1,185 research outputs found

    Using ontologies to map between research data and policymakers’ presumptions: the experience of the KNOWMAK project

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    Understanding knowledge co-creation in key emerging areas of European research is critical for policy makers wishing to analyze impact and make strategic decisions. However, purely data-driven methods for characterising policy topics have limitations relating to the broad nature of such topics and the differences in language and topic structure between the political language and scientific and technological outputs. In this paper, we discuss the use of ontologies and semantic technologies as a means to bridge the linguistic and conceptual gap between policy questions and data sources for characterising European knowledge production. Our experience suggests that the integration between advanced techniques for language processing and expert assessment at critical junctures in the process is key for the success of this endeavour

    Arithmetic-based pretraining improving numeracy of pretrained language models

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    State-of-the-art pretrained language models tend to perform below their capabilities when applied out-of-the-box on tasks that require understanding and working with numbers. Recent work suggests two main reasons for this: (1) popular tokenisation algorithms have limited expressiveness for numbers, and (2) common pretraining objectives do not target numeracy. Approaches that address these shortcomings usually require architectural changes or pretraining from scratch. In this paper, we propose a new extended pretraining approach called Arithmetic-Based Pretraining that jointly addresses both in one extended pretraining step without requiring architectural changes or pretraining from scratch. Arithmetic-Based Pretraining combines contrastive learning to improve the number representation, and a novel extended pretraining objective called Inferable Number Prediction Task to improve numeracy. Our experiments show the effectiveness of Arithmetic-Based Pretraining in three different tasks that require improved numeracy, i.e., reading comprehension in the DROP dataset, inference-on-tables in the InfoTabs dataset, and table-to-text generation in the WikiBio and Sci-Gen datasets

    Classification aware neural topic model and its application on a new COVID-19 disinformation corpus

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    The explosion of disinformation related to the COVID-19 pandemic has overloaded fact-checkers and media worldwide. To help tackle this, we developed computational methods to support COVID-19 disinformation debunking and social impacts research. This paper presents: 1) the currently largest available manually annotated COVID-19 disinformation category dataset; and 2) a classification-aware neural topic model (CANTM) that combines classification and topic modelling under a variational autoencoder framework. We demonstrate that CANTM efficiently improves classification performance with low resources, and is scalable. In addition, the classification-aware topics help researchers and end-users to better understand the classification results

    Classification aware neural topic model for COVID-19 disinformation categorisation

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    The explosion of disinformation accompanying the COVID-19 pandemic has overloaded fact-checkers and media worldwide, and brought a new major challenge to government responses worldwide. Not only is disinformation creating confusion about medical science amongst citizens, but it is also amplifying distrust in policy makers and governments. To help tackle this, we developed computational methods to categorise COVID-19 disinformation. The COVID-19 disinformation categories could be used for a) focusing fact-checking efforts on the most damaging kinds of COVID-19 disinformation; b) guiding policy makers who are trying to deliver effective public health messages and counter effectively COVID-19 disinformation. This paper presents: 1) a corpus containing what is currently the largest available set of manually annotated COVID-19 disinformation categories; 2) a classification-aware neural topic model (CANTM) designed for COVID-19 disinformation category classification and topic discovery; 3) an extensive analysis of COVID-19 disinformation categories with respect to time, volume, false type, media type and origin source

    Suppression of Surface-Related Loss in a Gated Semiconductor Microcavity

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    We present a surface-passivation method that reduces surface-related losses by almost 2 orders of magnitude in a highly miniaturized GaAs open microcavity. The microcavity consists of a curved dielectric distributed Bragg reflector with radius of approximately 10 ?m paired with a GaAs-based heterostructure. The heterostructure consists of a semiconductor distributed Bragg reflector followed by an n-i-p diode with a layer of quantum dots in the intrinsic region. Free-carrier absorption in the highly -n-doped and highly -p-doped layers is minimized by our positioning them close to a node of the vacuum electromagnetic field. The surface, however, resides at an antinode of the vacuum field and results in significant loss. These losses are much reduced by surface passivation. The strong dependence on wavelength implies that the main effect of the surface passivation is to eliminate the surface electric field, thereby quenching below-band-gap absorption via a Franz-Keldysh-like effect. An additional benefit is that the surface passivation reduces scattering at the GaAs surface. These results are important in other nanophotonic devices that rely on a GaAs-vacuum interface to confine the electromagnetic field

    A Study of Time-Dependent CP-Violating Asymmetries and Flavor Oscillations in Neutral B Decays at the Upsilon(4S)

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    We present a measurement of time-dependent CP-violating asymmetries in neutral B meson decays collected with the BABAR detector at the PEP-II asymmetric-energy B Factory at the Stanford Linear Accelerator Center. The data sample consists of 29.7 fb1{\rm fb}^{-1} recorded at the Υ(4S)\Upsilon(4S) resonance and 3.9 fb1{\rm fb}^{-1} off-resonance. One of the neutral B mesons, which are produced in pairs at the Υ(4S)\Upsilon(4S), is fully reconstructed in the CP decay modes J/ψKS0J/\psi K^0_S, ψ(2S)KS0\psi(2S) K^0_S, χc1KS0\chi_{c1} K^0_S, J/ψK0J/\psi K^{*0} (K0KS0π0K^{*0}\to K^0_S\pi^0) and J/ψKL0J/\psi K^0_L, or in flavor-eigenstate modes involving D()π/ρ/a1D^{(*)}\pi/\rho/a_1 and J/ψK0J/\psi K^{*0} (K0K+πK^{*0}\to K^+\pi^-). The flavor of the other neutral B meson is tagged at the time of its decay, mainly with the charge of identified leptons and kaons. The proper time elapsed between the decays is determined by measuring the distance between the decay vertices. A maximum-likelihood fit to this flavor eigenstate sample finds Δmd=0.516±0.016(stat)±0.010(syst)ps1\Delta m_d = 0.516\pm 0.016 {\rm (stat)} \pm 0.010 {\rm (syst)} {\rm ps}^{-1}. The value of the asymmetry amplitude sin2β\sin2\beta is determined from a simultaneous maximum-likelihood fit to the time-difference distribution of the flavor-eigenstate sample and about 642 tagged B0B^0 decays in the CP-eigenstate modes. We find sin2β=0.59±0.14(stat)±0.05(syst)\sin2\beta=0.59\pm 0.14 {\rm (stat)} \pm 0.05 {\rm (syst)}, demonstrating that CP violation exists in the neutral B meson system. (abridged)Comment: 58 pages, 35 figures, submitted to Physical Review

    Measurement of the Branching Fraction for B- --> D0 K*-

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    We present a measurement of the branching fraction for the decay B- --> D0 K*- using a sample of approximately 86 million BBbar pairs collected by the BaBar detector from e+e- collisions near the Y(4S) resonance. The D0 is detected through its decays to K- pi+, K- pi+ pi0 and K- pi+ pi- pi+, and the K*- through its decay to K0S pi-. We measure the branching fraction to be B.F.(B- --> D0 K*-)= (6.3 +/- 0.7(stat.) +/- 0.5(syst.)) x 10^{-4}.Comment: 7 pages, 1 postscript figure, submitted to Phys. Rev. D (Rapid Communications

    Cognitive behavioural therapy in elderly type 2 diabetes patients with minor depression or mild major depression: study protocol of a randomized controlled trial (MIND-DIA)

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    <p>Abstract</p> <p>Background</p> <p>The global prevalence of diabetes among adults will be 6.4% in 2010 and will increase to 7.7% by 2030. Diabetes doubles the odds of depression, and 9% of patients with diabetes are affected by depressive disorders. When subclinical depression is included, the proportion of patients who have clinically relevant depressive symptoms increases to 26%. In patients aged over 65 years, the interaction of diabetes and depression has predicted increased mortality, complications, disability, and earlier occurrence of all of these adverse outcomes. These deleterious effects were observed even in minor depression, where the risk of mortality within 7 years was 4.9 times higher compared with diabetes patients who did not have depressive symptoms. In this paper we describe the design and methods of the Minor Depression and Diabetes trial, a clinical trial within the 'Competence Network for Diabetes mellitus', which is funded by the German Federal Ministry of Education and Research.</p> <p>Methods/Design</p> <p>Patients' inclusion criteria are: Type 2 diabetes mellitus, 65 to 85 years of age, 3 to 6 depressive symptoms (minor depression or mild major depression). Our aim is to compare the efficacy of diabetes-specific cognitive behavioural therapy adapted for the elderly vs. intensified treatment as usual vs. a guided self-help intervention regarding improvement of health related quality of life as the primary outcome. The trial will be conducted as a multicentre, open, observer-blinded, parallel group (3 groups) randomized controlled trial. Patients will be randomized to one of the three treatment conditions. After 12 weeks of open-label therapy in all treatment conditions, both group interventions will be reduced to one session per month during the one-year long-term phase of the trial. At the one-year follow-up, all groups will be re-examined regarding the primary and secondary parameters, for example reduction of depressive symptoms, prevention of moderate/severe major depression, improvement of glycaemic control, mortality, and cost effectiveness. Depending on additional funding, the sample will be continuously observed as a prospective cohort; the primary outcome will be changed to mortality for all subsequent follow-up measurements.</p> <p>Trial registration</p> <p>Current Controlled Trials Register (ISRCTN58007098).</p

    Study of e+e- --> pi+ pi- pi0 process using initial state radiation with BABAR

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    The process e+e- --> pi+ pi- pi0 gamma has been studied at a center-of-mass energy near the Y(4S) resonance using a 89.3 fb-1 data sample collected with the BaBar detector at the PEP-II collider. From the measured 3pi mass spectrum we have obtained the products of branching fractions for the omega and phi mesons, B(omega --> e+e-)B(omega --> 3pi)=(6.70 +/- 0.06 +/- 0.27)10-5 and B(phi --> e+e-)B(phi --> 3pi)=(4.30 +/- 0.08 +/- 0.21)10-5, and evaluated the e+e- --> pi+ pi- pi0 cross section for the e+e- center-of-mass energy range 1.05 to 3.00 GeV. About 900 e+e- --> J/psi gamma --> pi+ pi- pi0 gamma events have been selected and the branching fraction B(J/psi --> pi+ pi- pi0)=(2.18 +/- 0.19)% has been measured.Comment: 21 pages, 37 postscript figues, submitted to Phys. Rev.
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