension of this analysis to an Array-CGH dataset (glioblastomas) from The Cancer Genome Atlas we demonstrate the validity of this approach to investigate the functional impact of CNAs. Conclusions The presented results indicate promising clinical and therapeutic implications. Our findings also directly point out to the necessity of adopting a function-centric, rather a gene-centric, view in the understanding of phenotypes or diseases harboring CNAs.Spanish Ministry of Science and Innovation (grant BIO2008-04212)Spanish Ministry of Science and Innovation (grant FIS PI 08/0440)GVA-FEDER (PROMETEO/2010/001)Red Temática de Investigación Cooperativa en Cáncer (RTICC) (grant RD06/0020/1019)Instituto de Salud Carlos III (ISCIII)Spanish Ministry of Science and InnovationSpanish Ministry of Health (FI06/00027

Signaling in Secret: Pay-for-Performance and the Incentive and Sorting Effects of Pay Secrecy

Key Findings: Pay secrecy adversely impacts individual task performance because it weakens the perception that an increase in performance will be accompanied by increase in pay; Pay secrecy is associated with a decrease in employee performance and retention in pay-for-performance systems, which measure performance using relative (i.e., peer-ranked) criteria rather than an absolute scale (see Figure 2 on page 5); High performing employees tend to be most sensitive to negative pay-for- performance perceptions; There are many signals embedded within HR policies and practices, which can influence employees’ perception of workplace uncertainty/inequity and impact their performance and turnover intentions; and When pay transparency is impractical, organizations may benefit from introducing partial pay openness to mitigate these effects on employee performance and retention