1,632 research outputs found

    Barriers to colorectal cancer screening among American Indian men aged 50 or older, Kansas and Missouri, 2006-2008

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    American Indian (AI) men have some of the highest rates of colorectal cancer (CRC) in the United States but among the lowest screening rates. Our goal was to better understand awareness and discourse about colorectal cancer in a heterogeneous group of AI men in the Midwestern United States. Focus groups were conducted with AI men (N = 29); data were analyzed using a community-participatory approach to qualitative text analysis. Several themes were identified regarding knowledge, knowledge sources, and barriers to and facilitators of screening. Men in the study felt that awareness about colorectal cancer was low, and people were interested in learning more. Education strategies need to be culturally relevant and specific

    Does wage rank affect employees' well-being?

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    How do workers make wage comparisons? Both an experimental study and an analysis of 16,000 British employees are reported. Satisfaction and well-being levels are shown to depend on more than simple relative pay. They depend upon the ordinal rank of an individual's wage within a comparison group. “Rank” itself thus seems to matter to human beings. Moreover, consistent with psychological theory, quits in a workplace are correlated with pay distribution skewness

    Assay strategies for the discovery and validation of therapeutics targeting <i>Brugia pahangi</i> Hsp90

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    The chemotherapy of lymphatic filariasis relies upon drugs such as diethylcarbamazine and ivermectin that largely target the microfilarial stages of the parasite, necessitating continued treatment over the long reproductive life span of the adult worm. The identification of compounds that target adult worms has been a long-term goal of WHO. Here we describe a fluorescence polarization assay for the identification of compounds that target Hsp90 in adult filarial worms. The assay was originally developed to identify inhibitors of Hsp90 in tumor cells, and relies upon the ability of small molecules to inhibit the binding of fluorescently labelled geldanamycin to Hsp90. We demonstrate that the assay works well with soluble extracts of Brugia, while extracts of the free-living nematode C. elegans fail to bind the probe, in agreement with data from other experiments. The assay was validated using known inhibitors of Hsp90 that compete with geldanamycin for binding to Hsp90, including members of the synthetic purine-scaffold series of compounds. The efficacy of some of these compounds against adult worms was confirmed in vitro. Moreover, the assay is sufficiently sensitive to differentiate between binding of purine-scaffold compounds to human and Brugia Hsp90. The assay is suitable for high-throughput screening and provides the first example of a format with the potential to identify novel inhibitors of Hsp90 in filarial worms and in other parasitic species where Hsp90 may be a target

    Turbulence Heating ObserveR – satellite mission proposal

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    The Universe is permeated by hot, turbulent, magnetized plasmas. Turbulent plasma is a major constituent of active galactic nuclei, supernova remnants, the intergalactic and interstellar medium, the solar corona, the solar wind and the Earth’s magnetosphere, just to mention a few examples. Energy dissipation of turbulent fluctuations plays a key role in plasma heating and energization, yet we still do not understand the underlying physical mechanisms involved. THOR is a mission designed to answer the questions of how turbulent plasma is heated and particles accelerated, how the dissipated energy is partitioned and how dissipation operates in different regimes of turbulence. THOR is a single-spacecraft mission with an orbit tuned to maximize data return from regions in near-Earth space – magnetosheath, shock, foreshock and pristine solar wind – featuring different kinds of turbulence. Here we summarize the THOR proposal submitted on 15 January 2015 to the ‘Call for a Medium-size mission opportunity in ESAs Science Programme for a launch in 2025 (M4)’. THOR has been selected by European Space Agency (ESA) for the study phase

    Analysis and modeling of high temporal resolution spectroscopic observations of flares on AD Leo

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    We report the results of a high temporal resolution spectroscopic monitoring of the flare star AD Leo. During 4 nights, more than 600 spectra were taken in the optical range using the Isaac Newton Telescope (INT) and the Intermediate Dispersion Spectrograph (IDS). We have observed a large number of short and weak flares occurring very frequently (flare activity > 0.71 hours-1). This is in favour of the very important role that flares can play in stellar coronal heating. The detected flares are non white-light flares and, though most of solar flares belong to this kind, very few such events had been previously observed on stars. The behaviour of different chromospheric lines (Balmer series from H_alpha to H_11, Ca II H & K, Na I D_1 & D_2, He I 4026 AA and He I D_3) has been studied in detail for a total of 14 flares. We have also estimated the physical parameters of the flaring plasma by using a procedure which assumes a simplified slab model of flares. All the obtained physical parameters are consistent with previously derived values for stellar flares, and the areas - less than 2.3% of the stellar surface - are comparable with the size inferred for other solar and stellar flares. Finally, we have studied the relationships between the physical parameters and the area, duration, maximum flux and energy released during the detected flares.Comment: Latex file with 17 pages, 11 figures. Available at http://www.ucm.es/info/Astrof/invest/actividad/actividad_pub.html Accepted for publication in: Astronomy & Astrophysics (A&A

    Turing learning: : A metric-free approach to inferring behavior and its application to swarms

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    We propose Turing Learning, a novel system identification method for inferring the behavior of natural or artificial systems. Turing Learning simultaneously optimizes two populations of computer programs, one representing models of the behavior of the system under investigation, and the other representing classifiers. By observing the behavior of the system as well as the behaviors produced by the models, two sets of data samples are obtained. The classifiers are rewarded for discriminating between these two sets, that is, for correctly categorizing data samples as either genuine or counterfeit. Conversely, the models are rewarded for 'tricking' the classifiers into categorizing their data samples as genuine. Unlike other methods for system identification, Turing Learning does not require predefined metrics to quantify the difference between the system and its models. We present two case studies with swarms of simulated robots and prove that the underlying behaviors cannot be inferred by a metric-based system identification method. By contrast, Turing Learning infers the behaviors with high accuracy. It also produces a useful by-product - the classifiers - that can be used to detect abnormal behavior in the swarm. Moreover, we show that Turing Learning also successfully infers the behavior of physical robot swarms. The results show that collective behaviors can be directly inferred from motion trajectories of individuals in the swarm, which may have significant implications for the study of animal collectives. Furthermore, Turing Learning could prove useful whenever a behavior is not easily characterizable using metrics, making it suitable for a wide range of applications.Comment: camera-ready versio
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