A new simulation technique accelerates modeling to help us better understand complex molecular processes and facilitate rational drug design.
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Building new reservoirs can have unexpected consequences on water security
Any discussion about the role of new reservoirs must focus on the creation of new unsustainable demand.
Climate change and the city
With increasing rates of urbanization and its detrimental effects on the environment, reducing the risk posed by “urban climate change” requires more research to prepare ourselves for an uncertain future.
How do you sample blood in a non-invasive way?
Graphene-based biosensors incorporated in arrays of microneedles are emerging as an alternative to hypodermic needles and could be the next generation of blood sampling devices.
What’s so special about rivers that run dry?
As an increasing global population moves into areas where non-perennial rivers are common, we need to understand how human water needs impact when, where, and how much these rivers flow.
Today’s green investment is tomorrow’s emission reduction — models must grasp this
How ignoring the dynamics of the energy transition leads to overestimating transition cost and unjustified delay of climate action.
Challenges in establishing eco-cities within urban agglomeration
Urbanization is threatening global water supplies, but finding a way to balance expansion with sustainable water management between nature, people, and the city water infrastructure.
Learning energy efficiency networks in Argentina
The Argentinean experience can inform experts on LEEN efforts to make industrial sectors more energy efficient in developing regions.
Guideomics to live up to the promise of biotechnology for precision medicine of brain diseases
Personalized medicine for diseases that affect the central nervous system requires renewed focus on visualising the behaviour of drugs in the brain.
Simulations that reach biological timescales
A new computational technique allows researchers to model biological processes with better accuracy and at a lower computational cost.