Lifeboat Foundation

Researchers at Rice University have shown how they can hack the brains of fruit flies to make them remote controlled. The flies performed a specific action within a second of a command being sent to certain neurons in their brain.

The team started by genetically engineering the flies so that they expressed a certain heat-sensitive ion channel in some of their neurons. When this channel sensed heat, it would activate the neuron – in this case, that neuron caused the fly to spread its wings, which is a gesture they often use during mating.

Continue reading “Scientists hack fly brains to make them remote controlled” »

Human brains process loads of information. When wine aficionados taste a new wine, neural networks in their brains process an array of data from each sip. Synapses in their neurons fire, weighing the importance of each bit of data—acidity, fruitiness, bitterness—before passing it along to the next layer of neurons in the network. As information flows, the brain parses out the type of wine.

Scientists want artificial intelligence (AI) systems to be sophisticated data connoisseurs too, and so they design computer versions of neural networks to process and analyze information. AI is catching up to the human brain in many tasks, but usually consumes a lot more energy to do the same things. Our brains make these calculations while consuming an estimated average of 20 watts of power. An AI system can use thousands of times that. This hardware can also lag, making AI slower, less efficient and less effective than our brains. A large field of AI research is looking for less energy-intensive alternatives.

Now, in a study published in the journal Physical Review Applied, scientists at the National Institute of Standards and Technology (NIST) and their collaborators have developed a new type of hardware for AI that could use less energy and operate more quickly—and it has already passed a virtual wine-tasting test.

Summary: A new artificial neural network aced a wine tasting test and promises a less energy-hungry version of artificial intelligence, researchers report.

Source: NIST

Human brains process loads of information. When wine aficionados taste a new wine, neural networks in their brains process an array of data from each sip. Synapses in their neurons fire, weighing the importance of each bit of data — acidity, fruitiness, bitterness — before passing it along to the next layer of neurons in the network. As information flows, the brain parses out the type of wine.

The question of how the chemical composition of a protein—the amino acid sequence—determines its 3D structure has been one of the biggest challenges in biophysics for more than half a century. This knowledge about the so-called “folding” of proteins is in great demand, as it contributes significantly to the understanding of various diseases and their treatment, among other things. For these reasons, Google’s DeepMind research team has developed AlphaFold, an artificial intelligence that predicts 3D structures.

A team consisting of researchers from Johannes Gutenberg University Mainz (JGU) and the University of California, Los Angeles, has now taken a closer look at these structures and examined them with respect to knots. We know knots primarily from shoelaces and cables, but they also occur on the nanoscale in our cells. Knotted proteins can not only be used to assess the quality of structure predictions but also raise important questions about folding mechanisms and the evolution of proteins.

A team of scientists in the Physical Intelligence Department at the Max Planck Institute for Intelligent Systems have combined robotics with biology by equipping E. coli bacteria with artificial components to construct biohybrid microrobots. First, as can be seen in Figure 1, the team attached several nanoliposomes to each bacterium. On their outer circle, these spherical-shaped carriers enclose a material (ICG, green particles) that melts when illuminated by near infrared light. Further towards the middle, inside the aqueous core, the liposomes encapsulate water soluble chemotherapeutic drug molecules (DOX).

The second component the researchers attached to the bacterium is magnetic nanoparticles. When exposed to a magnetic field, the iron oxide particles serve as an on-top booster to this already highly motile microorganism. In this way, it is easier to control the swimming of bacteria —an improved design toward an in vivo application. Meanwhile, the rope binding the liposomes and magnetic particles to the bacterium is a very stable and hard to break streptavidin and biotin complex, which was developed a few years prior and reported in a Nature article, and comes in useful when constructing biohybrid microrobots.

E. coli bacteria are fast and versatile swimmers that can navigate through material ranging from liquids to highly viscous tissues. But that is not all, they also have highly advanced sensing capabilities. Bacteria are drawn to chemical gradients such as low oxygen levels or high acidity—both prevalent near tumor tissue. Treating cancer by injecting bacteria in proximity is known as bacteria mediated tumor therapy. The microorganisms flow to where the tumor is located, grow there and in this way activate the immune system of patients. Bacteria mediated tumor therapy has been a therapeutic approach for more than a century.

A strain-sensing smart skin developed at Rice University that uses very small structures, carbon nanotubes, to monitor and detect damage in large structures is ready for prime time.

The ‘strain paint’ first revealed by Rice in 2012 uses the fluorescent properties of nanotubes to show when a surface has been deformed by stress.

Continue reading “Nanotube-embedded coating detects threats from wear and tear in large structures” »

A strain-sensing smart skin developed at Rice University that uses very small structures, carbon nanotubes, to monitor and detect damage in large structures is ready for prime time.

The “strain paint” first revealed by Rice in 2012 uses the fluorescent properties of nanotubes to show when a surface has been deformed by stress.

Continue reading “Strain-sensing smart skin ready to deploy” »

Korea Advanced Institute of Science and Technology (KAIST) researchers and their collaborators at home and abroad have successfully demonstrated a new platform for guiding the compressed light waves in very thin van der Waals crystals. Their method to guide the mid-infrared light with minimal loss will provide a breakthrough for the practical applications of ultra-thin dielectric crystals in next-generation optoelectronic devices based on strong light-matter interactions at the nanoscale.

Phonon-polaritons are collective oscillations of ions in polar dielectrics coupled to electromagnetic waves of light, whose electromagnetic field is much more compressed compared to the light wavelength. Recently, it was demonstrated that the phonon-polaritons in thin van der Waals crystals can be compressed even further when the material is placed on top of a highly conductive metal. In such a configuration, charges in the polaritonic crystal are “reflected” in the metal, and their coupling with light results in a new type of polariton waves called the image phonon-polaritons. Highly compressed image modes provide strong light-matter interactions, but are very sensitive to the substrate roughness, which hinders their practical application.

Challenged by these limitations, four research groups combined their efforts to develop a unique experimental platform using advanced fabrication and measurement methods. Their findings were published in Science Advances on July 13.