Do research performances of universities and disciplines in England converge or diverge? An assessment of the progress between research excellence frameworks in 2014 and 2021

Performance-based research funding systems (PBRFSs) have been used in selectively distributing research funding, increasing public money accountability and efciency. Two recent such evaluations in England were called the Research Excellence Framework (REF), which took place in 2014 and 2021, and the research environment, outputs and impact of the research were evaluated. Even though various aspects of the REF were examined, there has been limited research on how the performance of the universities and disciplines changed between the two evaluation periods. This paper assesses whether there has been convergence or divergence in research quality across universities and subject areas between 2014 and 2021 and found that there was an absolute convergence between universities in all three research elements evaluated, and universities that performed relatively worse in REF in 2014 experienced higher growth in their performance between 2014 and 2021. There was also an absolute convergence in the research environment and impact across diferent subject areas, but there is no signifcant convergence in the quality of research outputs across disciplines. Our fndings also highlight that there has been an absolute convergence in research quality within the universities (between diferent disciplines in a given university) and within disciplines (between universities in a given subject)

A New Index of Environmental Quality

An optimal weighting scheme is proposed to construct a new index of environmental quality for different countries using an approach that relies on consistent tests for stochastic dominance efficiency. The test statistics and the estimators are computed using mixed integer programming methods. The variables that are considered include countries’ greenhouse emissions, water pollution and forest benefits, as from the dataset of the World Bank. First, the stochastic efficient weighting for each set of variables is calculated to build three sub-indices (for greenhouse emissions, water pollution and land without forests) and then an overall risk index of environmental quality is constructed. One main result is that land without forest contributes the most (with around 70%), greenhouse emissions contribute with around 20% and water pollution contributes less (with around 10%). Finally, countries are ranked according to their index of environmental quality and their rankings are compared with those of the Kyoto Protocol.Environmental Quality; Emissions; Water Pollution; Nonparametric Stochastic Dominance, Mixed Integer Programming

Magnetic-Visual Sensor Fusion-based Dense 3D Reconstruction and Localization for Endoscopic Capsule Robots

Reliable and real-time 3D reconstruction and localization functionality is a crucial prerequisite for the navigation of actively controlled capsule endoscopic robots as an emerging, minimally invasive diagnostic and therapeutic technology for use in the gastrointestinal (GI) tract. In this study, we propose a fully dense, non-rigidly deformable, strictly real-time, intraoperative map fusion approach for actively controlled endoscopic capsule robot applications which combines magnetic and vision-based localization, with non-rigid deformations based frame-to-model map fusion. The performance of the proposed method is demonstrated using four different ex-vivo porcine stomach models. Across different trajectories of varying speed and complexity, and four different endoscopic cameras, the root mean square surface reconstruction errors 1.58 to 2.17 cm.Comment: submitted to IROS 201

Do we need all the components of the research excellence framework?

The Research Excellence Framework (REF) is underpinned by three areas of assessment: outputs, impact and environment. However, discussing the findings of their recent research Mehmet Pinar and Tim Horne argue that these elements correlate to the extent that assessing all of them is largely inefficient. If this is the case, they pose the question: is it time to eliminate one of these elements in the next REF cycle