40 research outputs found

    Device-Engendered Cognitive Ability Score Differences on Unproctored Internet-Based Assessments: The Role of Selective Attention

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    Although a volume of literature suggests that the device used to complete unproctored Internet-based tests (UIT) affects observed test scores, there have been a limited number of attempts to provide a psychological explanation for why this occurs. One such exception is Arthur, Keiser, and Doverspike's (2018) Structural Characteristics/Information Processing (SCIP) model, which provides a psychological explanation regarding the conditions under which one would expect UIT device types (e.g., desktop computer, smartphone, tablet) to affect test scores. The model proposes that systematic error is introduced via construct-irrelevant cognitive load attributable to the additional information-processing demands elicited by the UIT device's structural characteristics. While conceptually sound, there has been only one empirical examination of the propositions advanced by the model to date. Consequently, the primary objective of the present study was to test the SCIP model's propositions regarding selective attention, the information-processing demand elicited by permissibility, the associated structural characteristic of UIT devices. Two hundred sixty-one participants completed measures of general mental ability (GMA), personality, and selective attention. Participants were randomly assigned to one of two conditions differing in terms of the testing (1) environment and (2) device used to complete the GMA test and personality assessment (i.e., a busy, outdoor location [smartphone condition] or a quiet, indoor location [desktop condition]). Scores on the GMA test did not differ as a function of the testing device and environment, however, in accordance with the tenets of the SCIP model, it appears that test takers in the smartphone condition experienced a greater degree of selective-attention demands while completing the GMA test. All of the observed results are interpreted within the context of using an undergraduate student sample, low testing stakes, and random assignment instead of the self-selection of participants into conditions. Implications and limitations of the present study as well as recommendations for future research are discussed

    Rift Valley fever virus infection induces activation of the NLRP3 inflammasome

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    AbstractInflammasome activation is gaining recognition as an important mechanism for protection during viral infection. Here, we investigate whether Rift Valley fever virus, a negative-strand RNA virus, can induce inflammasome responses and IL-1β processing in immune cells. We have determined that RVFV induces NLRP3 inflammasome activation in murine dendritic cells, and that this process is dependent upon ASC and caspase-1. Furthermore, absence of the cellular RNA helicase adaptor protein MAVS/IPS-1 significantly reduces extracellular IL-1β during infection. Finally, direct imaging using confocal microscopy shows that the MAVS protein co-localizes with NLRP3 in the cytoplasm of RVFV infected cells

    RNA helicase signaling is critical for type I interferon production and protection against rift valley fever virus during mucosal challenge

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    Rift Valley fever virus (RVFV) is an emerging RNA virus with devastating economic and social consequences. Clinically, RVFV induces a gamut of symptoms ranging from febrile illness to retinitis, hepatic necrosis, hemorrhagic fever, and death. It is known that type I interferon (IFN) responses can be protective against severe pathology; however, it is unknown which innate immune receptor pathways are crucial for mounting this response. Using both in vitro assays and in vivo mucosal mouse challenge, we demonstrate here that RNA helicases are critical for IFN production by immune cells and that signaling through the helicase adaptor molecule MAVS (mitochondrial antiviral signaling) is protective against mortality and more subtle pathology during RVFV infection. In addition, we demonstrate that Toll-like-receptor-mediated signaling is not involved in IFN production, further emphasizing the importance of the RNA cellular helicases in type I IFN responses to RVFV

    Observation of gravitational waves from the coalescence of a 2.5−4.5 M⊙ compact object and a neutron star

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    Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

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    Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

    Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

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    Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

    Ultralight vector dark matter search using data from the KAGRA O3GK run

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    Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

    Device-Engendered Cognitive Ability Score Differences on Unproctored Internet-Based Assessments: The Role of Selective Attention

    Get PDF
    Although a volume of literature suggests that the device used to complete unproctored Internet-based tests (UIT) affects observed test scores, there have been a limited number of attempts to provide a psychological explanation for why this occurs. One such exception is Arthur, Keiser, and Doverspike's (2018) Structural Characteristics/Information Processing (SCIP) model, which provides a psychological explanation regarding the conditions under which one would expect UIT device types (e.g., desktop computer, smartphone, tablet) to affect test scores. The model proposes that systematic error is introduced via construct-irrelevant cognitive load attributable to the additional information-processing demands elicited by the UIT device's structural characteristics. While conceptually sound, there has been only one empirical examination of the propositions advanced by the model to date. Consequently, the primary objective of the present study was to test the SCIP model's propositions regarding selective attention, the information-processing demand elicited by permissibility, the associated structural characteristic of UIT devices. Two hundred sixty-one participants completed measures of general mental ability (GMA), personality, and selective attention. Participants were randomly assigned to one of two conditions differing in terms of the testing (1) environment and (2) device used to complete the GMA test and personality assessment (i.e., a busy, outdoor location [smartphone condition] or a quiet, indoor location [desktop condition]). Scores on the GMA test did not differ as a function of the testing device and environment, however, in accordance with the tenets of the SCIP model, it appears that test takers in the smartphone condition experienced a greater degree of selective-attention demands while completing the GMA test. All of the observed results are interpreted within the context of using an undergraduate student sample, low testing stakes, and random assignment instead of the self-selection of participants into conditions. Implications and limitations of the present study as well as recommendations for future research are discussed
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