240 research outputs found

    Concrete Periodic Inverse Spectral Transform (Theory of Nonlinear Waves)

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    The ‘uberization of policing’? How police negotiate and operationalise predictive policing technology

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    Predictive policing generally refers to police work that utilises strategies, algorithmic technologies, and big data to generate near-future predictions about the people and places deemed likely to be involved in or experience crime. Claimed benefits of predictive policing centre on the technology’s ability to enable pre-emptive police work by automating police decisions. The goal is that officers will rely on computer software and smartphone applications to instruct them about where and who to police just as Uber drivers rely on similar technologies to instruct them about where to pick up passengers. Unfortunately, little is known about the experiences of the in-field users of predictive technologies. This article helps fill this gap by addressing the under researched area of how police officers engage with predictive technologies. As such, data is presented that outlines the findings of a qualitative study with UK police organisations involved in designing and trialing predictive policing software. Research findings show that many police officers have a detailed awareness of the limitations of predictive technologies, specifically those brought about by errors and biases in input data. This awareness has led many officers to develop a sceptical attitude towards predictive technologies and, in a few cases, these officers have expressed a reluctance to use predictive technologies. Based on these findings, this paper argues that claims about predictive software’s ability to neutralise the subjectivity of police work overlooks the ongoing struggles of the police officer to assert their agency and mediate the extent to which predictions will be trusted and utilised

    Sagittarius II, Draco II and Laevens 3: Three New Milky Way Satellites Discovered in the Pan-STARRS 1 3 Survey

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    We present the discovery of three new Milky Way satellites from our search for compact stellar overdensities in the photometric catalog of the Panoramic Survey Telescope and Rapid Response System 1 (Pan-STARRS 1, or PS1) 3π survey. The first satellite, Laevens 3, is located at a heliocentric distance of d = 67 ± 3 kpc. With a total magnitude of MV = −4.4 ± 0.3 and a half-light radius of rh = 7 ± 2 pc, its properties resemble those of outer halo globular clusters. The second system, Draco II/Laevens 4, is a closer and fainter satellite (d ~ 20 kpc, MV = −2.9 ± 0.8), whose uncertain size (rh=19−6+8  pc{r}_{h}={19}_{-6}^{+8}\;\mathrm{pc}) renders its classification difficult without kinematic information; it could either be a faint and extended globular cluster or a faint and compact dwarf galaxy. The third satellite, Sagittarius II/Laevens 5 (Sgr II), has an ambiguous nature, as it is either the most compact dwarf galaxy or the most extended globular cluster in its luminosity range (rh=37−8+9  pc{r}_{h}={37}_{-8}^{+9}\;\mathrm{pc} and MV = −5.2 ± 0.4). At a heliocentric distance of 67 ± 5 kpc, this satellite lies intriguingly close to the expected location of the trailing arm of the Sagittarius stellar stream behind the Sagittarius dwarf spheroidal galaxy (Sgr dSph). If confirmed through spectroscopic follow up, this connection would locate this part of the trailing arm of the Sagittarius stellar stream that has so far gone undetected. It would further suggest that Sgr II was brought into the Milky Way halo as a satellite of the Sgr dSph

    Why do people ïŹtted with hearing aids not wear them?

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    Objective: Age-related hearing loss is an increasingly important public health problem affecting approximately 40% of 55–74 year olds. The primary clinical management intervention for people with hearing loss is hearing aids, however, the majority (80%) of adults aged 55–74 years who would benefit from a hearing aid, do not use them. Furthermore, many people given a hearing aid do not wear it. The aim was to collate the available evidence as to the potential reasons for non-use of hearing aids among people who have been fitted with at least one. Design: Data were gathered via the use of a scoping study. Study sample: A comprehensive search strategy identified 10 articles reporting reasons for non-use of hearing aids. Results: A number of reasons were given, including hearing aid value, fit and comfort and maintenance of the hearing aid, attitude, device factors, financial reasons, psycho-social/situational factors, healthcare professionals attitudes, ear problems, and appearance. Conclusions: The most important issues were around hearing aid value, i.e. the hearing aid not providing enough benefit, and comfort related to wearing the hearing aid. Identifying factors that affect hearing aid usage are necessary for devising appropriate rehabilitation strategies to ensure greater use of hearing aids

    An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

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    For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

    Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

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    Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

    Search for jet extinction in the inclusive jet-pT spectrum from proton-proton collisions at s=8 TeV

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    Published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. Further distribution of this work must maintain attribution to the author(s) and the published articles title, journal citation, and DOI.The first search at the LHC for the extinction of QCD jet production is presented, using data collected with the CMS detector corresponding to an integrated luminosity of 10.7  fb−1 of proton-proton collisions at a center-of-mass energy of 8 TeV. The extinction model studied in this analysis is motivated by the search for signatures of strong gravity at the TeV scale (terascale gravity) and assumes the existence of string couplings in the strong-coupling limit. In this limit, the string model predicts the suppression of all high-transverse-momentum standard model processes, including jet production, beyond a certain energy scale. To test this prediction, the measured transverse-momentum spectrum is compared to the theoretical prediction of the standard model. No significant deficit of events is found at high transverse momentum. A 95% confidence level lower limit of 3.3 TeV is set on the extinction mass scale

    Mouse Chromosome 11

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46996/1/335_2004_Article_BF00648429.pd
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