University of Oxford

About: University of Oxford is a education organization based out in Oxford, Oxfordshire, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 99713 authors who have published 258108 publications receiving 12972806 citations. The organization is also known as: Oxford University & Oxon..

The Impact of Conservation on the Status of the World’s Vertebrates

Abstract: Using data for 25,780 species categorized on the International Union for Conservation of Nature Red List, we present an assessment of the status of the world's vertebrates. One-fifth of species are classified as Threatened, and we show that this figure is increasing: On average, 52 species of mammals, birds, and amphibians move one category closer to extinction each year. However, this overall pattern conceals the impact of conservation successes, and we show that the rate of deterioration would have been at least one-fifth again as much in the absence of these. Nonetheless, current conservation efforts remain insufficient to offset the main drivers of biodiversity loss in these groups: agricultural expansion, logging, overexploitation, and invasive alien species.

End-to-End Representation Learning for Correlation Filter Based Tracking

Abstract: The Correlation Filter is an algorithm that trains a linear template to discriminate between images and their translations. It is well suited to object tracking because its formulation in the Fourier domain provides a fast solution, enabling the detector to be re-trained once per frame. Previous works that use the Correlation Filter, however, have adopted features that were either manually designed or trained for a different task. This work is the first to overcome this limitation by interpreting the Correlation Filter learner, which has a closed-form solution, as a differentiable layer in a deep neural network. This enables learning deep features that are tightly coupled to the Correlation Filter. Experiments illustrate that our method has the important practical benefit of allowing lightweight architectures to achieve state-of-the-art performance at high framerates.

PRACTITIONERS’ CORNER: Computing Robust Standard Errors for Within‐groups Estimators*

Abstract: The purpose of this note is to explain how to use standard packages to calculate heteroskedasticity and serial c orrelation consistent standard errors for within-groups estimators of a linear regression model from panel data. The within-groups estimat or is calculated as the least squares estimator in a transformed mult ivariate regression with cross-equation linear restrictions. The Whit e standard errors obtained in this way are the desired ones. Copyright 1987 by Blackwell Publishing Ltd

Children's Reading Comprehension Ability: Concurrent Prediction by Working Memory, Verbal Ability, and Component Skills.

Abstract: The authors report data from a longitudinal study that addresses the relations between working memory capacity and reading comprehension skills in children aged 8, 9, and 11 years. At each time point, the authors assessed children's reading ability, vocabulary and verbal skills, performance on 2 working memory assessments (sentence-span and digit working memory), and component skills of comprehension. At each time point, working memory and component skills of comprehension (inference making, comprehension monitoring, story structure knowledge) predicted unique variance in reading comprehension after word reading ability and vocabulary and verbal ability controls. Further analyses revealed that the relations between reading comprehension and both inference making and comprehension monitoring were not wholly mediated by working memory. Rather, these component skills explained their own unique variance in reading comprehension.

Warming caused by cumulative carbon emissions towards the trillionth tonne

Abstract: Global efforts to mitigate climate change are guided by projections of future temperatures. But the eventual equilibrium global mean temperature associated with a given stabilization level of atmospheric greenhouse gas concentrations remains uncertain, complicating the setting of stabilization targets to avoid potentially dangerous levels of global warming. Similar problems apply to the carbon cycle: observations currently provide only a weak constraint on the response to future emissions. Here we use ensemble simulations of simple climate-carbon-cycle models constrained by observations and projections from more comprehensive models to simulate the temperature response to a broad range of carbon dioxide emission pathways. We find that the peak warming caused by a given cumulative carbon dioxide emission is better constrained than the warming response to a stabilization scenario. Furthermore, the relationship between cumulative emissions and peak warming is remarkably insensitive to the emission pathway (timing of emissions or peak emission rate). Hence policy targets based on limiting cumulative emissions of carbon dioxide are likely to be more robust to scientific uncertainty than emission-rate or concentration targets. Total anthropogenic emissions of one trillion tonnes of carbon (3.67 trillion tonnes of CO(2)), about half of which has already been emitted since industrialization began, results in a most likely peak carbon-dioxide-induced warming of 2 degrees C above pre-industrial temperatures, with a 5-95% confidence interval of 1.3-3.9 degrees C.