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Category: biological

Serena Corr looks at the science behind batteries, discusses why we are hunting for new ones and investigates what tools we use to pave this pathway to discovery.
Watch the Q&A: https://youtu.be/lZjqiR0czLo.

The hunt is on for the next generation of batteries that will power our electric vehicles and help our transition to a renewables-led future. Serena shows how researchers at the Faraday Institution are developing new chemistries and manufacturing processes to deliver safer, cheaper, and longer-lasting batteries and provide higher power or energy densities for electric vehicles.

Serena Corr is a Chair in Functional Materials and Professor in Chemical and Biological Engineering at the University of Sheffield. She works on next-generation battery materials and advanced characterisation techniques for nanomaterials.

This event was generously supported by The Faraday Institution.

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There is a renaissance occurring in the field of artificial intelligence. For some drawn-out specialists in the field, it isn’t excessively self-evident. Many are making against the advancements of Deep Learning is anyway an amazingly radical departure from classical methods.

Old style A.I. procedures has zeroed in generally on the legitimate premise of cognition, Deep Learning by contrast works in the territory of cognitive intuition. Deep learning frameworks display behavior that seems biological despite not being founded on biological material. It so happens that humankind has fortunately discovered Artificial Intuition as Deep Learning.

Artificial intuition is a simple term to misconstrue since it seems like artificial emotion and artificial empathy. In any case, it contrasts fundamentally. Scientists are dealing with artificial intuition so that machines can impersonate human behavior all the more precisely. Artificial intuition plans to distinguish a human’s perspective in real-time. Along these lines, for instance, chatbots, virtual assistants and care robots can react to people all the more appropriately in context. Artificial intuition is more similar to human intuition since it can quickly evaluate the totality of a situation, including subtle indicators of a specific activity.

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AI solves a 50 year biological problem of protein folding!

Han from WrySci HX goes through the recent scientific breakthrough by AlphaFold from DeepMind. The ability to accurately predict a protein structure just based on an amino acid sequence will be a complete game changer. More below ↓↓↓

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Video credits from DeepMind: https://www.youtube.com/watch?v=gg7WjuFs8F4

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Stanford University engineers have developed an airborne method for imaging underwater objects by combining light and sound to break through the seemingly impassable barrier at the interface of air and water.

The researchers envision their hybrid optical-acoustic system one day being used to conduct drone-based biological marine surveys from the air, carry out large-scale aerial searches of sunken ships and planes, and map the ocean depths with a similar speed and level of detail as Earth’s landscapes. Their “Photoacoustic Airborne Sonar System” is detailed in a recent study published in the journal IEEE Access.

“Airborne and spaceborne radar and laser-based, or LIDAR, systems have been able to map Earth’s landscapes for decades. Radar signals are even able to penetrate cloud coverage and canopy coverage. However, seawater is much too absorptive for imaging into the water,” said study leader Amin Arbabian, an associate professor of electrical engineering in Stanford’s School of Engineering. “Our goal is to develop a more robust system which can image even through murky water.”

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Artificial intelligence (AI) has solved one of biology’s grand challenges: predicting how proteins curl up from a linear chain of amino acids into 3D shapes that allow them to carry out life’s tasks. Today, leading structural biologists and organizers of a biennial protein-folding competition announced the achievement by researchers at DeepMind, a U.K.-based AI company. They say the DeepMind method will have far-reaching effects, among them dramatically speeding the creation of new medications.

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A long-standing and incredibly complex scientific problem concerning the structure and behaviour of proteins has been effectively solved by a new artificial intelligence (AI) system, scientists report.

DeepMind, the UK-based AI company, has wowed us for years with its parade of ever-advancing neural networks that continually trounce humans at complex games such as chess and Go.

All those incremental advancements were about much more than mastering recreational diversions, however.

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For the first time, scientists with the National Oceanic and Atmospheric Administration (NOAA) have formally identified a new species of undersea creature based solely on high-definition video footage captured at the bottom of the ocean.

And what an undersea creature it is. Meet Duobrachium sparksae – a strange, gelatinous species of ctenophore, encountered by the remotely operated vehicle (ROV) Deep Discoverer during a dive off the coast of Puerto Rico.

That encounter took place back in 2015, but when you’re laying claim to discovering a wholly new species – based solely on video evidence, for that matter, with no physical specimens to help make your case – it helps to do your due diligence.

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