Surprisingly, the functions of a huge number of microbial genes are still unknown. This knowledge gap can be thought of as "genomic dark matter" in microbes, and neither computational biology nor current lab techniques have been able address this gap. This challenge has now been tackled through an international collaboration between the Institute for Research in Biomedicine (IRB Barcelona) and two other interdisciplinary research centres, namely the IJS in Ljubljana (Slovenia) and RBI in Zagreb (Croatia).
Many designers for the virtual world find it challenging to design efficiently believable complex textures or patterns on a large scale. Indeed, so-called 'texture synthesis,' the design of accurate textures such as water ripples in a river, concrete walls, or patterns of leaves, remains a difficult task for artists. A plethora of non-stationary textures in the 'real world' could be re-created in gaming or virtual worlds, but the existing techniques are tedious and time-consuming.
Your torso is more intuitive -- and more precise -- than joysticks for piloting drones, both simulated and real, according to a recent study by EPFL scientists. Work is already underway to implement this new body-machine-interface technology for search and rescue with drones.
Understanding how a robot will react under different conditions is essential to guaranteeing its safe operation. But how do you know what will break a robot without actually damaging it? A new method developed by scientists at IST Austria and the MPI for Intelligent Systems is the first machine learning method that can use observations made under safe conditions to make accurate predictions for all possible conditions governed by the same physical dynamics.
Designing new molecules for pharmaceuticals is primarily a manual, time-consuming process that's prone to error. But MIT researchers have now taken a step toward fully automating the design process, which could drastically speed things up -- and produce better results.
Researchers at the Max Planck Florida Institute for Neuroscience release open source software, connecting and building the neuroscience coding community. The software has the potential to dramatically increase experiment workflow, shaving off hours of imaging time. Weaving in an element of machine learning, the algorithm can be taught how to differentiate between dendrite backbone and dendritic spines after being fed a training data set of previously identified spines.
MIT's Cheetah 3 robot can now leap and gallop across rough terrain, climb a staircase littered with debris, and quickly recover its balance when suddenly yanked or shoved, all while essentially blind. The 90-pound mechanical beast -- about the size of a full-grown Labrador -- is intentionally designed to do all this without relying on cameras or any external environmental sensors.
A research team, led by computer scientists from the University of Bern-Switzerland and University of Maryland-College Park, have devised a sketch-based editing framework that enables a user to edit their photos by sketching a few strokes on top of them.
Researchers at The University of Texas at Austin have designed a way to sense dangerous chemicals using, in part, a simple rig consisting of a smartphone and a box made from Lego bricks, which could help first responders and scientists in the field identify deadly and difficult-to-detect nerve agents such as VX and sarin.
Researchers at the MIT Media Lab have now developed a type of personalized machine learning that helps robots estimate the engagement and interest of each child during these interactions, using data that are unique to that child. Armed with this personalized 'deep learning' network, the robots' perception of the children's responses agreed with assessments by human experts, with a correlation score of 60 percent, the scientists report June 27 in Science Robotics.