Tech Friday (12 – 18 Sep 2020)

Virtual Tourism, Robot Sensing, Neural Implants, Autonomous Machines, Fibre Optical Comms, Organoids, Robot Hand, Neural Networks


Note: None of the news bits given here are written by Newanced's authors. The links on each of the news bits will redirect to the news source. Content given under each headline is a basic gist and not the full story.

Virtual Tourism Could Offer New Opportunities for Travel Industry, Travelers

Source: Medical College of Georgia at Augusta University

A new proposal for virtual travel, using advanced mathematical techniques and combining livestream video with existing photos and videos of travel hotspots, could help revitalize an industry that has been devastated by the coronavirus pandemic, according to researchers at the Medical College of Georgia at Augusta University.

Original written by: Jennifer Hilliard Scott

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Light Processing Improves Robotic Sensing, Study Finds

Source: U.S. Army Research Laboratory

A team of Army researchers uncovered how the human brain processes bright and contrasting light, which they say is a key to improving robotic sensing and enabling autonomous agents to team with humans.

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SMART Researchers Develop Fast and Efficient Method to Produce Red Blood Cells

Source: Singapore-MIT Alliance for Research and Technology (SMART)

Researchers have developed a faster and more efficient way to manufacture red blood cells that cuts down on cell culture time by half. The cells are frozen in liquid nitrogen and thawed on demand to produce matured RBCs in only 11 days, removing the need for continuous 23-day manufacturing. The team also designed complementary technology for more targeted cell sorting and purification.

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Real Neurons Are Noisy. Can Neural Implants Figure That Out?

Source: Duke University

The brain’s visual centers must be adept at filtering out the noise from the retinal cells to get to the true signal, and those filters have to constantly adapt to light conditions to keep the signal clear. Prosthetic retinas and neural implants are going to need this same kind of adaptive noise-filtering to succeed, new research suggests.

Original written by: Karl Leif Bates

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Future Autonomous Machines May Build Trust Through Emotion

Source: U.S. Army Research Laboratory

Research has extended the state-of-the-art in autonomy by providing a more complete picture of how actions and nonverbal signals contribute to promoting cooperation. Researchers suggested guidelines for designing autonomous machines such as robots, self-driving cars, drones and personal assistants that will effectively collaborate with Soldiers.

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Ultra-Fast Magnetic Switching with Potential to Transform Fibre Optical Communications

Source: Trinity College Dublin

Researchers at CRANN and Trinity’s School of Physics have discovered that a new material can act as a super-fast magnetic switch. When struck by successive ultra-short laser pulses it exhibits “toggle switching” that could increase the capacity of the global fibre optic cable network by an order of magnitude.

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Next-Gen Organoids Grow and Function Like Real Tissues

Source: Ecole Polytechnique Fédérale de Lausanne

Bioengineers at EPFL have created miniature intestines in a dish that match up anatomically and functionally to the real thing better than any other lab-grown tissue models. The biological complexity and longevity of the new organoid technology is an important step towards enabling drug testing, personalized medicine, and perhaps, one day, transplantations.

Original written by: Nik Papageorgiou

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Medical Robotic Hand? Rubbery Semiconductor Makes It Possible

Source: University of Houston

A medical robotic hand could allow doctors to more accurately diagnose and treat people from halfway around the world, but currently available technologies aren’t good enough to match the in-person experience.

Original written by: Jeannie Kever

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New Data Processing Module Makes Deep Neural Networks Smarter

Source: North Carolina State University

Artificial intelligence researchers at North Carolina State University have improved the performance of deep neural networks by combining feature normalization and feature attention modules into a single module that they call attentive normalization (AN). The hybrid module improves the accuracy of the system significantly, while using negligible extra computational power.

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