You might have observed plants competing for sunlight — the way they stretch upwards and outwards to block each other’s access to the sun’s rays — but out of sight, another type of competition is happening underground. In the same way that you might change the way you forage for free snacks in the break room when your colleagues are present, plants change their use of underground resources when they’re planted alongside other plants.
Researchers from Skoltech and the University of Texas at Austin have presented a proof-of-concept for a wearable sensor that can track healing in sores, ulcers and other kinds of chronic skin wounds, even without the need to remove the bandages. The paper was published in the journal ACS Sensors.
Chronic wounds that fail to heal quickly, such as diabetic foot ulcers or pressure ulcers, can be very tricky to manage for healthcare professionals and a nightmare for patients. To monitor the healing process and assess the need for treatment, doctors and nurses normally
Researchers at Oak Ridge National Laboratory are developing a first-of-a-kind toolkit drawing on video game development software to visualize radiation data.
Using data sets originally produced by ORNL for analysis of NASA radioisotope power systems, the toolkit leverages gaming development software such as Unreal Engine® to couple three-dimensional radiation transport results with CAD geometries in a cinematic — yet scientific —
Teaching robots to paint in a manner similar to a human painter is an important task in computer vision. A recent paper on arXiv.org proposes a novel approach to this problem, which tackles several limitations of current algorithms.
Like in other methods, reinforcement learning is used to predict a sequence of brush strokes from a given image. However, instead of depicting one single image, the novel method employs a semantic guidance pipeline to learn the distinction between foreground and background brush strokes. Also, a neural alignment model is used to zoom in
A Lancaster University researcher will conduct ground-breaking Artificial Intelligence (AI) research to revolutionise the use of AI in autonomous vehicles and cybersecurity, as part of a prestigious Turing AI Acceleration Fellowship.
As technology advances, there is a growing need to collect vast quantities of data easily and inexpensively and to use these data to deliver significant benefits across a wide range of applications such as energy consumption and public health.
A key challenge in AI research is to extract meaningful value from these data sources to make decisions that can be trusted and understood to improve the way society functions.
Researchers at ETH Zurich have identified a self-regulating mechanism in European deciduous trees that limit their growing-season length: Trees that photosynthesise more in spring and summer lose their leaves earlier in autumn.
Leaves of temperate deciduous trees glow in all their yellow and red glory just before falling, signalling that autumn has come. This process, called leaf senescence, allows trees to prepare for the coming winter by suspending their growth and extracting nutrients from the foliage. In the trees’ phenological cycle, leaf senescence marks the end of the productive period during which they absorb CO2 through photosynthesis.