Maastricht Economic and social Research and  training centre on Innovation and Technology

Evidence-Based Policy Research Methods
Developing competence and specific skills to effectively perform evidence-based academic or policy-oriented research is essential for knowledge creation and decision-making, whether in business, government or civil society. The Evidence-Based Policy Research Methods (EPRM) course, offered by UNU-MERIT aims to equip participants with the fundamental tools for designing and analysing evidence-based research.

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All headlines
  • Why modern mortar crumbles, but Roman concrete lasts millennia
  • Cleaning bots can zap bacteria out of water in minutes
  • Bee brains can help cameras to take better photos
  • Nanotechnology can turn windows into mirrors
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  • Bee brains can help cameras to take better photos
    New research on how bees perceive colour could be put to good use in our digital cameras, meaning photos shot by drones or phones would look more natural than ever.

    It's all to do with colour constancy, the way that bees (and humans) can tell a flower is red no matter what the colour or quality of the light - a mental trick that the digital cameras of today really struggle with.

    Researchers from RMIT University in Australia found that bees are using two colour receptors in their ocelli, the three extra eyes on the top of the head, that judge the colour of ambient light, in combination with two main compound eyes that detect flower colours more directly.

    In the past it was thought bees might use some kind of chromatic adaptation, like humans, to make colour constancy corrections. It's similar to adjusting the white balance on a photo to correct for the ambient light. What the new research suggests is that bees are doing something different: the scientists traced neural activity from the ocelli, discovering that information was passed to the key colour processing areas of the bee brain.

    Those three tiny upward-facing eyes measure the light coming from the sky and can make adjustments accordingly, correctly identifying flower colours. The team then set down some mathematical principles behind this mix of data from the ocelli and compound eyes, principles which could eventually be used to program the same trick into a smartphone camera or an exploratory robot.

    As well as making your pictures look more realistic in unusual lighting situations, this model could help robots trek through sunlight and shade without getting confused about what they're looking at.

    Science Alert / PNAS    July 05, 2017