139 research outputs found

    Space for Two to Think: Large, High-Resolution Displays for Co-located Collaborative Sensemaking

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    Large, high-resolution displays carry the potential to enhance single display groupware collaborative sensemaking for intelligence analysis tasks by providing space for common ground to develop, but it is up to the visual analytics tools to utilize this space effectively. In an exploratory study, we compared two tools (Jigsaw and a document viewer), which were adapted to support multiple input devices, to observe how the large display space was used in establishing and maintaining common ground during an intelligence analysis scenario using 50 textual documents. We discuss the spatial strategies employed by the pairs of participants, which were largely dependent on tool type (data-centric or function-centric), as well as how different visual analytics tools used collaboratively on large, high-resolution displays impact common ground in both process and solution. Using these findings, we suggest design considerations to enable future co-located collaborative sensemaking tools to take advantage of the benefits of collaborating on large, high-resolution displays

    Large High Resolution Displays for Co-Located Collaborative Intelligence Analysis

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    Large, high-resolution vertical displays carry the potential to increase the accuracy of collaborative sensemaking, given correctly designed visual analytics tools. From an exploratory user study using a fictional intelligence analysis task, we investigated how users interact with the display to construct spatial schemas and externalize information, as well as how they establish shared and private territories. We investigated the spatial strategies of users partitioned by tool type used (document- or entity-centric). We classified the types of territorial behavior exhibited in terms of how the users interacted with the display (integrated or independent workspaces). Next, we examined how territorial behavior impacted the common ground between the pairs of users. Finally, we recommend design guidelines for building co-located collaborative visual analytics tools specifically for use on large, high-resolution vertical displays

    Computational prediction and experimental validation of novel Hedgehog-responsive enhancers linked to genes of the Hedgehog pathway

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    Abstract Background The Hedgehog (Hh) signaling pathway, acting through three homologous transcription factors (GLI1, GLI2, GLI3) in vertebrates, plays multiple roles in embryonic organ development and adult tissue homeostasis. At the level of the genome, GLI factors bind to specific motifs in enhancers, some of which are hundreds of kilobases removed from the gene promoter. These enhancers integrate the Hh signal in a context-specific manner to control the spatiotemporal pattern of target gene expression. Importantly, a number of genes that encode Hh pathway molecules are themselves targets of Hh signaling, allowing pathway regulation by an intricate balance of feed-back activation and inhibition. However, surprisingly few of the critical enhancer elements that control these pathway target genes have been identified despite the fact that such elements are central determinants of Hh signaling activity. Recently, ChIP studies have been carried out in multiple tissue contexts using mouse models carrying FLAG-tagged GLI proteins (GLIFLAG). Using these datasets, we tested whether a meta-analysis of GLI binding sites, coupled with a machine learning approach, could reveal genomic features that could be used to empirically identify Hh-regulated enhancers linked to loci of the Hh signaling pathway. Results A meta-analysis of four existing GLIFLAG datasets revealed a library of GLI binding motifs that was substantially more restricted than the potential sites predicted by previous in vitro binding studies. A machine learning method (kmer-SVM) was then applied to these datasets and enriched k-mers were identified that, when applied to the mouse genome, predicted as many as 37,000 potential Hh enhancers. For functional analysis, we selected nine regions which were annotated to putative Hh pathway molecules and found that seven exhibited GLI-dependent activity, indicating that they are directly regulated by Hh signaling (78 % success rate). Conclusions The results suggest that Hh enhancer regions share common sequence features. The kmer-SVM machine learning approach identifies those features and can successfully predict functional Hh regulatory regions in genomic DNA surrounding Hh pathway molecules and likely, other Hh targets. Additionally, the library of enriched GLI binding motifs that we have identified may allow improved identification of functional GLI binding sites.http://deepblue.lib.umich.edu/bitstream/2027.42/134520/1/12861_2016_Article_106.pd

    The DEEP Groth Strip Galaxy Redshift Survey. III. Redshift Catalog and Properties of Galaxies

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    The Deep Extragalactic Evolutionary Probe (DEEP) is a series of spectroscopic surveys of faint galaxies, targeted at the properties and clustering of galaxies at redshifts z ~ 1. We present the redshift catalog of the DEEP 1 GSS pilot phase of this project, a Keck/LRIS survey in the HST/WFPC2 Groth Survey Strip. The redshift catalog and data, including reduced spectra, are publicly available through a Web-accessible database. The catalog contains 658 secure galaxy redshifts with a median z=0.65, and shows large-scale structure walls to z = 1. We find a bimodal distribution in the galaxy color-magnitude diagram which persists to z = 1. A similar color division has been seen locally by the SDSS and to z ~ 1 by COMBO-17. For red galaxies, we find a reddening of only 0.11 mag from z ~ 0.8 to now, about half the color evolution measured by COMBO-17. We measure structural properties of the galaxies from the HST imaging, and find that the color division corresponds generally to a structural division. Most red galaxies, ~ 75%, are centrally concentrated, with a red bulge or spheroid, while blue galaxies usually have exponential profiles. However, there are two subclasses of red galaxies that are not bulge-dominated: edge-on disks and a second category which we term diffuse red galaxies (DIFRGs). The distant edge-on disks are similar in appearance and frequency to those at low redshift, but analogs of DIFRGs are rare among local red galaxies. DIFRGs have significant emission lines, indicating that they are reddened mainly by dust rather than age. The DIFRGs in our sample are all at z>0.64, suggesting that DIFRGs are more prevalent at high redshifts; they may be related to the dusty or irregular extremely red objects (EROs) beyond z>1.2 that have been found in deep K-selected surveys. (abridged)Comment: ApJ in press. 24 pages, 17 figures (12 color). The DEEP public database is available at http://saci.ucolick.org

    The DEEP Groth Strip Survey. I. The Sample

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    The Deep Extragalactic Exploratory Probe (DEEP) is a multi-phase research program dedicated to the study of the formation and evolution of galaxies and of large scale structure in the distant Universe. This paper describes the first five-year phase, denoted DEEP1. A series of ten DEEP1 papers will discuss a range of scientific topics (e.g., the study of photometric and spectral properties of a general distant galaxy survey, the evolution observed in galaxy populations of varied morphologies). The observational basis for these studies is the Groth Survey Strip field, a 127 square arcminute region which has been observed with the Hubble Space Telescope in both broad I-band and V-band optical filters and with the Low Resolution Imaging Spectrograph on the Keck Telescopes. Catalogs of photometric and structural parameters have been constructed for 11,547 galaxies and stars at magnitudes brighter than 29, and spectroscopy has been conducted for a magnitude-color weighted subsample of 818 objects. We evaluate three independent techniques for constructing an imaging catalog for the field from the HST data, and discuss the depth and sampling of the resultant catalogs. The selection of the spectroscopic subsample is discussed, and we describe the multifaceted approach taken to prioritizing objects of interest for a variety of scientific subprograms. A series of Monte Carlo simulations then demonstrates that the spectroscopic subsample can be adequately modeled as a simple function of magnitude and color cuts in the imaging catalog.Comment: ApJS accepted, 15 pages, 12 figures. Version with higher-quality figures available at http://astronomy.nmsu.edu/nicol

    Comparison of the influence of cyclosporine and tacrolimus on the pharmacokinetics of prednisolone in adult male kidney transplant recipients

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    Cyclosporine has been observed to precipitate cushingoid features in kidney transplant recipients already on prednisolone. Some pharmacokinetic studies have demonstrated increased prednisolone exposure in patients on cyclosporine therapy compared with azathioprine, whereas other studies have found no difference. The objective of this study was to determine whether cyclosporine impacts on prednisolone exposure as compared with tacrolimus
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