The Void Galaxy Survey

The Void Galaxy Survey (VGS) is a multi-wavelength program to study $\sim$60 void galaxies. Each has been selected from the deepest interior regions of identified voids in the SDSS redshift survey on the basis of a unique geometric technique, with no a prior selection of intrinsic properties of the void galaxies. The project intends to study in detail the gas content, star formation history and stellar content, as well as kinematics and dynamics of void galaxies and their companions in a broad sample of void environments. It involves the HI imaging of the gas distribution in each of the VGS galaxies. Amongst its most tantalizing findings is the possible evidence for cold gas accretion in some of the most interesting objects, amongst which are a polar ring galaxy and a filamentary configuration of void galaxies. Here we shortly describe the scope of the VGS and the results of the full analysis of the pilot sample of 15 void galaxies.Comment: 9 pages, 6 figures. This is an extended version of a paper to appear in "Environment and the Formation of Galaxies: 30 years later", Proceedings of Symposium 2 of JENAM 2010, eds. I. Ferreras, A. Pasquali, ASSP, Springer. Version with highres figures at http://www.astro.rug.nl/~weygaert/vgs_jenam_weygaert.col.pd

Large Scale Structure of the Universe

Galaxies are not uniformly distributed in space. On large scales the Universe displays coherent structure, with galaxies residing in groups and clusters on scales of ~1-3 Mpc/h, which lie at the intersections of long filaments of galaxies that are >10 Mpc/h in length. Vast regions of relatively empty space, known as voids, contain very few galaxies and span the volume in between these structures. This observed large scale structure depends both on cosmological parameters and on the formation and evolution of galaxies. Using the two-point correlation function, one can trace the dependence of large scale structure on galaxy properties such as luminosity, color, stellar mass, and track its evolution with redshift. Comparison of the observed galaxy clustering signatures with dark matter simulations allows one to model and understand the clustering of galaxies and their formation and evolution within their parent dark matter halos. Clustering measurements can determine the parent dark matter halo mass of a given galaxy population, connect observed galaxy populations at different epochs, and constrain cosmological parameters and galaxy evolution models. This chapter describes the methods used to measure the two-point correlation function in both redshift and real space, presents the current results of how the clustering amplitude depends on various galaxy properties, and discusses quantitative measurements of the structures of voids and filaments. The interpretation of these results with current theoretical models is also presented.Comment: Invited contribution to be published in Vol. 8 of book "Planets, Stars, and Stellar Systems", Springer, series editor T. D. Oswalt, volume editor W. C. Keel, v2 includes additional references, updated to match published versio

Gastro-enteritis outbreak among Nordic patients with psoriasis in a health centre in Gran Canaria, Spain: a cohort study

BACKGROUND: Between November 2 and 10, 2002 several patients with psoriasis and personnel staying in the health centre in Gran Canaria, Spain fell ill with diarrhoea, vomiting or both. Patient original came from Norway, Sweden and Finland. The patient group was scheduled to stay until 8 November. A new group of patients were due to arrive from 7 November. METHODS: A retrospective cohort study was conducted to assess the extent of the outbreak, to identify the source and mode of transmission and to prevent similar problems in the following group. RESULTS: Altogether 41% (48/116) of persons staying at the centre fell ill. Norovirus infection was suspected based on clinical presentations and the fact that no bacteria were identified. Kaplan criteria were met. Five persons in this outbreak were hospitalised and the mean duration of diarrhoea was 3 days. The consequences of the illness were more severe compared to many other norovirus outbreaks, possibly because many of the cases suffered from chronic diseases and were treated with drugs reported to affect the immunity (methotrexate or steroids). During the two first days of the outbreak, the attack rate was higher in residents who had consumed dried fruit (adjusted RR = 3.1; 95% CI: 1.4–7.1) and strawberry jam (adjusted RR = 1.9; 95% CI: 0.9–4.1) than those who did not. In the following days, no association was found. The investigation suggests two modes of transmission: a common source for those who fell ill during the two first days of the outbreak and thereafter mainly person to person transmission. This is supported by a lower risk associated with the two food items at the end of the outbreak. CONCLUSIONS: We believe that the food items were contaminated by foodhandlers who reported sick before the outbreak started. Control measures were successfully implemented; food buffets were banned, strict hygiene measures were implemented and sick personnel stayed at home >48 hours after last symptoms

Genetic, environmental and stochastic factors in monozygotic twin discordance with a focus on epigenetic differences

PMCID: PMC3566971This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Properties of Graphene: A Theoretical Perspective

In this review, we provide an in-depth description of the physics of monolayer and bilayer graphene from a theorist's perspective. We discuss the physical properties of graphene in an external magnetic field, reflecting the chiral nature of the quasiparticles near the Dirac point with a Landau level at zero energy. We address the unique integer quantum Hall effects, the role of electron correlations, and the recent observation of the fractional quantum Hall effect in the monolayer graphene. The quantum Hall effect in bilayer graphene is fundamentally different from that of a monolayer, reflecting the unique band structure of this system. The theory of transport in the absence of an external magnetic field is discussed in detail, along with the role of disorder studied in various theoretical models. We highlight the differences and similarities between monolayer and bilayer graphene, and focus on thermodynamic properties such as the compressibility, the plasmon spectra, the weak localization correction, quantum Hall effect, and optical properties. Confinement of electrons in graphene is nontrivial due to Klein tunneling. We review various theoretical and experimental studies of quantum confined structures made from graphene. The band structure of graphene nanoribbons and the role of the sublattice symmetry, edge geometry and the size of the nanoribbon on the electronic and magnetic properties are very active areas of research, and a detailed review of these topics is presented. Also, the effects of substrate interactions, adsorbed atoms, lattice defects and doping on the band structure of finite-sized graphene systems are discussed. We also include a brief description of graphane -- gapped material obtained from graphene by attaching hydrogen atoms to each carbon atom in the lattice.Comment: 189 pages. submitted in Advances in Physic

Reduced auditory steady state responses in autism spectrum disorder

Background Auditory steady state responses (ASSRs) are elicited by clicktrains or amplitude-modulated tones, which entrain auditory cortex at their specific modulation rate. Previous research has reported reductions in ASSRs at 40 Hz for autism spectrum disorder (ASD) participants and first-degree relatives of people diagnosed with ASD (Mol Autism. 2011;2:11, Biol Psychiatry. 2007;62:192–197). Methods Using a 1.5 s-long auditory clicktrain stimulus, designed to elicit an ASSR at 40 Hz, this study attempted to replicate and extend these findings. Magnetencephalography (MEG) data were collected from 18 adolescent ASD participants and 18 typically developing controls. Results The ASSR localised to bilateral primary auditory regions. Regions of interest were thus defined in left and right primary auditory cortex (A1). While the transient gamma-band response (tGBR) from 0-0.1 s following presentation of the clicktrain stimulus was not different between groups, for either left or right A1, the ASD group had reduced oscillatory power at 40 Hz from 0.5 to 1.5 s post-stimulus onset, for both left and right A1. Additionally, the ASD group had reduced inter-trial coherence (phase consistency over trials) at 40 Hz from 0.64-0.82 s for right A1 and 1.04-1.22 s for left A1. Limitations In this study, we did not conduct a clinical autism assessment (e.g. the ADOS), and therefore, it remains unclear whether ASSR power and/or ITC are associated with the clinical symptoms of ASD. Conclusion Overall, our results support a specific reduction in ASSR oscillatory power and inter-trial coherence in ASD, rather than a generalised deficit in gamma-band responses. We argue that this could reflect a developmentally relevant reduction in non-linear neural processing

Comparison of machine learning and semi-quantification algorithms for (I123)FP-CIT classification: the beginning of the end for semi-quantification?

Background Semi-quantification methods are well established in the clinic for assisted reporting of (I123) Ioflupane images. Arguably, these are limited diagnostic tools. Recent research has demonstrated the potential for improved classification performance offered by machine learning algorithms. A direct comparison between methods is required to establish whether a move towards widespread clinical adoption of machine learning algorithms is justified. This study compared three machine learning algorithms with that of a range of semi-quantification methods, using the Parkinson’s Progression Markers Initiative (PPMI) research database and a locally derived clinical database for validation. Machine learning algorithms were based on support vector machine classifiers with three different sets of features: Voxel intensities Principal components of image voxel intensities Striatal binding radios from the putamen and caudate. Semi-quantification methods were based on striatal binding ratios (SBRs) from both putamina, with and without consideration of the caudates. Normal limits for the SBRs were defined through four different methods: Minimum of age-matched controls Mean minus 1/1.5/2 standard deviations from age-matched controls Linear regression of normal patient data against age (minus 1/1.5/2 standard errors) Selection of the optimum operating point on the receiver operator characteristic curve from normal and abnormal training data Each machine learning and semi-quantification technique was evaluated with stratified, nested 10-fold cross-validation, repeated 10 times. Results The mean accuracy of the semi-quantitative methods for classification of local data into Parkinsonian and non-Parkinsonian groups varied from 0.78 to 0.87, contrasting with 0.89 to 0.95 for classifying PPMI data into healthy controls and Parkinson’s disease groups. The machine learning algorithms gave mean accuracies between 0.88 to 0.92 and 0.95 to 0.97 for local and PPMI data respectively. Conclusions Classification performance was lower for the local database than the research database for both semi-quantitative and machine learning algorithms. However, for both databases, the machine learning methods generated equal or higher mean accuracies (with lower variance) than any of the semi-quantification approaches. The gain in performance from using machine learning algorithms as compared to semi-quantification was relatively small and may be insufficient, when considered in isolation, to offer significant advantages in the clinical context

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente