2,185 research outputs found

    Extended Limber Approximation

    Full text link
    We develop a systematic derivation for the Limber approximation to the angular cross-power spectrum of two random fields, as a series expansion in 1/(\ell+1/2). This extended Limber approximation can be used to test the accuracy of the Limber approximation and to improve the rate of convergence at large \ell's. We show that the error in ordinary Limber approximation is O(1/\ell^2). We also provide a simple expression for the second order correction to the Limber formula, which improves the accuracy to O(1/\ell^4). This correction can be especially useful for narrow redshift bins, or samples with small redshift overlap, for which the zeroth order Limber formula has a large error. We also point out that using \ell instead of (\ell+1/2), as is often done in the literature, spoils the accuracy of the approximation to O(1/\ell).Comment: 7 pages, 6 figure

    Imagining 5G: Public sensemaking through advertising in China and the US

    Get PDF
    This study initiates a line of research on how the fifth generation of wireless infrastructure (“5G”) is being imagined through media portrayals—in this case through advertising. At the time of this writing, 5G is not yet widely available, however the media is saturated with narratives about how it will revolutionize everyday life. Drawing from the social imaginaries and media infrastructures traditions, this textual analysis examines the social shaping of 5G through advertisements from leading telecoms in leading markets, including China and the United States. Findings reveal an overarching trend with ads from both societies imagining 5G in futuristic and utopian ways, suggesting new possibilities for people, objects, and places to be connected through smart homes, vehicles, factories, and cities—not just through smart phones. The findings also reveal distinctions in how 5G is envisioned at the societal level. For example, ads from China imagine 5G as a source of national pride that will elevate its global standing, while the US telecoms have a more inward focus on domestic competition. The discussion offers interpretations of these and other findings, along with directions for future research

    Forty years on: Uta Frith's contribution to research on autism and dyslexia, 1966–2006

    Get PDF
    Uta Frith has made a major contribution to our understanding of developmental disorders, especially autism and dyslexia. She has studied the cognitive and neurobiological bases of both disorders and demonstrated distinctive impairments in social cognition and central coherence in autism, and in phonological processing in dyslexia. In this enterprise she has encouraged psychologists to work in a theoretical framework that distinguishes between observed behaviour and the underlying cognitive and neurobiological processes that mediate that behaviour

    Gentle Masking of Low-Complexity Sequences Improves Homology Search

    Get PDF
    Detection of sequences that are homologous, i.e. descended from a common ancestor, is a fundamental task in computational biology. This task is confounded by low-complexity tracts (such as atatatatatat), which arise frequently and independently, causing strong similarities that are not homologies. There has been much research on identifying low-complexity tracts, but little research on how to treat them during homology search. We propose to find homologies by aligning sequences with “gentle” masking of low-complexity tracts. Gentle masking means that the match score involving a masked letter is , where is the unmasked score. Gentle masking slightly but noticeably improves the sensitivity of homology search (compared to “harsh” masking), without harming specificity. We show examples in three useful homology search problems: detection of NUMTs (nuclear copies of mitochondrial DNA), recruitment of metagenomic DNA reads to reference genomes, and pseudogene detection. Gentle masking is currently the best way to treat low-complexity tracts during homology search

    The role of working memory in visual selective attention

    Get PDF
    The hypothesis is that working memory is crucial for reducing distraction by maintaining the prioritization of relevant information was tested in neuroimaging and psychological experiments with humans. Participants performed a selective attention task that required them to ignore distractor faces while holding in working memory a sequence of digits that were in the same order (low memory load) or a different order (high memory load) on every trial. Higher memory load, associated with increased prefrontal activity, resulted in greater interference effects on behavioral performance from the distractor faces, plus increased face-related activity in the visual cortex. These findings confirm a major role for working memory in the control of visual selective attention

    Neural correlates of attentional capture in visual search

    Get PDF
    Much behavioral research has shown that the presence of a unique singleton distractor during a task of visual search will typically capture attention and thus disrupt search. Here we examined the neural correlates of such attentional capture using functional magnetic resonance imaging in human divisions during performance of a visual search task. The presence (vs. absence) of a salient yet irrelevant color singleton distractor was associated with activity in the superior parietal cortex and frontal cortex. These findings imply that the singleton distractor induced spatial shifts of attention despite its irrelevance, as predicted from an AC account. Moreover, behavioral interference by singleton distractors was strongly and negatively correlated with frontal activity. These findings provode direct evidence that the frontal cortex is involved in control of interference from irrelevant but attention-capturing distractors

    Mitigating Gender Bias in Machine Learning Data Sets

    Full text link
    Artificial Intelligence has the capacity to amplify and perpetuate societal biases and presents profound ethical implications for society. Gender bias has been identified in the context of employment advertising and recruitment tools, due to their reliance on underlying language processing and recommendation algorithms. Attempts to address such issues have involved testing learned associations, integrating concepts of fairness to machine learning and performing more rigorous analysis of training data. Mitigating bias when algorithms are trained on textual data is particularly challenging given the complex way gender ideology is embedded in language. This paper proposes a framework for the identification of gender bias in training data for machine learning.The work draws upon gender theory and sociolinguistics to systematically indicate levels of bias in textual training data and associated neural word embedding models, thus highlighting pathways for both removing bias from training data and critically assessing its impact.Comment: 10 pages, 5 figures, 5 Tables, Presented as Bias2020 workshop (as part of the ECIR Conference) - http://bias.disim.univaq.i

    Why are animals cognitive?

    Get PDF
    The study of animal behaviour has revealed many intricate ways in which individuals deal adaptively with their world, some of which raise controversial issues of interpretation. Scrub jays, for instance, adjust their food-hiding according to the likely competition from other jays. If a competitor has seen them cache food, and they have themselves had the experience of pilfering others ’ caches, they re-cache in private [1]. If privacy is denied them, they prefer t
    • …
    corecore