Problem detection in legislative oversight:An analysis of legislative committee agendas in the U.K. and U.S.

This paper outlines a dynamic problem-detection model of legislative oversight where legislative committees engage in information-gathering to identify emerging policy problems. It is argued that activities of legislative committees are responsive to indicators of problem status across a range of policy domains. This enables committees to react to problems before, or at least simultaneously to, citizens. Our analyses use a new dataset on the policy agenda of UK Parliamentary Select Committees in combination with directly comparable data on US Congressional hearings. Aggregate measures of problem status (e.g. GDP, crime rates) and public opinion on the �most important problem� facing the country are used as independent variables. The comparison between a well-established and developing committee system offers insights into common dynamics across institutional contexts. The findings show that committee agendas in both the UK and US are responsive to problem status for the majority of issues

Neutrino interaction vertex reconstruction in DUNE with Pandora deep learning

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours

Enhanced Postural Stability Following Driver Training Is Associated With Positive Effects in Vehicle Kinematics During Cornering

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Exclusion or interests? Why females in elected office reduce petty and grand corruption

Disappointed by the numerous failures of anticorruption reforms, international organisations, scholars and policy makers increasingly place their hopes on measures aimed at enhancing gender equality and in particular increasing the inclusion of female representatives in elected assemblies. Yet most studies to date focus on aggregate measures of corruption and fail to explain why the correlation between women's representation and levels of corruption occurs. Using newly collected regional-level, non-perception-based measures of corruption, this study distinguishes between different forms of corruption and shows that the inclusion of women in local councils is strongly negatively associated with the prevalence of both petty and grand forms of corruption. However, the reduction in corruption is primarily experienced among women. This suggests that female representatives seek to further two separate political agendas once they attain public office: the improvement of public service delivery in sectors that tend to primarily benefit women; and the breakup of male-dominated collusive networks