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Harnessing local knowledge for scientific knowledge production : challenges and pitfalls within evidence-based sustainability studies

The calls for evidence-based public policy making have increased dramatically in the last decades, and so has the interest in evidence-based sustainability studies. But questions remain about what “evidence” actually means in different contexts and if the concept travels well between different domains of application. Some of the most relevant questions asked by sustainability studies are not, and

Extensive green roofs in Porto Alegre, Brazil : Effect on indoor thermal comfort in residential buildings

Brazil had a significant quantitative housing deficit of 7.7 million residences in 2015, especially in low-income housing. Traditionally, these projects have low levels of thermal insulation which can result in discomfort caused by warmth or cold. The residential sector is responsible for a significant part of the energy use in Brazil. A green roof, a rooftop system with the addition of vegetation

Disparities in colorectal cancer between Northern and SouthernSweden–a report from the new RISK North database

Background: Geographic cancer health disparities have been reported in Sweden. The disparities are not fully understood, but may be attributed to differences in exposure to risk factors as well as differences in health care, socioeconomics and demography. The aim of this study was to describe the new nationwide population based RISK North database and its potential by analysing health disparities

Enhanced constraints on the interior composition and structure of terrestrial exoplanets

Exoplanet interior modelling usually makes the assumption that the elemental abundances of a planet are identical to those of its host star. Host stellar abundances are good proxies of planetary abundances, but only for refractory elements. This is particularly true for terrestrial planets, as evidenced by the relative differences in bulk chemical composition between the Sun and the Earth and othe

Cumulative inhibition in neural networks

We show how a multi-resolution network can model the development of acuity and coarse-to-fine processing in the mammalian visual cortex. The network adapts to input statistics in an unsupervised manner, and learns a coarse-to-fine representation by using cumulative inhibition of nodes within a network layer. We show that a system of such layers can represent input by hierarchically composing large